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1.
Phys Rev Lett ; 132(20): 201002, 2024 May 17.
Artículo en Inglés | MEDLINE | ID: mdl-38829077

RESUMEN

Cosmology offers opportunities to test dark matter independently of its interactions with the standard model. We study the imprints of long-range forces acting solely in the dark sector on the distribution of galaxies, the so-called large scale structure (LSS). We derive the strongest constraint on such forces from a combination of Planck and BOSS data. Along the way we consistently develop, for the first time, the effective field theory of LSS in the presence of new dynamics in the dark sector. We forecast that future surveys will improve the current bound by an order of magnitude.

2.
Phys Rev Lett ; 131(11): 111201, 2023 Sep 15.
Artículo en Inglés | MEDLINE | ID: mdl-37774263

RESUMEN

The large scale limit of the galaxy power spectrum provides a unique window into the early Universe through a possible detection of scale dependent bias produced by primordial non Gaussianities. On such large scales, relativistic effects could become important and be confused for a primordial signal. In this Letter we provide the first consistent estimate of such effects in the observed galaxy power spectrum, and discuss their possible degeneracy with local primordial non Gaussianities. We also clarify the physical differences between the two signatures, as revealed by their different sensitivity to the large scale gravitational potential. Our results indicate that, while relativistic effects could easily account for 10% of the observed power spectrum, the subset of those with a similar scale dependence to a primordial signal can be safely ignored for current galaxy surveys, but it will become relevant for future observational programs.

3.
Phys Rev Lett ; 121(10): 101301, 2018 Sep 07.
Artículo en Inglés | MEDLINE | ID: mdl-30240255

RESUMEN

We develop a new method to constrain primordial non-Gaussianities of the local kind using unclustered tracers of the large scale structure. We show that, in the limit of low noise, zero bias tracers yield large improvement over standard methods, mostly due to vanishing sampling variance. We propose a simple technique to construct such a tracer, using environmental information obtained from the original sample and validate our method with N-body simulations. Our results indicate that σ_{f_{NL}^{loc}}≃1 can be reached using only information on a single tracer of sufficiently high number density.

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