<figure><img src="image_12.png" /><figcaption>**Figure 11.** Examples showing a variety of white dwarf spectra in the range 3850–5550 Å. White dwarfs have large surface gravities (log g ≃ 8), which result in the chemical stratification of their constituents. Most white dwarfs have atmospheres dominated by hydrogen or helium, and their spectra contain only Balmer (DA) or He (DB) lines. However, ≃20 per cent of white dwarfs exhibit spectroscopic peculiarities. Accretion of disrupted planetesimals results in photospheric contamination by metals (DAZ, DBZ, DZ), providing a unique window into the bulk abundances of exoplanetary bodies. Cool white dwarfs with deep convective envelopes may dredge up carbon and oxygen from their cores (cDQ), allowing sensitive tests of stellar evolution. A small number of hotter white dwarfs with carbon-dominated atmospheres (hDQ) are thought to be products of white dwarf mergers, possibly descending from R Corona Borealis stars. Finally, up to 10 per cent show magnetic fields, across all atmospheric compositions (e.g. DAH, DBH), and serve as laboratories for atomic physics under extreme conditions. The WEAVE Survey will target ≃100 000 white dwarfs selected from Gaia DR3 (Fig. 12).</figcaption></figure>

<figure><img src="image_13.png" /><figcaption>**Figure 12.** Hertzsprung–Russell diagram (left) and magnitude distribution (right) of the 104 198 high-confidence white dwarf candidate targets (red, Dec > −10 deg and G ≤ 20), selected from Gaia DR2 (Gentile Fusillo et al. 2019). Synthetic photometry was computed for main-sequence stars, subgiants, and giants (the blue lines labelled V, IV, and III, respectively) using the spectral library of Pickles (1998), and for white dwarfs with masses of 0.2, 0.6, and 1.0 M⊙ (unlabelled black lines, from top to bottom) using the cooling sequences of Holberg & Bergeron (2006) and model spectra from Koester (2010).</figcaption></figure>

to 3700 Å) of WEAVE is essential for covering the higher Balmer lines, which are important diagnostics for the surface gravity (Kepler et al. 2006), and to probe for atmospheric pollution by planetary debris via Ca H/K absorption. Our large sample size will result in the identification of rare white dwarf species, tracing the extremes of parameter space of short-lived phases in their evolution, such as stellar remnants from stars near the core-collapse boundary (Gänsicke et al. 2010), products of thermonuclear supernovae (Vennes et al. 2017; Raddi et al. 2018a, b; Shen et al. 2018), of as-yet not fully understood binary interactions (Dufour et al. 2007; Kepler, Koester & Ourique 2016), and possibly examples of entirely new evolutionary channels (Marsh et al. 2016). WEAVE spectroscopy will also provide radial velocity measurements that are an important complement to the Gaia proper motions – most white dwarfs have no features in the Gaia RVS spectra, or are too faint for Gaia radial velocities altogether. This first large sample of white dwarfs with full 3D kinematics will allow us to distinguish them into their thin and thick disc, and halo populations (Pauli et al. 2003, 2006; Anguiano et al. 2017), with an expected ≃1 per cent of halo white dwarfs. Furthermore, the kinematics will provide constraints on the age–velocity dispersion relation, and insight into the mass distribution of white dwarfs that formed via binary mergers (Wegg & Pinney 2012).

Given their low luminosity, the surface density of white dwarfs varies only mildly, with an average ≃5 stars deg⁻², or ≃15 per WEAVE pointing. The WEAVE White Dwarfs survey is therefore multiplexed into the entire WEAVE Survey footprint and the white dwarfs will also be used for the spectro-photometric flux calibration of the entire WEAVE Survey (Section 4.3.1).

## 4.4 The WEAVE-Apertif Survey

The detailed analysis of galaxies in the local Universe is crucial to understanding galaxy evolution. However, recent local IFU surveys of galaxies (e.g. CALIFA, Sánchez et al. 2012; SAMI, Croom et al. 2012; MANGA, Bundy et al. 2015) suffer from an optical selection bias that makes it difficult to address the effects of environment on the evolution of galaxies. The gas content of galaxies is less strongly bound to the gravitational potential well than its stellar content. Thus, one possible approach to study the effect of environment on galaxy evolution is to characterize the morphology of galaxies seen in the atomic gas, which indicates interactions that have taken place, and to select galaxies with a range of features. To this end, a wide-area survey of resolved neutral atomic hydrogen (HⅠ) is needed.

### 4.4.1 Apertif and synergy with WEAVE LIFU observations

In the last decade, the Westerbork Synthesis Radio Telescope (WSRT) was upgraded with a new receiver: an innovative focal-plane array system named Apertif (Verheijen et al. 2008; van Cappellen et al. 2022) that allowed for the execution of wide-field radio surveys, and HⅠ surveys out to cosmological distances (z ~ 0.2). Apertif survey operations were conducted between 2019 July 1 and 2022 February 28, surveying a large portion of the Northern hemisphere in 1.4 GHz radio continuum, polarization, and the 21-cm spectral line of neutral atomic hydrogen. The Apertif instrument was the first working focal-plane array capable of full Westerbork resolution [15 arcsec × 15 sin (Dec) arcsec beam²] over a field of view of 6.5 deg² per pointing, after tiling, and with HⅠ spectral resolution of down to 2.6 km s⁻¹. The 300 MHz bandwidth could

<footnote n="22">²²The factor of sin(Dec) is distinctive to WSRT as an East–West array.</footnote>
be tuned to operate between roughly 1130 and 1750 MHz, although
observations were heavily impacted by radio frequency interference
below ~1300 MHz. With about half of the sensitivity of the original
single-pixel WSRT front-end, the wide field of view of Apertif
nonetheless drastically enhanced the survey speed of WSRT by
imaging an area on the sky about 25 times the size of the full moon
in a single pointing.

Apertif conducted a two-tiered H I imaging survey<fnref n="23" /> that provides a
strong synergy with WEAVE: a medium-deep survey of 150 deg² and
a wide-area survey of approximately 2200 deg² between ~+27 and
65 deg declination (Hess et al., in preparation). The wide-area survey
targeted areas with multiwavelength coverage from Northern sky
surveys including LOFAR, SDSS, and the Hobby-Eberly Telescope
Dark Energy Experiment (HETDEX; Hill et al. 2008) in the Spring
sky, and PanSTARRS (Chambers et al. 2016) in both the Fall
and Spring skies. The medium-deep survey targeted areas with
substantial ancillary data in the Herschel-ATLAS (Eales et al. 2010)
North Galactic Pole field (Smith et al. 2017), and a volume of
particular environmental interest in the Perseus-Pisces supercluster.
Apertif released its first year of imaging data to the community in
late 2020²⁴ (Adams et al. 2020), and the data are described in further
detail by Adams et al. (2022). A companion paper describes the radio-
continuum source catalogue for DR1 (Kutkin et al. 2022). Processing
of the full survey data is currently ongoing. Together, the two Apertif
surveys are expected to yield thousands of H I-detected galaxies, of
which about 10–15 per cent have optical dimensions and a surface
brightness distribution that fit the field of view of WEAVE’s LIFU
for our required signal-to-noise ratio (S/N). The Apertif H I surveys
will provide redshifts, neutral gas content, environment densities,
morphologies, kinematics, and dynamical masses at the aforemen-
tioned resolutions. Furthermore, Apertif will also detect and measure
H I absorption against radio-loud AGNs, yielding information on gas
accretion and outflows, provide spatially resolved, extinction-free
star formation maps from the radio continuum emission, and identify
OH megamasers as locations of intense star formation (Hess et al.
2021).

The natural goal when exploiting the synergy between a spatially
resolved H I survey and the data coming from the LIFU mode of
WEAVE is to compare in detail the cold gas properties of the
H I-selected sample with the spatially resolved properties (stellar
and ionized gas) of those galaxies. WEAVE-Apertif will study
the transformation of gas into stars within galaxies by comparing
the optical and ISM properties of galaxies belonging to the so-
called main star-forming sequence, the red sequence, and the
intermediate region, distinguishing whether the last represents a
transition population triggered by a quenching episode in the fairly
recent past (e.g. Schawinski et al. 2014) or smoothly evolving on
timescales comparable to the age of the Universe (e.g. Casado et al.
2015).

With this goal in mind, we will select a sample of around 400
galaxies from the Apertif survey covering the following parameters
with at least five galaxies per bin: H I mass, H I morphology
(perturbed or not), stellar mass, and star formation. The unique aspect
of this survey (compared to other IFU surveys) resides in the H I
selection of targets, which enables the detailed analysis of galaxies
in different stages of the transformation process. We will use the
LIFU in both low and high spectral resolution modes to study nearby
galaxies. A large-scale integral-field survey with WEAVE creates

a strong synergy with the Apertif imaging surveys, significantly
increasing the power of both instruments as compared to each on
its own.

Fig. 13 illustrates the kind of regular and perturbed galaxies that we expect to probe during the WEAVE-Apertif survey and the typical spatial coverage of the LIFU. In addition, the bottom panel shows examples of the spectral coverage and instrumental modes that will be used for the different science cases planned for the survey. While the LR mode will be most useful for emission-line morphologies/diagnostics and stellar-population studies, the HR mode will allow us to measure the stellar kinematics of both the stars and ionized gas with unprecedented accuracy, especially for low-mass systems.

4.4.2 Scientific goals of the WEAVE-Apertif survey

In the optical, galaxies are distributed according to their colour and luminosity (based on the colour–magnitude diagram, e.g. Bell et al. 2004) in two main groups – the red sequence and blue cloud, with a transitioning class named the green valley. The physical processes governing the movement of a galaxy from one group to another are still unclear, with the following questions still open: Why is there a bimodality in galaxy properties today, such that there are both star-forming blue galaxies and red-and-dead galaxies? Where does the gas fuelling the star formation in these galaxies come from? And how is star formation in galaxies regulated?

WEAVE-Apertif will analyse the spatially resolved stellar and ionized gas properties of galaxies, sampling the colour–magnitude diagram with respect to their H I properties (e.g. mass and morphology) and general environment to address the possible mechanisms that regulate the conversion of gas into stars within galaxies, including potential rejuvenation or quenching episodes. We will establish what processes – revealed by the Apertif H I images, such as major mergers, accretion of small gas-rich satellites, tidal- or ram-pressure gas stripping – have a direct impact on (i) the star formation history of galaxies, (ii) the spatial distribution of star formation in their discs, (iii) the physical state of the ionized ISM, and (iv) the foreseeable evolution of galaxies. To this aim, we will observe the full sample of ~400 galaxies in the LR LIFU mode of WEAVE (R ~ 2500) with S/N per Å per spatial bin sufficient to derive stellar population parameters. These data will allow us to derive spatially resolved mean stellar ages and metallicities, as well as [α/Fe] ratios. The data will also make possible the detection of kinematic twists, warps, and decoupled components. The WEAVE-Apertif survey will also deliver spatially resolved stellar-age distributions, ionized-gas metallicities, and star formation rates that, together with the H I data, will provide a true legacy survey.

As the effects of the environment on the general properties of
galaxies will have been revealed by the LR data set, a detailed study
of a subsample of galaxies using the high-resolution capabilities of
the LIFU will help to establish the effects of H I accretion history in
the secular (i.e. internal) evolution of spiral-galaxy discs (for a review,
see van Gorkom 2013). The impact of the H I accretion history on
the chemo-dynamical properties of galaxies can be quantified by
analysing the stellar kinematics and stellar properties of a sample
of galaxies with perturbed H I morphologies, and comparing them
to those of galaxies with no signs of perturbed H I morphologies.
Our study will allow us to provide answers to crucial questions such
as the following: What is the process driving radial migration of
stars? What is the level of scattering and radial motions induced by
spiral arms and bars in stars? What is the impact of the accretion

<footnote n="23">²³https://www.astron.nl/telescopes/wsrt-apertif</footnote>

<footnote n="24">²⁴https://www.astron.nl/telescopes/wsrt-apertif/apertif-dr1-documentation</footnote>
be tuned to operate between roughly 1130 and 1750 MHz, although observations were heavily impacted by radio frequency interference below ~1300 MHz. With about half of the sensitivity of the original single-pixel WSRT front-end, the wide field of view of Apertif nonetheless drastically enhanced the survey speed of WSRT by imaging an area on the sky about 25 times the size of the full moon in a single pointing.

Apertif conducted a two-tiered H I imaging survey<fnref n="23" /> that provides a strong synergy with WEAVE: a medium-deep survey of 150 deg² and a wide-area survey of approximately 2200 deg² between ~+27 and 65 deg declination (Hess et al., in preparation). The wide-area survey targeted areas with multiwavelength coverage from Northern sky surveys including LOFAR, SDSS, and the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX; Hill et al. 2008) in the Spring sky, and PanSTARRS (Chambers et al. 2016) in both the Fall and Spring skies. The medium-deep survey targeted areas with substantial ancillary data in the Herschel-ATLAS (Eales et al. 2010), North Galactic Pole field (Smith et al. 2017), and a volume of particular environmental interest in the Perseus-Pisces supercluster. Apertif released its first year of imaging data to the community in late 2020²⁴ (Adams et al. 2020), and the data are described in further detail by Adams et al. (2022). A companion paper describes the radio-continuum source catalogue for DR1 (Kutkin et al. 2022). Processing of the full survey data is currently ongoing. Together, the two Apertif surveys are expected to yield thousands of H I-detected galaxies, of which about 10–15 per cent have optical dimensions and a surface brightness distribution that fit the field of view of WEAVE’s LIFU for our required signal-to-noise ratio (S/N). The Apertif H I surveys will provide redshifts, neutral gas content, environment densities, morphologies, kinematics, and dynamical masses at the aforementioned resolutions. Furthermore, Apertif will also detect and measure H I absorption against radio-loud AGNs, yielding information on gas accretion and outflows, provide spatially resolved, extinction-free star formation maps from the radio continuum emission, and identify OH megamasers as locations of intense star formation (Hess et al. 2021).

The natural goal when exploiting the synergy between a spatially resolved H I survey and the data coming from the LIFU mode of WEAVE is to compare in detail the cold gas properties of the H I-selected sample with the spatially resolved properties (stellar and ionized gas) of those galaxies. WEAVE-Apertif will study the transformation of gas into stars within galaxies by comparing the optical and ISM properties of galaxies belonging to the so-called main star-forming sequence, the red sequence, and the intermediate region, distinguishing whether the last represents a transition population triggered by a quenching episode in the fairly recent past (e.g. Schawinski et al. 2014) or smoothly evolving on timescales comparable to the age of the Universe (e.g. Casado et al. 2015).

With this goal in mind, we will select a sample of around 400 galaxies from the Apertif survey covering the following parameters with at least five galaxies per bin: H I mass, H I morphology (perturbed or not), stellar mass, and star formation. The unique aspect of this survey (compared to other IFU surveys) resides in the H I selection of targets, which enables the detailed analysis of galaxies in different stages of the transformation process. We will use the LIFU in both low and high spectral resolution modes to study nearby galaxies. A large-scale integral-field survey with WEAVE creates

a strong synergy with the Apertif imaging surveys, significantly increasing the power of both instruments as compared to each on its own.

Fig. 13 illustrates the kind of regular and perturbed galaxies that we expect to probe during the WEAVE-Apertif survey and the typical spatial coverage of the LIFU. In addition, the bottom panel shows examples of the spectral coverage and instrumental modes that will be used for the different science cases planned for the survey. While the LR mode will be most useful for emission-line morphologies/diagnostics and stellar-population studies, the HR mode will allow us to measure the stellar kinematics of both the stars and ionized gas with unprecedented accuracy, especially for low-mass systems.

### 4.4.2 Scientific goals of the WEAVE-Apertif survey

In the optical, galaxies are distributed according to their colour and luminosity (based on the colour–magnitude diagram, e.g. Bell et al. 2004) in two main groups – the red sequence and blue cloud, with a transitioning class named the green valley. The physical processes governing the movement of a galaxy from one group to another are still unclear, with the following questions still open: Why is there a bimodality in galaxy properties today, such that there are both star-forming blue galaxies and red-and-dead galaxies? Where does the gas fuelling the star formation in these galaxies come from? And how is star formation in galaxies regulated?

WEAVE-Apertif will analyse the spatially resolved stellar and ionized gas properties of galaxies, sampling the colour–magnitude diagram with respect to their H I properties (e.g. mass and morphology) and general environment to address the possible mechanisms that regulate the conversion of gas into stars within galaxies, including potential rejuvenation or quenching episodes. We will establish what processes – revealed by the Apertif H I images, such as major mergers, accretion of small gas-rich satellites, tidal- or ram-pressure gas stripping – have a direct impact on (i) the star formation history of galaxies, (ii) the spatial distribution of star formation in their discs, (iii) the physical state of the ionized ISM, and (iv) the foreseeable evolution of galaxies. To this aim, we will observe the full sample of ~400 galaxies in the LR LIFU mode of WEAVE (R ~ 2500) with S/N per Å per spatial bin sufficient to derive stellar population parameters. These data will allow us to derive spatially resolved mean stellar ages and metallicities, as well as [α/Fe] ratios. The data will also make possible the detection of kinematic twists, warps, and decoupled components. The WEAVE-Apertif survey will also deliver spatially resolved stellar-age distributions, ionized-gas metallicities, and star formation rates that, together with the H I data, will provide a true legacy survey.

As the effects of the environment on the general properties of galaxies will have been revealed by the LR data set, a detailed study of a subsample of galaxies using the high-resolution capabilities of the LIFU will help to establish the effects of H I accretion history in the secular (i.e. internal) evolution of spiral-galaxy discs (for a review, see van Gorkom 2013). The impact of the H I accretion history on the chemo-dynamical properties of galaxies can be quantified by analysing the stellar kinematics and stellar properties of a sample of galaxies with perturbed H I morphologies, and comparing them to those of galaxies with no signs of perturbed H I morphologies. Our study will allow us to provide answers to crucial questions such as the following: What is the process driving radial migration of stars? What is the level of scattering and radial motions induced by spiral arms and bars in stars? What is the impact of the accretion

<footnote n="23">²³https://www.astron.nl/telescopes/wsrt-apertif</footnote>

<footnote n="24">²⁴https://www.astron.nl/telescopes/wsrt-apertif/apertif-dr1-documentation</footnote>
<figure><img src="image_13.png" /><figcaption>**Figure 13.** Examples of typical galaxies to be observed in the WEAVE-Apertif survey. Top panels: H1 contours plotted over SDSS colour images. The WEAVE LIFU footprint is indicated in red over the SDSS image. The galaxy on the left, UGC 9837, is the proto-typical example of a *regular* galaxy, whereas the galaxy on the right, NGC 3769, represents a *perturbed* case. Bottom panel: example of spectral instrumental set-ups used for the survey. The black line (main line, covering the entire wavelength range) shows the wavelength range of our LR observations (R ~ 2500), while the green and red lines (covering shorter wavelength ranges, centred around 5100 and 6400 Å, respectively) indicate the wavelength coverage of the two HR arms (R ~ 10 000). Shaded areas mark the location of some of the main spectral features in our wavelength range, which can be found in absorption (blue), emission (red), or both (green).</figcaption></figure>

of satellites in the chemo-dynamical properties of galaxies? And how does this all connect with observations in the Milky Way, as revealed, for example, through the GA survey described in Section 4.1?

To accomplish these aims, we will analyse in detail the line-of-sight velocity distribution (velocity, velocity dispersion, and higher-order moments) of a sample of low-inclination nearby objects (including both high- and low-surface-brightness galaxies), exploiting WEAVE's HR LIFU mode (R ~ 10 000). The sample will include 30–50 galaxies with perturbed H1 morphologies and approximately the same number of galaxies with non-perturbed H1 morphologies, all taken from the parent low-resolution sample of 400 galaxies. The success of the project and its legacy impact rely on obtaining quality data reaching $\mu_g = 24 \text{ mag arcsec}^{-2}$ at $\sim 3\sigma$.

Finally, these data sets will enable us to constrain the disc mass of the full sample of 400 Apertif galaxies, allowing us to relate dynamical mass to the environment. The dark matter content in both high- and low-surface-brightness galaxies can be constrained by combining kinematic data from both H1 and optical data and applying the traditional technique of rotation-curve decomposition as well as other dynamical modelling techniques. However, the actual total mass residing within a galaxy's disc remains a controversial matter. This is an important calculation to get right, as the mass-to-light ratio of a disc determines the disc's contribution to the galaxy's

rotation curve, which in turn constrains the density and scale length of the halo. The WEAVE-Apertif survey will be able to expand on previous efforts on this topic (e.g. DiskMass survey; Bershady et al. 2010) and constrain the surface mass density of discs using stellar velocity dispersions, with the HR mode being of particular value to the challenges presented by low-mass systems. The mass modelling will be possible for the entire sample of galaxies included in the two projects mentioned above, using different modelling techniques.

In line with many of the other WEAVE surveys, an extra programme has also been designed within the WEAVE-Apertif survey to help maximize the use of sub-optimal weather conditions and/or undersubscribed observing conditions, while simultaneously extending the scientific output of the survey by relieving some of our most stringent constraints on sample selection. Within this programme, there will be no restrictions to stay within the Apertif footprint, and the removal of this condition will allow for a much more flexible scheduling that will enable us to venture into the ALFALFA survey (Giovanelli et al. 2007) to obtain upper limit H1 mass estimates. In addition, we will allow for the inclusion of highly inclined galaxies and compact ($\le 0.2$ arcmin) high-surface-brightness systems. This will enable us to obtain observations for certain types of galaxies that would otherwise be missed in the main survey, for example Markarian galaxies, which usually display peculiar H1 properties.
<figure><img src="image_14.png" /><figcaption>**Figure 13.** Examples of typical galaxies to be observed in the WEAVE-Apertif survey. Top panels: H1 contours plotted over SDSS colour images. The WEAVE LIFU footprint is indicated in red over the SDSS image. The galaxy on the left, UGC 9837, is the proto-typical example of a *regular* galaxy, whereas the galaxy on the right, NGC 3769, represents a *perturbed* case. Bottom panel: example of spectral instrumental set-ups used for the survey. The black line (main line, covering the entire wavelength range) shows the wavelength range of our LR observations (R ~ 2500), while the green and red lines (covering shorter wavelength ranges, centred around 5100 and 6400 Å, respectively) indicate the wavelength coverage of the two HR arms (R ~ 10 000). Shaded areas mark the location of some of the main spectral features in our wavelength range, which can be found in absorption (blue), emission (red), or both (green).</figcaption></figure>

of satellites in the chemo-dynamical properties of galaxies? And how does this all connect with observations in the Milky Way, as revealed, for example, through the GA survey described in Section 4.1?

To accomplish these aims, we will analyse in detail the line-of-sight velocity distribution (velocity, velocity dispersion, and higher-order moments) of a sample of low-inclination nearby objects (including both high- and low-surface-brightness galaxies), exploiting WEAVE's HR LIFU mode (R ~ 10 000). The sample will include 30–50 galaxies with perturbed H1 morphologies and approximately the same number of galaxies with non-perturbed H1 morphologies, all taken from the parent low-resolution sample of 400 galaxies. The success of the project and its legacy impact rely on obtaining quality data reaching $\mu_g = 24 \text{ mag arcsec}^{-2}$ at $\sim 3\sigma$.

Finally, these data sets will enable us to constrain the disc mass of the full sample of 400 Apertif galaxies, allowing us to relate dynamical mass to the environment. The dark matter content in both high- and low-surface-brightness galaxies can be constrained by combining kinematic data from both H1 and optical data and applying the traditional technique of rotation-curve decomposition as well as other dynamical modelling techniques. However, the actual total mass residing within a galaxy's disc remains a controversial matter. This is an important calculation to get right, as the mass-to-light ratio of a disc determines the disc's contribution to the galaxy's

rotation curve, which in turn constrains the density and scale length of the halo. The WEAVE-Apertif survey will be able to expand on previous efforts on this topic (e.g. DiskMass survey; Bershady et al. 2010) and constrain the surface mass density of discs using stellar velocity dispersions, with the HR mode being of particular value to the challenges presented by low-mass systems. The mass modelling will be possible for the entire sample of galaxies included in the two projects mentioned above, using different modelling techniques.

In line with many of the other WEAVE surveys, an extra programme has also been designed within the WEAVE-Apertif survey to help maximize the use of sub-optimal weather conditions and/or undersubscribed observing conditions, while simultaneously extending the scientific output of the survey by relieving some of our most stringent constraints on sample selection. Within this programme, there will be no restrictions to stay within the Apertif footprint, and the removal of this condition will allow for a much more flexible scheduling that will enable us to venture into the ALFALFA survey (Giovanelli et al. 2007) to obtain upper limit H1 mass estimates. In addition, we will allow for the inclusion of highly inclined galaxies and compact ($\le 0.2$ arcmin) high-surface-brightness systems. This will enable us to obtain observations for certain types of galaxies that would otherwise be missed in the main survey, for example Markarian galaxies, which usually display peculiar H1 properties.
## 4.5 The WEAVE Galaxy Clusters Survey

On the largest scales, matter is distributed as a vast network of filaments and sheets that connect dense galaxy clusters and groups. This cosmic web (Bond, Kofman & Pogosyan 1996) is the environment in which galaxies form and evolve. Relative to the small volume they occupy (much less than one per cent of the volume of the Universe), clusters and groups contain the largest fraction of the mass of the Universe (Cautun, van de Weygaert & Jones 2012; Tempel et al. 2014; Ganeshaiah Veena et al. 2019). Observations of galaxies in clusters are therefore of great interest, both for a test of galaxy formation in dense environments and as a measure of environmental influences on galaxy evolution. Consequently, in order to make meaningful progress in our understanding of galaxy evolution, we must consider galaxies evolving in relation to their environment, defined both by their local density and the global large-scale structure.

Observations of cluster galaxies have firmly established the importance of the environment in addition to galaxy mass for shaping galaxy properties: morphology, colour, star formation rate, stellar age, and AGN fraction correlate with both local galaxy density and location inside or outside clusters (e.g. Dressler 1980; Blanton et al. 2005; Postman et al. 2005; Smith et al. 2005; Bamford et al. 2009). In clusters, the fraction of early-type galaxies, defined either morphologically or by the amount of current star formation, is much higher than in the average, lower-density Universe, often referred to as the 'field'. Related studies show that cluster galaxies possess much less cold gas than field galaxies (e.g. Cayatte et al. 1990; Serra et al. 2011) and that galaxy luminosity functions are steeper for cluster galaxies, owing to the change in the relative contribution of massive quiescent galaxies (e.g. De Propris et al. 2003). These well-established findings may be summarized as manifestations of the morphology–density relation (Dressler 1980) and are related to the result of a series of processes involving the mass assembly, star formation, and morphological evolution of these galaxies (see e.g. Boselli & Gavazzi 2006). A variety of interactions with the hot intracluster medium (e.g. Gunn & Gott 1972; Bekki, Couch & Shioya 2001; Kawata & Mulchaey 2008; Zinger et al. 2018), as well as interactions and fly-bys of galaxies in this medium (e.g. Gnedin 2003; Aguerri & González-García 2009; Park & Hwang 2009; Sinha & Holley-Bockelmann 2012; Méndez-Abreu et al. 2014), affect the gas – and often the stellar – content of galaxies. Importantly, the accumulated effect of various galaxy encounters and the loss of gas, ultimately resulting in the suppression of star formation, may stimulate the transformation of late-type galaxies into early-type galaxies in dense environments (Moore et al. 1996; Boselli & Gavazzi 2006; Cappellari 2013; Kuchner et al. 2017; Joshi et al. 2020).

Despite active research on this topic, it is still a matter of debate as to which of the proposed physical mechanisms drive the evolution of galaxies in high-density environments and their relative importance (for a review, see Boselli & Gavazzi 2014). The difficulty lies in disentangling subtle and competing processes that act on different timescales. In addition, quantification of the observed changes has mainly been focused on the end point in the virialized regions of clusters. However, half of a nearby cluster's galaxy population originates from the cosmic web (McGee et al. 2009; Dressler et al. 2013). Clusters grow by accreting galaxies from their surroundings, and a significant fraction of cluster galaxies have therefore been environmentally affected long before they fall into the cluster. This effect is called 'pre-processing' and is receiving increasing attention by the community (e.g. Wetzel et al. 2013).

The morphology–density relation is particularly strong for dwarf galaxies (Peng et al. 2010; Kovač et al. 2014; Tal et al. 2014; Wetzel, Tollerud & Weisz 2015): early-type dwarfs (dwarf elliptical and dwarf spheroidals) dominate the galaxy population in clusters, but they are very rarely found in the field (Geha et al. 2012; Grossi et al. 2016). Despite their smooth appearances, these systems are more complex than they might appear: dwarf ellipticals can host stellar late-type features such as discs and spiral arms (Jerjen, Kalnajs & Binggeli 2000; Lisker, Grebel & Binggeli 2006; Lisker et al. 2007; Janz et al. 2012), some with clear signs of rotation (Pedraz et al. 2002; Toloba et al. 2009) and atomic gas or dust components (di Serego Alighieri et al. 2007, 2013; Hallenbeck et al. 2017). Star-forming dwarf galaxies accreted into a cluster are easily stripped of their gas and dust when interacting with the cluster environment (Grossi et al. 2015, 2016), but the variety of signatures suggests that more than one process may determine dwarf-galaxy evolution.

Evidently, stellar mass is a dominant driver for galaxy evolution (e.g. Kauffmann et al. 2004; Peng et al. 2010). However, intrinsic properties like galaxy mass are highly dependent on their surrounding large-scale environment through their assembly process. Thus, a comprehensive theory of galaxy formation and evolution must account for the influence of the environment on galaxy evolution while carefully controlling for stellar mass. Within this context, several, large, multiwavelength studies of galaxy clusters have successfully used cluster number counts as a function of mass and redshift to constrain cosmological models (Rozo et al. 2009; de Haan et al. 2016; Planck Collaboration XXXVI 2016a; Planck Collaboration XXIV 2016b; Planck Collaboration XXVII 2016c; Pacaud et al. 2018). The complexity of the physical processes acting in clusters complicates the obtaining of reliable mass determinations, forcing us to fall back on having to rely on combining a number of scaling relations at various wavelengths. This is still a paramount challenge for performing precision cosmology using clusters for next-generation surveys such as the LSST, and surveys with *Euclid* and the *Nancy Grace Roman Space Telescope* (see e.g. Salvati, Douspis & Aghanim 2020).

The WEAVE Galaxy Clusters survey was designed as a response to these challenges. The main goal of the survey is to provide a better understanding of the impact of different environmentally induced physical mechanisms on galaxy evolution. Three layers focus on three complementary aspects: WEAVE Galaxy Clusters aims to (1) gain a detailed understanding of the formation history of low-mass dwarf galaxies in dense environments; (2) follow mass and stellar assembly of clusters from the cosmic web through filamentary accretion; and (3) obtain an accurate calibration of the scaling relations and perform precision cosmology on a complete sample of Sunyaev–Zeldovich (SZ) effect-selected clusters (Planck Collaboration XXVII 2016c), and infer the star formation histories of the galaxies in the cores of these clusters (see Fig. 14, which summarizes the three observing modes for WEAVE Galaxy Clusters).

(i) **Layer 1 – WEAVE Nearby Clusters (WCN) survey:** Low-mass systems dominate the galaxy population at all redshifts, and are crucial for the hierarchical build-up of galaxies. However, the processes driving the formation of dwarf galaxies and how the environment affects their evolution are poorly understood (e.g. Silk & Mamon 2012). The transformation from a star-forming to a passive dwarf galaxy could involve ISM removal by ram pressure, a series of tidal interactions that kinematically heat the stellar disc and thereby modify its morphology (Gnedin 2003; Lisker et al. 2009; Toloba et al. 2015). The main goal of the Nearby Clusters survey is to study the
## 4.5 The WEAVE Galaxy Clusters Survey

On the largest scales, matter is distributed as a vast network of filaments and sheets that connect dense galaxy clusters and groups. This cosmic web (Bond, Kofman & Pogosyan 1996) is the environment in which galaxies form and evolve. Relative to the small volume they occupy (much less than one per cent of the volume of the Universe), clusters and groups contain the largest fraction of the mass of the Universe (Cautun, van de Weygaert & Jones 2012; Tempel et al. 2014; Ganeshaiah Veena et al. 2019). Observations of galaxies in clusters are therefore of great interest, both for a test of galaxy formation in dense environments and as a measure of environmental influences on galaxy evolution. Consequently, in order to make meaningful progress in our understanding of galaxy evolution, we must consider galaxies evolving in relation to their environment, defined both by their local density and the global large-scale structure.

Observations of cluster galaxies have firmly established the importance of the environment in addition to galaxy mass for shaping galaxy properties: morphology, colour, star formation rate, stellar age, and AGN fraction correlate with both local galaxy density and location inside or outside clusters (e.g. Dressler 1980; Blanton et al. 2005; Postman et al. 2005; Smith et al. 2005; Bamford et al. 2009). In clusters, the fraction of early-type galaxies, defined either morphologically or by the amount of current star formation, is much higher than in the average, lower-density Universe, often referred to as the 'field'. Related studies show that cluster galaxies possess much less cold gas than field galaxies (e.g. Cayatte et al. 1990; Serra et al. 2011) and that galaxy luminosity functions are steeper for cluster galaxies, owing to the change in the relative contribution of massive quiescent galaxies (e.g. De Propris et al. 2003). These well-established findings may be summarized as manifestations of the morphology-density relation (Dressler 1980) and are related to the result of a series of processes involving the mass assembly, star formation, and morphological evolution of these galaxies (see e.g. Boselli & Gavazzi 2006). A variety of interactions with the hot intracluster medium (e.g. Gunn & Gott 1972; Bekki, Couch & Shioya 2001; Kawata & Mulchaey 2008; Zinger et al. 2018), as well as interactions and fly-bys of galaxies in this medium (e.g. Gnedin 2003; Aguerri & González-García 2009; Park & Hwang 2009; Sinha & Holley-Bockelmann 2012; Méndez-Abreu et al. 2014), affect the gas – and often the stellar – content of galaxies. Importantly, the accumulated effect of various galaxy encounters and the loss of gas, ultimately resulting in the suppression of star formation, may stimulate the transformation of late-type galaxies into early-type galaxies in dense environments (Moore et al. 1996; Boselli & Gavazzi 2006; Cappellari 2013; Kuchner et al. 2017; Joshi et al. 2020).

Despite active research on this topic, it is still a matter of debate as to which of the proposed physical mechanisms drive the evolution of galaxies in high-density environments and their relative importance (for a review, see Boselli & Gavazzi 2014). The difficulty lies in disentangling subtle and competing processes that act on different timescales. In addition, quantification of the observed changes has mainly been focused on the end point in the virialized regions of clusters. However, half of a nearby cluster's galaxy population originates from the cosmic web (McGee et al. 2009; Dressler et al. 2013). Clusters grow by accreting galaxies from their surroundings, and a significant fraction of cluster galaxies have therefore been environmentally affected long before they fall into the cluster. This effect is called 'pre-processing' and is receiving increasing attention by the community (e.g. Wetzel et al. 2013).

The morphology-density relation is particularly strong for dwarf galaxies (Peng et al. 2010; Kovač et al. 2014; Tal et al. 2014; Wetzel, Tollerud & Weisz 2015): early-type dwarfs (dwarf elliptical and dwarf spheroidals) dominate the galaxy population in clusters, but they are very rarely found in the field (Geha et al. 2012; Grossi et al. 2016). Despite their smooth appearances, these systems are more complex than they might appear: dwarf ellipticals can host stellar late-type features such as discs and spiral arms (Jerjen, Kalnajs & Binggeli 2000; Lisker, Grebel & Binggeli 2006; Lisker et al. 2007; Janz et al. 2012), some with clear signs of rotation (Pedraz et al. 2002; Toloba et al. 2009) and atomic gas or dust components (di Serego Alighieri et al. 2007, 2013; Hallenbeck et al. 2017). Star-forming dwarf galaxies accreted into a cluster are easily stripped of their gas and dust when interacting with the cluster environment (Grossi et al. 2015, 2016), but the variety of signatures suggests that more than one process may determine dwarf-galaxy evolution.

Evidently, stellar mass is a dominant driver for galaxy evolution (e.g. Kauffmann et al. 2004; Peng et al. 2010). However, intrinsic properties like galaxy mass are highly dependent on their surrounding large-scale environment through their assembly process. Thus, a comprehensive theory of galaxy formation and evolution must account for the influence of the environment on galaxy evolution while carefully controlling for stellar mass. Within this context, several, large, multiwavelength studies of galaxy clusters have successfully used cluster number counts as a function of mass and redshift to constrain cosmological models (Rozo et al. 2009; de Haan et al. 2016; Planck Collaboration XXXVI 2016a; Planck Collaboration XXIV 2016b; Planck Collaboration XXVII 2016c; Pacaud et al. 2018). The complexity of the physical processes acting in clusters complicates the obtaining of reliable mass determinations, forcing us to fall back on having to rely on combining a number of scaling relations at various wavelengths. This is still a paramount challenge for performing precision cosmology using clusters for next-generation surveys such as the LSST, and surveys with *Euclid* and the *Nancy Grace Roman Space Telescope* (see e.g. Salvati, Douspis & Aghanim 2020).

The WEAVE Galaxy Clusters survey was designed as a response to these challenges. The main goal of the survey is to provide a better understanding of the impact of different environmentally induced physical mechanisms on galaxy evolution. Three layers focus on three complementary aspects: WEAVE Galaxy Clusters aims to (1) gain a detailed understanding of the formation history of low-mass dwarf galaxies in dense environments; (2) follow mass and stellar assembly of clusters from the cosmic web through filamentary accretion; and (3) obtain an accurate calibration of the scaling relations and perform precision cosmology on a complete sample of Sunyaev-Zeldovich (SZ) effect-selected clusters (Planck Collaboration XXVII 2016c), and infer the star formation histories of the galaxies in the cores of these clusters (see Fig. 14, which summarizes the three observing modes for WEAVE Galaxy Clusters).

(i) **Layer 1 – WEAVE Nearby Clusters (WCN) survey:** Low-mass systems dominate the galaxy population at all redshifts, and are crucial for the hierarchical build-up of galaxies. However, the processes driving the formation of dwarf galaxies and how the environment affects their evolution are poorly understood (e.g. Silk & Mamon 2012). The transformation from a star-forming to a passive dwarf galaxy could involve ISM removal by ram pressure, a series of tidal interactions that kinematically heat the stellar disc and thereby modify its morphology (Gnedin 2003; Lisker et al. 2009; Toloba et al. 2015). The main goal of the Nearby Clusters survey is to study the
<figure><img src="image_14.png" /></figure>

**Figure 14.** The WEAVE Galaxy Clusters survey encompasses three layers that observe in the three instrument modes, as illustrated in this image of cluster Abell 2142 (background image from PanSTARRS1). Layer 1 focuses on cluster-dwarf-galaxy evolution and uses the mIFU mode centred on selected dwarf galaxies (red circles), which will be selected from previous MOS spectra. The zoomed-in image shows the mIFU arrangement of 37 fibres placed on a single dwarf galaxy. Layer 2 focuses on the filamentary large-scale structures that feed galaxy clusters, and uses WEAVE's ~1000-fibre MOS mode (yellow diamonds). Each cluster will be covered by up to 20 pointings. Layer 3 focuses on the evolution of central cluster galaxies, and cosmological constraints that can be drawn from cluster scaling relations. It uses WEAVE's LIFU mode (blue squares), highlighted in the zoomed-in image that shows a LIFU pattern placed on a group falling into Abell 2142.

properties and formation history of dwarf galaxies in high-density environments.

Specific scientific questions addressed in this layer of the survey include: Are dwarf galaxies primordial or the end products of galaxy transformations? How do dwarf galaxies contribute to 'archaeological downsizing' of galaxies (e.g. Nelan et al. 2005; Thomas et al. 2005)? What processes drive the transformation of dwarf galaxies in clusters? What are the internal dynamics of dwarf galaxies; are they dark-matter-dominated systems, and what are their angular momenta? How do these processes depend on properties of the galaxies themselves, e.g. stellar populations, metallicities, mass, and star formation history, as well as their local environment?

The WCN survey is a low-spectral-resolution programme combining the MOS and mIFU modes of WEAVE (see Fig. 15). WCN will observe an X-ray flux-limited sample of 47 nearby galaxy clusters in the redshift range $0.01 < z < 0.04$, covering a large range in cluster mass [$13.2 < \log(M_*/M_\odot) < 14.5$], corresponding to X-ray luminosities of $\log(L_{500}) \in [42, 45]$. This survey will provide single-fibre spectroscopic information for several thousands of dwarf-galaxy ($M_r < -16$) members, thus providing the largest spectroscopically confirmed sample of dwarf-galaxy cluster members observed so far. In addition, we will obtain spatially resolved spectroscopic information for ~1000 dwarf cluster members using the mIFU mode. The cluster sample is compiled from ROSAT All-Sky Survey data: the ROSAT Brightest Cluster Sample (BCS; Ebeling et al. 1998) and its extension (eBCS; Ebeling et al. 2000). The BCS is 90 per cent complete for fluxes higher than $4.4 \times 10^{-12} \text{ erg cm}^{-2} \text{ s}^{-1}$ in the ROSAT 0.1–2.4 keV band. The eBCS extends the BCS down to $2.8 \times 10^{-12} \text{ erg cm}^{-2} \text{ s}^{-1}$ with 75 per cent completeness. The

<figure><img src="image_15.png" /></figure>

**Figure 15.** The WCN survey aims to obtain high-resolution spectroscopy in both MOS and mIFU observing modes for a significant population of dwarf galaxies in every cluster. The example in the middle panel shows archival images for A2152 from the SDSS with two selected dwarf galaxies with absolute magnitudes $M_r \sim -17$. Top panel: a one-dimensional spectrum of an example dwarf galaxy (not shown in the image in the middle panel) is extracted from Toloba et al. (2014). Bottom panel: two-dimensional velocity and velocity dispersion maps of another example dwarf galaxy from Ryś, Falcón-Barroso & van de Ven (2013).

WEAVE field of view allows us to observe galaxies in the range $0 \le r/r_{200} < 1-2$ in a single pointing for the selected redshift range, where $r_{200}$ is the cluster radius within which the mean density is 200 times the critical energy density of the Universe at that redshift. The general survey strategy of using 1-hour observing blocks alongside dedicated, existing photometry ensures that selected targets will have an $S/N \ge 5 \AA^{-1}$ in the galaxy spectra for galaxies with mean surface brightness within a 1.3 arcsec aperture of $22 \text{ mag arcsec}^{-2}$. We thus expect to obtain LR spectra with high enough $S/N$ to obtain reliable radial velocities for all galaxies down to $M_r \sim -16.0$ in our selected clusters.<fnref n="25" /> This is equivalent to tracing the galaxy luminosity function down to at least $M^* + 6$ for all of the clusters, where $M^*$ is magnitude of the knee of the luminosity function. The sample is statistically large enough to study the effects of cluster properties (e.g. mass, galaxy density, cluster velocity dispersion) on the evolution of dwarf galaxies. We will therefore be able to explore systematic differences in dwarf galaxy properties related to the main properties of cluster environments, together with cluster-to-cluster variations.

<footnote n="25">²⁵At the mean redshift of the cluster survey, the limiting magnitude of the observations will be $M_r \sim -15.0$, and for the closest ones $M_r \sim -14.0$.</footnote>
<figure><img src="image_15.png" /></figure>

**Figure 14.** The WEAVE Galaxy Clusters survey encompasses three layers that observe in the three instrument modes, as illustrated in this image of cluster Abell 2142 (background image from PanSTARRS1). Layer 1 focuses on cluster-dwarf-galaxy evolution and uses the mIFU mode centred on selected dwarf galaxies (red circles), which will be selected from previous MOS spectra. The zoomed-in image shows the mIFU arrangement of 37 fibres placed on a single dwarf galaxy. Layer 2 focuses on the filamentary large-scale structures that feed galaxy clusters, and uses WEAVE's ~1000-fibre MOS mode (yellow diamonds). Each cluster will be covered by up to 20 pointings. Layer 3 focuses on the evolution of central cluster galaxies, and cosmological constraints that can be drawn from cluster scaling relations. It uses WEAVE's LIFU mode (blue squares), highlighted in the zoomed-in image that shows a LIFU pattern placed on a group falling into Abell 2142.

properties and formation history of dwarf galaxies in high-density environments.

Specific scientific questions addressed in this layer of the survey include: Are dwarf galaxies primordial or the end products of galaxy transformations? How do dwarf galaxies contribute to 'archaeological downsizing' of galaxies (e.g. Nelan et al. 2005; Thomas et al. 2005)? What processes drive the transformation of dwarf galaxies in clusters? What are the internal dynamics of dwarf galaxies; are they dark-matter-dominated systems, and what are their angular momenta? How do these processes depend on properties of the galaxies themselves, e.g. stellar populations, metallicities, mass, and star formation history, as well as their local environment?

The WCN survey is a low-spectral-resolution programme combining the MOS and mIFU modes of WEAVE (see Fig. 15). WCN will observe an X-ray flux-limited sample of 47 nearby galaxy clusters in the redshift range $0.01 < z < 0.04$, covering a large range in cluster mass [$13.2 < \log(M_*/M_\odot) < 14.5$], corresponding to X-ray luminosities of $\log(L_{500}) \in [42, 45]$. This survey will provide single-fibre spectroscopic information for several thousands of dwarf-galaxy ($M_r < -16$) members, thus providing the largest spectroscopically confirmed sample of dwarf-galaxy cluster members observed so far. In addition, we will obtain spatially resolved spectroscopic information for ~1000 dwarf cluster members using the mIFU mode. The cluster sample is compiled from ROSAT All-Sky Survey data: the ROSAT Brightest Cluster Sample (BCS; Ebeling et al. 1998) and its extension (eBCS; Ebeling et al. 2000). The BCS is 90 per cent complete for fluxes higher than $4.4 \times 10^{-12} \text{ erg cm}^{-2} \text{ s}^{-1}$ in the ROSAT 0.1–2.4 keV band. The eBCS extends the BCS down to $2.8 \times 10^{-12} \text{ erg cm}^{-2} \text{ s}^{-1}$ with 75 per cent completeness. The

<figure><img src="image_16.png" /></figure>

**Figure 15.** The WCN survey aims to obtain high-resolution spectroscopy in both MOS and mIFU observing modes for a significant population of dwarf galaxies in every cluster. The example in the middle panel shows archival images for A2152 from the SDSS with two selected dwarf galaxies with absolute magnitudes $M_r \sim -17$. Top panel: a one-dimensional spectrum of an example dwarf galaxy (not shown in the image in the middle panel) is extracted from Toloba et al. (2014). Bottom panel: two-dimensional velocity and velocity dispersion maps of another example dwarf galaxy from Ryś, Falcón-Barroso & van de Ven (2013).

WEAVE field of view allows us to observe galaxies in the range $0 \le r/r_{200} < 1-2$ in a single pointing for the selected redshift range, where $r_{200}$ is the cluster radius within which the mean density is 200 times the critical energy density of the Universe at that redshift. The general survey strategy of using 1-hour observing blocks alongside dedicated, existing photometry ensures that selected targets will have an $S/N \ge 5 \text{ Å}^{-1}$ in the galaxy spectra for galaxies with mean surface brightness within a 1.3 arcsec aperture of $22 \text{ mag arcsec}^{-2}$. We thus expect to obtain LR spectra with high enough $S/N$ to obtain reliable radial velocities for all galaxies down to $M_r \sim -16.0$ in our selected clusters.<fnref n="25" /> This is equivalent to tracing the galaxy luminosity function down to at least $M^* + 6$ for all of the clusters, where $M^*$ is magnitude of the knee of the luminosity function. The sample is statistically large enough to study the effects of cluster properties (e.g. mass, galaxy density, cluster velocity dispersion) on the evolution of dwarf galaxies. We will therefore be able to explore systematic differences in dwarf galaxy properties related to the main properties of cluster environments, together with cluster-to-cluster variations.

<footnote n="25">²⁵At the mean redshift of the cluster survey, the limiting magnitude of the observations will be $M_r \sim -15.0$, and for the closest ones $M_r \sim -14.0$.</footnote>
<figure><img src="image_16.png" /><figcaption>**Figure 16.** The WWFCS will observe 20 nearby clusters with several WEAVE pointings to cover at least $5R_{200}$. The left side shows the observing strategy of WWFCS based on simulations from THE THREEHUNDRED simulations tailored to the survey (Cornwell et al. 2022). Each shaded blue disc represents one WEAVE pointing; the black circles are at 1 and $5r_{200}$. This particular cluster is covered with seven pointings, but others require fewer or more. The right side of the figure shows filaments identified using the software DISPERSE and groups in the infall region of the same cluster simulation (see Kuchner et al. 2020 for details).</figcaption></figure>

(ii) **Layer 2 – WEAVE Wide-Field Cluster survey (WWFCS):** To understand the effect of environment on galaxy evolution, we must understand processes acting during the assembly of clusters. This includes the collapse and feeding of clusters via filaments and groups from the cosmic web. This layer of the WEAVE Galaxy Clusters survey concentrates on the still-to-be-explored accretion physics of cluster infall regions. The WWFCS will observe galaxy clusters out to five times their virial radius to include galaxies in filaments directly feeding the clusters as well as infalling groups. WWFCS will help answer important questions such as: What kind of galaxies feed clusters? Does their fraction vary with the mass and dynamical state of the cluster? Is pre-processing in the form of gas-specific (e.g. ram-pressure stripping) or gravitational (e.g. galaxy–galaxy mergers) processes significant in groups or filaments outside the cluster cores? How and where do changes in morphology and star formation occur, over what timescales, and at which mass? How is AGN activity related to filaments? The WWFCS will observe 16–20 clusters at $z \sim 0.05$ with $13.8 < \log(M_*/M_{\odot}) < 15.5$ (where $M_*$ is the stellar mass of the cluster) that are drawn from the WINGS sample (Fasano et al. 2006), making use of the availability of extensive ancillary data in the inner region. We will obtain a complete census of galaxies in and around clusters over a broad range of masses [$10^9 < (M_*/M_{\odot}) < 10^{11.5}$], corresponding to a magnitude limit of $r = 19.75$. To ensure uniform coverage out to at least $\sim 5R_{vir}$, each cluster will be covered by between 6 and 18 MOS pointings, each with WEAVE’s 2-deg field of view (see left side of Fig. 16). Given the low density contrast of filaments (Martínez, Muriel & Coenda 2015), it is important to target the highest possible fraction of cluster and infall region members. This will be achieved by selecting galaxies with magnitudes, colours, and importantly, photometric redshifts. Photometric redshifts are obtained from the 12-band photometry of the Javalambre Photometric Local Universe Survey (J-PLUS; Cenarro et al. 2019) fields and open-time observations using the spectral energy distribution fitting code LEPHARE (Arnouts & Ilbert 2011). Tests have shown that rejecting targets with $\sim 3$ times the typical photometric redshift error of J-PLUS introduces at most $\sim 3$ per cent incompleteness, while increasing the number of cluster structure members by a factor of $\sim 2$ in comparison to a pure magnitude and colour cut. This leads to an unprecedented total of

4000–6000 structure member galaxies per cluster, which will ensure well-sampled density fields, crucial for mapping and characterizing the filamentary structure around these clusters (see right side of Fig. 16).

The WWFCS programme will use WEAVE’s MOS mode in low spectral resolution, covering 370–960 nm at $R \sim 5000$. The spectra will yield emission-line diagnostics, accurate spectral breaks, and absorption-line information for all galaxies. Velocity dispersions and accurate absorption-line information will be available for the brighter half of the galaxies individually, and statistically for the fainter half through stacking of spectra. This will shed light on the preferred routes of mass accretion and investigate the effect that this has on galaxy properties. Furthermore, the spectroscopic redshifts will be crucial for identifying cluster volumes for accurate filament extraction in redshift space (Kuchner et al. 2021). Defining filaments is a non-trivial task due to the multiscale and diffuse nature of the cosmic web (Rost et al. 2021). The challenge is to map galaxy environments in sufficient detail within – and to sufficient distance around – the dominating clusters, where the filaments converge (see right side of Fig. 16). In preparation for this survey, we have evaluated the performance of filament-finding strategies for WWFCS and quantified their robustness on hydrodynamical simulations of THE THREEHUNDRED project (Kuchner et al. 2020, 2021, 2022). The simulations are tailored to represent WWFCS cluster observations, which will also aid the interpretation of the survey’s findings (Cornwell et al. 2022).

(iii) **Layer 3 – WEAVE Cosmological Clusters survey:** The main goal of the Cosmological Clusters survey is to study the evolution of galaxies in the cores of clusters out to $z \sim 0.5$ and to place constraints on cosmological parameters and global scaling relations using a complete sample of SZ-selected clusters. The baryonic component of clusters contains a wealth of information about the processes associated with galaxy formation, including the efficiency with which baryons are converted into stars and the effects of the resulting feedback processes on galaxy formation, which then allows us to estimate the total baryon ($\Omega_b$: e.g. Voit, Kay & Bryan 2005; Borgani & Kravtsov 2011) and dark matter densities. Moreover, cluster abundance studies as a function of mass and redshift, $N(M, z)$, are powerful cosmological tools (e.g. Carlstrom, Holder & Reese 2002) that allow us to set constraints on cosmological parameters such as the dark matter and dark energy densities, or the equation of state of the dark energy (e.g. Vikhlinin et al. 2009; Mantz et al. 2010). Furthermore, by selecting galaxy clusters at $z \lesssim 0.5$, WEAVE can directly observe the evolution of the stellar populations of galaxies in cluster cores over a cosmic epoch over which galaxy transformations are already well documented (e.g. Dressler & Gunn 1982; Butcher & Oemler 1984; Dressler et al. 1997) and which can be directly compared with other WEAVE surveys like StePS (see Section 4.6). Specific science questions that will be addressed include: obtaining an accurate mass calibration and global scaling relations for a sample of 75 SZ clusters selected from Planck (Planck Collaboration XXVII 2016c); using the calibration to provide error bars a factor of two smaller than the existing ones on the key cosmological parameters $\sigma_8$ and $\Omega_m$; studying the evolution of the stellar populations for a large sample of massive galaxies in the central regions of a galaxy cluster in the last 6 Gyr of evolution, using the method pioneered by Sánchez et al. (2007); making comparisons between the $z = 0$ cluster galaxies in Layer 1 and 2 surveys and the $z \sim 0.5$ field galaxies in StePS to understand how and when early-type galaxies cease and quench their star formation activity, and transition to the red sequence.
<figure><img src="image_17.png" /><figcaption>**Figure 16.** The WWFCS will observe 20 nearby clusters with several WEAVE pointings to cover at least $5R_{200}$. The left side shows the observing strategy of WWFCS based on simulations from THE THREEHUNDRED simulations tailored to the survey (Cornwell et al. 2022). Each shaded blue disc represents one WEAVE pointing; the black circles are at 1 and $5r_{200}$. This particular cluster is covered with seven pointings, but others require fewer or more. The right side of the figure shows filaments identified using the software DISPERSE and groups in the infall region of the same cluster simulation (see Kuchner et al. 2020 for details).</figcaption></figure>

(ii) **Layer 2 – WEAVE Wide-Field Cluster survey (WWFCS):** To understand the effect of environment on galaxy evolution, we must understand processes acting during the assembly of clusters. This includes the collapse and feeding of clusters via filaments and groups from the cosmic web. This layer of the WEAVE Galaxy Clusters survey concentrates on the still-to-be-explored accretion physics of cluster infall regions. The WWFCS will observe galaxy clusters out to five times their virial radius to include galaxies in filaments directly feeding the clusters as well as infalling groups. WWFCS will help answer important questions such as: What kind of galaxies feed clusters? Does their fraction vary with the mass and dynamical state of the cluster? Is pre-processing in the form of gas-specific (e.g. ram-pressure stripping) or gravitational (e.g. galaxy–galaxy mergers) processes significant in groups or filaments outside the cluster cores? How and where do changes in morphology and star formation occur, over what timescales, and at which mass? How is AGN activity related to filaments? The WWFCS will observe 16–20 clusters at $z \sim 0.05$ with $13.8 < \log(M_*/M_{\odot}) < 15.5$ (where $M_*$ is the stellar mass of the cluster) that are drawn from the WINGS sample (Fasano et al. 2006), making use of the availability of extensive ancillary data in the inner region. We will obtain a complete census of galaxies in and around clusters over a broad range of masses [$10^9 < (M_*/M_{\odot}) < 10^{11.5}$], corresponding to a magnitude limit of $r = 19.75$. To ensure uniform coverage out to at least $\sim 5R_{vir}$, each cluster will be covered by between 6 and 18 MOS pointings, each with WEAVE’s 2-deg field of view (see left side of Fig. 16). Given the low density contrast of filaments (Martínez, Muriel & Coenda 2015), it is important to target the highest possible fraction of cluster and infall region members. This will be achieved by selecting galaxies with magnitudes, colours, and importantly, photometric redshifts. Photometric redshifts are obtained from the 12-band photometry of the Javalambre Photometric Local Universe Survey (J-PLUS; Cenarro et al. 2019) fields and open-time observations using the spectral energy distribution fitting code LEPHARE (Arnouts & Ilbert 2011). Tests have shown that rejecting targets with $\sim 3$ times the typical photometric redshift error of J-PLUS introduces at most $\sim 3$ per cent incompleteness, while increasing the number of cluster structure members by a factor of $\sim 2$ in comparison to a pure magnitude and colour cut. This leads to an unprecedented total of

4000–6000 structure member galaxies per cluster, which will ensure well-sampled density fields, crucial for mapping and characterizing the filamentary structure around these clusters (see right side of Fig. 16).

The WWFCS programme will use WEAVE’s MOS mode in low spectral resolution, covering 370–960 nm at $R \sim 5000$. The spectra will yield emission-line diagnostics, accurate spectral breaks, and absorption-line information for all galaxies. Velocity dispersions and accurate absorption-line information will be available for the brighter half of the galaxies individually, and statistically for the fainter half through stacking of spectra. This will shed light on the preferred routes of mass accretion and investigate the effect that this has on galaxy properties. Furthermore, the spectroscopic redshifts will be crucial for identifying cluster volumes for accurate filament extraction in redshift space (Kuchner et al. 2021). Defining filaments is a non-trivial task due to the multiscale and diffuse nature of the cosmic web (Rost et al. 2021). The challenge is to map galaxy environments in sufficient detail within – and to sufficient distance around – the dominating clusters, where the filaments converge (see right side of Fig. 16). In preparation for this survey, we have evaluated the performance of filament-finding strategies for WWFCS and quantified their robustness on hydrodynamical simulations of THE THREEHUNDRED project (Kuchner et al. 2020, 2021, 2022). The simulations are tailored to represent WWFCS cluster observations, which will also aid the interpretation of the survey’s findings (Cornwell et al. 2022).

(iii) **Layer 3 – WEAVE Cosmological Clusters survey:** The main goal of the Cosmological Clusters survey is to study the evolution of galaxies in the cores of clusters out to $z \sim 0.5$ and to place constraints on cosmological parameters and global scaling relations using a complete sample of SZ-selected clusters. The baryonic component of clusters contains a wealth of information about the processes associated with galaxy formation, including the efficiency with which baryons are converted into stars and the effects of the resulting feedback processes on galaxy formation, which then allows us to estimate the total baryon ($\Omega_b$: e.g. Voit, Kay & Bryan 2005; Borgani & Kravtsov 2011) and dark matter densities. Moreover, cluster abundance studies as a function of mass and redshift, $N(M, z)$, are powerful cosmological tools (e.g. Carlstrom, Holder & Reese 2002) that allow us to set constraints on cosmological parameters such as the dark matter and dark energy densities, or the equation of state of the dark energy (e.g. Vikhlinin et al. 2009; Mantz et al. 2010). Furthermore, by selecting galaxy clusters at $z \lesssim 0.5$, WEAVE can directly observe the evolution of the stellar populations of galaxies in cluster cores over a cosmic epoch over which galaxy transformations are already well documented (e.g. Dressler & Gunn 1982; Butcher & Oemler 1984; Dressler et al. 1997) and which can be directly compared with other WEAVE surveys like StePS (see Section 4.6). Specific science questions that will be addressed include: obtaining an accurate mass calibration and global scaling relations for a sample of 75 SZ clusters selected from Planck (Planck Collaboration XXVII 2016c); using the calibration to provide error bars a factor of two smaller than the existing ones on the key cosmological parameters $\sigma_8$ and $\Omega_m$; studying the evolution of the stellar populations for a large sample of massive galaxies in the central regions of a galaxy cluster in the last 6 Gyr of evolution, using the method pioneered by Sánchez et al. (2007); making comparisons between the $z = 0$ cluster galaxies in Layer 1 and 2 surveys and the $z \sim 0.5$ field galaxies in StePS to understand how and when early-type galaxies cease and quench their star formation activity, and transition to the red sequence.
<figure><img src="image_17.png" /><figcaption>**Figure 17.** Top panel: LIFU footprint (with three dithers) superimposed on PanSTARRS1 imaging of cluster PSZ2-77. Middle panels: sum of simulated blue-arm (top left) and red-arm (bottom right) data cubes from OpR3b. The circles highlight the brightest cluster galaxy, while the thinner green circle within each thicker circle labels the extraction apertures in each data cube. A projection of the blue-arm data cube (short wavelengths at bottom left, long wavelengths at top right) is shown diagonally across the middle panels. Bottom panel: one-dimensional spectral extraction of the (simulated) brightest cluster galaxy with spectral features indicated in the plot. The blue- and red-arm spectral regions are covered by the blue and red spectra, respectively.</figcaption></figure>

The Cosmological Clusters survey will use both the LIFU and MOS modes in the low-resolution mode (see Fig. 17 for an example of a dithered LIFU footprint on a cluster). This survey will observe a total of ~70 SZ-selected clusters, with low-projected-density clusters

(typically at $z < 0.25$) observed with the MOS mode and high-projected-density clusters (typically at $z > 0.25$) observed with the LIFU.

## 4.6 The Stellar Populations at intermediate redshifts Survey

One of the major goals of extragalactic astrophysics is to understand the physical processes that control the formation and evolution of luminous structures. While large-scale-structure evolution in our Universe is theoretically understood and well reproduced by simulations on scales larger than ~1 Mpc, on smaller scales the stellar mass growth of galaxies within dark matter haloes and thus the complex mechanisms sometimes called 'gastrophysics' (Bond 1993) depend on highly non-linear processes (e.g. star formation, energetic feedback mechanisms, and mergers), whose detailed mechanisms are still largely unknown (Kuhlen, Vogelsberger & Angulo 2012; Bullock & Boylan-Kolchin 2017). Advanced theoretical models are needed to shed light on the mechanisms that regulate the connection between galaxies and their dark matter haloes, but the complexity of the problem is such that observations are essential to empirically constrain both theories and simulations of galaxy assembly history (Wechsler & Tinker 2018).

In the last few decades, the study of galaxies in the local Universe has greatly enriched our knowledge and understanding of galaxy evolution. Theoretical and empirical approaches are now anchored at $z \sim 0$ by the large, uniform, complete spectroscopic measurements from the SDSS (York et al. 2000), providing high S/N and 'high resolution' ($R \sim 2000$) spectra of a large, representative sample of local galaxies. However, despite their high quality and statistical richness, data from the local Universe are not, in general, the ideal tool for retrieving finer details of the star formation and evolutionary history of galaxies. Archaeological reconstruction – retrieving star formation histories at earlier times from spectra observed at $z \sim 0$ – is an extremely difficult task: most of the local galaxies are too old (Gallazzi et al. 2005) to resolve differences in the early star formation history, due to the similarity of stellar spectra at ages >5 Gyr. An alternative approach is the lookback approach, studying and making a census of galaxies at earlier and earlier cosmic epochs, comparing snapshots of the galaxy population taken at different cosmic epochs. This approach enables us to trace back in time the evolution of galaxies as a population, but linking the galaxies observed in the local Universe directly to their actual progenitors at higher redshifts is a difficult task, due to our fundamental lack of understanding of what the actual progenitors of present-day galaxies of different types are.

None of the recent or current large ($N_{gal} \ge 10000$) surveys of distant galaxies ($z \ge 0.3$) – e.g. AGES (Kochanek et al. 2012), SHELS (Geller et al. 2014), GAMA (Driver et al. 2012), and BOSS (Dawson et al. 2013) at the lower redshift end; DEEP2 (Newman et al. 2013), VIPERS (Guzzo et al. 2014), zCOSMOS (Lilly et al. 2009), VVDS/VUDS (Le Fèvre et al. 2005, 2015), and GMASS (Kurk et al. 2013) at the higher redshift end – have adequate spectral resolution and/or quality to derive stellar population properties in sufficient detail for archaeological studies. Low-resolution and low-S/N spectroscopic observations can provide galaxy redshifts, rough measurements of emission lines, and a reliable estimate of the $D_{4000}$ break, but detailed information on the stellar and gas content of galaxies can only be achieved through higher S/N and higher resolution ($R \sim 5000$) spectroscopy – ingredients needed to provide reliable measurements of the absorption features in the stellar continuum and detailed stellar population and gas modelling. The only notable survey to date designed to obtain high-quality,
<figure><img src="image_18.png" /><figcaption>**Figure 17.** Top panel: LIFU footprint (with three dithers) superimposed on PanSTARRS1 imaging of cluster PSZ2-77. Middle panels: sum of simulated blue-arm (top left) and red-arm (bottom right) data cubes from OpR3b. The circles highlight the brightest cluster galaxy, while the thinner green circle within each thicker circle labels the extraction apertures in each data cube. A projection of the blue-arm data cube (short wavelengths at bottom left, long wavelengths at top right) is shown diagonally across the middle panels. Bottom panel: one-dimensional spectral extraction of the (simulated) brightest cluster galaxy with spectral features indicated in the plot. The blue- and red-arm spectral regions are covered by the blue and red spectra, respectively.</figcaption></figure>

The Cosmological Clusters survey will use both the LIFU and MOS modes in the low-resolution mode (see Fig. 17 for an example of a dithered LIFU footprint on a cluster). This survey will observe a total of ~70 SZ-selected clusters, with low-projected-density clusters

(typically at $z < 0.25$) observed with the MOS mode and high-projected-density clusters (typically at $z > 0.25$) observed with the LIFU.

## 4.6 The Stellar Populations at intermediate redshifts Survey

One of the major goals of extragalactic astrophysics is to understand the physical processes that control the formation and evolution of luminous structures. While large-scale-structure evolution in our Universe is theoretically understood and well reproduced by simulations on scales larger than ~1 Mpc, on smaller scales the stellar mass growth of galaxies within dark matter haloes and thus the complex mechanisms sometimes called ‘gastrophysics’ (Bond 1993) depend on highly non-linear processes (e.g. star formation, energetic feedback mechanisms, and mergers), whose detailed mechanisms are still largely unknown (Kuhlen, Vogelsberger & Angulo 2012; Bullock & Boylan-Kolchin 2017). Advanced theoretical models are needed to shed light on the mechanisms that regulate the connection between galaxies and their dark matter haloes, but the complexity of the problem is such that observations are essential to empirically constrain both theories and simulations of galaxy assembly history (Wechsler & Tinker 2018).

In the last few decades, the study of galaxies in the local Universe has greatly enriched our knowledge and understanding of galaxy evolution. Theoretical and empirical approaches are now anchored at $z \sim 0$ by the large, uniform, complete spectroscopic measurements from the SDSS (York et al. 2000), providing high S/N and ‘high resolution’ ($R \sim 2000$) spectra of a large, representative sample of local galaxies. However, despite their high quality and statistical richness, data from the local Universe are not, in general, the ideal tool for retrieving finer details of the star formation and evolutionary history of galaxies. Archaeological reconstruction – retrieving star formation histories at earlier times from spectra observed at $z \sim 0$ – is an extremely difficult task: most of the local galaxies are too old (Gallazzi et al. 2005) to resolve differences in the early star formation history, due to the similarity of stellar spectra at ages >5 Gyr. An alternative approach is the lookback approach, studying and making a census of galaxies at earlier and earlier cosmic epochs, comparing snapshots of the galaxy population taken at different cosmic epochs. This approach enables us to trace back in time the evolution of galaxies as a population, but linking the galaxies observed in the local Universe directly to their actual progenitors at higher redshifts is a difficult task, due to our fundamental lack of understanding of what the actual progenitors of present-day galaxies of different types are.

None of the recent or current large ($N_{gal} \ge 10000$) surveys of distant galaxies ($z \ge 0.3$) – e.g. AGES (Kochanek et al. 2012), SHELS (Geller et al. 2014), GAMA (Driver et al. 2012), and BOSS (Dawson et al. 2013) at the lower redshift end; DEEP2 (Newman et al. 2013), VIPERS (Guzzo et al. 2014), zCOSMOS (Lilly et al. 2009), VVDS/VUDS (Le Fèvre et al. 2005, 2015), and GMASS (Kurk et al. 2013) at the higher redshift end – have adequate spectral resolution and/or quality to derive stellar population properties in sufficient detail for archaeological studies. Low-resolution and low-S/N spectroscopic observations can provide galaxy redshifts, rough measurements of emission lines, and a reliable estimate of the $D_{4000}$ break, but detailed information on the stellar and gas content of galaxies can only be achieved through higher S/N and higher resolution ($R \sim 5000$) spectroscopy – ingredients needed to provide reliable measurements of the absorption features in the stellar continuum and detailed stellar population and gas modelling. The only notable survey to date designed to obtain high-quality,
high-resolution spectra in the relatively distant Universe is LEGA-C, whose data are limited to the redshift window $0.6 \le z \le 1.0$ and to a sample of ~3200 galaxies within the COSMOS field. The LEGA-C spectra have a median S/N ~20, and resolution R ~3500 (see van der Wel et al. 2016; Straatman et al. 2018).

StePS will use the WEAVE spectrograph to perform a high-S/N survey of galaxies at moderate redshift, targeting a volume-limited sample lying mainly in the redshift interval $0.3 \le z \le 0.7$ (Iovino et al. 2023). StePS is thus designed to fill the interesting, yet largely unexplored niche of the intermediate redshift slice, fitting in between the SDSS and the LEGA-C survey data. StePS and the SDSS alone already encompass 6 Gyr of the age of the Universe, i.e. nearly one-half of its present age, over the period when the cosmic star formation rate density continues to drop, while galaxies have almost doubled their stellar mass in dark matter haloes that are still assembling (Conroy & Wechsler 2009).

To emphasize the need for high spectral resolution, consider that while Lick indices (Worthey et al. 1994) tend to have central bandpasses of the order of 20–30 Å, the features themselves may only be 2–5 Å wide. Moreover, accurately fitting the absorption lines is vital for measuring the Balmer emission lines, which often sit on top of deep absorption features that cannot be modelled and accounted for in typical low-resolution spectra (R ~ 1000, see Fig. 18).

Individual spectra of good S/N are another important ingredient. While spectral stacking (e.g. Gallazzi et al. 2008) can enable us to obtain high S/N spectra that provide the correct (light-weighted) average properties in a given bin of galaxy properties, it provides no information about the scatter around this average or the higher moments of the distribution. Pinning down these moments is important for quantifying the amount of stochasticity involved in galaxy evolution processes and the timescales of transitional phases. This clearly adds much more understanding to galaxy evolution than simply tracing the average time evolution of the properties of galaxy populations in given bins. Good-quality individual spectra are crucial for obtaining a description of any statistical distribution of physical properties that goes beyond the most typical. In addition, only a study of individual galaxies would allow for the identification of rare oddball objects, which may be the ones that will teach us the most interesting physics.

StePS will obtain approximately 25 000 spectra of high S/N and resolution ~1 Å using WEAVE’s LR mode (R ~ 5000), spanning the wide wavelength range of 3660–9590 Å. StePS targets will be selected within four areas on the sky totalling ~25 deg². The areas are a subset of the CFHTLS-W1 (02h18m00s – 07°00'00'') and W4 (22h13m18s + 01°9'00'') regions, and of the ELAIS-N1 region (16h12m10s0 + 54°30'00''). An area centred on the COSMOS field (10h00m28s + 02°12'21''; Scoville et al. 2007) is also included, where richer ancillary data – including HST imaging – are available. This large sample will enable us to characterize the ingredients that shape the history of galaxy assembly with sufficient statistics, exploring galaxy evolution in a sufficient number of bins of different galaxy masses, galaxy morphologies and colours, environments, and cosmic epochs.

We have estimated that S/N ≥ 10 Å⁻¹ in the observed *I* band is an essential requirement to estimate the physical parameters of interest with reasonable accuracy, including – but not limited to – stellar ages, stellar and ionized gas metallicities and kinematics, and star formation rates (see e.g. Costantin et al. 2019 and Ditrani et al. 2023 for a detailed investigation of the potential of WEAVE-like spectra at such typical S/N values). Such S/N values can be obtained in WEAVE’s red arm with an exposure time of ~7 hours in the R ~ 5000 mode for galaxies down to total galaxy magnitudes

$I_{AB} \le 20.5$. At a resolution of R ~ 5000, which in WEAVE is defined as the low-resolution mode, and at the required signal-to-noise level, even narrow features of galaxy spectra will be easily resolved, allowing for an accurate measurement of the intrinsic stellar velocity dispersion. At these – what would be termed in this area of study – ‘high’ resolutions, galaxy spectra reveal a vast number of spectral features, providing an immense resource for fitting models, including the ability to disentangle multiple stellar populations, such as the effect of a frosting of a low level of young stars overlaid on an underlying old stellar population, or the effects of recent short bursts of star formation followed by rapid quenching. Equally, accurately fitting the absorption lines is vital for measuring the Balmer emission lines, which often sit at the bottom of deep absorption features that cannot be modelled and be accounted for in lower-resolution spectra. The magnitude limit of $I_{AB} \le 20.5$ corresponds to a logarithmic stellar mass limit (using a Chabrier IMF) of $\log(M_*/M_\odot) = 10.2$ at $z \sim 0.3$, $11.0$ at $z \sim 0.5$, and $11.3$ at $z \sim 0.7$, thus sampling the high-stellar-mass tail of the galaxy population. The galaxy surface density of targets, selected using high-quality photometric redshifts to be at $z \ge 0.3$, is ~1500 deg⁻², and is well suited for WEAVE’s multiplex capabilities with a multipass strategy involving several passes of each sky region.

For the majority of observed galaxy spectra, StePS will derive stellar ages, stellar and gas metallicities, dust attenuation, electron densities, and ionization parameters. We will infer the past evolution of galaxies at different masses and redshifts and relate their star formation histories to their intrinsic (e.g. stellar mass, galaxy morphology, and dominant power source) and environmental properties, making use of the option to stack spectra when their S/N are low. Using available ancillary photometric data will allow us to create well-defined stacks of spectra of even relatively small homogeneous sub-samples. The observed spectra will also be used to provide information on gas kinematics (including the presence of outflows) and stellar velocity dispersions, allowing us to perform a dynamical classification of the observed galaxies and to explore in detail the link between star formation history, mass-assembly history, and dynamics.

Last but not the least, the StePS redshift range, coupled with the wide spectral range of WEAVE, will enable observations of the near-ultraviolet and *U*-band rest-frame spectral windows, bands that can provide unprecedented constraints on the youngest components in galaxies (Vazdekis et al. 2016; Salvador-Rusñol et al. 2020).

## 4.7 The WEAVE-LOFAR Survey

The WL survey (Smith et al. 2016, and in preparation) will provide the spectroscopic information to unlock the power of the International Low Frequency Array Telescope<fnref n="26" /> (LOFAR; van Haarlem et al. 2013). Since its inception, an important driver for LOFAR has been to carry out a series of surveys of the sky at low radio frequencies, in particular to advance our understanding of the formation and evolution of galaxies, galaxy clusters, and AGNs. The LOFAR Surveys Key Science Project (LSKSP; Röttgering et al. 2011) is carrying out this aim, using a suite of related surveys.

The observations with LOFAR’s High-Band Antennae (HBA) include those used for LoTSS (Shimwell et al. 2017), and are providing observations across the whole of the Northern sky between 120 and 168 MHz. A lower frequency counterpart of LoTSS, using

<footnote n="26">²⁶http://www.lofar.org</footnote>
high-resolution spectra in the relatively distant Universe is LEGA-C, whose data are limited to the redshift window $0.6 \le z \le 1.0$ and to a sample of ~3200 galaxies within the COSMOS field. The LEGA-C spectra have a median S/N ~20, and resolution R ~3500 (see van der Wel et al. 2016; Straatman et al. 2018).

StePS will use the WEAVE spectrograph to perform a high-S/N survey of galaxies at moderate redshift, targeting a volume-limited sample lying mainly in the redshift interval $0.3 \le z \le 0.7$ (Iovino et al. 2023). StePS is thus designed to fill the interesting, yet largely unexplored niche of the intermediate redshift slice, fitting in between the SDSS and the LEGA-C survey data. StePS and the SDSS alone already encompass 6 Gyr of the age of the Universe, i.e. nearly one-half of its present age, over the period when the cosmic star formation rate density continues to drop, while galaxies have almost doubled their stellar mass in dark matter haloes that are still assembling (Conroy & Wechsler 2009).

To emphasize the need for high spectral resolution, consider that while Lick indices (Worthey et al. 1994) tend to have central bandpasses of the order of 20–30 Å, the features themselves may only be 2–5 Å wide. Moreover, accurately fitting the absorption lines is vital for measuring the Balmer emission lines, which often sit on top of deep absorption features that cannot be modelled and accounted for in typical low-resolution spectra (R ~ 1000, see Fig. 18).

Individual spectra of good S/N are another important ingredient. While spectral stacking (e.g. Gallazzi et al. 2008) can enable us to obtain high S/N spectra that provide the correct (light-weighted) average properties in a given bin of galaxy properties, it provides no information about the scatter around this average or the higher moments of the distribution. Pinning down these moments is important for quantifying the amount of stochasticity involved in galaxy evolution processes and the timescales of transitional phases. This clearly adds much more understanding to galaxy evolution than simply tracing the average time evolution of the properties of galaxy populations in given bins. Good-quality individual spectra are crucial for obtaining a description of any statistical distribution of physical properties that goes beyond the most typical. In addition, only a study of individual galaxies would allow for the identification of rare oddball objects, which may be the ones that will teach us the most interesting physics.

StePS will obtain approximately 25 000 spectra of high S/N and resolution ~1 Å using WEAVE’s LR mode (R ~ 5000), spanning the wide wavelength range of 3660–9590 Å. StePS targets will be selected within four areas on the sky totalling ~25 deg². The areas are a subset of the CFHTLS-W1 (02h18m00s – 07°00'00'') and W4 (22h13m18s + 01°9'00'') regions, and of the ELAIS-N1 region (16h12m10s0 + 54°30'00''). An area centred on the COSMOS field (10h00m28s + 02°12'21''; Scoville et al. 2007) is also included, where richer ancillary data – including HST imaging – are available. This large sample will enable us to characterize the ingredients that shape the history of galaxy assembly with sufficient statistics, exploring galaxy evolution in a sufficient number of bins of different galaxy masses, galaxy morphologies and colours, environments, and cosmic epochs.

We have estimated that S/N ≥ 10 Å⁻¹ in the observed I band is an essential requirement to estimate the physical parameters of interest with reasonable accuracy, including – but not limited to – stellar ages, stellar and ionized gas metallicities and kinematics, and star formation rates (see e.g. Costantin et al. 2019 and Ditrani et al. 2023 for a detailed investigation of the potential of WEAVE-like spectra at such typical S/N values). Such S/N values can be obtained in WEAVE’s red arm with an exposure time of ~7 hours in the R ~ 5000 mode for galaxies down to total galaxy magnitudes

$I_{AB} \le 20.5$. At a resolution of R ~ 5000, which in WEAVE is defined as the low-resolution mode, and at the required signal-to-noise level, even narrow features of galaxy spectra will be easily resolved, allowing for an accurate measurement of the intrinsic stellar velocity dispersion. At these – what would be termed in this area of study – ‘high’ resolutions, galaxy spectra reveal a vast number of spectral features, providing an immense resource for fitting models, including the ability to disentangle multiple stellar populations, such as the effect of a frosting of a low level of young stars overlaid on an underlying old stellar population, or the effects of recent short bursts of star formation followed by rapid quenching. Equally, accurately fitting the absorption lines is vital for measuring the Balmer emission lines, which often sit at the bottom of deep absorption features that cannot be modelled and be accounted for in lower-resolution spectra. The magnitude limit of $I_{AB} \le 20.5$ corresponds to a logarithmic stellar mass limit (using a Chabrier IMF) of $\log(M_*/M_\odot) = 10.2$ at z ~ 0.3, 11.0 at z ~ 0.5, and 11.3 at z ~ 0.7, thus sampling the high-stellar-mass tail of the galaxy population. The galaxy surface density of targets, selected using high-quality photometric redshifts to be at z ≥ 0.3, is ~1500 deg⁻², and is well suited for WEAVE’s multiplex capabilities with a multipass strategy involving several passes of each sky region.

For the majority of observed galaxy spectra, StePS will derive stellar ages, stellar and gas metallicities, dust attenuation, electron densities, and ionization parameters. We will infer the past evolution of galaxies at different masses and redshifts and relate their star formation histories to their intrinsic (e.g. stellar mass, galaxy morphology, and dominant power source) and environmental properties, making use of the option to stack spectra when their S/N are low. Using available ancillary photometric data will allow us to create well-defined stacks of spectra of even relatively small homogeneous sub-samples. The observed spectra will also be used to provide information on gas kinematics (including the presence of outflows) and stellar velocity dispersions, allowing us to perform a dynamical classification of the observed galaxies and to explore in detail the link between star formation history, mass-assembly history, and dynamics.

Last but not the least, the StePS redshift range, coupled with the wide spectral range of WEAVE, will enable observations of the near-ultraviolet and U-band rest-frame spectral windows, bands that can provide unprecedented constraints on the youngest components in galaxies (Vazdekis et al. 2016; Salvador-Rusñol et al. 2020).

## 4.7 The WEAVE-LOFAR Survey

The WL survey (Smith et al. 2016, and in preparation) will provide the spectroscopic information to unlock the power of the International Low Frequency Array Telescope<fnref n="26" /> (LOFAR; van Haarlem et al. 2013). Since its inception, an important driver for LOFAR has been to carry out a series of surveys of the sky at low radio frequencies, in particular to advance our understanding of the formation and evolution of galaxies, galaxy clusters, and AGNs. The LOFAR Surveys Key Science Project (LSKSP; Röttgering et al. 2011) is carrying out this aim, using a suite of related surveys.

The observations with LOFAR’s High-Band Antennae (HBA) include those used for LoTSS (Shimwell et al. 2017), and are providing observations across the whole of the Northern sky between 120 and 168 MHz. A lower frequency counterpart of LoTSS, using

<footnote n="26">²⁶http://www.lofar.org</footnote>
<figure><img src="image_18.png" /><figcaption>**Figure 18.** Comparison of typical SDSS (z ~ 0.1, solid coloured lines; York et al. 2000) and VIPERS (z ~ 0.5, dashed lines; Guzzo et al. 2014) spectra of four early-type galaxies of different stellar masses (see legend; note that the ordering of the stellar masses matches the ordering of the lines in the figure). VIPERS spectra are vertically offset by 10 units for clarity. The S/N of all of these spectra are close to the median value for galaxies of that mass in the corresponding survey. The black curves show model spectra of single stellar populations with solar metallicities and ages of 2.5–10 Gyr (from bottom to top) from the MILES spectral library (Vazdekis et al. 2010). Key spectral indices used for estimating the stellar ages or metallicities are indicated, from left to right (CaH + K, Fe4045, Hδ, Mgb, Fe5270, Fe5335), the grey bands indicating the width of the central Lick wavebands. The low resolution (~16 Å FWHM) of the VIPERS spectra smooth out (or fill in) the key spectral absorption features, and the low S/N prevent reliable measurements of the Lick indices for individual galaxies. The higher resolution SDSS spectra retain these absorption features, allowing us to reconstruct their finer features.</figcaption></figure>

the LOFAR Low Band Antennae (LBA), is the LOFAR LBA Sky Survey (LoLSS; de Gasperin et al. 2021), covering the frequency range 42–66 MHz. Because of the influence of ionospheric effects on low-frequency observations, LoTSS required the development of new direction-dependent calibration schemes (e.g. Tasse 2014; Williams & Röttgering 2015; Hardcastle et al. 2016; van Weeren et al. 2016; Tasse et al. 2018). It is now possible to routinely generate science-quality, pipeline-processed images and mosaics with unsurpassed sensitivity, image quality, resolution, and field of view. The most recent second data release of LoTSS (DR2; Shimwell et al. 2022) builds on the huge success of DR1 (Shimwell et al. 2019; Duncan et al. 2019; Williams et al. 2019), and consists of LOFAR maps and catalogues, plus extensive ancillary information for more than four million sources identified at 150 MHz at >5σ over 5700 deg². The median root mean square of the LoTSS data is 83 µJy beam⁻¹, while the resolution of the LoTSS mosaics is 6 arcsec, and the astrometric accuracy relative to the Gaia reference frame is <0.2 arcsec, ideal for selecting WEAVE targets. Progress continues to be rapid, and well over half of the Northern sky has so far been observed.

The LSKSP team recently completed the first data release for its Deep Fields (fully described in four works: Duncan et al. 2021; Kondapally et al. 2021; Sabater et al. 2021; Tasse et al. 2021), along with a slew of new science (e.g. Cloudemans et al. 2021; Hardcastle et al. 2021; Herrera Ruiz et al. 2021; Mandal et al. 2021; Morganti et al. 2021; Osinga et al. 2021; Smith et al. 2021; Wang et al. 2021; Mingo et al. 2022; Kondapally et al. 2022). The LoTSS Deep Fields first data release is based on hundreds of hours of 150 MHz observations of the best multiwavelength ‘famous fields’ visible from Northern Europe. The LoTSS Deep fields DR1 includes tens of deg² of observations spread over three fields: Boötes and Lockman Hole (described in Tasse et al. 2021), as well as the ELAIS-N1 field (which contains the deepest data, reaching 20 µJy RMS; Sabater et al. 2021). The Deep Fields data release includes extensive ancillary

information, including host galaxy identifications for over 97 per cent of the sources (Kondapally et al. 2021), as well as photometric redshifts (Duncan et al. 2021). Future Deep Fields releases will be based on even deeper 150 MHz data, and include the field at the North Ecliptic Pole (NEP). Each field’s position is indicated in Fig. 19.

LOFAR selection of targets for WEAVE is ideal since 150 MHz observations identify targets on the basis of radio activity (whether that activity is due to star formation or accretion), and independent of dust obscuration. While the latter effect means that LOFAR-selected samples are more representative of the activity in the Universe than samples identified at other wavelengths (e.g. in the optical), the former ensures that the WL sample is rich with emission-line sources. WEAVE’s low-resolution mode having continuous wavelength coverage between 360 and 960 nm and high throughput means that we expect a redshift success rate approaching 100 per cent out to z = 1, and to be able to obtain redshifts for samples of extreme sources out to beyond z = 6.

However, spectra are required for much more than simply measuring redshifts; it is only by using these data that we are able to produce the most robust source classifications, and distinguish between sources dominated by star formation, i.e. SFGs, and those dominated by accretion on to an AGN (e.g. using emission-line classifications based on the ratios of Balmer and forbidden lines; Baldwin, Phillips & Terlevich 1981). Spectroscopy also allows us to reliably distinguish between different accretion modes among the AGNs, determining whether they are dominated by efficient accretion of cold gas (resulting in high-excitation sources) or by inefficient accretion of hot gas (resulting in low-excitation sources; e.g. Best & Heckman 2012; O’Sullivan et al. 2015). The ratios of equivalent widths of forbidden and Balmer lines as well as the [O III] emission line are widely used for this purpose (e.g. Laing et al. 1994; Tadhunter et al. 1998; Buttiglione et al. 2010; Best & Heckman 2012). These capabilities are essential given that, even in the widest area LOFAR observations, the 150 MHz source population is diverse at the faint
<figure><img src="image_19.png" /><figcaption>**Figure 18.** Comparison of typical SDSS (z ~ 0.1, solid coloured lines; York et al. 2000) and VIPERS (z ~ 0.5, dashed lines; Guzzo et al. 2014) spectra of four early-type galaxies of different stellar masses (see legend; note that the ordering of the stellar masses matches the ordering of the lines in the figure). VIPERS spectra are vertically offset by 10 units for clarity. The S/N of all of these spectra are close to the median value for galaxies of that mass in the corresponding survey. The black curves show model spectra of single stellar populations with solar metallicities and ages of 2.5–10 Gyr (from bottom to top) from the MILES spectral library (Vazdekis et al. 2010). Key spectral indices used for estimating the stellar ages or metallicities are indicated, from left to right (CaH + K, Fe4045, Hδ, Mgb, Fe5270, Fe5335), the grey bands indicating the width of the central Lick wavebands. The low resolution (~16 Å FWHM) of the VIPERS spectra smooth out (or fill in) the key spectral absorption features, and the low S/N prevent reliable measurements of the Lick indices for individual galaxies. The higher resolution SDSS spectra retain these absorption features, allowing us to reconstruct their finer features.</figcaption></figure>

the LOFAR Low Band Antennae (LBA), is the LOFAR LBA Sky Survey (LoLSS; de Gasperin et al. 2021), covering the frequency range 42–66 MHz. Because of the influence of ionospheric effects on low-frequency observations, LoTSS required the development of new direction-dependent calibration schemes (e.g. Tasse 2014; Williams & Röttgering 2015; Hardcastle et al. 2016; van Weeren et al. 2016; Tasse et al. 2018). It is now possible to routinely generate science-quality, pipeline-processed images and mosaics with unsurpassed sensitivity, image quality, resolution, and field of view. The most recent second data release of LoTSS (DR2; Shimwell et al. 2022) builds on the huge success of DR1 (Shimwell et al. 2019; Duncan et al. 2019; Williams et al. 2019), and consists of LOFAR maps and catalogues, plus extensive ancillary information for more than four million sources identified at 150 MHz at >5σ over 5700 deg². The median root mean square of the LoTSS data is 83 µJy beam⁻¹, while the resolution of the LoTSS mosaics is 6 arcsec, and the astrometric accuracy relative to the Gaia reference frame is <0.2 arcsec, ideal for selecting WEAVE targets. Progress continues to be rapid, and well over half of the Northern sky has so far been observed.

The LSKSP team recently completed the first data release for its Deep Fields (fully described in four works: Duncan et al. 2021; Kondapally et al. 2021; Sabater et al. 2021; Tasse et al. 2021), along with a slew of new science (e.g. Cloudemans et al. 2021; Hardcastle et al. 2021; Herrera Ruiz et al. 2021; Mandal et al. 2021; Morganti et al. 2021; Osinga et al. 2021; Smith et al. 2021; Wang et al. 2021; Mingo et al. 2022; Kondapally et al. 2022). The LoTSS Deep Fields first data release is based on hundreds of hours of 150 MHz observations of the best multiwavelength ‘famous fields’ visible from Northern Europe. The LoTSS Deep fields DR1 includes tens of deg² of observations spread over three fields: Boötes and Lockman Hole (described in Tasse et al. 2021), as well as the ELAIS-N1 field (which contains the deepest data, reaching 20 µJy RMS; Sabater et al. 2021). The Deep Fields data release includes extensive ancillary

information, including host galaxy identifications for over 97 per cent of the sources (Kondapally et al. 2021), as well as photometric redshifts (Duncan et al. 2021). Future Deep Fields releases will be based on even deeper 150 MHz data, and include the field at the North Ecliptic Pole (NEP). Each field’s position is indicated in Fig. 19.

LOFAR selection of targets for WEAVE is ideal since 150 MHz observations identify targets on the basis of radio activity (whether that activity is due to star formation or accretion), and independent of dust obscuration. While the latter effect means that LOFAR-selected samples are more representative of the activity in the Universe than samples identified at other wavelengths (e.g. in the optical), the former ensures that the WL sample is rich with emission-line sources. WEAVE’s low-resolution mode having continuous wavelength coverage between 360 and 960 nm and high throughput means that we expect a redshift success rate approaching 100 per cent out to z = 1, and to be able to obtain redshifts for samples of extreme sources out to beyond z = 6.

However, spectra are required for much more than simply measuring redshifts; it is only by using these data that we are able to produce the most robust source classifications, and distinguish between sources dominated by star formation, i.e. SFGs, and those dominated by accretion on to an AGN (e.g. using emission-line classifications based on the ratios of Balmer and forbidden lines; Baldwin, Phillips & Terlevich 1981). Spectroscopy also allows us to reliably distinguish between different accretion modes among the AGNs, determining whether they are dominated by efficient accretion of cold gas (resulting in high-excitation sources) or by inefficient accretion of hot gas (resulting in low-excitation sources; e.g. Best & Heckman 2012; O’Sullivan et al. 2015). The ratios of equivalent widths of forbidden and Balmer lines as well as the [O III] emission line are widely used for this purpose (e.g. Laing et al. 1994; Tadhunter et al. 1998; Buttiglione et al. 2010; Best & Heckman 2012). These capabilities are essential given that, even in the widest area LOFAR observations, the 150 MHz source population is diverse at the faint
<figure><img src="image_19.png" /><figcaption>**Figure 19.** Outlines of the main WL fields, in the context of the LoTSS data, in equatorial (left) and Galactic (right, compare with Fig. 6) coordinates. In both versions, the LoTSS hemisphere grid is shown using small black dots, while filled orange circles indicate the LOFAR pointing centres included in the second data release of LoTSS, covering approximately 5700 deg² of the extragalactic sky. Also overlaid are the principal WL Deep Fields (open magenta circles/ellipses), and outlines of mid-tier fields (thick lines in light blue, including HETDEX, the region covered by LoTSS DR1; see also Fig. 20). The provisional area that will be observed by J-PAS is outlined in burgundy, while the perimeter of the fields shared with the WEAVE GA and WQ teams is outlined by the thin green lines in the left panel. The coverage of the Legacy Surveys (Dey et al. 2019) that we use for cross-identification in LoTSS is indicated by the grey shaded background. In the right panel, the Galactic Centre and Anticentre are indicated by black open circles, while the poles in the equatorial reference frame are indicated by black circled crosses. In the left panel, the Galactic Anticentre is indicated by black open circle.</figcaption></figure>

radio-flux densities sampled, consisting predominantly of SFGs and radio-quiet AGNs. LoTSS data are considerably deeper than all other existing surveys of comparable areas including FIRST (Becker, White & Helfand 1995), NVSS (Condon et al. 1998), and VLASS (e.g. Lacy & VLASS Survey Team 2018; Myers & VLASS Survey Team 2018) and, interestingly, at the faintest flux levels probed by the deepest LOFAR data, the SFGs and radio-quiet AGNs comprise more than 90 per cent of the radio-source population (Best et al. 2023); spectroscopic follow-up of large statistical samples of SFGs and radio-quiet AGNs detected by the deep LOFAR surveys will enable detailed characterization of these populations. Spectroscopy of radio sources also permits us to measure velocity dispersions, estimate metallicities (the high resolution of WEAVE – even in its ‘low-resolution’ mode – is essential here), and derive virial black hole mass estimates.

Some of the topics that WL will address include: the star formation history of the Universe; the evolution of accretion and AGN-driven feedback; the nature of the Epoch of Reionization (EoR); cosmology; cluster haloes and relic radio sources; and radio galaxies and protoclusters. We expect, for example, to identify a statistical sample of around 50 radio galaxies at $z > 6$ (Saxena, Röttgering & Rigby 2017; Saxena et al. 2018); these sources are pivotal for conducting 21-cm absorption experiments, giving a new window on the change of state brought about in the IGM during the EoR by the first stars/galaxies/AGNs. EoR 21-cm studies offer the best way to answer key questions about this poorly understood period in cosmic history: how long did it last, and which sources were responsible? The MOS component of WL will obtain more than a million spectra of 150 MHz-selected sources, almost three orders of magnitude more than the largest existing spectroscopic surveys targeting radio sources. These large numbers of sources will lend immense statistical power to this uniformly selected and homogeneous spectroscopic data bank, offering us the chance to simultaneously model the populations of SFGs and AGNs as a

function of stellar mass, environment, and redshift. In this way, we can shed new light on the complicated interplay between the key processes thought to shape galaxy formation and evolution. WL spectroscopic redshifts will also enable much improved cosmological parameter determination from LoTSS, building on the earlier work by Siewert et al. (2020), Alonso et al. (2021), and Tiwari et al. (2022).

To achieve these goals, WL has been designed to predominantly utilize WEAVE’s MOS mode, using a tiered layout. The tiers – chosen to statistically sample the redshift–luminosity plane, the changing demographics of the radio-source population, and the processes driving their evolution – are as follows:

(i) **Wide tier**, targeting sources brighter than ~10 mJy at 150 MHz selected over an area of up to 10 000 deg² from LoTSS.

(ii) **Mid tier**, targeting 150 MHz sources brighter than ~1 mJy, including over the HETDEX spring field (Fig. 20; where more than 400 deg² of the LoTSS first data release are located) and targeting fainter 150 MHz sources > 500 µJy over the unique Herschel-ATLAS NGP field.

(iii) **Deep tier**, covering an area of up to 50 deg² and targeting all radio-detected sources detected in the LoTSS Deep fields data covering the Boötes, Lockman Hole, ELAIS-N1, and NEP fields.

We emphasize that we do not make use of any selection criteria other than the 150 MHz flux limits. Given the flux limit, sources detected in the Wide tier will have low-frequency radio spectral index information from the combination of LoTSS (144 MHz) and LoLSS (54 MHz) data. In the Wide and Mid tiers, we will use 1-hour integrations for every target. In the Deep tier, we will revisit those ‘hard’ sources (perhaps 30 per cent of the whole sample) that do not yield redshifts within a single 1-hour OB for up to four further hours. By doing this, we expect to obtain redshifts for 15–20 per cent of these hard sources and, in doing so, sample a part of the radio-source population that would otherwise have remained completely inaccessible. Since we are relying on the prevalence of
<figure><img src="image_20.png" /><figcaption>**Figure 19.** Outlines of the main WL fields, in the context of the LoTSS data, in equatorial (left) and Galactic (right, compare with Fig. 6) coordinates. In both versions, the LoTSS hemisphere grid is shown using small black dots, while filled orange circles indicate the LOFAR pointing centres included in the second data release of LoTSS, covering approximately 5700 deg² of the extragalactic sky. Also overlaid are the principal WL Deep Fields (open magenta circles/ellipses), and outlines of mid-tier fields (thick lines in light blue, including HETDEX, the region covered by LoTSS DR1; see also Fig. 20). The provisional area that will be observed by J-PAS is outlined in burgundy, while the perimeter of the fields shared with the WEAVE GA and WQ teams is outlined by the thin green lines in the left panel. The coverage of the Legacy Surveys (Dey et al. 2019) that we use for cross-identification in LoTSS is indicated by the grey shaded background. In the right panel, the Galactic Centre and Anticentre are indicated by black open circles, while the poles in the equatorial reference frame are indicated by black circled crosses. In the left panel, the Galactic Anticentre is indicated by black open circle.</figcaption></figure>

radio-flux densities sampled, consisting predominantly of SFGs and radio-quiet AGNs. LoTSS data are considerably deeper than all other existing surveys of comparable areas including FIRST (Becker, White & Helfand 1995), NVSS (Condon et al. 1998), and VLASS (e.g. Lacy & VLASS Survey Team 2018; Myers & VLASS Survey Team 2018) and, interestingly, at the faintest flux levels probed by the deepest LOFAR data, the SFGs and radio-quiet AGNs comprise more than 90 per cent of the radio-source population (Best et al. 2023); spectroscopic follow-up of large statistical samples of SFGs and radio-quiet AGNs detected by the deep LOFAR surveys will enable detailed characterization of these populations. Spectroscopy of radio sources also permits us to measure velocity dispersions, estimate metallicities (the high resolution of WEAVE – even in its ‘low-resolution’ mode – is essential here), and derive virial black hole mass estimates.

Some of the topics that WL will address include: the star formation history of the Universe; the evolution of accretion and AGN-driven feedback; the nature of the Epoch of Reionization (EoR); cosmology; cluster haloes and relic radio sources; and radio galaxies and protoclusters. We expect, for example, to identify a statistical sample of around 50 radio galaxies at $z > 6$ (Saxena, Röttgering & Rigby 2017; Saxena et al. 2018); these sources are pivotal for conducting 21-cm absorption experiments, giving a new window on the change of state brought about in the IGM during the EoR by the first stars/galaxies/AGNs. EoR 21-cm studies offer the best way to answer key questions about this poorly understood period in cosmic history: how long did it last, and which sources were responsible? The MOS component of WL will obtain more than a million spectra of 150 MHz-selected sources, almost three orders of magnitude more than the largest existing spectroscopic surveys targeting radio sources. These large numbers of sources will lend immense statistical power to this uniformly selected and homogeneous spectroscopic data bank, offering us the chance to simultaneously model the populations of SFGs and AGNs as a

function of stellar mass, environment, and redshift. In this way, we can shed new light on the complicated interplay between the key processes thought to shape galaxy formation and evolution. WL spectroscopic redshifts will also enable much improved cosmological parameter determination from LoTSS, building on the earlier work by Siewert et al. (2020), Alonso et al. (2021), and Tiwari et al. (2022).

To achieve these goals, WL has been designed to predominantly utilize WEAVE’s MOS mode, using a tiered layout. The tiers – chosen to statistically sample the redshift–luminosity plane, the changing demographics of the radio-source population, and the processes driving their evolution – are as follows:

(i) **Wide tier**, targeting sources brighter than ~10 mJy at 150 MHz selected over an area of up to 10 000 deg² from LoTSS.

(ii) **Mid tier**, targeting 150 MHz sources brighter than ~1 mJy, including over the HETDEX spring field (Fig. 20; where more than 400 deg² of the LoTSS first data release are located) and targeting fainter 150 MHz sources > 500 µJy over the unique Herschel-ATLAS NGP field.

(iii) **Deep tier**, covering an area of up to 50 deg² and targeting all radio-detected sources detected in the LoTSS Deep fields data covering the Boötes, Lockman Hole, ELAIS-N1, and NEP fields.

We emphasize that we do not make use of any selection criteria other than the 150 MHz flux limits. Given the flux limit, sources detected in the Wide tier will have low-frequency radio spectral index information from the combination of LoTSS (144 MHz) and LoLSS (54 MHz) data. In the Wide and Mid tiers, we will use 1-hour integrations for every target. In the Deep tier, we will revisit those ‘hard’ sources (perhaps 30 per cent of the whole sample) that do not yield redshifts within a single 1-hour OB for up to four further hours. By doing this, we expect to obtain redshifts for 15–20 per cent of these hard sources and, in doing so, sample a part of the radio-source population that would otherwise have remained completely inaccessible. Since we are relying on the prevalence of
<figure><img src="image_20.png" /></figure>

**Figure 20.** 150 MHz mosaic of the region surrounding the HETDEX field using LoTSS data from the second data release (red colour scale, from Martin Hardcastle, private communication). The HETDEX spring field is one of the principal areas of sky in the WL 'Mid' tier. Overlaid on the map (the full-resolution version of which reaches a median noise level of 69 µJy beam⁻¹ and contains >500k sources detected at >5σ at 150 MHz) is the pointing grid for the fields shared with the WEAVE GA and WQ surveys, covering the whole sky north of Dec = −10 deg (black dots, derived using the method of Saff & Kuijlaars 1997). The blue dots indicate those WEAVE pointings on the hemisphere grid within the outline of the HETDEX survey (black thick line; Hill et al. 2008). Note that this grid differs from the one used for LoTSS on account of LOFAR's even larger field of view. The black thick line also corresponds to the WQ-HighDens footprint boundary for WQ. The grey circle indicates the field of view of WEAVE in its MOS mode, to give a sense of the scale of this field.

bright emission lines in our LOFAR-selected sample for achieving a high redshift success rate, it follows that for many of our targets the WEAVE LR spectra will not detect the continuum. Spectral stacking experiments – relying on the large samples coupled with the high quality and uniformity of the WEAVE LR spectra – are therefore a critical means of studying the continuum of 150 MHz sources (and all of the information it contains) as a function of stellar mass, environment, redshift, and source classification.

We also have plans to use the WEAVE integral-field spectrographs (mIFU and LIFU) in relatively undersubscribed weather conditions to study individual sources in more detail and, in doing so, build on the broad picture that will be produced by the MOS survey. Using the WEAVE mIFUs in LR mode, we will obtain resolved spectroscopy of around 1000 bright background sources identified in the WL-Wide tier, and which have foreground neighbours that appear close in projection. This sample will enable us to identify absorption systems in the line of sight, and allow for the study of the properties of the extended neutral gas reservoirs. These reservoirs can only be detected in absorption against a bright background continuum source, but they play a critical role in fuelling star formation (e.g. Maddox et al. 2015; Dutta et al. 2017). We will also use the LIFU in HR mode to study the details of AGN feedback in nearby cluster cores, including the relationship between the radio jets, the intracluster medium, and the central cluster galaxy. We will revisit the same targets as often as the conditions and WEAVE SCHEDULER allow, building increasingly sensitive data cubes. With this data set, we can conduct the best-yet study of the 10⁶ K plasma probed by coronal lines (revealing the cooling in action), as well as the kinematics of the ionized gas, and deconstruct the stellar population in these local analogues of starburst galaxies containing powerful AGNs at *z* > 1.

The scope of WL is unprecedented, and it is therefore all but guaranteed that the WL survey will also discover some wholly unexpected phenomena within the rich legacy data set that it will produce.

## 4.8 The WEAVE-QSO Survey

The WQ survey (Pieri et al. 2016, and in preparation) will observe around 450 000 high-redshift quasars over an area of up to 10 000 deg² called WQ-Wide. Nested within this, we intend to survey a denser sampling of quasars targeted with J-PAS (Javalambre Physics of the Accelerating Universe Survey; Benitez et al. 2014) data over ~6000 deg². Further nested within this wide J-PAS area is a special, high-density footprint of ~420 deg² in the HETDEX spring field called WQ-HighDens. All objects targeted by WQ will be chosen to recover spectra of quasars with $z_q > 2.2$, which is sufficiently high to provide coverage of the Lyman-α (Lyα) forest at $z > 2$ (hereafter, we use the term 'Lyα-forest quasars' for these objects). The objective is to deepen our understanding of the IGM, the circumgalactic medium (CGM), and large-scale-structure cosmology through the study of intervening Lyα and metal-line absorption.

The science objectives of WQ are associated with two observational challenges: the probing of three-dimensional large-scale structures that span multiple quasar sight-lines (both statistically and in the form of maps), and the detailed study of small (extragalactic) scales in one dimension along isolated sight-lines. The former is contingent on WQ's expected observations of an unrivalled number density of Lyα-forest quasars, while the latter rests on the WEAVE Survey's unprecedented resolution and S/N among massive spectroscopic surveys. This science is based on a near-complete and pure sampling of Lyα-forest quasars.<fnref n="27" /> WQ fields are predominantly at high Galactic latitudes, where the science return is optimized by wide-area coverage in WQ-Wide. Fields will therefore be shared with the WEAVE GA and WL surveys in the LR mode, with some limited data also in the HR mode through additional field-sharing with the GA survey. WQ will also have a smaller, higher density

<footnote n="27">²⁷Our projections are based on estimates of the quasar population given by Palanque-Delabrouille et al. (2016).</footnote>
<figure><img src="image_21.png" /></figure>

**Figure 20.** 150 MHz mosaic of the region surrounding the HETDEX field using LoTSS data from the second data release (red colour scale, from Martin Hardcastle, private communication). The HETDEX spring field is one of the principal areas of sky in the WL 'Mid' tier. Overlaid on the map (the full-resolution version of which reaches a median noise level of 69 µJy beam⁻¹ and contains >500k sources detected at >5σ at 150 MHz) is the pointing grid for the fields shared with the WEAVE GA and WQ surveys, covering the whole sky north of Dec = −10 deg (black dots, derived using the method of Saff & Kuijlaars 1997). The blue dots indicate those WEAVE pointings on the hemisphere grid within the outline of the HETDEX survey (black thick line; Hill et al. 2008). Note that this grid differs from the one used for LoTSS on account of LOFAR's even larger field of view. The black thick line also corresponds to the WQ-HighDens footprint boundary for WQ. The grey circle indicates the field of view of WEAVE in its MOS mode, to give a sense of the scale of this field.

bright emission lines in our LOFAR-selected sample for achieving a high redshift success rate, it follows that for many of our targets the WEAVE LR spectra will not detect the continuum. Spectral stacking experiments – relying on the large samples coupled with the high quality and uniformity of the WEAVE LR spectra – are therefore a critical means of studying the continuum of 150 MHz sources (and all of the information it contains) as a function of stellar mass, environment, redshift, and source classification.

We also have plans to use the WEAVE integral-field spectrographs (mIFU and LIFU) in relatively undersubscribed weather conditions to study individual sources in more detail and, in doing so, build on the broad picture that will be produced by the MOS survey. Using the WEAVE mIFUs in LR mode, we will obtain resolved spectroscopy of around 1000 bright background sources identified in the WL-Wide tier, and which have foreground neighbours that appear close in projection. This sample will enable us to identify absorption systems in the line of sight, and allow for the study of the properties of the extended neutral gas reservoirs. These reservoirs can only be detected in absorption against a bright background continuum source, but they play a critical role in fuelling star formation (e.g. Maddox et al. 2015; Dutta et al. 2017). We will also use the LIFU in HR mode to study the details of AGN feedback in nearby cluster cores, including the relationship between the radio jets, the intracluster medium, and the central cluster galaxy. We will revisit the same targets as often as the conditions and WEAVE SCHEDULER allow, building increasingly sensitive data cubes. With this data set, we can conduct the best-yet study of the 10⁶ K plasma probed by coronal lines (revealing the cooling in action), as well as the kinematics of the ionized gas, and deconstruct the stellar population in these local analogues of starburst galaxies containing powerful AGNs at *z* > 1.

The scope of WL is unprecedented, and it is therefore all but guaranteed that the WL survey will also discover some wholly unexpected phenomena within the rich legacy data set that it will produce.

## 4.8 The WEAVE-QSO Survey

The WQ survey (Pieri et al. 2016, and in preparation) will observe around 450 000 high-redshift quasars over an area of up to 10 000 deg² called WQ-Wide. Nested within this, we intend to survey a denser sampling of quasars targeted with J-PAS (Javalambre Physics of the Accelerating Universe Survey; Benitez et al. 2014) data over ~6000 deg². Further nested within this wide J-PAS area is a special, high-density footprint of ~420 deg² in the HETDEX spring field called WQ-HighDens. All objects targeted by WQ will be chosen to recover spectra of quasars with $z_q > 2.2$, which is sufficiently high to provide coverage of the Lyman-α (Lyα) forest at $z > 2$ (hereafter, we use the term 'Lyα-forest quasars' for these objects). The objective is to deepen our understanding of the IGM, the circumgalactic medium (CGM), and large-scale-structure cosmology through the study of intervening Lyα and metal-line absorption.

The science objectives of WQ are associated with two observational challenges: the probing of three-dimensional large-scale structures that span multiple quasar sight-lines (both statistically and in the form of maps), and the detailed study of small (extragalactic) scales in one dimension along isolated sight-lines. The former is contingent on WQ's expected observations of an unrivalled number density of Lyα-forest quasars, while the latter rests on the WEAVE Survey's unprecedented resolution and S/N among massive spectroscopic surveys. This science is based on a near-complete and pure sampling of Lyα-forest quasars.<fnref n="27" /> WQ fields are predominantly at high Galactic latitudes, where the science return is optimized by wide-area coverage in WQ-Wide. Fields will therefore be shared with the WEAVE GA and WL surveys in the LR mode, with some limited data also in the HR mode through additional field-sharing with the GA survey. WQ will also have a smaller, higher density

<footnote n="27">²⁷Our projections are based on estimates of the quasar population given by Palanque-Delabrouille et al. (2016).</footnote>
LR-mode footprint in WQ-HighDens, sharing fields only with GA
targets.

A major goal of WQ is to help address one of the main cosmological challenges of our time: determining the cause of the acceleration in the expansion of the Universe (termed ‘dark energy’). A natural approach to the problem is to measure the expansion history of the Universe at various epochs to characterize its emergence. Baryon Acoustic Oscillations (BAOs; e.g. Seo & Eisenstein 2003) are potentially observable over the entire post-recombination Universe and so provide a convenient standard ruler with which to achieve this. In quasar absorption spectroscopy, we measure large-scale structure in ‘skewers’ of density through the Universe, along the lines of sight to these quasars. In this way, we can probe the large-scale 3D distribution of gas using statistical correlations between lines of sight, allowing a measurement of BAO and hence expansion at $z > 2$. This method was first demonstrated with the Baryon Oscillation Spectroscopic Survey (BOSS; e.g. Busca et al. 2013), and reached maturity in final BOSS results (Bautista et al. 2015; du Mas des Bourboux et al. 2017) with a sample of ~150 000 Lyα-forest spectra observed over five years, and further developed in eBOSS (Dawson et al. 2016; de Sainte Agathe et al. 2019; Blomqvist et al. 2019; du Mas des Bourboux et al. 2020) to reach over 200 000 quasars with $z_q > 2$.

WQ will approximately double the number of observed Lyα-forest quasars and, more importantly, achieve an unprecedented number density on the sky. Lyα-forest measurements of 3D large-scale structure remain far from the cosmic variance limit in next-generation surveys. Furthermore, the value to the survey of selecting any given quasar for these measurements is a weak function of signal-to-noise (e.g. McQuinn & White 2011). We therefore conclude that the principal driver of correlation-function precision (and hence expected BAO constraints) is the number density of quasars to be observed. WQ will provide competitive constraints despite observing little more than half the number of Lyα-forest quasars expected in DESI, the other next-generation quasar survey (DESI Collaboration 2016a). WQ will achieve the necessary boost in BAO precision by concentrating on a higher density sampling. This will be achieved through observing more quasars per unit area over a smaller footprint (up to 6000 deg² instead of the 14 000 deg² currently planned for DESI; DESI Collaboration 2016a), a narrower redshift range, and a magnitude limit fainter by $\Delta r \approx 0.5$.

In the magnitude range $21.5 < r < 23.5$ and within the wide J-PAS targeted footprint, WQ will observe a redshift subset of the available Lyα-forest quasar population. This is in order to obtain the highest sampling density possible for large-scale-structure analyses in 3D. Two options presented themselves as broadly bisecting the Lyα-forest quasar population: $z < 2.45$ and $z > 2.45$. A convenient metric for the 3D large-scale-structure statistics is provided by BAO measurement precision, and a convenient baseline for comparison is the DESI survey as currently planned (DESI Collaboration 2016a). Fisher forecasts were previously used to assess this choice (Pieri et al. 2016), and we return to the question here of using models based on 100 random realizations of correlation functions derived from the scaled BOSS covariance matrices (following the method set out by du Mas des Bourboux et al. 2017 and Blomqvist et al. 2018). The results are summarized in Fig. 21, assuming a 6000 deg² footprint, and show that the WQ survey is more optimal when directed towards this higher-redshift window. This projection neglects the fact that DESI is boosted in the low-redshift window through the cross-correlation of lower-redshift quasars, further reinforcing the preference for higher-redshift quasars.

Consequently, we choose to target faint quasars with $2.45 < z_q < 3$ for statistical measurements of 3D large-scale structure. Note

<figure><img src="image_21.png" /><figcaption>**Figure 21.** Lyα-forest BAO precision as a function of analysis redshift assuming a 6000 deg² WQ survey with quasars at either $2.1 < z_q < 2.5$ [triangles at $z \sim 2.15$ for autocorrelation (filled) and $z \sim 2.23$ for cross-correlation (open)] or $2.5 < z_q < 3$ [triangles at $z \sim 2.4$ for autocorrelation (filled) and $z \sim 2.5$ for cross-correlation (open)], compared with the planned DESI survey (squares; DESI Collaboration 2016a), which will cover both redshift ranges. Results are derived from random realizations of the Lyα-forest autocorrelation (filled symbols) and the Lyα-forest cross-correlations (open symbols) with quasar positions. These are broken down into a Hubble parameter constraint (radial BAO, $\|\|$) and an angular diameter distance constraint (transverse BAO, $\perp$). Both redshift bands offer a significant improvement on BOSS (and eBOSS) BAO precision, but the higher redshift band is preferred, given WEAVE’s performance with respect to DESI. Note that the Lyα forest is always observed in the foreground of the quasars, hence the lower redshift of the measurements compared to the redshift range of the quasars. In addition, the redshift of the predictions is the average of certain pairs – pairs of Lyα pixels in the case of the autocorrelation, and pairs of Lyα pixels and quasars for the cross-correlation, resulting in a lower redshift for the autocorrelation than for the cross-correlation in each case.</figcaption></figure>

that this requirement is lifted in the special high-density field of WQ-HighDens, where we target all available Lyα-forest quasars.

The high density of quasars required for competitive 3D large-scale-structure analyses and the maximal brighter sample needed for high-quality isolated sight-line studies both require $\gtrsim 90$ per cent Lyα-forest quasar completeness. This will be achieved with J-PAS for the majority of the WQ survey footprint. J-PAS is an imaging survey covering more than 8000 deg² (see Fig. 19) with 56 narrow-band filters, of which a coverage of ~6000 deg² of the WQ footprint is expected on a timescale practical for WQ target selection. Lyα-forest quasars will be derived from this sample using a variety of machine-learning methods trained and tested on a variety of simulated and observational data (Pérez-Rafols et al. 2020, 2023; Pérez-Rafols & Pieri 2020; Bonoli et al. 2021; Martínez-Solaeche et al. 2022; Queiroz et al. 2023; Rodrigues et al. 2023).

In addition to using J-PAS data for target selection, WQ will join with J-PAS to cross-correlate the Lyα forest with J-PAS quasars even when not targeted spectroscopically, and to explore cross-correlation with faint Lyα sources in J-PAS images treated as an intensity map. The ability to statistically study various IGM/CGM properties using such high-density quasar sampling and high completeness has been demonstrated in BOSS and eBOSS or tested in simulations (e.g. Blomqvist et al. 2018; Gontcho A Gontcho et al. 2018; Pérez-Rafols et al. 2018; Sorini et al. 2018; Sorini, Davé & Anglés-Alcázar 2020; Morrison et al. 2021).

Our measurement of 3D large-scale structure is not limited to statistical estimators such as correlation functions of the Lyα forest.
LR-mode footprint in WQ-HighDens, sharing fields only with GA
targets.

A major goal of WQ is to help address one of the main cosmological challenges of our time: determining the cause of the acceleration in the expansion of the Universe (termed ‘dark energy’). A natural approach to the problem is to measure the expansion history of the Universe at various epochs to characterize its emergence. Baryon Acoustic Oscillations (BAOs; e.g. Seo & Eisenstein 2003) are potentially observable over the entire post-recombination Universe and so provide a convenient standard ruler with which to achieve this. In quasar absorption spectroscopy, we measure large-scale structure in ‘skewers’ of density through the Universe, along the lines of sight to these quasars. In this way, we can probe the large-scale 3D distribution of gas using statistical correlations between lines of sight, allowing a measurement of BAO and hence expansion at $z > 2$. This method was first demonstrated with the Baryon Oscillation Spectroscopic Survey (BOSS; e.g. Busca et al. 2013), and reached maturity in final BOSS results (Bautista et al. 2015; du Mas des Bourboux et al. 2017) with a sample of ~150 000 Lyα-forest spectra observed over five years, and further developed in eBOSS (Dawson et al. 2016; de Sainte Agathe et al. 2019; Blomqvist et al. 2019; du Mas des Bourboux et al. 2020) to reach over 200 000 quasars with $z_q > 2$.

WQ will approximately double the number of observed Lyα-forest quasars and, more importantly, achieve an unprecedented number density on the sky. Lyα-forest measurements of 3D large-scale structure remain far from the cosmic variance limit in next-generation surveys. Furthermore, the value to the survey of selecting any given quasar for these measurements is a weak function of signal-to-noise (e.g. McQuinn & White 2011). We therefore conclude that the principal driver of correlation-function precision (and hence expected BAO constraints) is the number density of quasars to be observed. WQ will provide competitive constraints despite observing little more than half the number of Lyα-forest quasars expected in DESI, the other next-generation quasar survey (DESI Collaboration 2016a). WQ will achieve the necessary boost in BAO precision by concentrating on a higher density sampling. This will be achieved through observing more quasars per unit area over a smaller footprint (up to 6000 deg² instead of the 14 000 deg² currently planned for DESI; DESI Collaboration 2016a), a narrower redshift range, and a magnitude limit fainter by $\Delta r \approx 0.5$.

In the magnitude range $21.5 < r < 23.5$ and within the wide J-PAS targeted footprint, WQ will observe a redshift subset of the available Lyα-forest quasar population. This is in order to obtain the highest sampling density possible for large-scale-structure analyses in 3D. Two options presented themselves as broadly bisecting the Lyα-forest quasar population: $z < 2.45$ and $z > 2.45$. A convenient metric for the 3D large-scale-structure statistics is provided by BAO measurement precision, and a convenient baseline for comparison is the DESI survey as currently planned (DESI Collaboration 2016a). Fisher forecasts were previously used to assess this choice (Pieri et al. 2016), and we return to the question here of using models based on 100 random realizations of correlation functions derived from the scaled BOSS covariance matrices (following the method set out by du Mas des Bourboux et al. 2017 and Blomqvist et al. 2018). The results are summarized in Fig. 21, assuming a 6000 deg² footprint, and show that the WQ survey is more optimal when directed towards this higher-redshift window. This projection neglects the fact that DESI is boosted in the low-redshift window through the cross-correlation of lower-redshift quasars, further reinforcing the preference for higher-redshift quasars.

Consequently, we choose to target faint quasars with $2.45 < z_q < 3$ for statistical measurements of 3D large-scale structure. Note

<figure><img src="image_22.png" /><figcaption>**Figure 21.** Lyα-forest BAO precision as a function of analysis redshift assuming a 6000 deg² WQ survey with quasars at either $2.1 < z_q < 2.5$ [triangles at $z \sim 2.15$ for autocorrelation (filled) and $z \sim 2.23$ for cross-correlation (open)] or $2.5 < z_q < 3$ [triangles at $z \sim 2.4$ for autocorrelation (filled) and $z \sim 2.5$ for cross-correlation (open)], compared with the planned DESI survey (squares; DESI Collaboration 2016a), which will cover both redshift ranges. Results are derived from random realizations of the Lyα-forest autocorrelation (filled symbols) and the Lyα-forest cross-correlations (open symbols) with quasar positions. These are broken down into a Hubble parameter constraint (radial BAO, $\|\|$) and an angular diameter distance constraint (transverse BAO, $\perp$). Both redshift bands offer a significant improvement on BOSS (and eBOSS) BAO precision, but the higher redshift band is preferred, given WEAVE’s performance with respect to DESI. Note that the Lyα forest is always observed in the foreground of the quasars, hence the lower redshift of the measurements compared to the redshift range of the quasars. In addition, the redshift of the predictions is the average of certain pairs – pairs of Lyα pixels in the case of the autocorrelation, and pairs of Lyα pixels and quasars for the cross-correlation, resulting in a lower redshift for the autocorrelation than for the cross-correlation in each case.</figcaption></figure>

that this requirement is lifted in the special high-density field of WQ-HighDens, where we target all available Lyα-forest quasars.

The high density of quasars required for competitive 3D large-scale-structure analyses and the maximal brighter sample needed for high-quality isolated sight-line studies both require $\gtrsim 90$ per cent Lyα-forest quasar completeness. This will be achieved with J-PAS for the majority of the WQ survey footprint. J-PAS is an imaging survey covering more than 8000 deg² (see Fig. 19) with 56 narrow-band filters, of which a coverage of ~6000 deg² of the WQ footprint is expected on a timescale practical for WQ target selection. Lyα-forest quasars will be derived from this sample using a variety of machine-learning methods trained and tested on a variety of simulated and observational data (Pérez-Ràfols et al. 2020, 2023; Pérez-Ràfols & Pieri 2020; Bonoli et al. 2021; Martínez-Solaeche et al. 2022; Queiroz et al. 2023; Rodrigues et al. 2023).

In addition to using J-PAS data for target selection, WQ will join with J-PAS to cross-correlate the Lyα forest with J-PAS quasars even when not targeted spectroscopically, and to explore cross-correlation with faint Lyα sources in J-PAS images treated as an intensity map. The ability to statistically study various IGM/CGM properties using such high-density quasar sampling and high completeness has been demonstrated in BOSS and eBOSS or tested in simulations (e.g. Blomqvist et al. 2018; Gontcho A Gontcho et al. 2018; Pérez-Ràfols et al. 2018; Sorini et al. 2018; Sorini, Davé & Anglés-Alcázar 2020; Morrison et al. 2021).

Our measurement of 3D large-scale structure is not limited to statistical estimators such as correlation functions of the Lyα forest.
<figure><img src="image_22.png" /><figcaption>**Figure 22.** Transverse slice of the original (left) and reconstructed (right) density field in two WQ configurations at $z = 2.12$. Top right: a projected 60 cMpc $h^{-1}$-thick slice of the tomographic reconstruction illustrating the potential WQ sample in WQ-HighDens. The transverse correlation length $L_T$ is set to 14 cMpc $h^{-1}$. Top left: original density field smoothed with a Gaussian kernel at the same scale. Bottom right: projected slice (20 cMpc $h^{-1}$ in thickness) of the peak tomographic reconstruction expected over a few Mpc around 60 small patches where quasars appear closely clustered. This corresponds to a transverse separation of ~1.5 cMpc $h^{-1}$. Bottom left: original density field smoothed with a Gaussian kernel at the same scale. The colours of the maps encode the density contrast.</figcaption></figure>

Cosmic-web mapping through large-scale-structure tomography will be pursued via three distinct programmes: a wide tier (in WQ-Wide) at low density (and so mapping LR), a higher density tier with higher resolution (in WQ-HighDens), and one focused on rare, close groups of quasars (in WQ-Wide). For the wide tier, WQ occupies a novel niche as the only current or imminent survey with an area larger than 15 deg$^2$. Other relevant facilities include the COSMOS Lyman-Alpha Mapping And Tomography Observations (CLAMATO: Lee et al. 2018; 0.8 deg$^2$), PFS (Takada et al. 2014; ~15 deg$^2$), the Multi-Object Spectrograph for Astrophysics, Intergalactic-medium studies and Cosmology for the Extremely Large Telescope (MOSAIC/ELT: Japelj et al. 2019; <10 deg$^2$), and the Maunakea Spectroscopic Explorer (MSE: The MSE Science Team 2019; ~80 deg$^2$). These surveys will achieve transverse lengths (the average separation between sight-lines) of 2–3 cMpc $h^{-1}$, and while WQ will only achieve ~15–20 cMpc $h^{-1}$, it will do so up to 6000 deg$^2$ and in rare cases will reach a peak resolution as high as ~1 cMpc $h^{-1}$.

Higher average resolution (~15 cMpc $h^{-1}$) is expected over the ~420 deg$^2$ of the WQ-HighDens footprint (Fig. 20), where we will survey quasars densely without limits on the Ly$\alpha$-forest redshift range.

The potential IGM tomography we may derive from this sample is illustrated in the upper panels of Fig. 22 and further detailed in a forthcoming WQ publication (Pieri et al., in preparation). The upper left panel shows a simulated H1 distribution generated from a dark matter simulation and the LYMAS code$^{28}$ (Peirani et al. 2014),

smoothed to reflect the desired resolution. The upper right panel shows a projection of WQ-based reconstruction of this simulation in WQ-HighDens through Wiener filtering (e.g. Pichon et al. 2001; Caucci et al. 2008; Lee et al. 2018) with a random distribution of Ly$\alpha$-forest quasars. Note that we neglect here the potential boost we may derive by incorporating the HETDEX data of Ly$\alpha$ emitters into the reconstruction.

The WQ-Wide footprint is expected to provide peak cosmic web reconstruction resolution in approximately 60 small patches where three or more quasars with $r < 21$ are separated by ~1 cMpc $h^{-1}$. This is demonstrated in the lower panels of Fig. 22. The bottom left panel shows a simulated H1 distribution smoothed to reflect our desired peak resolution. The corresponding tomographic reconstruction provided by these WQ multiplexes is shown in the bottom right panel (though this is naturally not available for the entire 100 cMpc $h^{-1}$-wide region shown). The IGM tomography potential of WQ is explored further in Kraljic et al. (2022). Beyond these peak-resolution regions and the WQ-HighDens area, the resolution will vary up to around 15–20 cMpc $h^{-1}$, making it suitable for a wide void/non-void separation (Ozbek, Croft & Khandai 2016).

All of these maps of varying resolution will provide insights into the impact of environment on IGM and galaxy properties, noting that $z > 2$ is the epoch where the star formation rate reaches its peak (Hopkins & Beacom 2006; Madau & Dickinson 2014), where intergalactic gas accretion along filaments is critical for the formation of galaxies (e.g. Kereš et al. 2005). Furthermore, a complete sample of quasars will allow for the study of their connection to large-scale (re)ionization of the cosmic web (e.g. Morrison et al. 2019).

Beyond the J-PAS targeted sub-area of WQ-Wide, WQ will observe bright quasars and, over its entire low-resolution footprint, WQ will obtain spectra of almost all bright ($r \lesssim 21$) Ly$\alpha$ quasars. This constitutes up to 4000 deg$^2$ targeted initially using a combination of Gaia + unWISE objects (Shu et al. 2019) and SDSS-IV DR16 (Lyke et al. 2020), with Gaia spectroscopy to be incorporated progressively (e.g. Gaia Collaboration 2023b).

With the addition of this sample, WQ will offer unparalleled spectral resolution (mostly $R = 5000$ but also $R = 20000$) with high signal-to-noise (>4–7 Å$^{-1}$). Improved spectral resolution will enable the study of gas temperature and structures on smaller scales (e.g. Palanque-Delabrouille et al. 2013; Viel et al. 2013): the relationship between temperature and density in the IGM is a fundamental quantity describing the physical state of baryons during reionization. Such data will allow the study of smaller scale power in the matter distribution, measuring neutrino masses and alternative forms of dark matter. The improved resolution provided by WQ will aide in breaking the degeneracy between the small-scale suppression of power caused by IGM temperature and these cosmological effects, which are currently marginalized over using extensive and expensive hydrodynamic simulations.

Galaxies and CGM regions are identified in absorption as damped Ly$\alpha$ systems (e.g. Krogager et al. 2017), Lyman-limit systems (e.g. Fumagalli et al. 2013), and strongly blended Ly$\alpha$ systems (Pieri et al. 2014, and Morrison et al. 2023). The BOSS and eBOSS surveys demonstrate that a great deal can be learnt about such systems (e.g. Noterdaeme et al. 2012; Pieri et al. 2014; Mas-Ribas et al. 2017). Improved spectral resolution and signal-to-noise provided by WQ will allow greater fidelity of such systems, and machine-learning methods have been developed to recover them (e.g. Fumagalli, Fotopoulou & Thomson 2020). In particular, damped systems with lower column density and/or higher redshift will be more readily identified. Furthermore, narrow metal absorption lines associated with the ISM, CGM, and IGM will be more statistically significant,

<footnote>$^{28}$http://www2.iap.fr/users/peirani/lymas/lymas.htm</footnote>
<figure><img src="image_23.png" /><figcaption>**Figure 22.** Transverse slice of the original (left) and reconstructed (right) density field in two WQ configurations at $z = 2.12$. Top right: a projected 60 cMpc $h^{-1}$-thick slice of the tomographic reconstruction illustrating the potential WQ sample in WQ-HighDens. The transverse correlation length $L_T$ is set to 14 cMpc $h^{-1}$. Top left: original density field smoothed with a Gaussian kernel at the same scale. Bottom right: projected slice (20 cMpc $h^{-1}$ in thickness) of the peak tomographic reconstruction expected over a few Mpc around 60 small patches where quasars appear closely clustered. This corresponds to a transverse separation of ~1.5 cMpc $h^{-1}$. Bottom left: original density field smoothed with a Gaussian kernel at the same scale. The colours of the maps encode the density contrast.</figcaption></figure>

Cosmic-web mapping through large-scale-structure tomography will be pursued via three distinct programmes: a wide tier (in WQ-Wide) at low density (and so mapping LR), a higher density tier with higher resolution (in WQ-HighDens), and one focused on rare, close groups of quasars (in WQ-Wide). For the wide tier, WQ occupies a novel niche as the only current or imminent survey with an area larger than 15 deg². Other relevant facilities include the COSMOS Lyman-Alpha Mapping And Tomography Observations (CLAMATO: Lee et al. 2018; 0.8 deg²), PFS (Takada et al. 2014; ~15 deg²), the Multi-Object Spectrograph for Astrophysics, Intergalactic-medium studies and Cosmology for the Extremely Large Telescope (MOSAIC/ELT: Japelj et al. 2019; <10 deg²), and the Maunakea Spectroscopic Explorer (MSE: The MSE Science Team 2019; ~80 deg²). These surveys will achieve transverse lengths (the average separation between sight-lines) of 2–3 cMpc $h^{-1}$, and while WQ will only achieve ~15–20 cMpc $h^{-1}$, it will do so up to 6000 deg² and in rare cases will reach a peak resolution as high as ~1 cMpc $h^{-1}$.

Higher average resolution (~15 cMpc $h^{-1}$) is expected over the ~420 deg² of the WQ-HighDens footprint (Fig. 20), where we will survey quasars densely without limits on the Ly$\alpha$-forest redshift range.

The potential IGM tomography we may derive from this sample is illustrated in the upper panels of Fig. 22 and further detailed in a forthcoming WQ publication (Pieri et al., in preparation). The upper left panel shows a simulated H1 distribution generated from a dark matter simulation and the LYMAS code<fnref n="28" /> (Peirani et al. 2014),

smoothed to reflect the desired resolution. The upper right panel shows a projection of WQ-based reconstruction of this simulation in WQ-HighDens through Wiener filtering (e.g. Pichon et al. 2001; Caucci et al. 2008; Lee et al. 2018) with a random distribution of Ly$\alpha$-forest quasars. Note that we neglect here the potential boost we may derive by incorporating the HETDEX data of Ly$\alpha$ emitters into the reconstruction.

The WQ-Wide footprint is expected to provide peak cosmic web reconstruction resolution in approximately 60 small patches where three or more quasars with $r < 21$ are separated by ~1 cMpc $h^{-1}$. This is demonstrated in the lower panels of Fig. 22. The bottom left panel shows a simulated H1 distribution smoothed to reflect our desired peak resolution. The corresponding tomographic reconstruction provided by these WQ multiplexes is shown in the bottom right panel (though this is naturally not available for the entire 100 cMpc $h^{-1}$-wide region shown). The IGM tomography potential of WQ is explored further in Kraljic et al. (2022). Beyond these peak-resolution regions and the WQ-HighDens area, the resolution will vary up to around 15–20 cMpc $h^{-1}$, making it suitable for a wide void/non-void separation (Ozbek, Croft & Khandai 2016).

All of these maps of varying resolution will provide insights into the impact of environment on IGM and galaxy properties, noting that $z > 2$ is the epoch where the star formation rate reaches its peak (Hopkins & Beacom 2006; Madau & Dickinson 2014), where intergalactic gas accretion along filaments is critical for the formation of galaxies (e.g. Kereš et al. 2005). Furthermore, a complete sample of quasars will allow for the study of their connection to large-scale (re)ionization of the cosmic web (e.g. Morrison et al. 2019).

Beyond the J-PAS targeted sub-area of WQ-Wide, WQ will observe bright quasars and, over its entire low-resolution footprint, WQ will obtain spectra of almost all bright ($r \lesssim 21$) Ly$\alpha$ quasars. This constitutes up to 4000 deg² targeted initially using a combination of Gaia + unWISE objects (Shu et al. 2019) and SDSS-IV DR16 (Lyke et al. 2020), with Gaia spectroscopy to be incorporated progressively (e.g. Gaia Collaboration 2023b).

With the addition of this sample, WQ will offer unparalleled spectral resolution (mostly $R = 5000$ but also $R = 20000$) with high signal-to-noise (>4–7 Å$^{-1}$). Improved spectral resolution will enable the study of gas temperature and structures on smaller scales (e.g. Palanque-Delabrouille et al. 2013; Viel et al. 2013): the relationship between temperature and density in the IGM is a fundamental quantity describing the physical state of baryons during reionization. Such data will allow the study of smaller scale power in the matter distribution, measuring neutrino masses and alternative forms of dark matter. The improved resolution provided by WQ will aide in breaking the degeneracy between the small-scale suppression of power caused by IGM temperature and these cosmological effects, which are currently marginalized over using extensive and expensive hydrodynamic simulations.

Galaxies and CGM regions are identified in absorption as damped Ly$\alpha$ systems (e.g. Krogager et al. 2017), Lyman-limit systems (e.g. Fumagalli et al. 2013), and strongly blended Ly$\alpha$ systems (Pieri et al. 2014, and Morrison et al. 2023). The BOSS and eBOSS surveys demonstrate that a great deal can be learnt about such systems (e.g. Noterdaeme et al. 2012; Pieri et al. 2014; Mas-Ribas et al. 2017). Improved spectral resolution and signal-to-noise provided by WQ will allow greater fidelity of such systems, and machine-learning methods have been developed to recover them (e.g. Fumagalli, Fotopoulou & Thomson 2020). In particular, damped systems with lower column density and/or higher redshift will be more readily identified. Furthermore, narrow metal absorption lines associated with the ISM, CGM, and IGM will be more statistically significant,

<footnote n="28">²⁸http://www2.iap.fr/users/peirani/lymas/lymas.htm</footnote>
resolved, and informative in WQ spectra. Studying the properties of such systems will be of increasing importance over the coming years given the quality and size of the WQ sample combined with wide-area $z > 2$ galaxy surveys such as HETDEX. This is a key epoch for galaxy assembly, as it includes the early portion of the peak in the star formation rate. The combination of absorber fidelity, gas temperature, improved galaxy identification, small-scale CGM effects, and large-scale-structure context, all at the peak of star formation rate, will make WQ transformative for our understanding of galaxy formation.

In weather conditions deemed sub-optimal for our primary-science purposes, we intend to use the LIFU to target quasar pairs or groups too close to be targeted in the MOS mode. We will also probe extended emission near quasars and unresolved galaxies in front of quasars using the mIFU mode. These science goals are well adapted to poor seeing, as the LIFU fibres have twice the diameter of their MOS counterparts (see Table 2), while extended or unresolved emission need only be within the mIFU.

The WQ survey aims to achieve an unprecedented diversity of IGM science goals spanning scales from sub-kpc structures in the CGM to the BAO scale. This will be achieved chiefly by exploiting WEAVE's high spectral resolution and WQ's high target density with respect to previous and contemporary spectroscopic surveys.

# 5 THE WEAVE SIMULATOR

During the preliminary design phase of the project, it was recognised that the spectral resolution delivered by the spectrograph would vary as a function of wavelength *and* as a function of fibre position along the slit (Fig. 23). After initial modelling of this effect at a low level for validation of the design, it was decided that a full image simulation would be required to provide representative input for end-to-end testing of the data-processing system. This section provides a description of such a simulator that was created in order to generate representative data for the majority of WEAVE Survey use cases as part of a full Operational Rehearsal (see Section 6 and Dalton et al. 2016b), in order to simulate the implementation of the Survey.

## 5.1 Point spread functions

In order to capture the variation in point spread function (PSF) across the field, we used ZEMAX<fnref n="29" /> to generate the PSF at nine equally spaced wavelengths for each fibre in the top half of the slit for each of the five modes given in Table 3. Each PSF is generated as a 25 × 25 pixel image with 15 µm pixels, using 10⁷ rays to ensure that the outer wings are fully sampled. The ray trace assumes a uniform circular output aperture for the fibre, which is not strictly correct but considered to be adequate for the purposes of this simulation. Internal vignetting in the spectrograph is included here. Each PSF generated in this way is centred on the chief ray, and the position of this in focal plane coordinates is recorded. These data are generated once only for each mode using the nominal configuration of the spectrograph optics and stored for use at runtime.

## 5.2 Input fields

The simulator is driven by an input in the form of an extended OB XML file, with additional elements for the actual conditions of the observation (time, date, seeing, and transparency), together with an additional descriptive element for each target containing velocity

(or redshift), magnitude, bandpass, target FWHM (for extended sources), and the appropriate spectral template to use. The input field is parsed to determine the location and fibre allocation for each target, and these are used to calculate the vignetting factor at the telescope focal plane (due to the prime-focus corrector optics) and the expected light loss at the spectrograph collimator (due to the non-telecentricity of the input to this fibre at this field position).

## 5.3 Sky background

For each OB, we use the expected date and time of observation to calculate the elevation, moon phase, and moon-target separation for the mid-point of the OB. We then use the ESO Paranal sky simulator (SKYCALC: Noll et al. 2012; Jones et al. 2013) to generate an estimate of the sky emission and absorption spectra for this observation at $R = 50\,000$ from 360 to 970 nm, which is then degraded to match the resolving power of WEAVE ($R = 5000$ for LR and $R = 20\,000$ for HR in the MOS/mIFU modes, each further lowered by a factor of two for the LIFU mode; see Table 3). We neglect the zodiacal emission terms, and scale the SKYCALC output spectrum to the recorded La Palma sky brightness for this date and time. The sky spectra are resampled to 20 000 pixels across the bandpass of each WEAVE mode to form a basis for each fibre input.

## 5.4 Template spectra

The template spectra referenced in the OB XML file are provided by the science teams to generate representative samples of spectra to test the data-processing pipelines. Each template is provided in flux units with the assumption that it will be scaled to a given apparent (AB) magnitude for observation. The only practical constraint on the input spectra is that they cover the full WEAVE spectral range. For each fibre allocated to a target, the template is read in, scaled to the appropriate magnitude and velocity or redshift, and converted from flux to incident photons. Finally, each spectrum is scaled to account for vignetting/telecentricity factors described in Section 5.2, aperture losses appropriate to the seeing extant at the time of the observations, and the telescope aperture and the exposure time. We apply the instrument throughput for the relevant mode, for which we adopt the as-designed throughput estimates reported in Dalton et al. (2014).

Since the different surveys have targets with very different characteristics, the simulator also allows for targets to have pre-determined aperture losses for extended sources, and pre-determined input fluxes (no magnitude scaling) for emission-line targets. Finally, the input sky spectrum (scaled by the appropriate factors for each fibre) is added, producing the final input spectrum for each fibre.

## 5.5 PSF resampling

For each fibre in turn, the PSF library described in Section 5.1 is then interpolated to give an array of 20 000 PSFs over the observed wavelength range (each centred on the effective position of the chief ray at the appropriate wavelength). For a subset of these, we directly calculated the same PSF in ZEMAX to check the validity of the interpolation. Each of these 20 000 PSFs is then resampled using a bivariate spline evaluated over a rectangular mesh to place the photons into the appropriate pixels of the WEAVE CCDs.

For fibres in the lower half of the slit, we use mirror images of the upper-half PSFs in order to save on storage space and save computation time.

<footnote n="29">²⁹https://www.zemax.com</footnote>
resolved, and informative in WQ spectra. Studying the properties of such systems will be of increasing importance over the coming years given the quality and size of the WQ sample combined with wide-area $z > 2$ galaxy surveys such as HETDEX. This is a key epoch for galaxy assembly, as it includes the early portion of the peak in the star formation rate. The combination of absorber fidelity, gas temperature, improved galaxy identification, small-scale CGM effects, and large-scale-structure context, all at the peak of star formation rate, will make WQ transformative for our understanding of galaxy formation.

In weather conditions deemed sub-optimal for our primary-science purposes, we intend to use the LIFU to target quasar pairs or groups too close to be targeted in the MOS mode. We will also probe extended emission near quasars and unresolved galaxies in front of quasars using the mIFU mode. These science goals are well adapted to poor seeing, as the LIFU fibres have twice the diameter of their MOS counterparts (see Table 2), while extended or unresolved emission need only be within the mIFU.

The WQ survey aims to achieve an unprecedented diversity of IGM science goals spanning scales from sub-kpc structures in the CGM to the BAO scale. This will be achieved chiefly by exploiting WEAVE's high spectral resolution and WQ's high target density with respect to previous and contemporary spectroscopic surveys.

# 5 THE WEAVE SIMULATOR

During the preliminary design phase of the project, it was recognised that the spectral resolution delivered by the spectrograph would vary as a function of wavelength *and* as a function of fibre position along the slit (Fig. 23). After initial modelling of this effect at a low level for validation of the design, it was decided that a full image simulation would be required to provide representative input for end-to-end testing of the data-processing system. This section provides a description of such a simulator that was created in order to generate representative data for the majority of WEAVE Survey use cases as part of a full Operational Rehearsal (see Section 6 and Dalton et al. 2016b), in order to simulate the implementation of the Survey.

## 5.1 Point spread functions

In order to capture the variation in point spread function (PSF) across the field, we used ZEMAX<fnref n="29" /> to generate the PSF at nine equally spaced wavelengths for each fibre in the top half of the slit for each of the five modes given in Table 3. Each PSF is generated as a 25 × 25 pixel image with 15 µm pixels, using 10⁷ rays to ensure that the outer wings are fully sampled. The ray trace assumes a uniform circular output aperture for the fibre, which is not strictly correct but considered to be adequate for the purposes of this simulation. Internal vignetting in the spectrograph is included here. Each PSF generated in this way is centred on the chief ray, and the position of this in focal plane coordinates is recorded. These data are generated once only for each mode using the nominal configuration of the spectrograph optics and stored for use at runtime.

## 5.2 Input fields

The simulator is driven by an input in the form of an extended OB XML file, with additional elements for the actual conditions of the observation (time, date, seeing, and transparency), together with an additional descriptive element for each target containing velocity

(or redshift), magnitude, bandpass, target FWHM (for extended sources), and the appropriate spectral template to use. The input field is parsed to determine the location and fibre allocation for each target, and these are used to calculate the vignetting factor at the telescope focal plane (due to the prime-focus corrector optics) and the expected light loss at the spectrograph collimator (due to the non-telecentricity of the input to this fibre at this field position).

## 5.3 Sky background

For each OB, we use the expected date and time of observation to calculate the elevation, moon phase, and moon-target separation for the mid-point of the OB. We then use the ESO Paranal sky simulator (SKYCALC: Noll et al. 2012; Jones et al. 2013) to generate an estimate of the sky emission and absorption spectra for this observation at $R = 50 000$ from 360 to 970 nm, which is then degraded to match the resolving power of WEAVE ($R = 5000$ for LR and $R = 20 000$ for HR in the MOS/mIFU modes, each further lowered by a factor of two for the LIFU mode; see Table 3). We neglect the zodiacal emission terms, and scale the SKYCALC output spectrum to the recorded La Palma sky brightness for this date and time. The sky spectra are resampled to 20 000 pixels across the bandpass of each WEAVE mode to form a basis for each fibre input.

## 5.4 Template spectra

The template spectra referenced in the OB XML file are provided by the science teams to generate representative samples of spectra to test the data-processing pipelines. Each template is provided in flux units with the assumption that it will be scaled to a given apparent (AB) magnitude for observation. The only practical constraint on the input spectra is that they cover the full WEAVE spectral range. For each fibre allocated to a target, the template is read in, scaled to the appropriate magnitude and velocity or redshift, and converted from flux to incident photons. Finally, each spectrum is scaled to account for vignetting/telecentricity factors described in Section 5.2, aperture losses appropriate to the seeing extant at the time of the observations, and the telescope aperture and the exposure time. We apply the instrument throughput for the relevant mode, for which we adopt the as-designed throughput estimates reported in Dalton et al. (2014).

Since the different surveys have targets with very different characteristics, the simulator also allows for targets to have pre-determined aperture losses for extended sources, and pre-determined input fluxes (no magnitude scaling) for emission-line targets. Finally, the input sky spectrum (scaled by the appropriate factors for each fibre) is added, producing the final input spectrum for each fibre.

## 5.5 PSF resampling

For each fibre in turn, the PSF library described in Section 5.1 is then interpolated to give an array of 20 000 PSFs over the observed wavelength range (each centred on the effective position of the chief ray at the appropriate wavelength). For a subset of these, we directly calculated the same PSF in ZEMAX to check the validity of the interpolation. Each of these 20 000 PSFs is then resampled using a bivariate spline evaluated over a rectangular mesh to place the photons into the appropriate pixels of the WEAVE CCDs.

For fibres in the lower half of the slit, we use mirror images of the upper-half PSFs in order to save on storage space and save computation time.

<footnote n="29">²⁹https://www.zemax.com</footnote>
<figure><img src="image_23.png" /><figcaption>**Figure 23.** Nominal WEAVE spectral resolution as a function of fibre number (x-axis) and wavelength (y-axis), computed from the spectrograph optical model. Left: low-resolution blue VPH grating. Right: low-resolution red VPH grating. Contours label regions of equal spectral resolution $R = \lambda/\Delta\lambda$. Note that these resolving powers correspond to MOS and mIFU modes, and are halved in the LIFU mode with its two-times larger fibres (see Table 2).</figcaption></figure>

## 5.6 Output images

When the spectra for all fibres have been added to the CCD images, the CCD bias, read-out noise, and Poisson noise are all added. The images are then saved with a complete *FITS* header, representative of the final WEAVE images. These images can then be sent to the WEAVE SPA pipelines for processing and distribution to the science teams via WEAVE's data archive system.

## 5.7 Calibration frames

In addition to science data frames, the simulator also generates calibration data frames in the form of bias, fibre flat-field, detector flat-field, and calibration arc-lamp frames. Fibre flat-fields and arcs include the same input losses at the telescope focal plane as the science data and the correct header information in order to allow the data-processing chains to function. For the flat-field lamp spectra, we assume a blackbody spectrum at 3500 K. For the arc lamp, we use the ThAr lamp spectral data from the National Optical Astronomy Observatory atlas,<fnref n="30" /> sampled at 0.002 nm pixel⁻¹ over the range 360–960 nm.

# 6 OPERATIONAL REHEARSALS

Using the WEAVE Simulator described in the previous section, a series of exercises were conducted to simulate the implementation of the Survey. These Operational Rehearsals (OpRs) were designed to simulate and test the flow of data in various guises through and between different nodes of the WEAVE data systems (see Sections 2.5 and 2.6), including the OCS, CPS, APS, and WAS. The OpRs have also seen significant involvement of Science Team members, mainly through the work of the SWG (see Section 3.1) and the QAG (see Section 3.3), as well as other key individuals in charge of assembling input target catalogues.

A simplified description of the flow of data and information in the OpR context is as follows:

(i) input *FITS* catalogues are submitted to the WASP, hosted at the Cambridge Astronomical Survey Unit (CASU), Cambridge, where all targets are assigned a ‘CNAME’ once a given catalogue has successfully passed verification tests for certain required header keywords, amongst others. The CNAME for a target is based on its right ascension and declination, and is an immutable attribute for identifying that particular target in the WEAVE data-processing and archive systems;

(ii) CNAME-containing *FITS* catalogues are then used by the science teams to create a series of ‘protofields’, which, for each WEAVE MOS and mIFU observation, contains a selection of potential science targets and guide stars:

(a) for the MOS mode, protofields containing approximately 2000 potential science targets, as well as lists of guide stars, white dwarf stars (for calibration and the White Dwarfs survey, Section 4.3), and ‘sky’ positions if the user chooses to specify these in advance, form the input to CONFIGURE (see Section 2.2), the output of which are configured (or ‘CONFIGURE-output’) XML files;

(b) for the mIFU mode, protofields are similar to those created for the MOS mode, but contain only positions of the objects lying within the boundaries of (and typically centred on) the 20 mIFU bundles, which CONFIGURE translates into a set of fibre positions for the individual mIFU fibres of each mIFU bundle;

(c) for the LIFU mode, a protofield contains a single pointing that defines the centre of the field (along with a position angle set to optimize the guide-star position on the offset LIFU guider), which CONFIGURE translates into a set of fibre positions for the fixed LIFU fibre array;

(iii) XML files are submitted to the WASP, which performs a series of checks on the files received, ranging from a baseline structure check against template XMLs for the checking of constituent elements, to the verification of instrumental mode and observational

<footnote n="30">³⁰http://iraf.noao.edu/spectatlas/thar/thar.html</footnote>
<figure><img src="image_24.png" /><figcaption>**Figure 23.** Nominal WEAVE spectral resolution as a function of fibre number (x-axis) and wavelength (y-axis), computed from the spectrograph optical model. Left: low-resolution blue VPH grating. Right: low-resolution red VPH grating. Contours label regions of equal spectral resolution $R = \lambda/\Delta\lambda$. Note that these resolving powers correspond to MOS and mIFU modes, and are halved in the LIFU mode with its two-times larger fibres (see Table 2).</figcaption></figure>

## 5.6 Output images

When the spectra for all fibres have been added to the CCD images, the CCD bias, read-out noise, and Poisson noise are all added. The images are then saved with a complete FITS header, representative of the final WEAVE images. These images can then be sent to the WEAVE SPA pipelines for processing and distribution to the science teams via WEAVE's data archive system.

## 5.7 Calibration frames

In addition to science data frames, the simulator also generates calibration data frames in the form of bias, fibre flat-field, detector flat-field, and calibration arc-lamp frames. Fibre flat-fields and arcs include the same input losses at the telescope focal plane as the science data and the correct header information in order to allow the data-processing chains to function. For the flat-field lamp spectra, we assume a blackbody spectrum at 3500 K. For the arc lamp, we use the ThAr lamp spectral data from the National Optical Astronomy Observatory atlas,<fnref n="30" /> sampled at 0.002 nm pixel⁻¹ over the range 360–960 nm.

# 6 OPERATIONAL REHEARSALS

Using the WEAVE Simulator described in the previous section, a series of exercises were conducted to simulate the implementation of the Survey. These Operational Rehearsals (OpRs) were designed to simulate and test the flow of data in various guises through and between different nodes of the WEAVE data systems (see Sections 2.5 and 2.6), including the OCS, CPS, APS, and WAS. The OpRs have also seen significant involvement of Science Team members, mainly through the work of the SWG (see Section 3.1) and the QAG (see Section 3.3), as well as other key individuals in charge of assembling input target catalogues.

A simplified description of the flow of data and information in the OpR context is as follows:

(i) input FITS catalogues are submitted to the WASP, hosted at the Cambridge Astronomical Survey Unit (CASU), Cambridge, where all targets are assigned a 'CNAME' once a given catalogue has successfully passed verification tests for certain required header keywords, amongst others. The CNAME for a target is based on its right ascension and declination, and is an immutable attribute for identifying that particular target in the WEAVE data-processing and archive systems;

(ii) CNAME-containing FITS catalogues are then used by the science teams to create a series of 'protofields', which, for each WEAVE MOS and mIFU observation, contains a selection of potential science targets and guide stars:

(a) for the MOS mode, protofields containing approximately 2000 potential science targets, as well as lists of guide stars, white dwarf stars (for calibration and the White Dwarfs survey, Section 4.3), and 'sky' positions if the user chooses to specify these in advance, form the input to CONFIGURE (see Section 2.2), the output of which are configured (or 'CONFIGURE-output') XML files;

(b) for the mIFU mode, protofields are similar to those created for the MOS mode, but contain only positions of the objects lying within the boundaries of (and typically centred on) the 20 mIFU bundles, which CONFIGURE translates into a set of fibre positions for the individual mIFU fibres of each mIFU bundle;

(c) for the LIFU mode, a protofield contains a single pointing that defines the centre of the field (along with a position angle set to optimize the guide-star position on the offset LIFU guider), which CONFIGURE translates into a set of fibre positions for the fixed LIFU fibre array;

(iii) XML files are submitted to the WASP, which performs a series of checks on the files received, ranging from a baseline structure check against template XMLs for the checking of constituent elements, to the verification of instrumental mode and observational

<footnote n="30">³⁰http://iraf.noao.edu/spectatlas/thar/thar.html</footnote>
requirements against the CNAME-containing FITS catalogues from an earlier stage of the process;

(iv) WASP-verified XML files are collated and sent to the OCS, which then ingests the files as OBs into its OB database;

(v) prior to and during each (simulated) observing night, the SCHEDULER (WEAVE observation queue scheduler; see Section 2.5) creates a real-time queue of OBs to be executed, depending on current and predicted weather conditions one hour ahead of observing time;

(vi) scheduled fields are ‘observed’ using the WEAVE Simulator (see Section 5);

(vii) raw data are sent from the ‘telescope’ to CASU, where they undergo initial processing by the CPS;

(viii) CPS-output data are transferred to the APS, hosted at the IAC, Tenerife, for further, advanced-level processing;

(ix) outputs from the CPS and the APS are ingested by the WAS, hosted at Telescopio Nazionale Galileo, La Palma, ready for inspection and download by the QAG through the archive system.

The first Operational Rehearsal (OpR1) was an exercise centred on testing particular aspects of the data-flow model, ensuring that raw and reduced data could be moved correctly around the data-processing and data-archiving systems. File transfer and data-processing speeds were monitored, allowing weaknesses in the configuration of the systems to be identified and improved.

The second Operational Rehearsal (OpR2) comprised a series of data-flow simulations aimed at pushing data from the telescope all the way to the end user through two stages of data processing and final archiving. Several enactments of OpR2 were performed (the most prominent of these being OpR2.5; see e.g. Fig. 5) following the identification and subsequent resolution of a number of issues in the data-processing pipelines, as well as in the inputs provided by the Science Team. The SWG, QAG, and other core members of the individual science teams<fnref n="31" /> were heavily involved in OpR2 through the preparation and submission of FITS catalogues of potential science targets as well as template spectra assigned to these targets, and in using CONFIGURE to produce configured fields in the form of XML files.

The third Operational Rehearsal (OpR3) – the latest in the series – again tested all of the previously listed steps on algorithms and pipelines for the MOS mode (upgraded in the interim) and the LIFU mode, as well as a number of other details related to node interactions. As the last of the OpRs with full involvement of the science teams before an external survey-readiness review (successfully completed in 2020 January) and before WEAVE going on sky, OpR3 has been crucially important for ensuring that node-to-node interfaces work efficiently and seamlessly, and that the workings within each node have been set up to proceed optimally. At the time of writing, the mIFU mode is undergoing a similar, dedicated exercise.

There are naturally some differences between the OpR set-up and what is envisaged for real Survey operations. However, the framework of the data flow used for the OpR exercises was established with real Survey operations heavily in mind, mimicking as closely as possible how, for instance, submissions and verification of input FITS catalogues and CONFIGURE-output XML files would be handled by the WASP. In general, OBs were scheduled (and thus also ‘observed’) on specific ‘nights’ corresponding to a real historical date, whose archived weather conditions at the WHT could be used to set the observing conditions. The WEAVE Simulator would then take, as input, a CONFIGURE-output XML file, along with the observing conditions for the time of the observation and template

spectra corresponding to the targets in the field, and simulate their observation by WEAVE.

Given the importance of the simulated implementation of information and data flow in preparing for the running of the WEAVE Survey, the following subsections provide further details of the key stages of OpR3, highlighting their initial goals as well as some lessons learnt.

## 6.1 Operational Rehearsal 3a

Operational Rehearsal 3a (OpR3a) was a scheduling exercise covering a virtual period of three non-contiguous months over the course of just over one year. These three periods, named S1–S3, allowed us to test the ability of the SCHEDULER to handle the creation of real-time queues of OBs on an hourly basis given realistic weather conditions. Each OB specified all required elements for an observation – field centre, requirements for observing conditions, and instrumental setup, etc. – apart from the location of individual fibres within the field, and the SCHEDULER was used to create nightly queues of OBs to be observed according to archival weather data at the WHT for the corresponding dates being used for the OpR3a simulation.

OpR3a enabled the SCHEDULER to be tested for OB queue creation using a mixture of fields prepared for the LIFU and MOS modes. While science can be performed using the LIFU with seeing of worse than 1.5 arcsec, most science cases using the MOS mode require a seeing of 1.1 arcsec or better. We recall from Section 2 that the configuration of a MOS field requires approximately one hour, so the length of a typical OB is therefore set at one hour. However, a MOS plate cannot be configured during a LIFU observation, as described above, which means that transitions from a LIFU to a MOS observation typically incur significant overhead. This overhead is expected (as specified in the WEAVE Concept of Observations) to be overcome with the aid of mIFU observations, which take less than 15 min to configure. The unavailability of the mIFU mode in OpR3a clearly showed that its presence was highly desirable in order to use intermediate seeing conditions effectively, and to efficiently transition between the LIFU and MOS modes without compromising on science or losing valuable observing time.

For OpR3a, surveys were also provided the choice of submitting OBs to be observed in the LR mode or the HR mode with either the red+green or red+blue grating combination (see Table 3). Opportunities to request ‘chained’ OBs that specify two or more duplicate OBs (for deep exposures) or ‘linked’ OBs that specify two or more OBs that should be observed within a given timeframe were also provided. In each case, as-yet unobserved OBs belonging to a set that had been started were prioritized over OBs from sets where no OB had yet been observed. In OpR3a, chained and linked OBs were scheduled by manual intervention of the SCHEDULER output. These modes were subsequently implemented into the SCHEDULER and successfully tested in OpR3c (see Section 6.3).

## 6.2 Operational Rehearsal 3b

From each of the semesters modelled in OpR3a, we selected a single week of MOS and LIFU observations (180 OBs in total) for which the target fields were then run through CONFIGURE, ingested into the survey system through the WASP, and then passed to the WEAVE Simulator. Additional XML elements were added to each field to specify the actual observing conditions, and to specify the spectral template and magnitude to use for each target. The data generated in this way were then uploaded to the Observatory and used to simulate the full operation of the WEAVE data-flow system through the OCS, quick-look pipeline, CPS, APS, and WAS. The ‘observations’ and

<footnote n="31">³¹https://ingconfluence.ing.iac.es/confluence/display/WEAV/Core+Science+Teams</footnote>
requirements against the CNAME-containing FITS catalogues from
an earlier stage of the process;

(iv) WASP-verified XML files are collated and sent to the OCS,
which then ingests the files as OBs into its OB database;

(v) prior to and during each (simulated) observing night, the SCHEDULER (WEAVE observation queue scheduler; see Section 2.5) creates a real-time queue of OBs to be executed, depending on current and predicted weather conditions one hour ahead of observing time;

(vi) scheduled fields are ‘observed’ using the WEAVE Simulator (see Section 5);

(vii) raw data are sent from the ‘telescope’ to CASU, where they undergo initial processing by the CPS;

(viii) CPS-output data are transferred to the APS, hosted at the IAC, Tenerife, for further, advanced-level processing;

(ix) outputs from the CPS and the APS are ingested by the WAS, hosted at Telescopio Nazionale Galileo, La Palma, ready for inspection and download by the QAG through the archive system.

The first Operational Rehearsal (OpR1) was an exercise centred
on testing particular aspects of the data-flow model, ensuring
that raw and reduced data could be moved correctly around the
data-processing and data-archiving systems. File transfer and data-
processing speeds were monitored, allowing weaknesses in the
configuration of the systems to be identified and improved.

The second Operational Rehearsal (OpR2) comprised a series of data-flow simulations aimed at pushing data from the telescope all the way to the end user through two stages of data processing and final archiving. Several enactments of OpR2 were performed (the most prominent of these being OpR2.5; see e.g. Fig. 5) following the identification and subsequent resolution of a number of issues in the data-processing pipelines, as well as in the inputs provided by the Science Team. The SWG, QAG, and other core members of the individual science teams<fnref n="31" /> were heavily involved in OpR2 through the preparation and submission of FITS catalogues of potential science targets as well as template spectra assigned to these targets, and in using CONFIGURE to produce configured fields in the form of XML files.

The third Operational Rehearsal (OpR3) – the latest in the series – again tested all of the previously listed steps on algorithms and pipelines for the MOS mode (upgraded in the interim) and the LIFU mode, as well as a number of other details related to node interactions. As the last of the OpRs with full involvement of the science teams before an external survey-readiness review (successfully completed in 2020 January) and before WEAVE going on sky, OpR3 has been crucially important for ensuring that node-to-node interfaces work efficiently and seamlessly, and that the workings within each node have been set up to proceed optimally. At the time of writing, the mIFU mode is undergoing a similar, dedicated exercise.

There are naturally some differences between the OpR set-
up and what is envisaged for real Survey operations. However,
the framework of the data flow used for the OpR exercises was
established with real Survey operations heavily in mind, mimicking
as closely as possible how, for instance, submissions and verification
of input FITS catalogues and CONFIGURE-output XML files would
be handled by the WASP. In general, OBs were scheduled (and
thus also ‘observed’) on specific ‘nights’ corresponding to a real
historical date, whose archived weather conditions at the WHT could
be used to set the observing conditions. The WEAVE Simulator
would then take, as input, a CONFIGURE-output XML file, along with
the observing conditions for the time of the observation and template

spectra corresponding to the targets in the field, and simulate their
observation by WEAVE.

Given the importance of the simulated implementation of informa-
tion and data flow in preparing for the running of the WEAVE Survey,
the following subsections provide further details of the key stages of
OpR3, highlighting their initial goals as well as some lessons learnt.

6.1 Operational Rehearsal 3a

Operational Rehearsal 3a (OpR3a) was a scheduling exercise cover-
ing a virtual period of three non-contiguous months over the course
of just over one year. These three periods, named S1–S3, allowed us
to test the ability of the SCHEDULER to handle the creation of real-time
queues of OBs on an hourly basis given realistic weather conditions.
Each OB specified all required elements for an observation – field
centre, requirements for observing conditions, and instrumental set-
up, etc. – apart from the location of individual fibres within the field,
and the SCHEDULER was used to create nightly queues of OBs to
be observed according to archival weather data at the WHT for the
corresponding dates being used for the OpR3a simulation.

OpR3a enabled the SCHEDULER to be tested for OB queue creation using a mixture of fields prepared for the LIFU and MOS modes. While science can be performed using the LIFU with seeing of worse than 1.5 arcsec, most science cases using the MOS mode require a seeing of 1.1 arcsec or better. We recall from Section 2 that the configuration of a MOS field requires approximately one hour, so the length of a typical OB is therefore set at one hour. However, a MOS plate cannot be configured during a LIFU observation, as described above, which means that transitions from a LIFU to a MOS observation typically incur significant overhead. This overhead is expected (as specified in the WEAVE Concept of Observations) to be overcome with the aid of mIFU observations, which take less than 15 min to configure. The unavailability of the mIFU mode in OpR3a clearly showed that its presence was highly desirable in order to use intermediate seeing conditions effectively, and to efficiently transition between the LIFU and MOS modes without compromising on science or losing valuable observing time.

For OpR3a, surveys were also provided the choice of submitting
OBs to be observed in the LR mode or the HR mode with either
the red+green or red+blue grating combination (see Table 3).
Opportunities to request ‘chained’ OBs that specify two or more
duplicate OBs (for deep exposures) or ‘linked’ OBs that specify two
or more OBs that should be observed within a given timeframe were
also provided. In each case, as-yet unobserved OBs belonging to a
set that had been started were prioritized over OBs from sets where
no OB had yet been observed. In OpR3a, chained and linked OBs
were scheduled by manual intervention of the SCHEDULER output.
These modes were subsequently implemented into the SCHEDULER
and successfully tested in OpR3c (see Section 6.3).

6.2 Operational Rehearsal 3b

From each of the semesters modelled in OpR3a, we selected a single
week of MOS and LIFU observations (180 OBs in total) for which
the target fields were then run through CONFIGURE, ingested into the
survey system through the WASP, and then passed to the WEAVE
Simulator. Additional XML elements were added to each field to
specify the actual observing conditions, and to specify the spectral
template and magnitude to use for each target. The data generated in
this way were then uploaded to the Observatory and used to simulate
the full operation of the WEAVE data-flow system through the OCS,
quick-look pipeline, CPS, APS, and WAS. The ‘observations’ and

<footnote n="31">³¹https://ingconfluence.ing.iac.es/confluence/display/WEAV/Core+Science+Teams</footnote>