Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 87 tok/s
Gemini 2.5 Pro 51 tok/s Pro
GPT-5 Medium 17 tok/s Pro
GPT-5 High 23 tok/s Pro
GPT-4o 102 tok/s Pro
Kimi K2 166 tok/s Pro
GPT OSS 120B 436 tok/s Pro
Claude Sonnet 4 37 tok/s Pro
2000 character limit reached

Enhancing Bispectrum Estimators for Galaxy Redshift Surveys with Velocities (2303.05535v2)

Published 9 Mar 2023 in astro-ph.CO, hep-ph, and hep-th

Abstract: We forecast the ability of bispectrum estimators to constrain primordial non-Gaussianity using future photometric galaxy redshift surveys. A full-sky survey with photometric redshift resolution of $\sigma_z/(1+z)=0.05$ in the redshift range $0.2<z<2$ can provide constraints $\sigma(f\mathrm{local}_\mathrm{NL})=3.4$, $\sigma(f\mathrm{equil}_\mathrm{NL})=15$, and $\sigma(f\mathrm{orth}_\mathrm{NL})=17$ for the local, equilateral, and orthogonal shapes respectively, delivering constraints on primordial non-Gaussianities competitive to those from the cosmic microwave background. We generalize these results by deriving a scaling relation for the constraints on the amplitude of primordial non-Gaussianity as a function of redshift error, depth, sky coverage, and nonlinear scale cutoff. Finally, we investigate the impact that photometric calibration errors on the largest scales will have on the constraining power of future experiments. We show that peculiar velocities reconstructed via kinetic Sunyaev Zeldovich tomography can be used to mitigate the impact of calibration errors on primordial non-Gaussianity constraints.

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube