Optimizing the Roman Space Telescope High-Latitude Wide Area Survey for mitigating chromatic PSF effects on shear measurement
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2026
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Abstract
Abstract Chromatic point-spread-function (PSF) effects arise from differences between the spectral energy distributions (SEDs) of stars, used to model the PSF, and galaxies, used to measure shape distortions due to weak gravitational lensing, or shear. For the Roman Space Telescope, these effects can bias shear measurement and cosmological inference, making them an important systematic effect for shear calibration. These biases depend sensitively on survey design choices, particularly filter coverage and the availability of color information. In this work, we investigate how different Roman survey strategies affect the ability to mitigate chromatic PSF effects and whether residual biases in shear propagate into cosmological inference. We quantify residual shear calibration biases for four-, three-, two-, and single-band survey configurations under representative and non-representative training assumptions and propagate these biases into Markov Chain Monte Carlo analyses of cosmic shear and 3 × 2-point statistics. We find that three- and four-band strategies can reduce residual shear biases to |m| ≲ 10−3, lowering the induced shifts in the lensing amplitude from ΔS8 ~ 0.6σ (cosmic shear) and ΔS8 ~ 0.9σ (3 × 2-pt) in the uncorrected case to ΔS8 ≲ 0.1σ. Single-band surveys perform worse than some multi-band configurations, with residual shear biases reaching or exceeding |m| ~ 2 × 10−3 in some tomographic bins. Average, sample-wide corrections reduce but do not eliminate chromatic systematics, leaving residual biases of ΔS8 ~ 0.13 − 0.23σ. Overall, our results demonstrate that we can robustly correct for these effects in the recommended Roman three-band medium tier, but may encounter residual biases in Roman’s single-band wide tier.
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| Authors | Federico Berlfein, Rachel Mandelbaum, Jiachuan Xu, Tianqing Zhang |
| Journal | monthly notices of the royal astronomical society |
| Year | 2026 |
| DOI |
10.1093/mnras/stag1032
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| URL | |
| Keywords | Keywords not found |
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