相关论文: A deep-learning algorithm to disentangle self-inte…
The interpretation of dark matter direct detection experiments is complicated by the fact that neither the astrophysical distribution of dark matter nor the properties of its particle physics interactions with nuclei are known in detail. To…
The lack of tangible evidence for non-gravitational interactions between dark and visible sectors drives the need for exploring new avenues of inferring dark matter properties through purely gravitational probes. In particular, addressing…
The next generation of cosmology surveys will probe the matter distribution of the universe to unparalleled precision. To match this level of precision in cosmological parameter estimation, we need to use information at small scales of…
Direct evidence for the existence of dark matter and measurements of its interaction cross-section have been provided by the physical offset between dark matter and intra- cluster gas in merging systems like the Bullet Cluster. Although a…
We present a new method to estimate redshift distributions and galaxy-dark matter bias parameters using correlation functions in a fully data driven and self-consistent manner. Unlike other machine learning, template, or correlation…
Self-interacting dark matter offers an interesting alternative to collisionless dark matter because of its ability to preserve the large-scale success of the cold dark matter model, while seemingly solving its challenges on small scales. We…
Merging galaxy clusters have been touted as one of the best probes for constraining self-interacting dark matter, but few simulations exist to back up this claim. We simulate equal mass mergers of 10$^{15}$ M$_\odot$ halos, like the El…
For a galaxy, given its observed rotation curve, can one directly infer parameters of the dark matter density profile (such as dark matter particle mass $m$, scaling parameter $s$, core-to-envelope transition radius $r_t$ and NFW scale…
Self-interacting dark matter (SIDM) arises generically in scenarios for physics beyond the Standard Model that have dark sectors with light mediators or strong dynamics. The self-interactions allow energy and momentum transport through…
We assess whether intracluster light (ICL) can serve as an observational discriminator of dark matter physics. The self-interacting dark matter (SIDM) model has gained increasing attention as a possible resolution to small-scale…
We analyze strongly lensed images in 8 galaxy clusters to measure their dark matter density profiles in the radial region between 10 kpc and 150 kpc, and use this to constrain the self-interaction cross section of dark matter (DM)…
Dark matter (DM) with self-interactions is a promising solution for the small-scale problems of the standard cosmological model. Here we perform the first cosmological simulation of frequent DM self-interactions, corresponding to…
The clustering of matter on cosmological scales is an essential probe for studying the physical origin and composition of our Universe. To date, most of the direct studies have focused on shear-shear weak lensing correlations, but it is…
The idea of Dark Matter (DM) with self interaction was invoked to resolve a number of discrepancies between the simulation based predictions by collisionless cold DM and the astrophysical observations on galactic and subgalactic scales.…
To fully take advantage of the data provided by large-scale structure surveys, we need to quantify the potential impact of baryonic effects, such as feedback from active galactic nuclei (AGN) and star formation, on cosmological observables.…
The distribution of offsets between the brightest cluster galaxies of galaxy clusters and the centroid of their dark matter distributions is a promising probe of the underlying dark matter physics. In particular, since this distribution is…
When a dark matter halo moves through a background of dark matter particles, self-interactions can lead to both deceleration and evaporation of the halo and thus shift its centroid relative to the collisionless stars and galaxies. We study…
We demonstrate the potential of Deep Learning methods for measurements of cosmological parameters from density fields, focusing on the extraction of non-Gaussian information. We consider weak lensing mass maps as our dataset. We aim for our…
Tens of thousands of galaxy-galaxy strong lensing systems are expected to be discovered by the end of the decade. These will form a vast new dataset that can be used to probe subgalactic dark matter structures through its gravitational…
A grand challenge of the 21st century cosmology is to accurately estimate the cosmological parameters of our Universe. A major approach to estimating the cosmological parameters is to use the large-scale matter distribution of the Universe.…