Papers
Research papers from arXiv and related sources
Precedence-Constrained Decision Trees and Coverings
This work considers a number of optimization problems and reductive relations between them. The two main problems we are interested in are the \emph{Optimal Decision Tree} and \emph{Set Cover}. We ...
Michał Szyfelbein, Dariusz Dereniowski
Coherent Quantum Evaluation of Collider Amplitudes for Effective Field Theory Constraints
Precision measurements at electron-positron colliders provide stringent tests of the Standard Model and powerful probes of possible higher-dimensional interactions. We present a hybrid quantum-clas...
Yacine Haddad, Kaidi Xu, Vincent Croft, Jad C. Halimeh, Michele Grossi
Implications for PBH Dark Matter from a single Sub-Solar$\unicode{x2013}$GW Detection in LVK O1$\unicode{x2013}$O4
The detection of sub-solar mass black holes is a milestone of modern astrophysics as it would open a window either onto new stellar physics or could potentially unveil the nature of Dark Matter as ...
Alberto Magaraggia, Nico Cappelluti
Evolution of Cosmic Voids: Structure, Galaxies, and Dynamics
We investigate the structural, photometric, and dynamical evolution of cosmic voids and their galaxy populations from $z=2.09$ to the present, focusing on void size as a key evolutionary parameter....
Saeed Tavasoli
Testing models for fully and partially stripped low-mass stars with Gaia: Implications for hot subdwarfs, binary RR Lyrae, and black hole impostors
When low-mass ($\lesssim 2$ $M_{\odot}$) red giants lose their envelopes to a companion just before the helium flash, the resulting mass transfer can produce binaries hosting hot subdwarfs, horizon...
Pranav Nagarajan, Kareem El-Badry, Alexey Bobrick, Giuliano Iorio, Francisco Molina, Joris Vos, M...
Test-Time Training with KV Binding Is Secretly Linear Attention
Test-time training (TTT) with KV binding as sequence modeling layer is commonly interpreted as a form of online meta-learning that memorizes a key-value mapping at test time. However, our analysis ...
Junchen Liu, Sven Elflein, Or Litany, Zan Gojcic, Ruilong Li
Variants of Raviart-Thomas mixed elements for curved domains using straight-edged tetrahedra
A numerical study of tetrahedral Raviart-Thomas mixed finite element methods is presented in the solution of model second order boundary value problems posed in a curved spatial domain. An emphasis...
Vittoriano Ruas
Revisiting CPL with sign-switching density: to cross or not to cross the NECB
Recent DESI DR2 BAO measurements, when combined with CMB and SNeIa data, exhibit a $3.2σ$-$3.4σ$ preference for dynamical dark energy (DE) described by the CPL-parametrized equation of state. A par...
Mine Gökçen, Özgür Akarsu, Eleonora Di Valentino
A Novel Explicit Filter for the Approximate Deconvolution in Large-Eddy Simulation on General Unstructured Grids: A posteriori tests on highly stretched grids
Explicit filters play a pivotal role in the scale separation and numerical stability of advanced Large Eddy Simulation (LES) closures, such as dynamic eddy-viscosity or Approximate Deconvolution (A...
Mohammad Bagher Molaei, Ehsan Amani, Morteza Ghorbani
Neural network optimization strategies and the topography of the loss landscape
Neural networks are trained by optimizing multi-dimensional sets of fitting parameters on non-convex loss landscapes. Low-loss regions of the landscapes correspond to the parameter sets that perfor...
Jianneng Yu, Alexandre V. Morozov
RAMSES-MCR: A consistent multi-group treatment of cosmic rays physics in momentum-space with the RAMSES code
Cosmic rays (CRs) are known to play a key role in many astrophysical environments: they can modify shock dynamics, influence the thermochemistry and the ionization of the interstellar medium, regul...
Nimatou-Seydi Diallo, Yohan Dubois, Alexandre Marcowith, Joki Rosdahl, Benoît Commerçon
Quantum Approximate Optimization for Decoding of Low-Density Parity-Check Codes
Decoding Low-Density Parity-Check (LDPC) codes is a fundamental problem in coding theory, and Belief Propagation (BP) is one of the most popular methods for LDPC code decoding. However, BP may enco...
Krishnakanta Barik, Goutam Paul
Scalar Lie point symmetries of the Standard Model with one or two real gauge singlets
We present a classification of all scalar Lie point symmetries of the Standard Model with one or two real gauge-singlet scalars (SM+S and SM+2S). By analyzing the associated field equations, we ide...
M. Aa. Solberg
Rapid Primary Radiation Damage Resistance Assessment of Precipitation-Hardened Cu Alloys
This study establishes a direct correlation between in situ irradiation-induced property changes measured by transient grating spectroscopy (TGS) and the resulting microstructural damage in Cu-Cr-T...
Elena Botica-Artalejo, Gregory Wallace, Michael P. Short
Elementary local representation densities at all primes via lifting recursions
Let $p$ be a prime and let $L$ be a quadratic $\mathbb{Z}_p$-lattice with quadratic form $Q$. For $t\neq 0$ the local representation density $α_p(t;L)$ is the stable normalised growth of the congru...
Samuel Griffiths
Detecting Where Effects Occur by Testing Hypotheses in Order
Experimental evaluations of public policies often randomize a new intervention within many sites or blocks. After a report of an overall result -- statistically significant or not -- the natural qu...
Jake Bowers, David Kim, Nuole Chen
The no-hair theorems at work in the tidal disruption event AT2020afhd
Recently, the coprecession of both the accretion disk and the jet formed following the tidal disruption event associated with the optical transient AT2020afhd, driven by a supermassive black hole o...
Lorenzo Iorio
Is Multi-Distribution Learning as Easy as PAC Learning: Sharp Rates with Bounded Label Noise
Towards understanding the statistical complexity of learning from heterogeneous sources, we study the problem of multi-distribution learning. Given $k$ data sources, the goal is to output a classif...
Rafael Hanashiro, Abhishek Shetty, Patrick Jaillet
Empirically Calibrated Conditional Independence Tests
Conditional independence tests (CIT) are widely used for causal discovery and feature selection. Even with false discovery rate (FDR) control procedures, they often fail to provide frequentist guar...
Milleno Pan, Antoine de Mathelin, Wesley Tansey
HiSAC: Hierarchical Sparse Activation Compression for Ultra-long Sequence Modeling in Recommenders
Modern recommender systems leverage ultra-long user behavior sequences to capture dynamic preferences, but end-to-end modeling is infeasible in production due to latency and memory constraints. Whi...
Kun Yuan, Junyu Bi, Daixuan Cheng, Changfa Wu, Shuwen Xiao, Binbin Cao, Jian Wu, Yuning Jiang