From the 2 of 16 linked papers with an AI index.
16 papers
Exploring Hu-Sawicki-like modified gravity with Genetic Algorithms
Chiara De Leo, Elisa Fazzari, Matteo Martinelli +1
The paper uses genetic algorithms to generate and test Hu‑Sawicki‑like f(R) modified‑gravity models against current background cosmological observations, finding only modest deviat…
DESI constraints on two-field quintessence with exponential potentials
George Alestas, Marienza Caldarola, Indira Ocampo +2
The paper examines a dark‑energy model with two scalar fields having double‑exponential potentials that together behave like a single shallow potential, and tests its viability usi…
To CPL, or not to CPL? What we have not learned about the dark energy equation of state
Savvas Nesseris, Yashar Akrami, Glenn D. Starkman
We show that using a Taylor expansion for the dark energy equation-of-state parameter and limiting it to the zeroth and first-order terms, i.e., the so-called Chevallier-Polarski-L…
A calibration-free null test from anisotropic BAO
Domenico Sapone, Savvas Nesseris
Baryon acoustic oscillation (BAO) analyses usually report the anisotropic shift parameters and relative to a fiducial cosmology, and these quantitie…
Interpretable and physics-informed emulator for the linear matter power spectrum from machine learning
J. Bayron Orjuela-Quintana, Domenico Sapone, Savvas Nesseris
We present an interpretable emulator for the linear matter power spectrum (MPS) in the standard cosmological model CDM, constructed via a physics-informed symbolic regression f…
Astrometric constraints on stochastic gravitational wave background with neural networks
Marienza Caldarola, Gonzalo Morrás, Santiago Jaraba +3
Astrometric measurements provide a unique avenue for constraining the stochastic gravitational wave background (SGWB). In this work, we investigate the application of two neural ne…