# CHIME/FRB Outriggers: Design Overview

Mandana Amiri, Bridget C Andersen, Shion Andrew, Kevin Bandura, Mohit Bhardwaj, Kalyani Bhopi, Vadym Bidula, P.J Boyle, Charanjot Brar, Mark Carlson, et al.

► To cite this version:

Mandana Amiri, Bridget C Andersen, Shion Andrew, Kevin Bandura, Mohit Bhardwaj, et al.  
CHIME/FRB Outriggers: Design Overview. The Astrophysical Journal, 2025, 993 (1), pp.55.  
10.3847/1538-4357/adfdcc.  
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CHIME/FRB Outriggers: Design Overview

The CHIME/FRB Collaboration, Mandana Amiri¹, Bridget C. Andersen²,³ ID, Shion Andrew⁴,⁵ ID, Kevin Bandura⁶,⁷ ID,
Mohit Bhardwaj⁸ ID, Kalyani Bhopi⁶,⁷ ID, Vadym Bidula²,³ ID, P. J. Boyle² ID, Charanjot Brar⁹ ID, Mark Carlson¹ ID,
Tomas Cassanelli¹⁰ ID, Alyssa Cassidy¹ ID, Shami Chatterjee¹¹ ID, Jean-François Cliche²,³ ID, Alice P. Curtin²,³ ID,
Rachel Darlinger²,³ ID, David R. DeBoer¹²,¹³ ID, Matt Dobbs²,³ ID, Fengqiu Adam Dong¹⁴ ID, Gwendolyn Eadie¹⁵,¹⁶,¹⁷ ID,
Emmanuel Fonseca⁷,¹⁸ ID, B. M. Gaensler¹⁵,¹⁹,²⁰ ID, Nina Gusinskaia¹⁵,²⁰,²¹ ID, Mark Halpern¹ ID, Ian Hendricksen²,³ ID,
Jason Hessels²,³,21,22 ID, Ronniy C. Joseph²,³ ID, Jane Kaczmarek²³,²⁴,²⁵ ID, Victoria M. Kaspi²,³ ID, Kholoud Khairy⁶,⁷ ID,
T. L. Landecker²⁵ ID, Adam E. Lanman⁴,⁵ ID, Albert Wai Kit Lau²⁰ ID, Mattias Lazda¹⁵,²⁰ ID, Calvin Leung²⁶,²⁷ ID,
Robert A. Main²,³ ID, Kiyoshi W. Masui⁴,⁵ ID, Ryan Mckinven²,³ ID, Juan Mena-Parra¹⁵,²⁰ ID, Bradley W. Meyers²⁸,²⁹ ID,
Daniele Michilli³⁰ ID, Nikola Milutinovic¹ ID, Kenzie Nimmo⁴ ID, Gavin Noble¹⁵,²⁰ ID, Ayush Pandhi¹⁵,²⁰ ID,
Aaron B. Pearlman²,³,31,32,33 ID, Jeffrey B. Peterson⁸ ID, Emily Petroff²,³,34 ID, Ziggy Pleunis²¹,²² ID, Alexander W. Pollak³⁵ ID,
Masoud Rafiei-Ravandi² ID, Andre Renard²⁰ ID, Mawson W. Sammons²,³ ID, Ketan R. Sand²,³ ID, Pranav Sanghavi³⁶ ID,
Paul Scholz³⁷,²⁰ ID, Vishwangi Shah²,³ ID, Kaitlyn Shin⁴,⁵ ID, Seth R. Siegel²,³,34 ID, Andrew Siemion³⁵ ID,
Jonathan L. Sievers²,³ ID, Kendrick Smith³⁴ ID, David Spear¹ ID, Ingrid Stairs¹ ID, Keith Vanderlinde¹⁵,²⁰ ID, Haochen Wang⁴,⁵ ID,
Jacob P. Willis⁴,⁵ ID, and Tarik J. Zegmott²,³ ID

¹Department of Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, BC V6T 1Z1, Canada

²Department of Physics, McGill University, 3600 rue University, Montréal, QC H3A 2T8, Canada

³Trottier Space Institute, McGill University, 3550 rue University, Montréal, QC H3A 2A7, Canada

⁴MIT Kavli Institute for Astrophysics and Space Research, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA; kmasui@mit.edu

⁵Department of Physics, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA

⁶Lane Department of Computer Science and Electrical Engineering, 1220 Evansdale Drive, PO Box 6109, Morgantown, WV 26506, USA

⁷Center for Gravitational Waves and Cosmology, West Virginia University, Chestnut Ridge Research Building, Morgantown, WV 26505, USA

⁸McWilliams Center for Cosmology & Astrophysics, Department of Physics, Carnegie Mellon University, Pittsburgh, PA 15213, USA

⁹National Research Council of Canada, Herzberg Astronomy and Astrophysics, 5071 West Saanich Road, Victoria, BC V9E2E7, Canada

¹⁰Department of Electrical Engineering, Universidad de Chile, Av. Tupper 2007, Santiago 8370451, Chile

¹¹Cornell Center for Astrophysics and Planetary Science, Cornell University, Ithaca, NY 14853, USA

¹²Sub-department of Astrophysics, University of Oxford, Oxford, OX1-3RH, UK

¹³Radio Astronomy Laboratory, University of California, Berkeley, CA 94720, USA

¹⁴National Radio Astronomy Observatory, 520 Edgemont Road, Charlottesville, VA 22903, USA

¹⁵David A. Dunlap Department of Astronomy and Astrophysics, 50 St. George Street, University of Toronto, ON M5S 3H4, Canada

¹⁶Department of Statistical Sciences, University of Toronto, 700 University Avenue, Toronto, ON M5G 1Z5, Canada

¹⁷Data Sciences Institute, University of Toronto, 700 University Avenue, Toronto, ON M5G 1Z5, Canada

¹⁸Department of Physics and Astronomy, West Virginia University, PO Box 6315, Morgantown, WV 26506, USA

¹⁹Department of Astronomy and Astrophysics, University of California Santa Cruz, 1156 High Street, Santa Cruz, CA 95060, USA

²⁰Dunlap Institute for Astronomy and Astrophysics, 50 St. George Street, University of Toronto, ON M5S 3H4, Canada

²¹ASTRON, Netherlands Institute for Radio Astronomy, Oude Hoogeveensdijk 4, 7991 PD Dwingeloo, The Netherlands

²²Anton Pannekoek Institute for Astronomy, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands

²³26 Dick Perry Avenue, Kensington WA 6151, Australia

²⁴CSIRO Space & Astronomy, PO Box 76, Epping, NSW 1710, Australia

²⁵Dominion Radio Astrophysical Observatory, Herzberg Research Centre for Astronomy and Astrophysics, National Research Council Canada, PO Box 248, Penticton, BC V2A 6J9, Canada

²⁶Department of Astronomy, University of California, Berkeley, CA 94720, USA

²⁷Miller Institute for Basic Research, Stanley Hall, Room 206B, Berkeley, CA 94720, USA

²⁸International Centre for Radio Astronomy Research (ICRAR), Curtin University, Bentley WA 6102, Australia

²⁹Australian SKA Regional Centre (AusSRC), Curtin University, Bentley WA 6102, Australia

³⁰Laboratoire d'Astrophysique de Marseille, Aix-Marseille Univ., CNRS, CNES, Marseille, France
³¹Banting Fellow

³²McGill Space Institute Fellow

³³FRQNT Postdoctoral Fellow

³⁴Perimeter Institute of Theoretical Physics, 31 Caroline Street North, Waterloo, ON N2L 2Y5, Canada

³⁵SETI Institute, 339 Bernardo Avenue, Suite 200 Mountain View, CA 94043, USA

³⁶Department of Physics, Yale University, New Haven, CT 06520, USA

³⁷Department of Physics and Astronomy, York University, 4700 Keele Street, Toronto, ON M3J 1P3, Canada
Received 2025 April 7; revised 2025 August 4; accepted 2025 August 17; published 2025 October 23

Abstract

The Canadian Hydrogen Intensity Mapping Experiment (CHIME) has emerged as the world's premier facility for studying fast radio bursts (FRBs) through its fast transient search backend CHIME/FRB. The CHIME/FRB Outriggers project will augment this high detection rate of 2–3 FRBs per day with the ability to precisely localize

<figure><img src="image_3.png" /></figure>
them using very long baseline interferometry (VLBI). Using three strategically located stations in North America and deploying recently developed synoptic VLBI observing techniques, the Outriggers will provide ~50 mas localization precision for the majority of detected FRBs. This paper presents an overview of the design and implementation of the Outriggers, covering their geographic distribution, structural design, and observational capabilities. We detail the scientific objectives driving the project, including the characterization of FRB populations, host galaxy demographics, and the use of FRBs as cosmological probes. We also discuss the calibration strategies available to mitigate ionospheric and instrumental effects, ensuring high-precision localization. With two stations currently in science operations, and the third in commissioning, the CHIME/FRB Outriggers project is poised to become a cornerstone of the FRB field, offering unprecedented insights into this enigmatic cosmic phenomenon.

*Unified Astronomy Thesaurus concepts: Radio transient sources (2008); Radio bursts (1339); Very long baseline interferometers (1768); Transit instruments (1708)*

**1. Introduction**

Fast radio bursts (FRBs) are brief and intense flashes of radio waves originating from galaxies beyond the Milky Way, with durations ranging from microseconds to milliseconds (for comprehensive reviews, see E. Petroff et al. 2019, 2022). Their high luminosities and cosmological distances make them compelling subjects for astrophysical research. Despite their intriguing nature, the origins of FRBs remain largely enigmatic, although they are believed to involve highly energetic processes. In addition to being interesting in their own right, FRBs serve as probes of the intergalactic and circumgalactic media, and have the potential to unveil the properties of their host galaxies, the distribution of matter in the Universe, and the fundamental physics of the extreme environments in which they are generated.

The Canadian Hydrogen Intensity Mapping Experiment (CHIME; CHIME Collaboration et al. 2022) and its fast transient search backend CHIME/FRB (CHIME/FRB Collaboration et al. 2018) currently have the highest detection rate among instruments searching for FRBs, 2–3 per day. CHIME/FRB’s first catalog of 536 events detected in its first year of operations contains the majority of FRBs reported in the literature to date (CHIME/FRB Collaboration et al. 2021). This high detection rate has produced a number of observational results that have substantially advanced our understanding of the FRB phenomenon. Precise localizations of FRBs are crucial for understanding their origins and the environments from which they emanate. Localizing an FRB is necessary for making an association between a source and its host galaxy, thereby enabling studies of the demographics and stellar populations of FRB hosts. Obtaining distances to FRBs —usually via optical redshifts of their hosts—facilitates studies of their energetics and volumetric abundances (C. W. James et al. 2022a, 2022b). CHIME is capable of localizing FRBs to the arcminute-scale precision (D. Michilli et al. 2021), which is sufficient to identify host galaxies only in rare cases of nearby FRBs in ~$L^*$ galaxies (e.g., M. Bhardwaj et al. 2021a, 2023; D. Michilli et al. 2023; A. L. Ibik et al. 2024). Consistently identifying host galaxies beyond ~100 Mpc requires arcsecond localization precision, which to date has been achieved for several dozen FRBs by interferometers such as the Karl G. Jansky Very Large Array (e.g., S. Chatterjee et al. 2017; C. J. Law et al. 2020); the Australian Square Kilometre Array Pathfinder (ASKAP; e.g., K. W. Bannister et al. 2019; J. P. Macquart et al. 2020; S. Bhandari et al. 2022); the Deep Synoptic Array (e.g., V. Ravi et al. 2019; C. J. Law et al. 2024); and MeerKAT (e.g., L. N. Driessen et al. 2024).

For a small number of repeating FRBs, millisecond-scale localizations have been obtained using very long baseline interferometry (VLBI) with the European VLBI Network. Although these instances are few, the precision of these localizations has provided rich information about the environments of FRB sources *within their hosts*. This includes the localization of FRB 20121102 within a dwarf galaxy and coincident with a persistent radio source (B. Marcote et al. 2017; S. P. Tendulkar et al. 2017); FRB 20180916B, which lies 60 pc offset from a star-forming region within a spiral galaxy (B. Marcote et al. 2020; S. P. Tendulkar et al. 2021); and FRB 20200120E, which resides in a globular cluster in the halo of M81 (M. Bhardwaj et al. 2021b; F. Kirsten et al. 2022).

Unfortunately, VLBI localizations of nonrepeating FRBs face significant challenges with existing observatories. The field of view of observatories within VLBI networks is not large enough to detect significant numbers of FRBs in an untargeted survey, making VLBI localizations only possible in targeted follow-up, which is impractical for nonrepeaters. Morphological differences in the dynamic spectra of FRBs suggest that repeating and nonrepeating sources may form distinct populations (Z. Pleunis et al. 2021; CHIME/FRB Collaboration et al. 2023; A. P. Curtin et al. 2024). Consequently, observations that shed light on the <3% of sources observed to repeat (CHIME/FRB Collaboration et al. 2023) may not lead to an understanding that applies to the nonrepeating population.

FRBs have the potential to serve as a powerful cosmological probe of the large- and intermediate-scale plasma distribution (M. McQuinn 2014; K. W. Masui & K. Sigurdson 2015; M. S. Madhavacheril et al. 2019; J. P. Macquart et al. 2020; I. Medlock et al. 2025). Roughly 90% of the Universe’s baryonic matter is in the form of diffuse plasma between and surrounding galaxies. FRBs can be used to trace this plasma via dispersion, which provides a precise measure of the free election column density. In contrast to other probes, which are sensitive only to the hottest or densest regions, dispersion traces even the most diffuse plasma. However, redshift information is critical to disentangling distance and density in dispersion measurements. Furthermore, since such studies are fundamentally statistical measurements of the plasma distribution, large numbers of localized FRBs are required.

Here, we provide an overview of the CHIME/FRB Outriggers project, which will perform VLBI localizations of thousands of FRBs, providing the premier data set for both studying the FRB phenomenon and deploying them as cosmological probes. The Outriggers, shown in Figure 1, will employ recently developed synoptic VLBI techniques
<figure><img src="image_4.png" /><figcaption>**Figure 1.** CHIME and the Outrigger stations. Clockwise from top left: CHIME, KKO, and the Outriggers at HCRO and GBO. Photo credits: J. Richard Shaw, National Research Council Canada/Conseil national de recherches Canada, Kiyoshi Masui, Kenzie Nimmo.</figcaption></figure>

(C. Leung et al. 2021; T. Cassanelli et al. 2022, 2023; P. Sanghavi et al. 2023) to obtain precise localizations for the majority of FRBs detected by CHIME over its approximately 200 sq. deg. field of view. A. E. Lanman et al. (2024b) provided an in-depth overview of the k'ni?atn k'l_stk'masqt Outrigger<fnref n="38" /> (KKO), the first of the three stations, focusing on the detailed design and instrument commissioning and performance. Here we take a broader view and focus on the design and capabilities of the full outrigger network. The commissioning and performance of the stations at the Green Bank Observatory (GBO) and the Hat Creek Radio Observatory (HCRO) will be described in other work.

The paper is organized as follows: Section 2 describes our scientific objectives and translates these into technical requirements. Section 3 provides a description of the design of both the full VLBI array as well as the individual telescope stations. Section 4 provides a description of our observational capabilities in the context of enabling calibration that will propel us to achieve our objectives. Section 5 provides statistical forecasts for the localization performance of the

complete array of Outriggers. Finally, Section 6 describes the current status and outlook for the program.

**2. Scientific Objectives and Requirements**

By establishing a large number of ultra-precise localizations, the CHIME/FRB Outrigger project aims to advance our understanding of FRBs themselves, and to provide a statistically significant number of probes of Galactic and extragalactic environments. Our scientific objectives are based on four pillars:

*FRB populations.*

By identifying host galaxies, we aim to assemble a large sample of FRBs with distances. This will allow for precise measurements of their energetics and abundances, shedding light on the nature and distribution of FRBs across the Universe.

*Host-galaxy demographics.*

Through follow-up observations, we intend to characterize the host galaxies of FRBs in terms of their global properties, including mass and star formation history. This will provide insights into the types of galaxies that

<footnote n="38">³⁸ The name of the first Outrigger k'ni?atn k'l_stk'masqt was a generous gift from the Upper Similkameen Indian Band and means “a listening device for outer space.”</footnote>
harbor FRBs and the potential relationship between FRBs and their host galaxies' evolutionary stages.

*Source environments.*

Our goal is to study the specific locations within their host galaxies where FRBs occur. To this end, we desire a large sample for statistical studies of properties such as offsets from galaxy centroids with kiloparsec precision, as well as a smaller sample at the lowest possible redshifts for detailed, high-resolution multiwavelength follow-up observations for studies of the host environment on scales of ~10 pc.

*FRB as cosmological probes.*

By obtaining a large sample of FRBs with accurately determined redshifts over a wide range of redshifts, we plan to use FRBs as probes for cosmological studies. This includes investigating the large-scale distribution of baryons in the Universe, which could offer new insights into the structure and evolution of the cosmos.

To meet the scientific objectives, we have identified several key survey and/or technical requirements:

1. *A sample of more than 1000 precisely localized FRBs.* The scope of our scientific objectives necessitates a large sample size. For statistical studies, the precision of measurements improves with the size of the sample. A larger data set also increases the likelihood of encountering rare and illuminating systems that can provide deeper insights into the FRB phenomenon. Cosmological studies, in particular, stand to benefit significantly from a large sample size, enabling precision measurements with substantial scientific impact. With the current tally of high-probability FRB hosts exceeding 100 at the time of writing, a tenfold increase to 1000 hosts will represent a major advance in our statistical power.

2. *Localization precision of ≲50 mas.* For typical CHIME-detected FRBs at Gpc distances, 50 mas corresponds to subkiloparsec physical resolution, sufficient for statistical studies of source locations. For nearby events at ≲100 Mpc distances, the physical scale of the localization precision becomes ~10 pc, providing information on the location within, e.g., star-forming regions or offsets from globular clusters and supernova remnants. This target is also well matched to the highest-resolution instruments at other wavelengths, e.g., the Hubble Space Telescope (~100 mas), Keck adaptive optics (~10 mas) JWST (~100 mas), the Atacama Large Millimeter/submillimeter Array (~20 mas), and upcoming telescopes like the Vera C. Rubin Observatory (200 mas) and extremely large telescopes (~10 mas). Finally, our target localization precision strikes a balance between technical feasibility (which is discussed in more detail throughout this paper) and the potential for scientific discovery, particularly for FRBs in the nearby Universe.

3. *High completeness or well-understood selection functions for host identifications and redshifts.* Accurate characterization of FRB populations and their host galaxies is paramount. Selection effects can significantly bias these characterizations, and the impact of such biases on cosmological studies is not fully understood. The CHIME/FRB project characterizes the radio

selection function of the FRB search engine using a real-time system of in situ synthetic pulse injections (M. Merryfield et al. 2023). To measure property distributions (of either FRBs or their hosts) at 10% precision, host identification and redshift determination must be within a few percent of being complete, or the selection function must be either measured or modeled at the few percent level.

Our requirement (3) of knowing the selection effects merits further discussion. After having met our localization precision requirements (2), our completeness will be limited not by the radio localization but by the ability to detect the host in the optical band and obtain its redshift. Since such factors feed more into our follow-up program than Outrigger design, we defer their detailed discussion to future work (B. C. Andersen et al. 2025, in preparation). Thus, the radio localization will not be a source of incompleteness, so long as we meet our astrometric precision requirements for a subset of FRBs for which the selection is well understood. For example the effects of imposing some S/N cutoff can be calibrated via synthetic signal injections into CHIME/FRB's detection pipeline (M. Merryfield et al. 2023).

It is also acceptable to include only a subset of the sky in our completeness requirement, so long as the included sky fulfills our sample-size requirement (1). At a minimum, it will be necessary to exclude dusty sight lines that preclude optical spectroscopic follow-up. Existing optical surveys (either imaging or spectroscopic galaxy surveys) can substantially reduce the required follow-up within those fields, and can be used to calibrate the completeness in other parts of the sky.

In practice, we expect our selection effect requirement to be fulfilled through a combination of the maximum possible completeness in both the radio and optical, and modeling the remaining incompleteness to enough precision such that the residual uncertainty is at the few percent level. Even so, selection issues will arise if completeness strongly depends on some aspect of the population that we wish to study. For example, repeating FRBs are known to be preferentially narrowband compared to nonrepeating FRBs (Z. Pleunis et al. 2021; CHIME/FRB Collaboration et al. 2023), and as we show in Section 5, narrowband FRBs are harder to localize. As such, effort will be required to be complete to narrowband FRBs and throughout the FRB parameter space.

## 3. Design

The design of the CHIME/FRB Outriggers was driven by the scientific objectives specified in the preceding section. Here, we explain the rationale for our design choices, which divide into two parts: the design of the VLBI array, through the geographic locations of the stations, and the design of the stations themselves.

### 3.1. Geographic Array Design

#### 3.1.1. Baseline Length Scale

The scientific objectives listed in the previous section motivate localization precision in the 10–100 mas range. On a single baseline, the statistical limit to the localization precision
is (A. E. E. Rogers 1970)

$$ \sigma_{\theta}^{\text{stat}} = \frac{c}{2\pi b (S/N_{\times}) \text{BW}_{\text{eff}}}, \qquad (1) $$

where $\sigma_{\theta}^{\text{stat}}$ is the localization angle statistical error, b is the baseline length, S/N$_{×}$ is the signal-to-noise ratio (S/N) in VLBI cross-correlation, and BW$_{eff}$ is the effective bandwidth (approximately equal to recorded FRB bandwidth). The factor of 1/(S/N$_{×}$) is a “super-resolution” boost, which results from the possibility of measuring phases to subradian precision at high S/N. This is analogous to optical telescopes being able to measure the centroid of point sources to precision ~FWHM/ (S/N), where FWHM is that of the point-spread function. This boost can be difficult to realize beyond S/N$_{×}$ ~ 10, as systematic uncertainty in phase, for instance, induced by telescope optics, becomes dominant. Other significant systematic errors include the ionosphere and clock calibration. These will all be discussed further below.

Plugging in CHIME’s 400–800 MHz passband, we have

$$ \sigma_{\theta}^{\text{stat}} = 24 \text{mas} \left( \frac{10}{S/N_{\times}} \right) \left( \frac{100 \text{km}}{b} \right). \qquad (2) $$

As can be seen, baselines in at least the 10–100 km range, depending on our ability to super-resolve, are required to meet our science goals. Limitations of CHIME’s site at the Dominion Radio Astrophysical Observatory (DRAO) make the use of connected-element interferometry at these baselines impractical, instead requiring VLBI.

Since our science goals already pushed us into the VLBI regime, we were faced with the further question of what baseline length to choose. Stations placed between 10 and 100 km of CHIME see reduced ionosphere variation, and are more accessible to CHIME personnel, but are capable of providing only a subset of our science goals, and require developing “green-field” sites with no pre-existing infrastructure. Longer baselines in the 1000 km open up many more options for sites, including cleaner radio frequency interference (RFI) environments and observatories with existing infrastructure throughout North America. Such baselines will see more ionospheric variation; however, should systematic errors be controlled, they have the potential to greatly exceed our localization requirements and enable ancillary science. We thus concluded that baselines in the 100–1000 km scale best fit our requirements.

### 3.1.2. Number of Stations and Distribution

Each baseline in an interferometric array measures a single Fourier mode of the sky. As such, when phrased as an imaging problem, one anticipates needing a large number of baselines to reconstruct the sky with any fidelity. However, with the Outriggers we are pursuing only a localization, not an image, meaning there are only two numbers of interest per FRB (the 2D sky location). Since FRBs can be separated from backgrounds in the time domain, it should be possible to infer these two parameters from only two measurements. However, the location of a point source cannot be inferred from two Fourier measurements, since each Fourier mode is minimally compact in sky coordinates, with 2π phase ambiguities, resulting in a comb of equally possible sky locations. This ambiguity is broken when performing

multifrequency observations, since a fixed baseline measures a different Fourier mode at each frequency, whereas the localization is frequency-independent. Put differently, over a finite frequency range, the visibilities from a point source can be synthesized into a single geometric delay measurement for each baseline, and the 2D point-source location can be inferred unambiguously from only two delay measurements on nonparallel baselines. CHIME’s broad 400–800 MHz observing band is well suited to not only inferring geometric delays, but separating them from dispersive delays due to the ionosphere. This process, called fringe-fitting, is similar to LOFAR’s clock-TEC separation procedure (R. J. van Weeren et al. 2016), and is described in more detail in Section 4.

With each Outrigger site incurring both a substantial financial cost in site preparation and development, and a large logistical cost for construction, deployment, and operation, there is a great advantage to minimizing the total number of stations. The minimal array that fulfills our science goals is two stations forming noncolinear (and preferably close to orthogonal) ~1000 km baselines. However, there were a number of advantages to a third station at ~100 km baseline to CHIME. The first is the ability to do early science, since a station that is accessible from CHIME can be built faster by available team members based at DRAO. The single baseline yields only 1D localizations, but, often this is sufficient for host-galaxy identification, and has enabled early science goals (M. Amiri et al. 2025; T. Eftekhari et al. 2025; V. Shah et al. 2025). Second, the shorter construction timeline enabled refinement of structural and system design for the other sites, as well as earlier development of observational capabilities, calibration techniques, and analysis pipelines. The ionosphere, with a characteristic height of around 300 km, is expected to be broadly similar between stations separated on that scale, providing a means to separately characterize the performance of our array with and without the ionosphere. Another advantage is operational redundancy, enabling a sufficiently precise localization for host identification and redshift determination if either of the distant stations is offline. Finally, a third baseline provides an internal consistency check on FRB localizations, for which external validations are largely impossible.

With these considerations, our design comprises one station at a ~100 km distance scale from CHIME, and two more at ~1000 km from CHIME.

### 3.1.3. Site Selection

The map of our selected sites, constituting the full Outriggers VLBI network, is shown in Figure 2.

The first site, which hosts KKO, is situated about ~4 km south of the town of Princeton in British Columbia. At 66 km line-of-sight distance to CHIME, it is close enough to provide easy access to our staff located at DRAO or the University of British Columbia (UBC). This relatively short baseline allows for arcsecond-scale resolution in the baseline direction while avoiding the worst effects of the ionosphere.

The second site selected was at the Green Bank Observatory (GBO) in West Virginia. At 3370 km from CHIME, it forms the longest baseline and so enables the highest possible precision among the Outriggers. The observatory is in the National Radio Quiet Zone, reducing RFI. Being a national observatory, the site already has significant infrastructure
<figure><img src="image_5.png" /><figcaption>**Figure 2.** Map of geographical locations of the CHIME and the Outrigger sites. Baselines between each Outrigger and CHIME are shown with dotted lines with corresponding label of baseline lengths.</figcaption></figure>

including a hydrogen maser clock, which was routed to the Outrigger backend for precision timing.

For the third site, we selected the Hat Creek Radio Observatory (HCRO) in Northern California, which provides substantial infrastructure and a radio-quite site. Its proximity to an airport with commercial flights in Redding, CA (approximately 90 minutes drive) enables convenient access to the science team. Being 956 km south of CHIME, the station provides a long baseline roughly orthogonal to that with GBO. Infrastructure available at HCRO spans heavy construction equipment to radio-frequency test instruments.

## 3.2. Station Design

Here we provide an overview of the design of the individual Outrigger stations. We start with the high-level design, including the required collecting area and best antenna architecture. We then proceed to more detailed aspects, including elements of the structure, analog chain, digital hardware, and software pipelines.

### 3.2.1. Required Collecting Area

The first consideration in designing the Outriggers was the required collecting area for the stations, driven by the required CHIME–Outrigger cross-correlation S/N for localization. In the statistically ideal case, this is given by

$$S/N_{\times} = S/N_{\text{CHIME}} \sqrt{\frac{2A_{\text{eff,out}}}{A_{\text{eff,CHIME}}}} \quad (3)$$

Here, $S/N_{\text{CHIME}}$ is the S/N of the FRB as measured using offline analysis pipelines in CHIME data alone, and $A_{\text{eff,out}}$ and $A_{\text{eff,chime}}$ are the effective collecting areas of the Outrigger and CHIME, respectively. The factor of $\sqrt{2}$ in the above equation

originates from differences in the statistics in cross-correlation versus autocorrelation (K. Masui et al. 2015).<fnref n="39" />

Our scientific requirement (1) is that we localize a large number of sources, a substantial fraction of the ~1000 per year detected by CHIME/FRB. CHIME/FRB’s detection threshold is $S/N_{\text{CHIME}} > 9$, however, false positives that are difficult to veto in real time make capturing the requisite baseband data challenging below $S/N_{\text{CHIME}} = 12$ (CHIME/FRB Collaboration et al. 2024). While lowering the baseband capture threshold is likely possible with some development effort, our experience is that detailed analysis of lower-S/N bursts is challenging. In any case, the higher threshold reduces the total number of bursts by a fraction $(9/12)^{3/2} = 0.65$ (CHIME/FRB Collaboration et al. 2021), which we deem to be an acceptable loss.

We estimate that $S/N_{\times} > 6$ is required to attempt VLBI localization. While this substantially exceeds what is required for statistical localization precision on 1000 km baselines as given in Equation (2), 6 is the minimum $S/N_{\times}$ for which we can confidently detect and identify the correct VLBI fringe, as verified using pulsars and steady sources (discussed in detail below). Note that in the fringe search, there is a nonnegligible “trials factor” (see A. R. Thompson et al. 2017), since the search space of potential localizations is large (for each baseline, which provides a 1D localization, this is roughly the ratio of the CHIME/FRB baseband localization precision to the VLBI localization precision, which is ~1'/10 mas = 6000). Note that the $S/N_{\text{CHIME}} = 12$ criterion used for triggering is the S/N yielded by the real-time search. For most events, offline analysis can achieve substantially higher S/N through coherent dispersion, forming a tied-array beam to the baseband localization

<footnote n="39">³⁹ One way to understand the factor of $\sqrt{2}$ is to consider the case where the Outriggers have identical antennas to CHIME, and we treat the feeds in the station arrays as individual VLBI elements. If CHIME has $n$ feeds and an Outrigger station $m$ feeds, then CHIME has $\approx n^2/2$ intra-station baselines, whereas there are $nm$ baselines between CHIME and the Outrigger.</footnote>
(CHIME/FRB Collaboration et al. 2024), and detailed modeling of the burst morphology (E. Fonseca et al. 2024). Offline analysis thus builds some conservatism into our collecting area specifications.

Given an S/N<sub>CHIME</sub> threshold of 12, and a required S/N<sub>x</sub> > 6, Equation (3) gives A<sub>eff,out</sub> = A<sub>eff,CHIME</sub>/8 as the appropriate station size. CHIME has an instrumented collecting area of 6400 m<sup>2</sup> and an aperture efficiency of η<sub>A</sub> ≈ 0.7 (CHIME Collaboration et al. 2022), which motivates A<sub>eff,out</sub> ≈ 550 m<sup>2</sup>.

We have so far only discussed CHIME–Outrigger baselines and have not mentioned Outrigger–Outrigger baselines. For the latter, S/N<sub>x</sub> is suppressed by a factor of &radic;<span style="text-decoration: overline;">A<sub>eff,out</sub>/A<sub>eff,CHIME</sub></span> compared to the former. Furthermore, as explained above, only two baselines are required to achieve a 2D localization. As such, the stations were sized to only rely on the baselines that include CHIME. We anticipate the inter-Outrigger baselines being useful only for the brightest FRBs or ancillary science.

On a final note, as discussed in Section 3.1.2, the specific scientific objectives of KKO at a baseline of 66 km differ from the other two sites. KKO's focus on early science from a less-complete sample of host identifications can be achieved with a smaller collecting area. Furthermore, KKO's 1D localizations will enable host associations only for lower-DM, lower-redshift sources. These preferentially have higher S/N<sub>CHIME</sub> (K. Shin et al. 2023; H.-H. Lin et al. 2024). As such, we chose A<sub>eff,KKO</sub> = A<sub>eff,CHIME</sub>/16.

### 3.2.2. Antenna Architecture

The required collecting area, 550 m², could be obtained from a number of antenna architectures, but we had the additional requirement that we cover the CHIME field of view, a 3° wide strip between the north and south horizons over the local meridian at DRAO. Several architectures were considered. We used CHIME's architecture of 20 m wide cylinders as a baseline, and which was ultimately selected. The required collecting area can be achieved with a single cylinder with 40 m instrumented length. The major disadvantage of this design is its large monolithic structure, where the cost of the material, structure fabrication, and foundations dominate. Furthermore, access to the focal line, 5 m above the reflector, to install and service analog components is challenging. A key advantage is that matching CHIME's field of view is straightforward.

Another possibility was a large array of dipoles, as in the Square Kilometre Array-Low,<fnref n="40" /> which would have a field of view covering the visible sky and would minimize structural costs. This would have been at the cost of requiring an extreme number (order 10⁴) of analog elements, since each dipole has an effective area ~λ²/4. Even if the cost of these would be reduced to ~100 per element, this would be comparable to structural costs of other architectures. Through analog summing, the number of digitization channels could be made to be less extreme. Nonetheless, a dipole array was rejected due to the high analog cost and large departure from the single-element analog-to-digital chains with which our team has substantial experience.

An array of dishes with a diameter in the 5–10 m range was also considered. This would have solved challenges due to a cylinder’s monolithic structure, and at smaller diameters, focal points could be accessed via ladder. However, dishes have a

severe mismatch to CHIME in field of view. Covering a substantial fraction of CHIME’s field of view could have been achieved by tiling it with effectively independent arrays of dishes, but that would increase both costs and the total footprint of the site, substantially constraining site selection. As such, a dish-based architecture was rejected. An option that was carefully considered was a cylindrical architecture but with a 10 m width instead of CHIME’s 20 m. Achieving the same collecting area would have required doubling the instrumented length as well as the number of analog chains and digitizers. However, structural and foundation costs would be substantially lower, and the focal line, at a height of 2.5 m, would be serviceable by ladder. More detailed costing estimates including structural, analog, and digital costs suggested that 20 and 10 m widths would be comparable.

The key advantage of using the same antenna architecture as CHIME is the prospect of matching beams. Differences in the primary beam between elements—particularly in the beam-induced phase—is a major systematic error in radio interferometry. Matching the beams between elements, in this case between CHIME and the Outrigger, eliminates this issue. However, even an Outrigger with identical optics to CHIME would have some mismatch due to zenith angle differences arising from the different latitudes of the Outrigger sites. Nonetheless, substantial investment has been made in calibrating and modeling CHIME’s beam, so it is likely that such measurements could be used to correct for any beam differences. Ultimately, it was decided that copying CHIME’s architecture as closely as possible with 20 m cylinders was feasible and was the most promising for mitigating systematic errors.

### 3.2.3. Station Design Summary

Having settled on 20 m wide cylinders as the station architecture, the structural designs largely mimic that of CHIME (CHIME Collaboration et al. 2022) with a few key differences. Many of the details of these differences were described by A. E. Lanman et al. (2024b); here, we provide only a summary.

Our size requirements from Section 3.2.1 are achieved for the GBO and HCRO stations with single cylinders with 40 m of instrumentation. This becomes a total reflector length of 64 m when allowing for 10 m of buffer reflector at either end (required for proper optics) and when constructing out of an integer number of 8 m sections, which is the spacing between the main structural beams. For KKO, this is 20 m of instrumentation, 40 m total. The cylinders are oriented such that they observe nearly the same field of view as CHIME along the DRAO meridian. This required the cylinders to be both rolled (along the cylinder axis) and rotated (in the plane of the local ground). These orientation differences are particularly pronounced for the station at GBO, due to its site at a substantially different longitude to CHIME, as can be seen in Figure 3. For the GBO and HCRO stations, there is a ~10 deg mismatch in decl. due to the Outriggers being at different latitudes to CHIME. This results in sensitivity mismatches at the few tens of percent level, which is most pronounced for the most northerly targets in CHIME’s field of view.

Furthermore, access to the instrumentation at the focal lines is from below, in contrast to CHIME where it is from above. Access is enabled from a traveling cart that runs on two rails

<footnote n="40">⁴⁰ https://www.skao.int</footnote>
<figure><img src="image_6.png" /><figcaption>**Figure 3.** Isometric view of the structural drawings for the GBO station. Due to its eastward location, the GBO station requires a substantial axial roll and a rotation from local north (in the plane of the ground) so as to approximately match its field of view to CHIME's along the meridian at DRAO. Image credit: Sightline Engineering.</figcaption></figure>

fixed to the sides of the focal-line structure. Due to design challenges and safety concerns specific to the high roll of the focal line, the cart is no longer in use for the GBO station, where access is now provided by aerial lift truck.

Like CHIME, the Outrigger focal lines are instrumented with dual-polarization clover-antenna feeds (M. Deng & D. Campbell-Wilson 2017), spaced by 305 mm, for a total of 64 feeds for KKO and 128 for the other two. Signals from each polarization channel are amplified by low-noise amplifiers (LNAs) at the feeds. Two such feeds and associated LNAs are assembled into focal-line modules called cassettes, which also incorporate the ground plane, facilitate deployment, and provide weatherproofing. In contrast to CHIME, the Outrigger cassettes incorporate a vacuum-formed acrylonitrile butadiene styrene polymer radome to keep moisture out. Signals are transported by coaxial cable to the shielded room in the receiver hut, then further amplified and filtered to the 400–800 MHz observing band by filter amplifiers (FLAs). There is no frequency conversion, as these signals are directly digitized in the second Nyquist zone. To achieve optimal signal levels for digitization, additional attenuation or filtering is added depending on the site-dependent RFI environment.

The Outrigger digital backend is designed as an FX correlator. The F-engine is implemented using the same field programmable gate array (FPGA)-based ICE framework used in CHIME (K. Bandura et al. 2016; CHIME Collaboration et al. 2022). A single ICE board can digitize and process 16 radio-frequency channels, or the equivalent of eight dual-polarization feeds, requiring 16 and eight boards for the larger Outriggers and KKO, respectively. The analog to digital converters (ADCs) on each ICE board are commercially available and configured to sample the incoming voltage stream at 800 MS s⁻¹. Due to the filtering in the FLAs, this recovers the 400–800 MHz operating band of CHIME, corresponding with the second Nyquist zone. Channelization is done with a polyphase filter bank in combination with a fast Fourier transform, producing 1024 channels, each 390 kHz wide. The ICE boards also perform the corner turn, regrouping the data by individual frequency channels instead of by the

larger RF channel. These data are henceforth referred to as the “baseband” data.<fnref n="41" />

The frequency-channelized and frequency-grouped baseband data are transmitted via direct network links to the X-engine. The X-engine performs three key operations on the data. First is the correlation the data into the $N^2$ visibilities, which enables each station to operate as an independent interferometer and facilitates calibration of the intra-station array. Second, these nodes host a large quantity of random access memory (RAM) to buffer the full-array baseband data so that it can be recorded upon receipt of an FRB trigger. This constitutes the primary science data stream used for VLBI localization, which will be described in more detail in Section 4.3.1. Finally, tied-array beams are formed to targeted sources, enabling traditional, nontriggered VLBI observations, which will be used for calibration and ancillary science. This capability is described in further detail in Section 4.3.2.

The X-engine consists of x86-architecture computers housing AMD MI100 graphics processing units (GPUs) for accelerated computing. These nodes run the Kotekan high-performance data pipeline framework (A. Recnik et al. 2015; A. Renard et al. 2021), with GPU kernels written in a mixture of OpenCL and assembly language. The number of such nodes is driven by the input data baseband data rate, with each node designed to receive about 205 Gbps. Four such nodes are required for each of the larger Outriggers and two for KKO.

Precise and accurate clocking and time-tagging of the data is a critical consideration for a VLBI system, where, as will be discussed, localization can be framed as a precision timing problem. Clock and timing signals for the F-engine (which hosts the ADCs) is generated by a GPS-disciplined crystal oscillator, which provides absolute time-tagging at tens of nanosecond precision but is lacking in short- and medium-term stability. As described by J. Mena-Parra et al. (2022), we use an auxiliary clock, fed directly into a correlator ADC, to correct our timing on these timescales. At KKO, the auxiliary clock is a free-running Stanford Research Systems FS725 Rubidium clock. For the GBO station and CHIME, we use the signal from the observatory maser. For the HCRO station, we use the observatory clock, which is an Endrun Technologies Meridian II Precision TimeBase with the US-Rb oscillator upgrade. This is a GPS-disciplined time and frequency standard whose underlying oscillator is the same Stanford Research Systems Rubidium clock as KKO. J. Mena-Parra et al. (2022) and S. Cary et al. (2021) demonstrated the ability to achieve 0.2 ns timing precision on 2000 s timescales for the stations with rubidium clocks and roughly day timescales for stations with masers.

## 4. Observational Capabilities and Calibration Strategies

In this section, we provide an overview of the Outriggers' observational capabilities and how they will enable us to meet our localization requirements. We begin with the detailed formalism of the calibration-localization inference problem, then provide an overview of available calibration sources within our band, and then proceed to observational capabilities and strategies that enable us to achieve our science goals. The

<footnote n="41">⁴¹ While the term “baseband” is accurate due to the absence of mixing in CHIME’s radio-frequency system, it is not particularly descriptive of the phase-persevering measurements of the incident electric field. Nonetheless, this nomenclature is commonly used in some radio-astronomy subfields and has been adopted within the CHIME/FRB Collaboration.</footnote>
ultimate calibration strategy that will be used for the Outriggers is not finalized. This stems from several sources of underlying uncertainty including availability of VLBI calibrators in our band, the spatiotemporal properties of the ionosphere, and what strategies turn out to be operationally most feasible. Nonetheless, work done so far has led to a promising calibration strategy where, upon receipt of an trigger from CHIME/FRB, observations of the nearest suitable pre-cataloged compact continuum calibrators are initiated at low-latency using coordinated tracking beams at CHIME and each Outrigger station. This strategy is detailed in Section 4.4.3.

## 4.1. VLBI Localization Measurement Equation

Here we describe our model for VLBI observations within the context of the point-source localization problem, including how phase referencing can mitigate the effects of unknown phase contributions to the visibility. We then discuss the parametrics of the measurement, including contributions to the interferometric phase from the geometric delay (which contains the localization information), and nuisance parameters for offsets in the observatory clocks and differences in dispersive delays due to the ionosphere. Finally, we use this understanding to motivate requirements for calibration observations that will enable use to achieve our localization goals.

Our model for the signal in a VLBI visibility is as follows:

$$V_{ab}^{s}(\nu, t) = S_{\nu}^{s} \exp \{i2\pi\nu[\tau_{ab}(\hat{n}^{s}, t) + \tau_{ab}^{c}(t) \\ + \kappa \text{sTEC}_{ab}^{s}(t)/\nu^{2}] + i\phi_{ab}(\nu)\}. \quad (4)$$

Here, $V_{ab}^{s}(\nu, t)$ is the visibility signal from source s between stations a and b as a function of observing frequency $\nu$ and time t. We note that for FRBs, the observation time is near instantaneous, but frequency dependent due to the dispersed pulsed emission. However, for the time being, we keep things general and carry forward the time and frequency dependence. $\tau_{ab}(\hat{n}^{s}, t)$ is the geometric delay between the two stations for source sky location $\hat{n}^{s}$. $S_{\nu}^{s}$ is the source's flux density, and $\tau_{ab}^{c}(t)$ is the difference in clock delays between the two stations. $\text{sTEC}_{ab}^{s} \equiv \text{sTEC}_{a}^{s} - \text{sTEC}_{b}^{s}$ is the difference in ionospheric slant total electron content between the two stations in the direction of the source. $\kappa$ is a physical constant such that $\kappa \text{sTEC}/\nu^2$ is the dispersive delay from the ionosphere. We adopt a value of $\kappa = 1.345 \times 10^3$ MHz TECu$^{-1}$ (R. J. van Weeren et al. 2016). $\phi_{ab}(\nu)$ is the difference between frequency-dependent instrumental phases between stations, for example, imparted by the analog chain, which is difficult to calibrate for a single station. Here we omit instrumental calibration factors affecting the amplitude (flux), since we will use exclusively phase information for localization, and amplitudes can, in principle, be calibrated station by station (before performing VLBI).

We assume that $\phi_{ab}(\nu)$ is not direction dependent, meaning the contribution from differences in the beams is small. In practice, beam phase constitutes a significant systematic error that, in the KKO system, has been found to be as high as a radian at the periphery of our field of view. As we will show below, this is nonetheless tolerable for our scientific objectives, and we leave careful consideration of this error to future work.

It is often useful to phase reference a visibility to an observation of a calibrator c, which cancels out much of the unknown systematic contributions to the phase. After phase referencing, the visibility signal is given by

$$V_{ab}^{s}(\nu, t_s) V_{ab}^{c*}(\nu, t_c) = S_{\nu}^{s} S_{\nu}^{c} \exp \{i2\pi\nu[\tau_{ab}(\hat{n}^{s}, t_s) \\ - \tau_{ab}(\hat{n}^{c}, t_c) + \tau_{ab}^{c}(t_s) - \tau_{ab}^{c}(t_c)] \\ + i2\pi\kappa[\text{sTEC}_{ab}^{s}(t_s) \\ - \text{sTEC}_{ab}^{c}(t_c)]/\nu\}. \quad (5)$$

This is the data product from which we will infer the localization. As written, the time dependence has been kept general, however, we will generally assume sufficiently brief observations such that the target and calibrator observations can be integrated down a visibility spectrum at a single effective time. That is, $t_s$ and $t_c$ are single numbers, whereas the frequency $\nu$ covers the full observing band. There are subtleties in removing the most rapidly changing contributions to the phase prior to integrating that are discussed in detail by C. Leung et al. (2024). In addition, for pulsars and FRBs, the dispersion delay in time of arrival makes the observation time dependent on frequency, which we discuss briefly in Appendix A. Both these effects are critical to account for when analyzing the data, but are not essential for motivating calibration strategies. As such, we will not discuss them further here.

Note also that for such short (effectively instantaneous) observations where Earth rotation is negligible, the dependence of the visibility on the source location is through a single intermediary variable, $\tau_{ab}(\hat{n}^{s})$. As such, only one component of $\hat{n}^{s}$ can be measured, the one colinear with the baseline. Two noncolinear baselines are required to precisely measure all components of the localization.

The key aspect of Equation (5) is its dependence on the source location $\hat{n}^{s}$, through the delay model $\tau_{ab}(\hat{n}, t)$. Before discussing the other contributions to the phase, it is instructive to consider how sensitive this term is to the localization so that we can develop a rough understanding of how well other terms will need to be known. While the delay model includes many effects, including relativistic delays and contributions from the refractive index of the troposphere, the largest contribution is purely geometric, such that $\tau_{ab} \approx \vec{b}_{ab} \cdot \hat{n}/c$, where $\vec{b}_{ab}$ is the baseline vector connecting telescopes a and b. This quantity is of the order of $b_{ab}\theta/c$, where $\theta$ is sky angle from zenith. Thus, constraints on the delay at precision $\sigma_{\tau}$ fix the source location to a small range of angles of width $\sigma_{\theta} \sim \sigma_{\tau c}/b_{ab}$. For our localization requirement of $\sigma_{\theta} \approx 50$ mas (as motivated in Section 2) and baselines $b_{ab} \sim 1000$ km, we have $\sigma_{\tau} \sim 0.8$ ns. As such, we must be able to isolate the $\tau_{ab}(\hat{n}^{s}, t_s)$ from the other terms (through calibration or otherwise) to nanosecond precision, or $\sigma_{\phi} = 2\pi\sigma_{\tau}\nu \sim 3$ rad when converted to phase units at 600 MHz. This justifies our above decision to defer consideration of beam phase, which, in the worst cases, contributed $\sim 2$ rad.

In practice, the dependence of the visibility on the target localization is best viewed as coming through the combined quantity $\tau_{ab}(\hat{n}^{s}, t_s) - \tau_{ab}(\hat{n}^{c}, t_c)$, which we henceforth refer to as the geometric delay. This makes it clear that the calibrator position $\hat{n}^{c}$ must be known to better than the localization requirement. It also hints at reduced sensitivity to errors in the delay model (including uncertainties in the station locations)
when the calibrator is near on the sky to the target. However, in practice, our delay model *calc11* (M. Eubanks et al. 1991) has been validated to precision exceeding our needs, and the baselines can be calibrated as shown by A. E. Lanman et al. (2024b). The geometric delay must be separated from other contributions to the interferometric phase. The first of these is $\tau_{ab}^{cl}(t_s) - \tau_{ab}^{cl}(t_c)$, describing the time transfer of our clocking solutions. In the previous section and in J. Mena-Parra et al. (2022), we described hardware solutions that render this term negligible compared to our localization specifications provided $|t_s - t_c| \lesssim 2000$ s.

The quantity $sTEC_{ab}^s(t_s) - sTEC_{ab}^s(t_c)$ represents the difference of the slant TECs from the ionosphere between the two lines of sight and between the target and calibrator observation times and directions. Thus, it is expected to be smaller for target-calibrator observations that are more proximal in time and sky location. We see from Equation (5) that the geometric delay causes a linear phase in the visibilities with frequency, whereas the dispersive delays induce phase that goes as $1/\nu$. As such, we anticipate that given a sufficiently wide band and S/N, these contributions should be nondegenerate and no further ionospheric calibration should be necessary. However, if statistical power is limited, degeneracy between the geometric and dispersive delays can substantially reduce localization precision. A prior on the differential slant TEC can help to break the degeneracy, motivating more proximal calibrators to enable tighter priors (for further discussion, see Appendix C). The phase-referencing and localization fitting procedure described above motivates the desire for calibrators and observations thereof with the following properties:

1. Compact on our ~3000 km baselines within our 400–800 MHz observing band.

2. Known astrometric precisions substantially better than our localization precision target of 50 mas.

3. Sufficient S/N observations such that the noise in the phase-referenced visibilities $V_{ab}^s V_{ab}^{cs*}$ observation is not dominated by noise from the calibrator observation. Since we wish to localize FRBs with $S/N_{\times} > 6$, calibrator observations with $S/N_{\times} \gtrsim 20$ are desired. This can be achieved through a combination of calibrator brightness and observation duration.

4. Calibrator observations separated in time from target observations by <2000 s, such that time transfer of our clocking solutions does not introduce large localization errors.

5. Calibrators with Earth-frame sky locations as close as possible to the target FRBs such that as narrow a prior as possible can be placed in the slant TEC differences. Given CHIME's drift-scan design and the shape of its beam, this implies a calibrator at a similar decl. to the target that transits within the required time frame.

## 4.2. Potential Calibrators

### 4.2.1. VLBI Continuum Calibrators

While global VLBI solutions exist for frequencies$^{42}>1$ GHz, many of these sources are unusable at ~600 MHz due to low-frequency turnover (e.g., from synchrotron self-absorption),

larger physical sizes of the emitting regions at low frequency and hence sources being resolved, and in some cases angular scatter broadening. Nevertheless, a survey conducted by S. Andrew et al. (2024) detected over 200 calibrators on the CHIME–GBO baseline from the radio fundamental catalog (L. Y. Petrov & Y. Y. Kovalev 2025), which are sufficiently bright (~500 mJy) to be observed in standard ~100 ms baseband captures. The density is such that, on average, there are about two such sources in CHIME’s field of view at a time. S. Andrew et al. (2024) also showed that with a deeper survey (1.4 s integration times), our calibrator density is expected to increase by a factor of ~7. Such a survey is currently underway.

### 4.2.2. Pulsars

Pulsars allow time-domain separation from constant backgrounds, and the pulsed emission is guaranteed to be compact (apart from scatter angular broadening for a small subset). Additionally, pulsars are sufficiently abundant that the Outriggers can observe them frequently enough to maintain phase coherence across our network. T. Cassanelli et al. (2022, 2023) described and demonstrated an end-to-end a calibration procedure relying on pulsars as calibrators (e.g., using giant pulses from the Crab pulsar (PSR B0531+21) detected on the baseline between CHIME and the Algonquin Radio Observatory, located >3000 km from CHIME).

Independent of our ultimate calibration strategy, the fact that dispersed pulsed emission from pulsars closely resembles FRBs makes these sources critical checks of our localization capabilities. By analyzing pulses from pulsars as if they were FRBs (as well as the small number of repeating FRBs localized by other instruments), we can verify the end-to-end performance of the Outrigger system. Such a performance characterization strategy has already been used for KKO (A. E. Lanman et al. 2024b) and CHIME/FRB’s baseband system (D. Michilli et al. 2021).

We have selected a sample of 97 pulsars to use as a possible calibrator sample for the CHIME/FRB Outriggers. Each of our targets is sufficiently bright to have a phase-folded detection significance S/N of at least 15 in a single CHIME transit.$^{43}$ This detection threshold is sufficient to detect the pulsars in cross-correlation between CHIME and the Outriggers. In contrast to extragalactic calibrators, pulsars preferentially lie in the Galactic plane where angular broadening from scattering causes some to be resolved on our longer baselines. As such, we included only those pulsars with estimated angular broadening <10 mas at 400 MHz. The angular broadening estimates were derived from temporal broadening measurements where available and from the *ne2001* model otherwise. However, this criterion yields a sample with gaps in sky coverage. We have relaxed the angular broadening criterion for nine targets with critical right ascensions. It is possible that some of these nine sources will be resolved and undetected on the CHIME–GBO baseline. The sky distribution of the 97 calibrator pulsars is shown in Figure 4.

The design plan for the Outriggers allows for an astrometric error of up to 50 mas, of which roughly 40 mas is budgeted for systematics and the ionospheric uncertainty. Therefore, to stay

<footnote>$^{42}$ https://astrogeo.smce.nasa.gov/sol/rfc/rfc_2024b/</footnote>

<footnote>$^{43}$ Transit time is a function of decl., with a minimum of ~10 minutes for southern decl. to hours close to the north celestial pole.</footnote>
<figure><img src="image_7.png" /><figcaption>**Figure 4.** Cartesian projection of the 97 pulsars that the CHIME/FRB Outriggers will use as calibrators (A. B. Pearlman 2024; A. P. Curtin et al. 2025, in preparation). Pulsars are shown with black circles, while the gray circles show the lower transits for the high-decl. pulsars. The width of the gray shaded area indicates the range of hour angles that the pulsar is observable by CHIME, which depends on the decl. of the source. Darker regions indicate that more than one pulsar is visible in the CHIME beam at the given time. Note that CHIME only sees the sky north of decl. -11°. Coordinates are J2000.</figcaption></figure>

within the remaining error margin when added in quadrature, our pulsar calibrator positional uncertainties must be <30 mas. While ~millisecond-level localizations can sometimes be achieved for millisecond pulsars using pulsar timing, there are currently not enough such pulsars to act as the calibrators for the Outriggers. Further complicating matters, pulsars typically have proper motions of ~10 mas yr⁻¹, with some displaying proper motions of >50 mas yr⁻¹ (e.g., S. Chatterjee et al. 2009; A. T. Deller et al. 2019).

Motivated by the need to have pulsar locations determined precisely and accurately, we have observed 84 pulsars at seven different epochs with the Very Long Baseline Array (VLBA) since 2021 February, in order to obtain precise positions and proper motions (VLBA/21A-314, PI: Kaczmarek; VLBA/22A-345, PI: Curtin; VLBA/23A-099, PI: Curtin; VLBA/24B-328). The remaining 13 pulsars have previous VLBA positions and proper motions from either S. Chatterjee et al. (2009) or A. T. Deller et al. (2019). Each pulsar is observed in the 1.35–1.61 GHz frequency band. As each pulsar has a well-determined timing ephemeris derived from the CHIME/Pulsar instrument, we employ matched-filter pulsar gating to increase the S/N per observation. Additionally, as absolute position measurements are imperative, each observation is phase-referenced. So far, we have obtained 360 hr of pulsar observations with the VLBA. This program will not only result in a pulsar calibrator survey that can be used across a variety of frequencies, but will also double the number of pulsars with well-measured positions, parallax, and proper motions. Results from this pulsar astrometry project will be published separately (A. P. Curtin et al. 2025, in preparation).

### 4.3. Observational Capabilities

CHIME and the Outriggers are capable of several observation modes, including the station $N^2$ correlation, full-array baseband captures, and tied-array tracking beams. The first of these is the traditional interferometric mode where each of a station's antennas is correlated against all of the others. While critical for internally calibrating and characterizing a station, it discards the global phase information required for VLBI. In contrast, full-array baseband captures and tied-array tracking

beams retain global phase information and can be used for VLBI. Here, we describe these two modes in more detail. All three of these data acquisition modes are run commensally.

Data from either the full-array baseband capture system or the tied-array tracking beams may be correlated between stations for VLBI. The details of this process have been provided by C. Leung et al. (2024).

#### 4.3.1. Full-array Baseband Acquisitions

Each Outrigger is equipped with a full-array baseband capture system as originally implemented for CHIME/FRB for more detailed characterization of FRBs (CHIME/FRB Collaboration et al. 2018; D. Michilli et al. 2021) and first used for VLBI with the CHIME Pathfinder (C. Leung et al. 2021). For this system, CHIME and the Outriggers store baseband data for all antennas in a ring buffer on the X-engine nodes. Short subsets of these data may be excised from the buffer and written to disk. Functionality exists to account for dispersion delay, such that the time-span captured is different for each frequency channel.

The key advantage of recording data in full-array mode is that it allows station beams to be formed in any direction within the 200 square-degree field of view of each station in subsequent offline analysis. This provides the ability to observe any target or calibrator within the field of view at the time of recording. Critically, because the sky locations of FRBs are not known a priori, this is the only system capable of capturing phase-preserving data for FRBs.

The main limitation of the baseband capture system is that, because we record data for all antennas in a station's array, the high data rates limit the duration and frequency of these captures. The full-array baseband data rate is 6.6 Tbps for CHIME, 0.41 Tbps for KKO, and 0.82 Tbps for the GBO and HCRO stations. Due to limitations in transferring data off the X-engine nodes, captures are limited in duration to the length of an intermediate 1.4 s "readout buffer." Multiple simultaneous captures are possible so long as their durations do not cumulatively surpass 1.4 s. Upon filling the readout buffer, it takes several minutes to transfer the data to disk so that additional data can be collected.
Functionality exists to capture full-array baseband data synchronously at CHIME and the Outriggers either at pre-scheduled times, or upon receipt of a trigger from CHIME/FRB, either from an FRB or a pulsar single pulse. For CHIME, this buffer has a duration of 33 s and for the Outriggers it is 38 s. CHIME/FRB's triggering latency from pulse arrival at 400 MHz is about 10 s, with the remainder of the buffer length used for the dispersion delay between 800 and 400 MHz. As such, the system enables capture of the full band for sources with DM up to ~1000 pc cm⁻³ at CHIME and the Outriggers.

### 4.3.2. Tracking Beams

CHIME and each of the Outrigger stations will utilize tied-array beams to digitally track compact calibrators (e.g., continuum sources and pulsars) that will be used for VLBI calibration (A. B. Pearlman 2024). This system was born out of the tracking beams developed for CHIME/Pulsar (CHIME/Pulsar Collaboration et al. 2021), paired with a VLBI recording backend. Simultaneous dual-polarization beams are formed to a specified position at each site and the resulting phase-preserving voltage data are streamed to disk in VLBI Data Interface Specification (VDIF) format.

Since the tied-array beams collapse the information from all of a station's antennas into a single data stream, the data rate is far lower (only 6.4 Mbps per beam for each station). This capability allows for much longer duration observations for sources for which the sky location is known a priori, such as pulsars and continuum calibrators. As such, observations that span the duration of a source's transit through CHIME's field of view are possible, which can be 10 minutes or longer depending on the source's decl. We initially plan to use two such tied-array beams simultaneously. This system has been designed to ensure the real-time tied-array beamformer and the offline beamformer for the full-array baseband capture system have consistent pointing and phase centers, allowing calibration solutions derived from one to be applied to the other.

## 4.4. Calibration Strategies

Having discussed both the potential calibration sources as well as our observational capabilities, we now sketch out a few calibration strategies that would allow us to achieve our scientific requirements. As stated previously, which of these strategies is used will depend on the resolution of lingering uncertainties about calibrator abundance, the ionosphere, and logistical considerations. However, the strategy described in Section 4.4.3 is promising in the long term and is a current development target.

### 4.4.1. Tracking Rare Calibrators and Time Transfer

At the beginning of the CHIME/FRB Outriggers program, the abundance of long-baseline continuum calibrators in the CHIME band was known but incomplete: existing catalogs covered either similar baseline lengths or similar frequencies but not both (E. Lenc et al. 2008; J. Moldón et al. 2015). There was a risk that our calibrator grid would be sparse: perhaps limited to pulsars and a small fraction of the continuum calibrators used at higher frequency.

As such, our initial calibration strategy—designed to mitigate this unlikely but potentially catastrophic scenario—was to continuously monitor up to two pulsars using the tracking beam capabilities described in Section 4.3.2. Tracking

beams provide ample observation lengths to achieve high S/N on even dim sources while keeping data volumes manageable. As can be seen from Figure 4, there exist ~1000 s periods for which there are no pulsars in the CHIME field of view, requiring the on-site atomic clocks described in Section 3.2.3 to interpolate timing solutions between transits.

While this strategy provides a means to calibrate timing offsets, it provides little control over target-calibrator sky separations. As such, the geometric and dispersive delays have to be disentangled by fringe-fitting, with wide priors on the differential ionosphere. Nonetheless, in Section 5, we show that it is still possible to achieve our localization precision specifications in most cases using this strategy. The concern over calibrator abundance has been relieved substantially by a direct VLBI survey performed on the CHIME-GBO baseline, as described in Section 4.2.1. Nevertheless, the clocking and data acquisition infrastructure already developed opens the possibility of future ancillary-science applications of the CHIME/FRB Outriggers.

### 4.4.2. In-beam Calibrators in Full-array Baseband Dumps

In the opposite extreme to the previous case, it is possible that continuum calibrators are sufficiently abundant that there would reliably be suitable sources in the same triggered baseband captures that contain our FRB targets. From the full-array baseband data, it is possible to phase the station arrays to any source within the field of view, meaning that the only additional data collection required would be to lengthen the duration of the captures to improve S/N.

One key advantage of this strategy is that the calibration observation is contemporaneous with the target observation, which completely eliminates the need to time transfer the calibration solution as well as any concern about time variability of the ionosphere. The primary drawback of this strategy is the limitations on the durations of the baseband captures, with 1.4 s being a hard limit, which causes several minutes of dead time in our ability to capture subsequent targets. This severely limits the S/N that can be achieved on the calibrators. Also problematic are data volumes, particularly for CHIME, where the 1024 feeds yield data at a rate higher than a tied-array beam by the same factor. Nonetheless, this strategy has already been found to be an effective calibration strategy on our shortest CHIME-KKO baseline, which has the weakest requirements on calibration sources due to the reduced ionosphere and fewer sources being resolved on the shorter baseline (M. Amiri et al. 2025).

S. Andrew et al. (2024) showed that this strategy is promising even on the CHIME-GBO baseline, where an average of about two sources can be detected in a 100 ms baseband capture. The modest source density makes this strategy vulnerable to Poisson fluctuations in the number of sources in the field of view during an FRB detection. Obtaining sufficiently high-S/N observations to calibrate requires lengthening the duration of the baseband captures, and even then does not always yield a calibration solution. This strategy is also insufficient to achieve very small target-calibrator separations, meaning, as in the previous strategy, fringe-fitting is required to separate the geometric and ionospheric delays. Nonetheless, when one of the brighter sources falls within the same field of view as a target, this strategy provides a convenient calibration.
### 4.4.3. Triggered Calibrator Follow-up

As discussed in Section 4.2.1, we now know that, on average, about 14 compact continuum calibrators are present in the CHIME field of view at any given time. However, detecting most of them requires a 1.4 s long observation (the maximum for the full-array baseband system), and obtaining the requisite $S/N_{\times} \approx 20$ for phase referencing requires substantially longer (e.g., 10–100 s).

This motivates a calibration strategy where we could use the low-latency FRB trigger to also trigger longer tracking beam observations of a previously verified continuum calibrator (A. B. Pearlman 2024). The tracking beams readily provide a longer integration and thus ample $S/N$. It would be feasible to start calibrator observations within tens of seconds of the target observation, limited primarily by the FRB dispersion delay and triggering latency. Using the on-site atomic clocks for time transfer of the calibration solution would still be necessary, but would incur negligible net clock error. Furthermore, with ~14 potential calibrators spread across CHIME's 120° long field of view, it would be possible to target sources within ~10° of the target, minimizing differences in the line-of-sight sTEC. We show in Section 5 that the resulting narrow prior on the ionosphere leads to substantial gains in localization precision, even for narrow-band sources.

However, the strategy requires a pre-survey to create a catalog of confirmed suitable calibrators to target, which, as mentioned above, is currently underway. In addition, the logistical implementation of this strategy is currently under development.

## 5. Forecasts

In this section we perform forecasts for the localization precision of the Outriggers for varying properties of target FRBs ($S/N$, band occupancy) as well as assumptions about the ionospheric TEC and our ability to remove its contribution through calibration. The goal of these forecasts is not to perfectly predict the performance of the array, as several uncertainties make this difficult prior to on-sky characterization of the system, which is beyond the scope of this work. Rather, given reasonable but simplistic assumptions about the performance of the system and magnitude of systematic errors, we aim for an approximate understanding of system performance, the impact of the various uncertainties and systematic errors, and the interplay between them.

For our forecasts, we calculate the full posterior distribution for fringe-fitting to Equation (5). Free parameters are the R.A. and decl. of the FRB ($\hat{n}^s$), with independent nuisance parameters for each of our three CHIME-Outrigger baselines for the differential clock delay ($\tau_{ab}^{cl} - \tau_{ab}^{cl}$) and the differential sTEC ($s\text{TEC}_{ab}^s - s\text{TEC}_{ab}^c$). We place priors on these nuisance parameters, as described in the following paragraphs. Details of the implementation are provided in Appendix B.

To place a prior on the differential sTEC nuisance parameters, we build a model for the distribution of these parameters by randomly sampling target and calibrator lines of sight from the International Reference Ionosphere (IRI; ISO 2022) model. Details of this procedure are provided in Appendix C, and we denote this as our fiducial model for the ionospheric priors. Sampling target and calibrator locations randomly from the field of view mimics calibration schemes

where sources are rare, such as those relying on pulsars (Section 4.4.1) or, on our longer baselines, when integration time is limited to the duration of full-array captures (Section 4.4.2).

In addition to the fiducial prior, we also consider two other cases. First, we envisage developing a calibration strategy or ionospheric measurement or modeling procedure that enables us to null or subtract 80% of the ionosphere on all baselines. For example, the strategy described in Section 4.4.3 could achieve target-calibrator separations of ~10°, which would null a large fraction of the ionospheric effects. In this scenario, we make the ionospheric priors 20% as wide as fiducial. Second, we consider the case where the ionosphere is dramatically stronger than in the IRI model, where we make our ionospheric priors a factor of 5 wider than in the fiducial case. Such an extreme case is unlikely, but can be viewed both as a worst-case scenario and as illustrative of the ability to fringe-fit for the ionosphere even without external constraints. These models define the priors $p(s\text{TEC}_a)$ used in Appendix B.

We also require a prior on the differential clock error on each baseline. For the CHIME-KKO baseline, where we have already determined that there is a high density of in-beam calibrators, we assume this error to be negligible. For the CHIME-GBO baseline, both sites have a hydrogen maser clock, and so we assume a Gaussian distributed prior on the clock offsets with a standard deviation of 100 ps. For CHIME-HCRO, where one site has only a rubidium clock, we assume that the clock offsets have a standard deviation of 200 ps.

Finally, there will unavoidably be additional systematic error. For example, a differential beam phase could exist between the two stations. This has yet to be studied in detail, although there have been isolated rare cases of unexplained phase residuals of ~1 radian on the CHIME-KKO baseline at the top of the observing band. For simplicity, we model such systematics as an additional delay error with a standard deviation of 300 ps (corresponding to 1.5 radians at the top of the band), which is added in quadrature to the clock offsets described above. This, combined with the previous paragraph defines the Gaussian prior $p(\tau_a^{cl})$ used in Appendix B.

We consider FRBs that occupy 400, 200, and 100 MHz effective bandwidth, all assumed to be centered at CHIME's band center of 600 MHz. We parameterize the FRB brightness by $S/N_{\text{CHIME}}$, the $S/N$ as seen by CHIME alone. We assume that the cross-correlation $S/N_{\times}$ is $S/N_{\text{CHIME}}/\sqrt{8}$ for the CHIME-KKO baselines and $S/N_{\text{CHIME}}/\sqrt{4}$ for the CHIME-GBO and CHIME-HCRO baselines (from Equation (3)). These assumptions neglect the fact that each site has RFI bands that do not overlap perfectly (we defer study of this effect to future work).

For simplicity, we assume that on each baseline, a calibrator with $S/N_{\times,c} = 20$ is observed. Note that this implies that a net brighter calibrator is observed for the less-sensitive CHIME-KKO baseline; however, calibrators have been found to be abundant on the short baseline. As such, for the phase-referenced visibilities $(S/N_{\times,sc})^{-2} = (S/N_{\times,s})^{-2} + (S/N_{\times,c})^{-2}$.

We assume that the $S/N$ is evenly distributed across the full band occupied by the FRB. Targets are assumed to be observed at CHIME's zenith, which affects the baseline projections but not signal strength, since we are parameterizing FRBs using $S/N_{\text{CHIME}}$.
<figure><img src="image_8.png" /><figcaption>**Figure 5.** Forecasted localization region for FRBs with three combinations of bandwidth occupancy, signal-to-noise ratio (S/N), and assumptions about the impact of the ionosphere. In each case, parameters are listed above the figure. Left panel: we forecast that we achieve our localization precision goal of 50 mas for fairly typical FRBs with S/N<sub>CHIME</sub> = 20 filling the observing band and fringe-fitting for the differential sTEC in our fiducial ionosphere model. Center panel: even at lower S/N<sub>CHIME</sub> and an ionosphere five times thicker than our fiducial model, the wideband fringe fits yields reasonably good localizations. Right panel: for a narrowband FRB, precise localization requires a calibration that nulls 80% of the ionosphere.</figcaption></figure>

<figure><img src="image_9.png" /><figcaption>**Figure 6.** Localization forecasts for the CHIME/FRB Outriggers. Forecasts are provided as a function of FRB band occupancy (see the text above the left, center, and right panels), and S/N as observed by CHIME. We show three different scenarios for the ionosphere: (1) our fiducial ionospheric prior model where we must fringe-fit for the differential sTEC between targets and calibrators randomly drawn from the field of view; (2) a scenario where we find nearby calibrators that allow us to null 80% of the ionospheric contribution; and (3) a scenario where the ionosphere is 5 times thicker than in our fiducial model widening the prior distribution by a factor of 5. We forecast that we will achieve our localization goal of ~50 mas precision in both dimensions for all band-filling FRBs except under the most pessimistic assumptions, and that even narrowband FRBs can be localized provided the majority of the ionosphere can be nulled.</figcaption></figure>

Full localization posterior distributions are shown in Figure 5 for three permutations of the band occupancies, S/Ns, and ionospheric scenarios considered. Several features are apparent: the localization ellipses have roughly the 3–1 aspect ratio expected from the ratio of baseline lengths involving the GBO and HCRO stations (whose information dominates over that from KKO). The orientation is as expected for GBO’s location to the east and south of CHIME. When the full bandwidth is available, distinct lobes are visible and are associated with local likelihood maxima in the fringe-fit for delay and sTEC. These are less pronounced in narrower-band observations. The overall envelopes of the localizations are set by a combination of the width of the ionospheric prior and S/N.

As summary statistics for the localization uncertainty, we use the standard deviations of the R.A. and decl., which, given our array geometry, are only slightly misaligned with the major and minor axes of the localization envelope. This is plotted for all FRB properties and ionospheric scenarios considered in Figure 6. Note that in our model, the distributions of the data errors and nuisance parameters are

all symmetric and centered at zero, so there is no net bias in the localizations.

We see that for band-filling FRBs, the fringe-fit is able to distinguish between the nondispersive delays that contain localization information and dispersive delays from the ionosphere, roughly reaching our ~50 mas precision target even for modest S/N and very pessimistic assumptions about the ionosphere. We note that band-filling FRBs represent 85% of CHIME/FRB sources (K. R. Sand et al. 2025), and that narrowband FRBs are preferentially repeaters, providing multiple opportunities to localize (V. Shah et al. 2025).

In all cases, our localization in the RA direction is far less sensitive to ionospheric assumptions than the decl. direction. This is likely because the CHIME–KKO baseline, which is predominantly EW but short enough that it experiences negligible differential sTEC, provides a prior on the RA localization that is mostly independent of the ionosphere. This breaks the degeneracy between dispersive and nondispersive delays in the CHIME–GBO fringe-fit, i.e., the baseline picks a lobe of an otherwise degenerate localization. This is more effective in wider band observations where these lobes are more pronounced.
Developing a calibration strategy that removes the majority of the ionospheric contribution (such as that described in Section 4.4.3) would allow us to significantly exceed our precision targets. The 20% TEC case in Figure 6 shows that in this scenario, localization precision quickly hits its systematic-error floor even at modest S/N, presenting opportunities to achieve even higher precision should those systematics (clock error and beam phase) be mitigated.

## 6. Current Status and Outlook

At the time of writing (mid-2025), the CHIME/FRB Outriggers project has made significant strides toward achieving its scientific goals. All three Outriggers are fully constructed, operational, and producing early science results.

Construction of the KKO station was completed in the summer of 2022. Since then, it has been collecting valuable data, including baseband captures of FRBs. The commissioning phase, which extended through to the summer of 2023, demonstrated the station's instrument performance and scientific capabilities as shown by A. E. Lanman et al. (2024b). Follow-up and analysis of the initial data from KKO are ongoing, with early results indicating promising avenues for further research (S. Andrew et al. 2024; A. E. Lanman et al. 2024a; M. Amiri et al. 2025; Y. Dong et al. 2025; T. Eftekhari et al. 2025; V. Shah et al. 2025).

Construction of the GBO station was completed in spring of 2023. Since becoming operational, it too has consistently been gathering data. The GBO station is now operating reliably, successfully detecting and localizing both pulsars and FRBs. The first results from the station where presented by A. P. Curtin et al. (2025).

After an extensive local permitting process, the HCRO station saw the completion of its telescope structure and reflector in the summer of 2024, which was followed by deployment of the analog instrumentation. Deployment of the digital instrumentation occurred in early 2025, with first light achieved shortly thereafter. While commissioning of the station is ongoing, first results from the full Outriggers array where presented by CHIME/FRB Collaboration et al. (2025). That work, in addition to its scientific findings, showcases the detailed follow-up enabled by 2D localizations (P. K. Blanchard et al. 2025).

Tests that verify KKO's performance were developed by A. E. Lanman et al. (2024b). Replicating these for the full network is currently underway, and will be a key step toward transitioning to science operations. Chief among these tests is the localization of roughly 100 single pulses from about 20 distinct pulsars as if they were FRBs. Comparing these to externally measured pulsar positions provides a means to characterize the end-to-end localization performance. This will in turn provide confidence in the robustness of our localizations and their uncertainties.

In terms of the observational capabilities described in Section 4.3, both the $N^2$ system and the full-array baseband captures have been deployed and are in use. The tied-array beams are still in active development. Our forecasts in Section 5 have shown that nulling as much of the ionosphere as possible is critical for localization precision, especially for narrowband FRBs. As such, the deployment of observational capabilities to access fainter calibrators that are closer to target FRBs will provide a substantial boost to our localization precision.

Looking ahead, the CHIME/FRB Outriggers project is set to make substantial contributions to the field of FRB research. With the completion of all three stations, the project will localize a large fraction of CHIME-detected FRBs, enabling both detailed studies of rare sources and the statistical analysis of FRB properties and their host environments. Continued efforts to refine calibration techniques will further improve localization accuracy, addressing challenges posed by ionospheric variations and other systematic errors. With the bulk commissioning having occurred near solar maximum, and upcoming operations to take place during a period of declining solar activity, dealing with the ionosphere (one of our biggest challenges) will become progressively easier. As such, we expect the performance of the Outriggers to continue to improve over the coming months and years.

The data collected by the CHIME/FRB Outriggers will be instrumental in advancing our understanding of the origins, environments, and characteristics of FRBs. Collaborative efforts with other observatories and research initiatives will amplify the scientific impact of the project. Overall, the CHIME/FRB Outriggers project is poised to become a leading contributor to FRB research, providing valuable insights and paving the way for future discoveries in astrophysics.

## Acknowledgments

We acknowledge that CHIME and the KKO are built on the traditional, ancestral, and unceded territory of the Syilx Okanagan people. k'niʔatn k'l_stk'masqt is situated on land leased from the Imperial Metals Corporation. We are grateful to the staff of the Dominion Radio Astrophysical Observatory, which is operated by the National Research Council of Canada. CHIME operations are funded by a grant from the NSERC Alliance Program and by support from McGill University, University of British Columbia, and University of Toronto. CHIME/FRB Outriggers are funded by a grant from the Gordon & Betty Moore Foundation. We are grateful to Robert Kirshner for early support and encouragement of the CHIME/FRB Outriggers Project, and to Dusan Pejakovic of the Moore Foundation for continued support. CHIME was funded by a grant from the Canada Foundation for Innovation (CFI) 2012 Leading Edge Fund (Project 31170) and by contributions from the provinces of British Columbia, Québec, and Ontario. The CHIME/FRB Project was funded by a grant from the CFI 2015 Innovation Fund (Project 33213) and by contributions from the provinces of British Columbia and Québec, and by the Dunlap Institute for Astronomy and Astrophysics at the University of Toronto. Additional support was provided by the Canadian Institute for Advanced Research (CIFAR), the Trottier Space Institute at McGill University, and the University of British Columbia. The CHIME/FRB baseband recording system is funded in part by a CFI John R. Evans Leaders Fund award to I.H.S. Additionally, B.C.A. is supported by a Fonds de Recherche du QuébecNature et Technologies (FRQNT) Doctoral Research Award. FRB research at WVU is supported by an NSF grant (2006548, 2018490). M.B. is a McWilliams fellow and an International Astronomical Union Gruber fellow. M.B. also receives support from the McWilliams seed grant. A.P.C. is a Vanier Canada Graduate Scholar. M.D. is supported by a CRC Chair, NSERC Discovery Grant, and CIFAR. F.A.D. is supported by an NRAO Jansky Fellowship. G.M.E. is supported by NSERC Discovery Grant and by a Collaborative Resaerch Team grant
from the Canadian Statistical Sciences Institute, which is supported by NSERC. E.F. is supported by an NSF grant (2407399). J.W.T.H. and the AstroFlash research group acknowledge support from a Canada Excellence Research Chair in Transient Astrophysics (CERC-2022-00009); the European Research Council (ERC) under the European Unions Horizon 2020 research and innovation program ("EuroFlash"; grant agreement No. 101098079); and an NWO-Vici grant ("AstroFlash"; VI.C.192.045). V.M.K. holds the Lorne Trottier Chair in Astrophysics & Cosmology, a Distinguished James McGill Professorship, and receives support from an NSERC Discovery grant (RGPIN 228738-13). A.W.K.L. is a Dunlap postdoctoral fellow. The Dunlap Institute is funded through an endowment established by the David Dunlap family and the University of Toronto. C.L. is supported by a Miller Fellowship in the Departments of Astronomy and Physics at UC Berkeley. K.W.M. holds the Adam J. Burgasser Chair in Astrophysics and is supported by an NSF grant (2018490). J.M.P. acknowledges the support of an NSERC Discovery Grant (RGPIN-2023-05373). D.M. acknowledges support from the French government under the France 2030 investment plan, as part of the Initiative d'Excellence d'Aix-Marseille Université—A*MIDEX (AMX-23-CEI-088). K.N. is an MIT Kavli Fellow. A.P. is funded by the NSERC Canada Graduate Scholarships—Doctoral program. A.B.P. is a Banting Fellow, a McGill Space Institute (MSI) Fellow, and a Fonds de Recherche du Quebec—Nature et Technologies (FRQNT) postdoctoral fellow. Z.P. is supported by an NWO Veni fellowship (VI.Veni.222.295). M.W.S. acknowledges support from the Trottier Space Institute Fellowship program. K.R.S is supported by a Fonds de Recherche du Quebec—Nature et Technologies (FRQNT) Doctoral Research Award. P.S. acknowledges the support of an NSERC Discovery Grant (RGPIN-2024-06266). V.S. is supported by a Fonds de Recherche du QuebecNature et Technologies (FRQNT) Doctoral Research Award. K.S. is supported by the NSF Graduate Research Fellowship Program. J.L.S. is supported by the Canada-150 program. FRB work at UBC is supported by the Canadian Institute for Advanced Research and an NSERC Discovery Grant. The baseband recorder on the CHIME telescope is funded in part by a Canada Foundation for Innovation John R. Evans Lesaders Fund grant to I.H.S. Additionally, J.W. is supported by the United States Space Force under an MIT Lincoln Laboratory Military Fellowship.

# Appendix A
## Effect of Frequency-dependent Observation Time for Dispersed Pulses

We consider the primary effect of Earth's rotation during the observation, showing that the additional information therein is hard to exploit and, therefore, solidifying the need for at least two baselines.

Due to the substantial dispersive time-sweep of FRBs, one can ask whether Earth rotation aperture synthesis can provide any 2D information on a single baseline. To consider this, take the observation time to be the dispersed time-of-arrival of the FRB:

$$t = t_{\infty} + k_{\text{DM}} \text{DM}/\nu^2, \qquad (\text{A1})$$

where $t_{\infty}$ is the pulse time of arrival at infinite frequency, and $k_{\text{DM}} = (2.41 \times 10^{-4})^{-1} \text{s MHz}^2 \text{pc}^{-1} \text{cm}^3$. Then, Taylor

expanding our delay model, we have

$$\tau_{ab}(\hat{n}^s, \nu) \approx \tau_{ab}(\hat{n}^s, t_{\infty}) + \frac{k_{\text{DM}} \text{DM}}{\nu^2} \frac{\partial \tau_{ab}}{\partial t}(\hat{n}^s, t_{\infty}). \quad (\text{A2})$$

The first term above contains the vast majority of the delay and is primarily affected by the projection of the baseline onto the source directions $\vec{b}_{ab} \cdot \hat{n}^s/c$. The second term is affected by the small rotation of the baseline over the FRB's dispersive delay, and is roughly proportional to $(\vec{\omega} \times \vec{b}_{ab}) \cdot \hat{n}^s$, where $\vec{\omega}$ is Earth's angular velocity vector, and is thus sensitive to the component of $n^s$ orthogonal to the baseline. Unfortunately, this term has the same frequency dependence as the ionospheric slant TEC terms in Equation (5). As such, this information is degenerate in the fit with the TEC nuisance parameter. The priors on this nuisance parameter from globally available TEC maps are not sufficiently precise to place any meaningful constraints on the orthogonal component of the baseline.

# Appendix B
## Fringe-fit Forecast Formalism

Here we provide details of our localization forecast procedure. We start by simplifying our notation from Equation (5) with the following assumptions:

1. We consider only baselines containing the CHIME core array, such that the baseline can be enumerated with a single index $a$.

2. All observations are phase referenced to a calibration source observation such that the geometric delays, clock offsets, and slant TECs are understood to be differences between the target and calibrator observation.

3. We suppress all time dependence in the notation, as we treat all observations, of both target and calibrator, as instantaneous (although not necessarily simultaneous). In practice, the FRB observations are spread over the dispersion delay of several seconds, and the calibrator observation may be seconds in duration. However, clock error and ionospheric variability on second timescales is assumed to be negligible.

4. We assume that the uncertainties on the phase-referenced visibilities are Gaussian distributed (instead of the more accurate Chi-squared), with the S/N equally distributed over the band.

5. The data are converted to units such that the amplitude is unity, and the uncertainty is $\sigma_{av}^2 = N_{\{\nu\}}/(S/N_a)^2$, where $N_{\{\nu\}}$ is the number of frequency bins.

With these changes to notation, our signal model becomes:

$$V_a = \exp\{i2\pi\nu[\tau_a(\hat{n}^s) + \tau_a^{\text{cl}} + \kappa \text{sTEC}_a/\nu^2]\} \quad (\text{B1})$$

and our data model is:

$$d_a(\nu) = V_a^T(\nu) + \epsilon_a(\nu) \qquad (\text{B2})$$

$$\langle \epsilon_a(\nu) \rangle = 0 \qquad (\text{B3})$$

$$\langle \epsilon_a(\nu) \epsilon_a(\nu)^* \rangle = \sigma_{av}^2, \qquad (\text{B4})$$

where $V_a^T(\nu)$ is the signal model evaluated at the true values of the parameters, and $\epsilon_a$ denotes the Gaussian noise on the visibilities.
The fringe-fit localization problem is a matter of fitting our signal model to our data for parameters $\hat{n}^s$ while marginalizing over nuisance parameters $\tau_a^{\text{cl}}$ and sTEC$_a$, for which we will typically have some prior (see, e.g., Appendix C). The challenge is the fairly high-dimensional parameter space (two localization parameters plus two nuisance parameters per baseline, for eight total parameters) coupled with the poorly behaved likelihood due to the periodic nature of the signal model, yielding a multimodal parameter space. However, we will show that marginalizing over the nuisance parameters can be reduced to a series of size 1D integrals, which vastly simplifies the calculation.

The log-likelihood can be related to the familiar $\chi^2$ statistic

$$ -2 \log \mathcal{L}(\hat{n}^s, \{\lambda_\mu\}) \propto \chi^2(\hat{n}^s, \{\lambda_\mu\}) \\ = \sum_{a\nu} \frac{|d_a(\nu) - V_a(\nu, \hat{n}^s, \{\lambda_\mu\})|^2}{\sigma_{a\nu}^2}, \qquad (B5) $$

where $\{\lambda_\mu\}$ represents the set of all nuisance parameters, and the sum runs over all baselines and frequencies. With some manipulation, this becomes (dropping any terms that do not depend on the parameters)

$$ \chi^2(\hat{n}^s, \{\lambda_\mu\}) = -2 \sum_{a\nu} \frac{\Re\{d_a(\nu) V_a(\nu)^*\}}{\sigma_{a\nu}^2} \qquad (B6) $$

$$ = -2 \sum_{a\nu} \frac{1}{\sigma_{a\nu}^2} \Re\{d_a(\nu) \exp[-i2\pi\nu(\tau_a(\hat{n}^s) + \tau_a^{\text{cl}} + \kappa \text{sTEC}_a/\nu^2)]\}. \qquad (B7) $$

Assuming the nuisance parameters to be independent, the posterior for the full parameter space is

$$ p(\hat{n}^s, \{\lambda_\mu\}|\{d_a(\nu)\}) \propto \exp\left(-\frac{\chi^2(\hat{n}^s, \{\lambda_\mu\})}{2}\right) p(\hat{n}^s) \prod_\mu p(\lambda_\mu). \qquad (B8) $$

The final marginalized posterior we would like to calculate is

$$ p(\hat{n}^s|\{d_a(\nu)\}) \propto \int \exp\left[-\frac{\chi^2(\hat{n}^s, \{\lambda_\mu\})}{2}\right] \times p(\hat{n}^s) \prod_\mu p(\lambda_\mu)d\lambda_\mu. \qquad (B9) $$

We see from Equation (B6) that each baseline has its own nuisance parameters such that they can nearly be thought of as separate fitting problems, with the only coupling between baselines through $\tau_a(\hat{n}^s)$. To break the problem apart, we define the baseline-by-baseline $\chi_a^2$ and intermediate parameters $\tilde{\tau}_a$:

$$ \chi_a^2 = -2 \sum_{\nu} \frac{1}{\sigma_{a\nu}^2} \Re\{d_a(\nu) \exp[-i2\pi\nu(\tilde{\tau}_a + \tau_a^{\text{cl}} + \kappa \text{sTEC}_a/\nu^2)]\}. \qquad (B10) $$

With this definition, the posterior for the intermediate parameters is:

$$ p(\tilde{\tau}_a|d_a(\nu)) \propto \int d\tau_a^{\text{cl}} d(\text{sTEC}_a) \times \exp\left[-\frac{\chi_a^2(\tilde{\tau}_a, \tau_a^{\text{cl}}, \text{sTEC}_a)}{2}\right] p(\tau_a^{\text{cl}}) p(\text{sTEC}_a) \qquad (B11) $$

$$ \propto \int d\tau_a^{\text{cl}} p(\tau_a^{\text{cl}}) \int d(\text{sTEC}_a) \times \exp\left[-\frac{\chi_a^2(\tilde{\tau}_a + \tau_a^{\text{cl}}, \text{sTEC}_a)}{2}\right] p(\text{sTEC}_a). \qquad (B12) $$

In the second line (in a slight abuse of functional notation), we have written $\chi_a^2$ as a function of $\tilde{\tau}_a + \tau_a^{\text{cl}}$ to indicate that it only depends on the sum of the two delays. After some rearrangement, this makes it clear that the outer integral is a convolution, which can be computed efficiently using Fourier methods.

The full posterior is then

$$ p(\hat{n}^s|\{d_a(\nu)\}) \propto \prod_a \int d\tilde{\tau}_a p[\tilde{\tau}_a|d_a(\nu)] \delta[\tilde{\tau}_a - \tau_a(\hat{n}^s)] \qquad (B13) $$

$$ \propto \prod_a p[\tilde{\tau}_a = \tau_a(\hat{n}^s)|d_a(\nu)]. \qquad (B14) $$

With the posterior specified, what remains is to convert it to a forecast on parameters $\hat{n}^s$. One possible method is to construct an estimator for the parameters (e.g., maximum of the posterior or its expectation value) and draw many realizations of the data errors ($\epsilon_a(\nu)$) and nuisance parameters ($\tau_a^{\text{cl}}$ and sTEC$_a$) from their expected distributions to see how the estimator is distributed via Monte Carlo methods. Another approach is to fix the data errors and nuisance parameter values and use the shape of the posterior itself to represent the uncertainty. Via Bayes' theorem, these should be roughly equivalent, and we choose to do the latter. Because we don't expect the shape of the posterior to depend strongly on the exact realization, we choose $\epsilon_a(\nu) = \tau_a^{\text{cl}} = \text{sTEC}_a = 0$, which centers our posterior on the true value of $\hat{n}^s$.

# Appendix C

## Model for the Differential Slant TEC Prior

We build a simple statistical model for the ionosphere based on the International Reference Ionosphere (IRI; ISO 2022) model, which we then use as a prior on the sTEC nuisance parameters. Note that we are not assuming that the IRI accurately predicts the sTEC as seen by the Outriggers, only that sampling from it yields similar statistics as the real ionosphere. The IRI model is chosen because of the convenience of available tools for evaluating it. While many ionospheric models exist, our loose requirement of only representing the distribution of sTEC values makes the IRI sufficient for our purposes. We will also consider scenarios that are both more optimistic and pessimistic by making the sTEC prior distributions narrower and wider when determining the localization uncertainty. Our procedure for building the model is as follows:
<figure><img src="image_10.png" /><figcaption>**Figure 7.** Samples from the IRI used to build our sTEC priors. We sample the sTEC at each site toward random sky locations for targets and calibrators within the CHIME field of view and at random times. We then calculated the double-difference sTEC between the target and the calibrator and between the two telescope sites for each baseline. The figure shows histograms of these differential sTEC values for each baseline, as specified above each of the three panels. Finally, the fitted Student's-t distribution that we use for the sTEC priors in our forecasts is over plotted, with the fit parameters listed in the legend.</figcaption></figure>

1. We draw times randomly between 2023 January 1, and 2024 January 1.

2. At each time, we randomly select a target and calibrator sky location from the CHIME meridian within 60° of CHIME zenith, roughly mimicking CHIME's field of view.

3. We evaluate the IRI model to determine the slant TEC toward the target and the calibrator at CHIME and each Outrigger.

4. We calculate “double-difference” slant TEC (sTEC<sub>ab</sub><sup>s</sup> - sTEC<sub>ab</sub><sup>c</sup>) between each Outrigger and CHIME and between the target and calibrator.

5. We draw many samples, and for each Outrigger fit a distribution to the double-difference slant TEC. We find that Student's-t distribution (which, compared to a Gaussian, has much higher kurtosis) provides a reasonable fit to the distribution after fitting for the degrees-of-freedom parameter v and scale parameter s. The samples and fits are shown in Figure 7.

6. The fitted distributions are used as a baseline-dependent prior on the differential slant TEC nuisance parameters.

We note that the sampled dates are close to solar maximum, whereas the bulk of Outrigger operations will occur during a period of declining solar activity, building some conservatism into this model.

Note that in this procedure, the calibrator and target lines of sight are sampled at the same time, whereas in some calibration procedures, there could be a significant time separation, over which the ionosphere might evolve. However, we expect that the large span of angular separations between the target and the calibrator is the dominant contribution to the differential sTEC, and that this procedure generates a fairly representative distribution.

In our forecasts, we also consider variations on this model, where the distributions are assumed to be either 5 times wider or 20% as wide. The former is deliberately extreme and has little physical basis. The latter, narrower prior, is intended to roughly approximate the case where calibrators are much more abundant. Instead of having a single calibrator over the 120° field of view for a typical target-calibrator separation of ~60°, we envisage ~10° separations being achieved. While we do not know how the differential sTEC scales with angular separation (and the IRI model does not capture small scales), we consider it plausible that moving from ~60° to ~10° separations could result in a fivefold decrease.

## ORCID iDs

Bridget C. Andersen https://orcid.org/0000-0001-5908-3152

Shion Andrew https://orcid.org/0000-0002-3980-815X

Kevin Bandura https://orcid.org/0000-0003-3772-2798

Mohit Bhardwaj https://orcid.org/0000-0002-3615-3514

Kalyani Bhopi https://orcid.org/0000-0002-9218-1624

Vadym Bidula https://orcid.org/0009-0008-9653-6104

P. J. Boyle https://orcid.org/0000-0001-8537-9299

Charanjot Brar https://orcid.org/0000-0002-1800-8233

Mark Carlson https://orcid.org/0009-0001-7664-5142

Tomas Cassanelli https://orcid.org/0000-0003-2047-5276

Alyssa Cassity https://orcid.org/0009-0007-0757-9800

Shami Chatterjee https://orcid.org/0000-0002-2878-1502

Jean-François Cliche https://orcid.org/0000-0001-6509-8430

Alice P. Curtin https://orcid.org/0000-0002-8376-1563

Rachel Darlinger https://orcid.org/0000-0001-7674-5066

David R. DeBoer https://orcid.org/0000-0003-3197-2294

Matt Dobbs https://orcid.org/0000-0001-7166-6422

Fengqiu Adam Dong https://orcid.org/0000-0003-4098-5222

Gwendolyn Eadie https://orcid.org/0000-0003-3734-8177

Emmanuel Fonseca https://orcid.org/0000-0001-8384-5049

B. M. Gaensler https://orcid.org/0000-0002-3382-9558

Nina Gusinskaia https://orcid.org/0000-0001-6128-3735

Mark Halpern https://orcid.org/0000-0002-1760-0868

Ian Hendricksen https://orcid.org/0009-0003-3736-2080

Jason Hessels https://orcid.org/0000-0003-2317-1446

Ronniy C. Joseph https://orcid.org/0000-0003-3457-4670

Jane Kaczmarek https://orcid.org/0000-0003-4810-7803

Victoria M. Kaspi https://orcid.org/0000-0001-9345-0307

Kholoud Khairy https://orcid.org/0009-0005-7115-3447

T. L. Landecker https://orcid.org/0000-0003-1455-2546

Adam E. Lanman https://orcid.org/0000-0003-2116-3573

Albert Wai Kit Lau https://orcid.org/0000-0002-2457-3298

Mattias Lazda https://orcid.org/0000-0002-5857-4264

Calvin Leung https://orcid.org/0000-0002-4209-7408

Robert A. Main https://orcid.org/0000-0002-7164-9507

Kiyoshi W. Masui https://orcid.org/0000-0002-4279-6946

Ryan Mckinven https://orcid.org/0000-0001-7348-6900

Juan Mena-Parra https://orcid.org/0000-0002-0772-9326

Bradley W. Meyers https://orcid.org/0000-0001-8845-1225

Daniele Michilli https://orcid.org/0000-0002-2551-7554

Nikola Milutinovic https://orcid.org/0000-0001-8292-0051
Kenzie Nimmo https://orcid.org/0000-0003-0510-0740

Gavin Noble https://orcid.org/0000-0002-5254-243X

Ayush Pandhi https://orcid.org/0000-0002-8897-1973

Aaron B. Pearlman https://orcid.org/0000-0002-8912-0732

Jeffrey B. Peterson https://orcid.org/0000-0003-1340-818X

Emily Petroff https://orcid.org/0000-0002-9822-8008

Ziggy Pleunis https://orcid.org/0000-0002-4795-697X

Alexander W. Pollak https://orcid.org/0000-0002-3430-7671

Masoud Rafiei-Ravandi https://orcid.org/0000-0001-7694-6650

Andre Renard https://orcid.org/0000-0003-3463-7918

Mawson W. Sammons https://orcid.org/0000-0002-4623-5329

Ketan R. Sand https://orcid.org/0000-0003-3154-3676

Pranav Sanghavi https://orcid.org/0000-0001-5504-229X

Paul Scholz https://orcid.org/0000-0002-7374-7119

Vishwangi Shah https://orcid.org/0000-0002-4823-1946

Kaitlyn Shin https://orcid.org/0000-0002-6823-2073

Seth R. Siegel https://orcid.org/0000-0003-2631-6217

Andrew Siemion https://orcid.org/0000-0003-2828-7720

Jonathan L. Sievers https://orcid.org/0000-0001-6903-5074

Kendrick Smith https://orcid.org/0000-0002-2088-3125

David Spear https://orcid.org/0009-0003-6054-8035

Ingrid Stairs https://orcid.org/0000-0001-9784-8670

Keith Vanderlinde https://orcid.org/0000-0003-4535-9378

Haochen Wang https://orcid.org/0000-0002-1491-3738

Jacob P. Willis https://orcid.org/0000-0002-4560-5316

Tarik J. Zegmott https://orcid.org/0000-0002-7076-8643

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