Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userBaryonic effects on the matter bispectrum
121
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
The large-scale clustering of matter is impacted by baryonic physics, particularly AGN feedback. Modelling or mitigating this impact will be essential for making full use of upcoming measurements of cosmic shear and other large-scale structure probes. We study baryonic effects on the matter bispectrum, using measurements from a selection of state-of-the-art hydrodynamical simulations: IllustrisTNG, Illustris, EAGLE, and BAHAMAS. We identify a low-redshift enhancement of the bispectrum, peaking at $ksim 3h,{rm Mpc}^{-1}$, that is present in several simulations, and discuss how it can be associated to the evolving nature of AGN feedback at late times. This enhancement does not appear in the matter power spectrum, and therefore represents a new source of degeneracy breaking between two- and three-point statistics. In addition, we provide physical interpretations for other aspects of these measurements, and make initial comparisons to predictions from perturbation theory, empirical fitting formulas, and the response function formalism. We publicly release our measurements (including estimates of their uncertainty due to sample variance) and bispectrum measurement code as resources for the community.
rate research
Read More
The cosmological simulations indicates that the dark matter haloes have specific self similar properties. However the halo similarity is affected by the baryonic feedback, the momentum injected by the supernovae re-shape the dark matter core and transform it to a flat density core, with a scale length imposed by the baryonic feedback. Additionally the baryon feedback impose also an equilibrium condition, which when coupled with the imposed baryonic scale length induce a new type of similarity. The new self similar solution implies that the acceleration generated by dark matter is scale free, which in turns implies that the baryonic acceleration at a reference radius is also scale free. Constant dark matter and baryonic accelerations at a reference radius have effectively been observed for a large class of different galaxies, which is in support of this approach. The new self similar properties implies that the total acceleration at larger distances is scale free, the transition between the dark matter and baryons dominated regime occurs at a constant acceleration, and the maximum of the velocity curve which defines the amplitude of the velocity curve at larger distances is proportional to $M^{frac{1}{4}}$. These results demonstrates that in this self similar model, cold dark matter is consistent with the basics of MOND phenomenology for the galaxies. In agreement with the observation the coincidence between the self similar model and MOND is expected to break at the scale of clusters of galaxies. Some numerical experiments shows that the behavior of the density near the origin is closely approximated by a Einasto profile.
We consider a dark matter halo (DMH) of a spherical galaxy as a Bose-Einstein condensate of the ultra-light axions interacting with the baryonic matter. In the mean-field limit, we have derived the integro-differential equation of the Hartree-Fock type for the spherically symmetrical wave function of the DMH component. This equation includes two independent dimensionless parameters: (i) b{eta}- the ratio of baryon and axion total mases and (ii) {xi}- the ratio of characteristic baryon and axion spatial parameters. We extended our dissipation algorithm for studying numerically the ground state of the axion halo in the gravitational field produced by the baryonic component. We calculated the characteristic size, Xc, of DMH as a function of b{eta} and {xi} and obtained an analytical approximation for Xc.
We demonstrate that baryonification algorithms, which displace particles in gravity-only simulations according to physically-motivated prescriptions, can simultaneously capture the impact of baryonic physics on the 2 and 3-point statistics of matter. Specifically, we show that our implementation of a baryonification algorithm jointly fits the changes induced by baryons on the power spectrum and equilateral bispectrum on scales up to k < 5 h/Mpc and redshifts z<2, as measured in six different cosmological hydrodynamical simulations. The accuracy of our fits are typically 1% for the power spectrum, and for the equilateral and squeezed bispectra, which somewhat degrades to 3% for simulations with extreme feedback prescriptions. Our results support the physical assumptions underlying baryonification approaches, and encourage their use in interpreting weak gravitational lensing and other cosmological observables.
Gravitational encounters between small-scale dark matter substructure and cold stellar streams in the Milky Way halo lead to density perturbations in the latter, making streams an effective probe for detecting dark matter substructure. The Pal 5 stream is one such system for which we have some of the best data. However, Pal 5 orbits close to the center of the Milky Way and has passed through the Galactic disk many times, where its structure can be perturbed by baryonic structures such as the Galactic bar and giant molecular clouds (GMCs). In order to understand how these baryonic structures affect Pal 5s density, we present a detailed study of the effects of the Galactic bar, spiral structure, GMCs, and globular clusters on the Pal 5 stream. We estimate the effect of each perturber on the stream density by computing its power spectrum and comparing it to the power induced by a CDM-like population of dark matter subhalos. We find that the bar and GMCs can each individually create power that is comparable to the observed power on large scales, leaving little room for dark matter substructure, while spirals are subdominant on all scales. On degree scales, the power induced by the bar is small, but GMCs create small-scale density variations that are similar in amplitude to the dark-matter induced variations but otherwise indistinguishable from it. These results demonstrate that Pal 5 is a poor system for constraining the dark matter substructure fraction and that observing streams further out in the halo will be necessary to confidently detect dark matter subhalos.
Many different studies have shown that a wealth of cosmological information resides on small, non-linear scales. Unfortunately, there are two challenges to overcome to utilize that information. First, we do not know the optimal estimator that will allow us to retrieve the maximum information. Second, baryonic effects impact that regime significantly and in a poorly understood manner. Ideally, we would like to use an estimator that extracts the maximum cosmological information while marginalizing over baryonic effects. In this work we show that neural networks can achieve that. We made use of data where the maximum amount of cosmological information is known: power spectra and 2D Gaussian density fields. We also contaminate the data with simplified baryonic effects and train neural networks to predict the value of the cosmological parameters. For this data, we show that neural networks can 1) extract the maximum available cosmological information, 2) marginalize over baryonic effects, and 3) extract cosmological information that is buried in the regime dominated by baryonic physics. We also show that neural networks learn the priors of the data they are trained on. We conclude that a promising strategy to maximize the scientific return of cosmological experiments is to train neural networks on state-of-the-art numerical simulations with different strengths and implementations of baryonic effects.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
