Challenges to a sharp change in $G$ as a solution to the Hubble tension
Symmetry in Hyper Suprime-Cam Galaxy Spin Directions
Abstract:
We perform a Bayesian analysis of anisotropy in binary galaxy spin directions in the Hyper-Suprime Cam Data Release 3 catalog, in response to a recent claim that it exhibits a dipole. We find no significant evidence for anisotropy, or for a direction-independent spin probability that differs from 0.5. These results are unchanged allowing for a quadrupole or simply searching for a fixed anisotropy between any two hemispheres, and the Bayes factor indicates decisive evidence for the isotropic model. Our principled method contrasts with the statistic employed by Shamir, which lacks a strong theoretical foundation. Our code is available at ✎.Evaluating the variance of individual halo properties in constrained cosmological simulations
No evidence for anisotropy in galaxy spin directions
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.