Related papers: Model independent calibrations of gamma ray bursts…
Testing the $\Lambda$CDM model requires cosmological probes spanning the wide redshift interval between Type Ia Supernovae (SNe Ia, $z\lesssim2.9$) and the Cosmic Microwave Background (CMB, $z\approx1100$). Gamma-Ray Bursts (GRBs), observed…
Making mock simulated catalogs is an important component of astrophysical data analysis. Selection criteria for observed astronomical objects are often too complicated to be derived from first principles. However the existence of an…
Computer models, aiming at simulating a complex real system, are often calibrated in the light of data to improve performance. Standard calibration methods assume that the optimal values of calibration parameters are invariant to the model…
The machine learning (ML) techniques to predict unitarity (UNI) and bounded from below (BFB) constraints in multi-scalar models is employed. The effectiveness of this approach is demonstrated by applying it to the two and three Higgs…
We introduce a novel methodology for addressing systematic uncertainties in unbinned inclusive cross-section measurements and related collider-based inference problems. Our approach incorporates known analytic dependencies on parameters of…
We present the constraints on the cosmological parameters obtained with the $E_{\rm peak}$--$E_{\gamma}$ correlation found with the most recent sample of 19 GRBs with spectroscopically measured redshift and well determined prompt emission…
We present single and binary black hole simulations that follow the moving puncture paradigm of simulating black-hole spacetimes without excision, and use moving boxes mesh refinement. Focussing on binary black hole configurations where the…
We have developed a machine learning algorithm capable of detecting ``out-of-domain data'' for trustworthy cosmological inference. By using data from two separate suites of cosmological simulations, we show that our algorithm is able to…
Accurate prediction of atmospheric optical turbulence in localized environments is essential for estimating the performance of free-space optical systems. Macro-meteorological models developed to predict turbulent effects in one environment…
In this work, our focus is on exploring the potential of current GRB measurements to provide reliable constraints on cosmological model parameters at high redshift. This work is divided into two parts. First, we calibrate the Amati relation…
Analyzes of next-generation galaxy data require accurate treatment of systematic effects such as the bias between observed galaxies and the underlying matter density field. However, proposed models of the phenomenon are either numerically…
Strongly lensed quasar systems with time delay measurements provide "time delay distances", which are a combination of three angular diameter distances and serve as powerful tools to determine the Hubble constant $H_0$. However, current…
A new method to constrain the cosmological equation of state is proposed by using combined samples of gamma-ray bursts (GRBs) and supernovae (SNeIa). The Chevallier-Polarski-Linder parameterization is adopted for the equation of state in…
Tight constraints on cosmological parameters can be obtained with standard candles spanning a range of redshifts as large as possible. We propose to treat SN Ia and long Gamma-Ray Bursts (GRBs) as a single class of candles. Taking advantage…
The recent extension of the Hubble diagram of Supernovae and quasars to redshifts much higher than 1 prompted a revived interest in non-parametric approaches to test cosmological models and to measure the expansion rate of the Universe. In…
We apply a graybox machine-learning framework to model and control a qubit undergoing Markovian and non-Markovian dynamics from environmental noise. The approach combines physics-informed equations with a lightweight transformer neural…
As datasets used in scientific applications become more complex, studying the geometry and topology of data has become an increasingly prevalent part of the data analysis process. This can be seen for example with the growing interest in…
Gamma-ray bursts represent some of the most energetic and complex phenomena in the universe, characterized by highly variable light curves that often contain observational gaps. Reconstructing these light curves is essential for gaining…
Quantum computing architectures require an accurate and efficient description in terms of many-electron states. Recent implementations include quantum dot arrays, where the ground state of a multi q-bit system can be altered by voltages…
We constrain an interacting, holographic dark energy model, first proposed by two of us in [1], with observational data from supernovae, CMB shift, baryon acoustic oscillations, x-rays, and the Hubble rate. The growth function for this…