分类： 天文学 >> 天文学 提交时间： 2023-02-19
Yun Wang
Zhongxu Zhai
Anahita Alavi
Elena Massara
Alice Pisani
Andrew Benson
Christopher M. Hirata
Lado Samushia
David H. Weinberg
James Colbert
Olivier Doré
Tim Eifler
Chen Heinrich
Shirley Ho
Elisabeth Krause
Nikhil Padmanabhan
David Spergel
Harry I. Teplitz
摘要： The Nancy Grace Roman Space Telescope will conduct a High Latitude Spectroscopic Survey (HLSS) over a large volume at high redshift, using the near-IR grism (1.0-1.93 $\mu$m, $R=435-865$) and the 0.28 deg$^2$ wide field camera. We present a reference HLSS which maps 2000 deg$^2$ and achieves an emission line flux limit of 10$^{-16}$ erg/s/cm$^2$ at 6.5$\sigma$, requiring $\sim$0.6 yrs of observing time. We summarize the flowdown of the Roman science objectives to the science and technical requirements of the HLSS. We construct a mock redshift survey over the full HLSS volume by applying a semi-analytic galaxy formation model to a cosmological N-body simulation, and use this mock survey to create pixel-level simulations of 4 deg$^2$ of HLSS grism spectroscopy. We find that the reference HLSS would measure $\sim$ 10 million H$\alpha$ galaxy redshifts that densely map large scale structure at $z=1-2$ and 2 million [OIII] galaxy redshifts that sparsely map structures at $z=2-3$. We forecast the performance of this survey for measurements of the cosmic expansion history with baryon acoustic oscillations and the growth of large scale structure with redshift space distortions. We also study possible deviations from the reference design, and find that a deep HLSS at $f_{\rm line}>7\times10^{-17}$erg/s/cm$^2$ over 4000 deg$^2$ (requiring $\sim$1.5 yrs of observing time) provides the most compelling stand-alone constraints on dark energy from Roman alone. This provides a useful reference for future optimizations. The reference survey, simulated data sets, and forecasts presented here will inform community decisions on the final scope and design of the Roman HLSS.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： Relativistic and free-streaming particles like neutrinos leave imprints in large scale structures (LSS), providing probes of the effective number of neutrino species $N_{\rm eff}$. In this paper, we use the Fisher formalism to forecast $N_{\rm eff}$ constraints from the bispectrum (B) of LSS for current and future galaxy redshift surveys, specifically using information from the baryon acoustic oscillations (BAOs). Modeling the galaxy bispectrum at the tree-level, we find that adding the bispectrum constraints to current CMB constraints from Planck can improve upon the Planck-only constraints on $N_{\rm eff}$ by about 10\% -- 40\% depending on the survey. Compared to the Planck + power spectrum (P) constraints previously explored in the literature, using Planck+P+B provides a further improvement of about 5\% -- 30\%. Besides using BAO wiggles alone, we also explore using the total information which includes both the wiggles and the broadband information (which is subject to systematics challenges), generally yielding better results. Finally, we exploit the interference feature of the BAOs in the bispectrum to select a subset of triangles with the most information on $N_{\rm eff}$. This allows for the reduction of computational cost while keeping most of the information, as well as for circumventing some of the shortcomings of applying directly to the bispectrum the current wiggle extraction algorithm valid for the power spectrum. In sum, our study validates that the current Planck constraint on $N_{\rm eff}$ can be significantly improved with the aid of galaxy surveys before the next-generation CMB experiments like CMB-Stage 4.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： The next-generation CMB experiments are expected to constrain the
tensor-to-scalar ratio $r$ with high precision. Delensing is an important
process as the observed CMB $B$-mode polarization that contains the primordial
tensor perturbation signal is dominated by a much larger contribution due to
gravitational lensing. To do so successfully, it is useful to explore methods
for lensing reconstruction beyond the traditional quadratic estimator (QE)
(which will become suboptimal for the next-generation experiments), and the
maximum a posterior estimator (which is still currently under development). In
Caldeira et al. 2020, the authors showed that a neural network (NN) method
using the ResUNet architectrue performs better than the QE and slightly
suboptimally compared to the iterative estimator in terms of the lensing
reconstruction performance. In this work, we take one step further to evaluate
the delensing performance of these estimators on maps with primordial tensor
perturbations using a standard delensing pipeline, and show that the
\emph{delensing} performance of the NN estimator is optimal, agreeing with that
of a converged iterative estimator, when tested on a suite of simulations with
$r=0.01$ and $r=0.001$ for $12.7^{\circ} \times 12.7^{\circ}$ maps at a
CMB-Stage~4 like polarization noise level $1\,\mu \rm{K\,arcmin}$ and 1' beam.
We found that for the purpose of delensing, it is necessary to train and
evaluate the NN on a set of CMB maps with $l
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