On the Origin of the Variety of Velocity Dispersion Profiles of Galaxies
Abstract:
Observed and simulated galaxies exhibit a significant variation in their velocity dispersion profiles. We examine the inner and outer slopes of stellar velocity dispersion profiles using integral field spectroscopy data from two surveys, SAMI (for z < 0.115) and CALIFA (for z < 0.03), comparing them with results from two cosmological hydrodynamic simulations: Horizon-AGN (for z = 0.017) and NewHorizon (for z ≲ 1). The simulated galaxies closely reproduce the variety of velocity dispersion slopes and stellar mass dependence of both inner and outer radii (0.5 r 50 and 3 r 50) as observed, where r 50 stands for half-light radius. The inner slopes are mainly influenced by the relative radial distribution of the young and old stars formed in situ: a younger center shows a flatter inner profile. The presence of accreted (ex situ) stars has two effects on the velocity dispersion profiles. First, because they are more dispersed in spatial and velocity distributions compared to in situ formed stars, it increases the outer slope of the velocity dispersion profile. It also causes the velocity anisotropy to be more radial. More massive galaxies have a higher fraction of stars formed ex situ and hence show a higher slope in outer velocity dispersion profile and a higher degree of radial anisotropy. The diversity in the outer velocity dispersion profiles reflects the diverse assembly histories among galaxies.Widespread AGN feedback in a forming brightest cluster galaxy at z = 4.1, unveiled by JWST
A precise symbolic emulator of the linear matter power spectrum
Abstract:
Context. Computing the matter power spectrum, P(k), as a function of cosmological parameters can be prohibitively slow in cosmological analyses, hence emulating this calculation is desirable. Previous analytic approximations are insufficiently accurate for modern applications, so black-box, uninterpretable emulators are often used.
Aims. We aim to construct an efficient, differentiable, interpretable, symbolic emulator for the redshift zero linear matter power spectrum which achieves sub-percent level accuracy. We also wish to obtain a simple analytic expression to convert As to σ8 given the other cosmological parameters.
Methods. We utilise an efficient genetic programming based symbolic regression framework to explore the space of potential mathematical expressions which can approximate the power spectrum and σ8. We learn the ratio between an existing low-accuracy fitting function for P(k) and that obtained by solving the Boltzmann equations and thus still incorporate the physics which motivated this earlier approximation.
Results. We obtain an analytic approximation to the linear power spectrum with a root mean squared fractional error of 0.2% between k = 9 × 10−3 − 9 h Mpc−1 and across a wide range of cosmological parameters, and we provide physical interpretations for various terms in the expression. Our analytic approximation is 950 times faster to evaluate than CAMB and 36 times faster than the neural network based matter power spectrum emulator BACCO. We also provide a simple analytic approximation for σ8 with a similar accuracy, with a root mean squared fractional error of just 0.1% when evaluated across the same range of cosmologies. This function is easily invertible to obtain As as a function of σ8 and the other cosmological parameters, if preferred.
Conclusions. It is possible to obtain symbolic approximations to a seemingly complex function at a precision required for current and future cosmological analyses without resorting to deep-learning techniques, thus avoiding their black-box nature and large number of parameters. Our emulator will be usable long after the codes on which numerical approximations are built become outdated.