Fisher Forecasts for Cosmological Yields from $3\!\times\!2$pt Analysis of the Roman Space Telescope High Latitude Imaging Survey

[2601.00438] Fisher Forecasts for Cosmological Yields from $3\!\times\!2$pt Analysis of the Roman Space Telescope High Latitude Imaging Survey Skip to main content Search Submit Donate Log in Astrophysics > Cosmology and Nongalactic Astrophysics arXiv:2601.00438 (astro-ph) [Submitted on 1 Jan 2026 ( v1 ), last revised 26 Aug 2026 (this version, v2)] Title: Fisher Forecasts for Cosmological Yields from $3\!\times\!2$pt Analysis of the Roman Space Telescope High Latitude Imaging Survey Authors: Kaili Cao , David H. Weinberg , Vivian Miranda , Nihar Dalal , Tim Eifler , Jiachuan Xu , Haley Bowden , Katarina Markovič View PDF HTML (experimental) Abstract: The High Latitude Imaging Survey (HLIS) of NASA's Nancy Grace Roman Space Telescope will provide powerful tests of cosmological models through sensitive measurements of cosmic shear, galaxy-galaxy lensing (GGL), and galaxy clustering. As part of the HLIS Project Infrastructure Team's Data Challenge 1 (DC1), we carry out Fisher forecasts of cosmological parameter constraints from combinations of these probes, focusing on inverse-variance figures of merit (FoMs) for the parameters $\sigma_8$ and $\Omega_{\rm{m}}$, which scale the amplitude of weak lensing signals. We find good agreement between Fisher analysis and Markov chain Monte Carlo (MCMC) analysis of the DC1 baseline data vector, and we investigate varied priors on cosmological parameters and on nuisance parameters describing unknown biases in photometric redshifts or shear measurements. The DC1 benchmark modeling assumes a ``lens $=$ source'' analysis with linear galaxy bias and no marginalization over baryonic physics. Under these assumptions, the forecast constraints from GGL+clustering are substantially stronger than those from cosmic shear, with the combination of all three probes (``$3\!\times\!2$pt'') providing moderate further improvement. Adding tight external priors on the power spectrum shape parameters $n_{\rm{s}}$, $\Omega_{\rm{b}}$, and $h_0$ can improve the $(\sigma_8, \Omega_{\rm{m}})$ FoMs by factors of $1.2$--$3.5$. The smallest scale angular bins provide much more information than the largest scale bins, and the highest redshift tomographic bins provide more information than the lowest redshift bins. Factor-of-two changes in the priors on photo-$z$ and shear biases, relative to the benchmark values based on anticipated calibration accuracy, produce changes of $\lesssim 20\%$ in FoMs. Comments: 37 pages, 20 figures, 6 tables, matches version accepted for publication Subjects: Cosmology and Nongalactic Astrophysics (astro-ph.CO) Cite as: arXiv:2601.00438 [astro-ph.CO] (or arXiv:2601.00438v2 [astro-ph.CO] for this version) https://doi.org/10.48550/arXiv.2601.00438 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Kaili Cao [ view email ] [v1] Thu, 1 Jan 2026 19:00:01 UTC (4,521 KB) [v2] Wed, 26 Aug 2026 18:00:08 UTC (4,539 KB) Full-text links: Access Paper: View PDF HTML (experimental) TeX Source view license Current browse context: astro-ph.CO < prev | next > new | recent | 2026-01 Change to browse by: astro-ph References & Citations INSPIRE HEP SciX Google Scholar Semantic Scholar export BibTeX citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) IArxiv recommender toggle IArxiv Recommender ( What is IArxiv? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. 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