ESO Survey Management Plan Form

1

Phase 1

VANDELS: A deep VIMOS survey of the CANDELS UDS
and CDFS fields
PI: R. McLure, Edinburgh University, UK; L. Pentericci, INAF-Rome, Italy

1.1

Abstract

VANDELS is a uniquely deep VLT spectroscopic survey of high-redshift galaxies, carefully designed to exploit
the multi-wavelength imaging and near-IR grism spectroscopy available in the CANDELS UDS and CDFS
fields. Our aim is to move beyond redshift acquisition, obtaining spectra with high enough signal-to-noise
to derive metallicities and velocity offsets from absorption and emission lines, allowing a detailed investigation of the physics of galaxies in the early Universe. Using integration times set to obtain a constant S/N(20 < tint < 80 hours), we will target: a) 2.5 < z < 5.5 star-forming galaxies with HAB ≤ 24 (IAB ≤ 25), b)
HAB < 22.5 passive galaxies at 1.5 < z < 2.5; c) fainter (HAB ≤ 27) star-forming galaxies at 3.0 < z < 7.0 andd) X-ray/radio selected AGN. Our strategy will deliver ≥ 2500 high signal-to-noise spectra within an area of' 0.2 deg2 . Combining the proposed VIMOS spectroscopy with the best optical+nearIR+Spitzer imaging willproduce a unique legacy dataset, capable of unveiling the physics underpinning high-redshift galaxy evolution.

2

Survey Observing Strategy

VANDELS will target the UDS and CDFS with four overlapping VIMOS pointings per field, designed to provide
full coverage of the WFC3/IR imaging provided by CANDELS (see Fig. 1). We intend to design four VIMOS
masks per pointing (i.e. 32 masks in total), observing each mask for 20 hours of on-source integration. The
instrument set-up for all observations will be identical: MR grism+GG475 order sorting filter, 100 slit widths anda minimum slit length of 600 . Using this instrumental set-up, repeated simulations with VMMPS indicates that
we can typically allocate up to 180 slits per mask set (i.e. up to 45 slits per VIMOS quadrant). The pointings(Fig. 1) are placed to ensure that each VIMOS quadrant always intersects the CANDELS HST imaging which,due to the high surface density of faint z ≥ 3 galaxies, allows us to maximize the number of slits in the central
HST area. All slits will be oriented E-W on the sky in order to minimize slit losses during long integrations onfields at the declinations of the UDS and CDFS. To ensure that our slits can be placed with maximum accuracy
we will use R−band pre-imaging obtained in P94 to properly account for VIMOS focal plane distortions andallocate 1-2 bright reference stars to each VIMOS mask.
To accommodate the range of exposure times needed to meet our science goals we will pursue a nested slit allocation strategy, whereby objects requiring 80 hours of integration are retained on all four masks, those requiring
40 hours are included on two masks and those only requiring 20 hours integration appear on a single mask.
The following table illustrates our slit-allocation for a single VIMOS quadrant over a series of four masks. The
columns indicate the number of objects that would be observed for 80 (N80), 40 (N40) and 20 hours (N20):
Mask
1
2
3
4
no. of spectra

N80
20
20
20
20
20

N40
20
20
20
20
40

N20
5
5
5
5
20

Total

80

Using this nested strategy, each quadrant provides 20 objects which receive 80 hours of integration (retained on all
4 masks), 40 objects which receive 40 hours of integration(two sub-samples of 20) and 20 objects which receive 20
hours of integration (four sub-samples of 5).

The eight VIMOS pointings are designed to provide a total of 2560 spectra, comprised of 640 (N80), 1280 (N40)
and 640 (N20) targets. Uniquely, 75% of our targets will receive 40+ hours, with 25% receiving 80 hours.

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ESO Survey Management Plan Form

Phase 1Figure 1: Layout of the proposed VANDELS pointings (4 in UDS and 4 in CDFS). In each figure the VIMOS
quadrants of a given pointing are shown as a different colour, overlaid on a greyscale image showing the available
HST H−band imaging (centre) and wider-area, ground-based, H−band imaging. The total area covered by
the eight VIMOS pointings is ' 0.2 square degrees. The quality of the multi-wavelength data available over
the wider UDS and CDFS fields is now excellent, and more than sufficient to select H ≤ 24 targets over thefull VANDELS footprint. The pointings are placed to ensure that each VIMOS quadrant always intersects the
CANDELS HST imaging which, due to the high surface density of faint z ≥ 3 galaxies, allows us to maximize thenumber of slits in the central HST area. The spectroscopic slits will be placed E-W on the sky, as recommended
to minimize slit losses during long integrations on fields at these declinations (Sánchez-Janssen et al. 2014).
Demonstrating the impact of 40-80 hour integrations:
The VANDELS observing strategy is designed to provide consistently high signal-to-noise ratio (SNR) continuum
detections for the bright star-forming (HAB ≤ 24) and passive galaxy (HAB ≤ 22.5) sub-samples. For thoseobjects with IAB ≤ 24.5, the final 1D spectra should provide a SNR/pix in the range 15 − 20, based on total
exposure times of 20, 40 or 80 hours. For the faintest objects in these sub-samples (IAB ' 25), the final spectra
will have a SNR/pix of ' 10 based on 80 hours of integration. For the fainter (HAB ≤ 27) star-forming galaxies
at z ≥ 3, the VANDELS observing strategy is designed to provide a consistent Lyα emission-line detection limitof ' 2 × 10−18 erg s−1 cm−2 (5σ).
In order to justify such long integration times, it is clearly necessary to demonstrate that our observing strategy and data reduction techniques produce final data products with the expected signal-to-noise ratios. The
provisional schedule for VANDELS is designed to ensure that two of our eight VANDELS pointings (one in
UDS and one in CDFS) will have received a full 80 hours of on-source integration by January 2017 (see Fig. 2).
The final reductions of this first batch of 80-hour spectra are scheduled to be publicly released as part of DR2(September 2017, see Table 5), after they have been processed by our data reduction pipeline and passed ourdata quality assessment.

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ESO Survey Management Plan Form

Phase 1Figure 2: Diagram illustrating our proposed allocation of on-source integration time (in hours) to the eight
VANDELS pointings (4 in UDS and 4 in CDFS) over a nominal 4-year survey period. At the end of season
four, all eight pointings will have obtained 80 hours of on-source integration. Importantly, our adopted strategy
ensures that two of the eight pointings will have received their full 80-hour allocation by January 2017.

2.1

Scheduling requirements

Here we evaluate the scheduling requirements for both the pre-imaging and spectroscopic components of VANDELS over a nominal 4-year survey period.
Pre-imaging requirements:
The whole of the VANDELS survey programme will be obtained over a total of only eight VIMOS pointings (4in CDFS and 4 in UDS) which results in only a modest pre-imaging requirement. At the start of P94 we received
8 hours of R−band pre-imaging in service mode. These pre-imaging observations (45 minutes on-source perpointing) ensure an accurate match between the VIMOS and target catalogue astrometry systems. VANDELS
should not require further pre-imaging observations unless it proves necessary to re-mount VIMOS on UT3, in
which case it is likely that we will require additional pre-imaging.
Table 1: Pre-imaging scheduling and observing requirements
PeriodP94

Number of
pre-imaging pointings
8

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FilterR

Tot. Exp. Time1[hrs]
6

Tot. Exec. Time
[hrs]
8

Observing conditions(seeing/Sky Transparency/Moon)< 100 /CLEAR/FLI ≤ 0.5

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Phase 1

Table 2: MOS scheduling requirements. In column two we report the number of nights VANDELS observers
will be required to staff the telescope (including half nights in August/September and December/January). It
should be noted that this is not the number of full nights allocated to VANDELS. The 10 nights scheduled for
P94 include 5 half-nights at the end of December shared with the LEGA-C programme, and we assume thatthe two 12-night runs scheduled during December-January each year (P96, P98, P100 and P102) will also beshared with LEGA-C. The number of observing nights is calculated using EST overhead estimates and observing
statistics, which indicate that our requested conditions will be met ' 60% of the time.
PeriodN. nights

N. observing runs

P94
P95
P96
P97
P98
P99
P100
P101
P102

10
17
48
17
48
17
48
17
48

2
2
4
2
4
2
4
2
4

N. observers †per run
2
1&2
2
1&2
2
1&2
2
1&2
2

Average run length5
5 & 12
12
5 & 12
12
5 & 12
12
5 & 12
12†

we have assumed that 5-night runs will be staffed by a single observer and that 12-night runs will be staffedby two observers, each covering 6 nights.
Spectroscopy requirements:
To calculate our spectroscopy requirements we explicitly assume that we require dark/grey time (i.e. FLI ≤ 0.5
and moon angular separation > 75◦ ), photometric/clear sky conditions and ≤ 100 FWHM seeing. In addition
to accounting for the frequency of poor seeing and non-photometric/clear conditions, we also assume that wewill not observe either of our two fields when they are above an airmass of sec z = 1.4 and that visitor mode isimpractical unless we can observe for 4+ hours per night.
The final integration target for VANDELS is 640 hours of on-source exposure time (8 pointings x 80 hours).
Based on calculations provided by the ESO survey team (EST), we assume that from a typical 7.5 hour observing
block, 2.25 hours will be overheads (i.e. 30%). Consequently, including overheads, we will require a total of
914.2 hours to obtain 640 hours of on-source integration. A provisional schedule for the VANDELS observations
over periods P94-P102 is set-out in Tables 2 & 3. This schedule is based upon EST observing statistics whichsuggest that our required observing conditions will be available ' 60% of the time.
Schedule optimisation:
We note that during December/January it will be possible (and desirable) to share observing runs with the
LEGA-C programme targeting the COSMOS field. In the provisional schedule set-out in Tables 2 & 3 wehave assumed that the two 12-night runs allocated during December-January in P96, P98, P100 and P102 will
be shared with LEGA-C. In P94 we have already been allocated 5 shared nights with LEGA-C at the end of
December 2014.
Visitor mode observing runs:
With the exception of the pre-imaging observations, all of the observing for VANDELS will be carried out invisitor mode. Given that VANDELS can make use of both dark and grey time, it would be most efficient to havelong observing runs, with an average length of ∼ 12 nights during September-January (∼ 5 nights in August).
In general, we have assumed that 5-night runs will be staffed by a single observer and 12-night runs will require
two observers, each staffing the telescope for 6 nights.

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ESO Survey Management Plan Form
2.2

Phase 1

Observing requirements

The instrumental set-up for the main spectroscopic observations is very straightforward. The intention is toobserve MOS masks at eight different VIMOS pointings, four in the UDS and four in the CDFS . As a resultof our nested slit allocation procedure (see Section 2 for details), we intend to observe four masks at eachpointing. In total, over the nominal 4-year duration of the survey, we therefore intend to observe a total of 32
distinct masks (i.e. 128 distinct VIMOS quadrants). Our default instrument set-up for all observations will beidentical: MR grism+GG475 order sorting filter, 100 slit widths and a minimum slit length of 600 . Initially weintend to employ individual integration times of 1200s and a dither pattern based on 0.7500 offsets. However, it ispossible that we may decide to slightly adjust our observing parameters based on the results of the observations
scheduled in P94.
RA distribution and target priorities:
VANDELS will target two fields which are only separated by ' 1 hour in RA (UDS: 02:17:38, −05:11:55
and CDFS: 03:32:30, −27:48:28). Overall, both fields have equal priority and will each account for 50% of
the total observing time. During October and November, when both fields have good visibility, a typicalvisitor mode observing run will spend roughly equal amounts of time observing UDS and CDFS. However, inAugust/September and December/January, it is clear that observations will be focused on the UDS and CDFS
respectively.
As highlighted previously (see Fig. 2), our observing schedule will ensure that two of our eight pointings (onein UDS and one in CDFS) will receive their full allocation of 80 hours of on-source integration by the end of
the second full observing season.
Meridian transit close to zenith:
From Paranal, one of the two VANDELS target fields (CDFS) transits the local meridian very close to zenith andwill therefore be unobservable for ' 30 minutes each night due to the rapid change in rotator angle. However, in
this instance, having two fields very close in RA is a distinct advantage, and there will be no significant impact
on VANDELS observing efficiency. Throughout the September-December observing season it will always be
possible to ensure that we are observing the UDS field during the ' 30 minutes when CDFS is transiting the
local meridian.
During a typical visitor mode observing run, our default strategy will always be to begin observing on the UDS
field, before switching to the CDFS after it has transited. By default, we will then observe the CDFS until itreaches an airmass of sec z = 1.4 or the onset of twilight. Over the course of the survey period, this strategy
will naturally result in roughly equal amounts of observing time being invested in the UDS and CDFS.
Worst acceptable weather conditions:
As stated previously, in order to guarantee the usefulness of the VANDELS survey as a genuine legacy data set,
we require the spectroscopic observations to be obtained in dark/grey time (i.e. FLI ≤ 0.5 and moon angularseparation > 75◦ ), photometric/clear sky conditions and ≤ 100 FWHM seeing. The seeing limit of ≤ 100 FWHM
and photometric/clear sky conditions are to be regarded as hard limits which, if not met, will result in thetelescope being returned to service mode observations. We proposed to re-visit our choice of FLI and moon
angular separation constraints at the end of the first full VANDELS observing season.

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Phase 1

Table 3: MOS observing requirements. The total exposure time listed in column 6 is the total on-source exposure
time, whereas the total execution time listed in column 7 includes the recommended EST overhead estimates.
The allocation in P94 includes five shared nights with the LEGA-C programme in December 2014. During P96,
P98, P100 and P102 we have assumed an allocation of two 12-night runs during December-January which arealso shared with LEGA-C. During the shared runs we will require a maximum of 4 VIMOS mask sets.
Period
P94
P94
P95
P95
P96
P96
P97
P97
P98
P98
P99
P99
P100
P100
P101
P101
P102
P102
Total

RA
02
03
02
03
02
03
02
03
02
03
02
03
02
03
02
03
02
03

DEC
-05
-27
-05
-27
-05
-27
-05
-27
-05
-27
-05
-27
-05
-27
-05
-27
-05
-27

N. of distinct

Grism and filter

mask sets

setup

1
2
2
2
3
3
2
2
3
3
2
2
3
3
2
2
3
3

MR+GG475
MR+GG475
MR+GG475
MR+GG475
MR+GG475
MR+GG475
MR+GG475
MR+GG475
MR+GG475
MR+GG475
MR+GG475
MR+GG475
MR+GG475
MR+GG475
MR+GG475
MR+GG475
MR+GG475
MR+GG475

Tot. exp.
time [hrs]
13.2
13.2
17.4
17.4
59.3
59.3
17.4
17.4
59.3
59.3
17.4
17.4
59.3
59.3
17.4
17.4
59.3
59.3
640.0

Tot. exec.
time [hrs]
18.7
18.7
24.8
24.8
84.8
84.8
24.8
24.8
84.8
84.8
24.8
24.8
84.8
84.8
24.8
24.8
84.8
84.8
914.2

Priority
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1

Av. moonconstraints
dark/grey
dark/grey
dark/grey
dark/grey
dark/grey
dark/grey
dark/grey
dark/grey
dark/grey
dark/grey
dark/grey
dark/grey
dark/grey
dark/grey
dark/grey
dark/grey
dark/grey
dark/grey

Wind constraints:
VANDELS will be subject to the same wind constraints as all other VLT observations. In the situation where
the wind speed exceeds 18 ms−1 no observations will be possible and the telescope will close. When the windspeed exceeds 12 ms−1 it is necessary to observe ≥ 90◦ away from the wind direction. However, in mostsituations, it will still be possible to observed either the UDS (Dec=−5◦ ) or the CDFS (Dec=−27◦ ). On rareoccasions when this is not possible, the telescope will return to service mode operations and the time will not
be charged to the VANDELS survey.
Quick-look software tools:
It is worth noting that the IASF-Milano team have already developed quick-look reduction software tools forspectroscopic observations with the VIMOS. This software will be available to all VANDELS observers and willallow us to very quickly identify sub-standard data in real-time at the the telescope.

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ESO Survey Management Plan Form

3

Phase 1

Survey data calibration needs

Given the public legacy status of the survey, it is clearly essential that the final data products are as accurately
calibrated as possible. Consequently, we have several requirements regarding flat fielding, arc frames and the
choice of spectrophotometric standards.
Night time flats and arc calibration frames:
During visitor mode observing runs we will typically execute consecutive long (1.5+ hrs) OBs on either UDS
or CDFS masks. We request that sandwiched between the two consecutive UDS or CDFS OBs we are able toobtain night-time flat-field and arc frame calibration data using standard templates.
Choice of spectrophotometric standard stars:
The MR mode spectroscopy observations for VANDELS will provide spectra with a wavelength coverage of
480-1000nm. We are therefore happy to rely on the standard calibration plan, provided that the standard stars
are carefully chosen to ensure good flux calibration extending to 1µm. In order to ensure that we are able
perform accurate flux calibration extending to 1µm, without being affected by second-order contamination, we
have identified suitable red spectrophotometric standard stars (e.g. LTT 3864 & LTT 9239).

4

Data reduction process

VANDELS data reduction will be performed with a fully-automated pipeline, starting from the raw data andflowing down to the wavelength- and flux-calibrated spectra. The pipeline is an updated version of the algorithms
and dataflow from the original VIPGI system, fully described in Scodeggio et al. (2005). The original VIPGI
system was used to reduce all the spectra from the VVDS (Le Fèvre et al. 2005; Garilli et al. 2008), zCosmos(Lilly et al. 2007) and VUDS surveys (Le Fèvre et al. 2014), while the updated system, called Easylife, is being
used to reduce all the spectra from the ongoing VIPERS survey (Garilli 2014). In Fig. 3 we provide a block
diagram which illustrates the main features of the data reduction pipeline.

A key feature of the data reduction process is the instrument model. Since the four VIMOS quadrants correspondto four physically distinct cameras within the instrument, each quadrant is characterised by its own instrument
model and all data reduction procedures are carried out on the data from each quadrant independently. The
instrument model consists of three parts:
1. The optical distortion model: provides a mapping between positions on the VIMOS focal plane andpixel coordinates on the CCD frame.
2. The curvature model: provides a description of the geometrical shape of each spectrum on the CCD,
to allow for its tracing and extraction.
3. The inverse dispersion solution: provides the mapping between wavelength and pixel coordinatesalong the geometrical shape traced by the curvature model.
The optical distortion and curvature models are based on accurate determinations of the location of the slit
spectra on the CCD frames derived from lamp flats. Using a global instrument model an initial estimate ismade of each slit position. Starting from this position, a search is made for the edges of the illuminated area
created by the spectrum on the CCD. The shape of these edges is then fitted with a polynomial to provide an
updated local determination of the curvature model and a very precise determination of the spectrum positionon the CCD.

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ESO Survey Management Plan Form

Phase 1Figure 3: Flow diagram illustrating the key features of the data reduction pipeline.

The inverse dispersion solution is obtained from arc lamp exposures, and employs low-order polynomial fits
together with an iterative σ−clipping procedure to compute two-dimensional inverse dispersion solutions foreach individual slit. The accuracy of the wavelength calibration is typically ±0.1 pixels, which is equivalent toa median r.m.s residual of 0.25Å for the MR grism employed in VANDELS (Garilli et al. 2014).
The first step in the reduction of VIMOS science data is the canonical preliminary reduction of the CCD frames,
which includes prescan level and average bias frame subtraction, trimming of the frame to eliminate prescan andoverscan areas, interpolation to remove bad CCD pixels and flat fielding. After the preliminary reduction step,
subsequent data reduction steps are carried out on all MOS slits individually. For each individual spectroscopic
exposure the wavelength calibration derived from the arc exposures is checked against the positions of brightsky lines and the local inverse dispersion solution modified to account for any discrepancies.

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Phase 1

The next steps in the data reduction procedure are the object detection and sky subtraction for each MOS
slit spectrum within each individual MOS science exposure. Initially, the slit spectrum is collapsed along the
wavelength axis, following the geometrical shape defined by the local curvature model, to produce a slit crossdispersion profile. A robust determination of the average signal level and r.m.s in this profile is then obtainedusing an iterative σ−clipping procedure, and objects are detected as groups of contiguous pixels above a given
detection threshold. Before wavelength calibration is applied, a median estimate of the sky spectrum, derived
using all the pixels that are devoid of object signal, is subtracted from each slit. The sky spectrum is estimatedseparately for each individual science exposure due to the significant variation in OH line strength over thetimescale of a typical spectroscopic exposure.
The sky-subtracted slit spectra are then two-dimensionally extracted using the tracing provided by the slit
curvature model, and resampled to a common linear wavelength scale. Only after this point are the single
exposures of a pointing combined together. The N exposures that are part of a pointing are combined together
twice. First, the N two-dimensionally extracted spectra for each slit are median combined (with object pixels
masked), without taking into account the jitter offsets, to produce a two-dimensional sky-subtraction residual
map. The residual map is then subtracted from all the N two-dimensional single-exposure slit spectra, improving
the sky-subtraction and removing any residual fringing. At this point a second combination is carried out, thistime taking into account the jitter offsets among the N individual two-dimensional slit spectra (as determined
during the previous object detection procedure). The single-exposure, residual-map subtracted, spectra are
off-set to compensate for the effect of the jitter, and a final average two-dimensional spectrum for each slit isobtained.
The object detection process is repeated on the combined two-dimensional spectra to produce the final catalogueof detected spectra, and a one-dimensional spectrum is extracted for each detected object, using the Horne
optimal extraction procedure (Horne 1986). Finally, spectra are flux calibrated using a simple polynomial fit to
the instrument response curve derived from observations of spectrophotometric standard stars, and corrected
for telluric absorption features. The last correction is based on a template absorption spectrum derived for eachcombined jitter sequence from the data themselves.
The final flux calibration will be performed by integrating the flux-calibrated spectra under the relevant photometric filter curves and comparing to the high-quality photometry available for each VANDELS target. In thisprocess we will exploit 4-6 photometric bands covering the 480-1000nm wavelength range of the spectra, using
a low-order polynomial fit to normalize the spectra to the photometry as a function of wavelength.

5Manpower and hardware capabilities devoted to data reduction
and quality assessment

In this section we provide details of our strategy for staffing the visitor mode observing runs required by
the VANDELS survey, a detailed breakdown of the team responsibilities (including allocated FTE) and the
hardware/software available for OB preparation, data reduction and data archive ingestion.
Observers:
According to the provisional observing schedule discussed in Section 2.1 we anticipate that, over a ∼4-year
period, the VANDELS survey will require ∼ 26 visitor mode observing runs. We intend to execute the vast
majority of the VANDELS observing using a small team of dedicated observers. The observing team of willcommit to undertaking 3-4 VANDELS observing runs over the ∼4-year duration of the survey. The members of
the observing team will be drawn from Co-Is actively working with the VANDELS data, who have a personal
investment in ensuring that the data quality is as high as possible. Those individuals who have already indicatedthere availability to join the observing team are highlighted in the full VANDELS Co-I list on page 16.

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Phase 1Team responsibilities:
The overall responsibility for both the successful execution of the survey and the distribution of the final data
products to the community will be shared by McLure and Pentericci as VANDELS Co-PIs. The Co-PIs will besupported by the members of the VANDELS management group (Dunlop, Fontana, Nandra, Elbaz & Cimatti)
who have been chosen on the basis of their multi-wavelength expertise and their previous experience in managing
large ESO projects (e.g. GOODS, Ultra-VISTA, K20, GMASS & UDSz).
To ensure the successful planning and execution of the VANDELS survey, we have constructed small teams tofocus on specific tasks. Below we list the tasks allocated to each team, together with those individuals who will
coordinate each team’s efforts. Additional team members drawn from the full Co-I list (see page 16) are notexplicitly listed.
1. Target selection teamMembers: S. Finkelstein • A. Grazian • R. Bowler • M. Cirasuolo • M. Bolzonella
The members of this team will be responsible for producing robust target catalogues from the available multiwavelength imaging in the UDS and CDFS fields to be used in VIMOS slit allocation. Together they willproduce consolidated catalogues of potential targets based on independent measurements of the photometricredshift probability functions.
2. VIMOS mask production teamMembers: A. Iovino • M. Nonino • O. Cucciati
The members of this team will be responsible for the necessary VANDELS pre-imaging and using VMMPS to
optimally allocate slits based on the information supplied by the target selection team.
3. Survey management teamMembers: E. Marmol-Queralto • A. Bongiorno • E. Curtis-Lake • M. Castellano• J. Mendez-Abreu
E. Marmol-Queralto and A. Bongiorno will take joint responsibility for the day-to-day survey management.
They will be assisted in the organisation and supervision of the VANDELS visitor observing programme by theother members of the team.
4. Data Reduction teamMembers: B. Garilli • M. Scodeggio • P. Franzetti
The members of this team will be responsible for the full data-reduction process, taking the raw data andproducing fully wavelength-calibrated and flux-calibrated 1D and 2D spectra using the VIPGI and Easylife
software developed in IASF-Milano. P. Franzetti will have overall responsibility for ensuring that the data
products delivered to ESO are phase 3 compliant. In addition to the staff listed here, IASF-Milano will employ
a dedicated post-doctoral researcher (in-post by September 2015) to work on the VANDELS data reduction
pipeline.
5. Data quality and redshift measurement teamMembers: E. Vanzella • F. Cullen • I. Balestra • L. Guaita • P. Popesso • K. Caputi • W. Hartley
The members of this team will be responsible for monitoring the quality of the spectra as they are obtained. Subsequently, this team will be responsible for redshift determination using a combination of automated algorithms
and detailed visual inspection.
6. Enhanced data products
Members: V. Sommariva • G. Cresci • A. Mortlock • N. Bourne • R. Amorin • S. Charlot• M. Mignoli • M. Talia • A. Galametz
The members of this team will be responsible for the production and dissemination of value-added data products,
in addition to the basic 1D+2D spectra and associated redshifts. These data products will include line flux andEW measurements, together with basic stellar-population parameters derived from SED fitting.

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Phase 1

Table 4: Summary of the team responsibilities, including the allocated FTE.
Name
R. McLure
L. Pentericci
J. Dunlop
A. Fontana
K. Nandra
D. Elbaz
A. Cimatti
S. Finkelstein
A. Grazian
R. Bowler
M. Cirasuolo
M. Bolzonella
A. Iovino
M. Nonino
O. Cucciati
E. Marmol-Queralto
A. Bongiorno
E. Curtis-Lake
M. Castellano
J. Mendez-Abreu
New Post-doc
B. Garilli
M. Scodeggio
P. Franzetti
F. Cullen
L. Guaita
E. VanzellaI. Balestra
P. Popesso
K. Caputi
W. Hartley
R. Amorin
A. Mortlock
V. Sommariva
G. Cresci
N. Bourne
S. Charlot
M. Mignoli
M. Talia
A. Galametz†

Function
Co-PI
Co-PI
Management GroupManagement GroupManagement GroupManagement GroupManagement Group
Target selection
Target selection
Target selection
Target selection
Target selection
Mask production
Mask production
Mask production
Survey Manager
Survey Manager
Observation supervision
Observation supervision
Observation supervision
Data reduction pipeline
Data reduction pipeline
Data reduction pipeline
Survey web site/Phase-3 compliance
Data quality + redshift determination
Data quality + redshift determination
Data quality + redshift determination
Data quality + redshift determination
Data quality + redshift determination
Data quality + redshift determination
Data quality + redshift determination
Enhanced data products
Enhanced data products
Enhanced data products
Enhanced data products
Enhanced data products
Enhanced data products
Enhanced data products
Enhanced data products
Enhanced data products

Affiliation
University of Edinburgh
INAF, Rome
University of Edinburgh
INAF, Rome
MPE
CEA
University of Bologna
University of Texas
INAF, Rome
University of Edinburgh
University of Edinburgh
INAF, Bologna
INAF, Brera
INAF, Trieste
University of Bologna
University of Edinburgh
INAF, Rome
University of Edinburgh
INAF, Rome
University of St. Andrews
IASF-Milano
IASF-Milano
IASF-Milano
IASF-Milano
University of Edinburgh
INAF, Rome
INAF, Bologna
INAF, Trieste
MPE
Groningen
ETH
INAF, Rome
University of Edinburgh
University of Bologna
INAF, Arcetri
University of Edinburgh
IAP
INAF, Bologna
University of Bologna
MPE

Country
UK
Italy
UK
Italy
Germany
France
Italy
USA
Italy
UK
UK
Italy
Italy
Italy
Italy
UK
Italy
UK
Italy
UK
Italy
Italy
Italy
Italy
UK
Italy
Italy
Italy
Germany
Netherlands
Switzerland
Italy
UK
Italy
Italy
UK
France
Italy
Italy
Germany

FTE
0.5
0.5
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.2†
0.2†
0.2†
0.3
0.3
0.2
0.2
0.1
1.0
0.2†
0.2†
0.2†
0.2
0.2
0.1
0.1
0.1
0.1
0.1
0.2
0.2
0.1
0.1
0.1
0.1
0.1
0.1
0.1

0.2 FTE in the first year of the survey, 0.1 FTE thereafter.

References:
Garilli et al. 2008, A&A, 486, 683• Garilli et al. 2012, PASP, 124, 1232• Garilli et al. 2014, A&A, 563, 92•
Hammersley et al., 2013, Msngr, 151, 2• Horne, 1986, PASP, 98, 609• Le Fèvre et al. 2005, A&A, 439, 845 •Le Fèvre et al. 2014, arXiv:1403.3938• Lilly et al. 2007, ApJS, 172, 70• Sánchez-Janssen et al., 2014, A&A,
566, 2• Scodeggio et al. 2005, PASP, 117, 1284

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ESO Survey Management Plan Form

Phase 1

Hardware:Due to the nature of the VANDELS survey (i.e. long integrations on only eight VIMOS positions) the data
volume is not large by modern survey standards. Specifically, assuming individual integrations of 1200s, the640 hours of on-source integration for VANDELS will require the reduction of 4x1920=7680 VIMOS quadrants.
Over a 4-year survey this corresponds to a relatively modest data flow rate and all of the data reduction will be
carried out on a dedicated linux machine (> 1Tb disk space) at IASF-Milano which will also host the VANDELS
website (vandels.inaf.it).
Similarly, because we are only required to prepare a total of 32 VIMOS masks (i.e. 8 pointings, 4 masks per
pointing) over a 4-year period, the hardware requirement for mask preparation is also modest. It is intended
that mask preparation will be carried out on standard linux desktop machines by the members of the mask
production team (see Table 4).
Software:
The members of the mask production and observation supervision teams are all experienced with the P2PP3
and VMMPS software packages. The data reduction team at IASF-Milano wrote the original data reduction
software for VIMOS (VIPGI) and its successor Easylife. These software packages are currently being used at
IASF-Milano to reduce the VIMOS data from the on-going VIPERS survey. Through their experience with
VIPERS (and previously with VVDS, zCOSMOS and VUDS), the data reduction team are familiar with phase-3
compliance regulations and the requirements for successful ingestion of data to the ESO data archive. Finally,
the IASF-Milano team have developed quick-look reduction software which will be available to all VANDELS
observers and will be indispensable for identifying data problems in real time at the telescope.

6

Data quality assessment process

We will implement a data quality control scheme following the successful system currently being employed for
the VIPERS survey (Garilli et al. 2014). This system carefully monitors the observing conditions for eachscientific exposure. The seeing is directly measured from the raw spectroscopic data using bright reference
objects. In addition, the median airmass of each exposure is computed on the basis of the observation hourangle and the airmass at the start and end of the observation. Moreover, the mean sky level is also measured
and stored on an exposure basis. Finally, the accuracy of the individual slit wavelength calibrations computed
via the inverse dispersion solutions is also monitored. All these data quality metrics are recorded in the FITS
header of each individual spectrum.
As all of the final VANDELS spectra will be a combination of many individual exposures, the mean value ofthese parameters will be computed during spectra combination (see Section 4). An error spectrum, which takes
into account poisson statistics as well as sky subtraction errors is computed following the prescription given in
Garilli et al. (2014), and will be delivered together with the final data products.
Throughout the survey, all of these parameters will be stored in a dedicated reduction database on an exposure
by exposure basis. In the case of slit dependent values, such as wavelength calibration r.m.s. and sky level, a
median value per quadrant per exposure will be computed and recorded. Diagnostic plots showing the temporal
behaviour of these parameters will be made after each observing run. Observations showing some statisticallysignificant deviation from the mean will be flagged and their further use will be subject of closer scrutiny,
manually carried out by the reduction team.

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ESO Survey Management Plan Form

7

Phase 1

External Data products and Phase 3 compliance:

In the following description we have split the VANDELS data products into basic and enhanced categories. The
basic data products are those which could be regarded as the minimum required for a spectroscopic survey ofthis nature. The basic data products for a given object will be made available at the scheduled data release (seeTable 5) following the completion of that object’s allocated on-source integration time (i.e. 20, 40 or 80 hours).
The enhanced data products are those which the team is committed to delivering as an additional service tothe community, and are designed to maximize the scientific productivity and legacy value of VANDELS. The
enhanced data products will form part of the final VANDELS data release (see Table 5). For the final VANDELS
data release, we are prepared to fully re-process the spectroscopic data if this is merited by improvements tothe data reduction process over the course of the VANDELS survey.
We note that, throughout the survey, each VANDELS target will be allocated a unique target identifier andprecise coordinates. All data products associated with a given object (including all catalogue entries) will betagged with the same unique target identifier and coordinates. In addition, we are also prepared to introduce
an additional KEYWORD to identify whether each target has been allocated 20, 40 or 80 hours of on-source
integration. Finally, all data catalogues (including redshifts, emission/absorption line features and derived
physical properties from SED fitting) will be formatted according to the Phase 3 data standard for tabulardata.
In order to be compliant with ESO public survey policy, all data products listed here will be delivered for
publication from the ESO archive via Phase 3. In addition, it is our intention to also make the data products
available to the community via our dedicated VANDELS website (vandels.inaf.it).

Basic Data Products• Final extracted one-dimensional (1D) spectra
The final wavelength-calibrated and flux-calibrated 1D spectra for all objects targeted by VANDELS. In addition
to flux calibration using spectrophotometric standards, the final flux calibration will be normalised to themulti-wavelength photometry available for each target. According to the requirements of the ESO Science
Data Products standard (SDP) document, the 1D spectrum of each object will be delivered in binary tableformat, with a monotonically increasing wavelength axis and a flux scale in physical units (e.g. erg/s/cm2 /Å).
In addition to the object spectrum, the binary table for each object will also contain the associated noise andsky spectrum.
• Final stacked two-dimensional (2D) spectra
The final wavelength-calibrated 2D spectrum for each target will be made available. The 2D spectra will beessential for confirming the reality of faint emission features and identifying potential emission-line velocity
gradients. The final 2D spectra will also be delivered in a format compliant with the ESO SDP.
• Spectroscopic redshift catalogue
A final catalogue will be made available which contains the essential information for each VANDELS target: ID,
RA, Dec, I-magnitude, H-magnitude, spectroscopic redshift and redshift quality flag. The redshift quality flag
will be defined on the same system previously employed by the VVDS and zCOSMOS surveys. This catalogue
will be delivered in compliance with the ESO SDP regulations for science catalogue data.

Intermediate Data Products
In addition to the data products associated with completed spectra, at each data release we also intend to releaseintermediate level data products. The intermediate level data products will consist of fully reduced 1D and 2D
spectra in sub-sets of 20 hours of on-source integration. For example, for a target which has been allocated a
total on-source integration time of 80 hours, at the appropriate data release milestone we will release reduced
spectra consisting of 20, 40 and 80 hours of integration (see Table 6). All intermediate data products will also
be delivered in a format compliant with ESO SDP regulations.
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ESO Survey Management Plan Form

Phase 1

Enhanced Data Products• VANDELS selection function
We intend to make available all of the relevant information necessary to compute the VANDELS selection
function. This information will allow the community to accurately calculate the completeness of the survey for
their own scientific purposes.
• Final combined spectroscopic redshift+photometric catalogue
In addition to the final spectroscopic redshift information, this catalogue will feature aperture-matched optical+nearIR photometry for each target. Based on this information the community should be able to directly
proceed to SED fitting using their preferred choice of software and templates.
• Basic stellar population parameters
Based on the final redshift+photometric catalogue we will release our own catalogue of basic stellar population
parameters (e.g. stellar mass, age & reddening) derived by fitting standard templates (e.g. Bruzual & Charlot
2003 + Chabrier IMF).
• Final catalogue of spectroscopic measurements
In addition to the final spectroscopic redshift determinations, a catalogue will be made available to the community which contains line flux and equivalent width measurements (together with error estimates and data
quality flags) for robustly detected emission/absorption features in each VANDELS spectrum.

8

Timeline delivery of data products to the ESO archive:

In Table 5 we present the timeline for the VANDELS survey, including the provisional schedule for publicdata releases via the ESO archive. In the timeline we assume that the first VANDELS data release via the
ESO archive will be in September 2016, with further data releases occurring at yearly intervals, until data
release four (DR4) in September 2019. In addition, we have scheduled a final data release (DR5) for June
2020, which will feature all of the enhanced data products and potentially a full re-reduction of the VANDELS
spectroscopic dataset. As described in Section 2, our observing strategy means that each VANDELS target
will be allocated 20, 40 or 80 hours of on-source integration. At each data release, we intend to provide thefinal reduced spectroscopic data for all objects whose spectroscopic observations were completed at the end of
the previous observing season (DR1 will also include data from two P94 observing runs scheduled for Nov/Dec
2014). For a given target, the spectrum is considered to have been completed when that target has received
its full allocation of on-source integration time (i.e. 20, 40 or 80 hours). In addition, at each data release wealso intend to provide reduced spectra for those 40-hour targets which have received 50% of their allocationand those 80-hour targets which have received 25% or 50% of their allocation. It is clear from Table 5 thatthe timescale between obtaining the data and releasing it via the ESO archive is short (i.e. 8 months). As aconsequence, it has been agreed with the EST that if it proves impossible to satisfy the data release timescale,
we are obliged to provide a report on the status of the spectroscopic data, including signal-to-noise estimates,
which will be made available to the public.
According to the observing schedule outlined in Section 2, and illustrated in Fig. 2, we can calculate the numberof completed and partially completed spectra we expect to release at each data release. This information isprovided in Table 6.

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ESO Survey Management Plan Form

Phase 1

Month

Year

Milestone

November

2014

Start of VANDELS

September

2015

VANDELS observing season one (START)January

2016

VANDELS observing season one (END)

September

2016

First VANDELS data release (DR1)

September

2016

VANDELS observing season two (START)January

2017

VANDELS observing season two (END)

September

2017

Second VANDELS data release (DR2)September

2017

VANDELS observing season three (START)January

2018

VANDELS observing season three (END)

September

2018

Third VANDELS data release (DR3)September

2018

VANDELS observing season four (START)January

2019

VANDELS observing season four (END)

September

2019

Fourth VANDELS data release (DR4)

June

2020

Final VANDELS data release (DR5)

Table 5: Provisional timeline highlighting the major milestones over the course of the VANDELS survey.

Data release
DR1
DR2
DR3
DR4

Date
Sept 2016
Sept 2017
Sept 2018
Sept 2019

No. of completed spectra
20-hrs 40-hrs
80-hrs
160
160
0
320
480
160
480
960
320
640
1280
640

No. of partially complete spectra
40-hrs(50%) 80-hrs(25%) 80-hrs(50%)
320
320
160
320
320
160
0
0
320
0
0
0

Total
1120
1760
2080
2560

Table 6: A summary of the numbers of completed and partially completed spectra we expect to release as afunction of data release schedule and integration time. Columns 6-8 list the number of 40-hr and 80-hr objects
for which, at the data release of interest, we intend to release a reduction based on 25% or 50% of the total
integration time.

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ESO Survey Management Plan Form

Phase 1

Full list of VANDELS Co-Is:
Co-PIs: R. McLure, University of Edinburgh, UK, L. Pentericci, INAF-Rome, Italy
Management board:
J. Dunlop, University of Edinburgh, UK
A. Fontana, INAF-Rome, Italy
K. Nandra, MPE, Germany
D. Elbaz, CEA, France
A. Cimatti, University of Bologna, Italy
O. Almaini, University of Nottingham, UK
R. Amorin, INAF-Rome, Italy
S. de Barros, UC Riverside, USA
I. Balestra, INAF-Trieste, Italy
E. Bell, Michigan, USA†M. Bolzonella, INAF-Bologna, Italy†A. Bongiorno, INAF-Rome, Italy
N. Bourne, University of Edinburgh, UK†R. Bowler, University of Edinburgh, UK
V. Bruce, University of Edinburgh, UK
M. Brusa, University of Bologna, Italy
F. Buitrago, University of Edinburgh, UK
K. Caputi, Groningen, Netherlands
P. Cassata, LAM, France†M. Castellano, INAF-Rome, Italy
S. Charlot, IAP, France
M. Cirasuolo, University of Edinburgh, UK
G. Cresci, INAF-Arcetri, Italy
S. Cristiani, INAF-Trieste, Italy†O. Cucciati, University of Bologna, Italy†F. Cullen, University of Edinburgh, UK†E. Curtis-Lake, University of Edinburgh, UK
M. Dickinson, NOAO, USA
S. Faber, University of California, USA
G. Fazio, Harvard, USA
H. Ferguson, STScI, USA
S. Finkelstein, Texas, USA
F. Fiore, INAF-Rome, Italy
F. Fontanot, INAF-Trieste, Italy
P. Franzetti, INAF-Milan, Italy
J. Fynbo, DARK, Denmark†A. Galametz, MPE, Germany
B. Garilli, INAF-Milan, Italy
A. Georgakakis, MPE, Germany
M. Giavalisco, UMASS, USA†A. Grazian, INAF-Rome, Italy†L. Guaita, INAF-Rome, Italy
W. Hartley, ETH, Switzerland
A. Iovino, INAF-Brera, Italy
M. Jarvis, University of Oxford, UK
S. Juneau, CEA, France
W. Karman, Groningen, Netherlands
S. Kim, PUC, Chile
A. Koekemoer, STScI, USA
O. Le Fèvre, LAM, France
J. Lotz, STScI, USA
F. Mannuci, INAF-Arcetri, Italy†E. Marmol-Queralto, University of Edinburgh, UK
D. McLeod, University of Edinburgh, UK
J. Medez-Abreu, University of St Andrews, UK
M. Mignoli, INAF-Bologna, Italy
M. Moresco, University of Bologna, Italy
A. Mortlock, University of Edinburgh, UK
M. Nonino, INAF-Trieste, Italy
M. Pannella, CEA, France
C. Papovich, Texas, USA
P. Popesso, MPE, Germany
L. Pozzetti, INAF-Bologna, Italy
D. Rosario, MPE, Germany
P. Rosati, University of Ferrara, Italy
M. Salvato, MPE, Germany
C. Schreiber, CEA, France
M. Scodeggio, INAF-Milan, Italy†V. Sommariva, University of Bologna, Italy
D. Stark, Arizona, USA†M. Talia, University of Bologna, Italy
L. Tasca, LAM, France
T. Treu, UCSB, USA
E. Vanzella, INAF-Bologna, Italy
V. Wild, University of St Andrews, UK
C. Williams, UMASS, USA
G. Zamorani, INAF-Bologna, Italy† Provisional members of the VANDELS core observing team

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