REVIEW 3 cited by
Will Kinematic Sunyaev-Zel'dovich Measurements Enhance the Science Return from Galaxy Redshift Surveys?
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
abstract
Yes. Future CMB experiments such as Advanced ACTPol and CMB-S4 should achieve measurements with S/N of $> 0.1$ for the typical galaxies in redshift surveys. These measurements will provide complementary measurements of the growth rate of large scale structure $f$ and the expansion rate of the Universe $H$ to galaxy clustering measurements. This paper emphasizes that there is significant information in the anisotropy of the relative pairwise kSZ measurements. We expand the relative pairwise kSZ power spectrum in Legendre polynomials and consider up to its octopole. Assuming that the noise in the filtered maps is uncorrelated between the positions of galaxies in the survey, we derive a simple analytic form for the power spectrum covariance of the relative pairwise kSZ temperature in redshift space. While many previous studies have assumed optimistically that the optical depth of the galaxies $\tau_{\rm T}$ in the survey is known, we marginalize over $\tau_{\rm T}$, to compute constraints on the growth rate $f$ and the expansion rate $H$. For realistic sure parameters, we find that combining kSZ and galaxy redshift survey data reduces the marginalized $1$-$\sigma$ errors on $H$ and $f$ by $\sim50$-$70\%$ compared to the galaxy-only analysis.
Forward citations
Cited by 3 Pith papers
-
Fast(er)PM and Moving Mesh: JAX-native Geometric Multigrid Methods
Warm-started Chebyshev geometric multigrid is competitive with distributed FFTs for FastPM and enables a differentiable moving-mesh particle–mesh gravity solver in JAX.
-
Anomaly detection with spiking neural networks for LHC physics
Claims spiking neural network autoencoders are competitive with conventional autoencoders for LHC anomaly detection across all signal models tested.
-
CMB-S4 Science Case, Reference Design, and Project Plan
Presents the science case, reference design, and project plan for the CMB-S4 ground-based CMB experiment.
Discussion (0). Sign in to comment.