From the 1 of 7 linked papers with an AI index.
7 papers
CutClean: Neural Network Pruning for Privacy-Preserving Inference
Leonardo Magliolo, Vito Paolo Pastore, Giuseppe Valenzise +1
Neural networks are increasingly deployed in high-stakes applications with growing privacy leakage concerns. We show that this privacy leakage can occur even in the absence of repr…
DESI DR2 Results IV: Alcock-Paczyński Measurements from the Lyman Alpha Forest and Cosmological Constraints
DESI Collaboration, A. G. Adame, J. Aguilar +164
The DESI DR2 analysis measures the Alcock‑Paczynski effect using the full shape of Lyman‑α forest auto‑ and cross‑correlations, achieving 1% precision at redshift 2.33 and providin…
Small-scale Lyman alpha forest cosmology with PRIYA: Constraints from XQ100 and KODIAQ-SQUAD one-dimensional flux power spectra
Ming-Feng Ho, Mahdi Qezlou, Simeon Bird +4
We present a new cosmological analysis of the small-scale Lyman alpha forest 1D flux power spectrum (P1D) using high-resolution quasar spectra from XQ100 and KODIAQ-SQUAD, interpre…
Design and optimization of neural networks for multifidelity cosmological emulation
Yanhui Yang, Simeon Bird, Ming-Feng Ho +1
Accurate and efficient simulation-based emulators are essential for interpreting cosmological survey data down to nonlinear scales. Multifidelity emulation techniques reduce simula…
Ten-dimensional neural network emulator for the nonlinear matter power spectrum
Yanhui Yang, Simeon Bird, Ming-Feng Ho +1
We present GokuNEmu, a ten-dimensional neural network emulator for the nonlinear matter power spectrum, designed to support next-generation cosmological analyses. Built on the Goku…
Ten-parameter simulation suite for cosmological emulation beyond CDM
Yanhui Yang, Simeon Bird, Ming-Feng Ho
We present Goku, a suite of cosmological -body simulations, and the corresponding 10-dimensional emulator, GokuEmu, for the nonlinear matter power spectrum. The simulations span…