宇宙学与河外天体物理

Scalar metric fluctuations generically source a spectrum of gravitational waves at second order in perturbation theory, poising gravitational wave experiments as potentially powerful probes of the small-scale curvature power spectrum. We…

We show that the nonperturbative decay of ultralight scalars into Abelian gauge bosons, recently proposed as a possible solution to the Hubble tension, produces a stochastic background of gravitational waves which is constrained by the…

We demonstrate that gravitational waves generated by efficient gauge preheating after axion inflation generically contribute significantly to the effective number of relativistic degrees of freedom $N_\mathrm{eff}$. We show that, with…

We study gravitational wave production from gauge preheating in a variety of inflationary models, detailing its dependence on both the energy scale and the shape of the potential. We show that preheating into Abelian gauge fields…

We study gravitational wave production during Abelian gauge-field preheating following inflation. We consider both scalar and pseudoscalar inflaton models coupled directly to Abelian gauge fields via either a dilatonic coupling to the…

It has been recently suggested that oscillons produced in the early universe from certain asymmetric potentials continue to emit gravitational waves for a number of $e$-folds of expansion after their formation, leading to potentially…

We present a framework that combines physics-informed neural networks (PINNs) with Markov Chain Monte Carlo (MCMC) inference to constrain dynamical dark energy models using the Pantheon+ Type Ia supernova compilation. First, we train a…

We perform a frequentist analysis using the standard profile likelihood method for clustering measurements from Data Release 1 of the Dark Energy Spectroscopic Instrument (DESI). While Bayesian inferences for Effective Field Theory models…

Constraints on local primordial non-Gaussianity (LPnG) obtained from galaxy power spectra are limited by the perfect degeneracy between the LPnG parameter $f_{\rm NL}$ and the bias parameter $b_{\phi}$ which encodes the response of galaxy…

Based on the Kolmogorov-Arnold Network (KAN), we present a novel emulator of the global 21 cm cosmology signal, $\texttt{21cmKAN}$, that provides extremely fast training speed while achieving nearly equivalent accuracy to the most accurate…

Modern machine learning techniques can unlock the vast cosmological information encoded in forthcoming Square Kilometre Array (SKA) observations. We show that tomographic 21 cm data from the reionisation era can yield stringent tests of…

The oscillation feature in primordial power spectrum (PPS), a fingerprint of not only a wide class of models of inflation but new physics, is of significant theoretical interest, and can be imprinted on the cosmic microwave background…

We present a strong lensing analysis and reconstruct the mass distribution of SPT-CL J0356-5337, a galaxy cluster at redshift z = 1.034. Our model supersedes previous models by making use of new multi-band HST data and MUSE spectroscopy. We…

Extragalactic foregrounds in cosmic microwave background (CMB) observations are both a source of cosmological and astrophysical information and a nuisance to the CMB. Effective field-level modeling that captures their non-Gaussian…

Recent analyses of cosmological hydrodynamic simulations from CAMELS have shown that machine learning models can predict the parameter describing the total matter content of the universe, $\Omega_{\rm m}$, from the features of a single…

Motivated by the morphological measures in assessing the geometrical and topological properties of a generic cosmological stochastic field, we propose an extension of the weighted morphological measures, specifically the $n$th conditional…

We present a new code and approach, JERALD -- JAX Enhanced Resolution Approximate Lagrangian Dynamics -- , that improves on and extends the Lagrangian Deep Learning method of Dai & Seljak (2021), producing high-resolution dark matter,…

We introduce a new method designed for Bayesian inference of the angular power spectrum of the Gravitational Wave Background (GWB) anisotropy. This scheme works with time-series data and can optionally incorporate the cross-correlations…

A precise measurement of photometric redshifts (photo-z) is key for the success of modern photometric galaxy surveys. Machine learning (ML) methods show great promise in this context, but suffer from covariate shift (CS) in training sets…

In the last decade, the study of the overall shape of the universe, called Cosmic Topology, has become testable by astronomical observations, especially the data from the Cosmic Microwave Background (hereafter CMB) obtained by WMAP and…