July 2023 arXiv papers

Juan M. Z. Pretel, Sergio E. Jorás, Ribamar R. R. Reis, Sergio B. Duarte

The macroscopic properties of compact stars in modified gravity theories can be significantly different from the general relativistic (GR) predictions. Within the gravitational context of scalar-tensor theories, with a scalar field $ϕ$ and coupling function $Φ(ϕ)= \exp[2ϕ/\sqrt{3}]$, we investigate the hydrostatic equilibrium structure of neutron stars for t

Julius Owusu

We develop randomization-based tests for heterogeneous treatment effects in the presence of network interference. Leveraging the exposure mapping framework, we study a broad class of null hypotheses that represent various forms of constant treatment effects in networked populations. These null hypotheses, unlike the classical Fisher sharp null, are not sharp

Niraj K. Nepal, Paul C. Canfield, Lin-Lin Wang

For Y$_2$C$_3$ with a superconducting critical temperature (T$_c$) $\sim$18 K, zone-center imaginary optical phonon modes have been found for the high-symmetry $I$-$43d$ structure due to C dimer wobbling motion and electronic instability from a flat band near Fermi energy. After lattice distortion to the more stable lowest symmetry $P1$ structure, these stab

Linsey K. Rodenbach, Jason M. Underwood, Ngoc Thanh Mai Tran, Alireza R. Panna

In the revised International System of Units (SI), the ohm and the volt are realized from the von Klitzing constant and the Josephson constant, and a practical realization of the ampere is possible by applying Ohm's law directly to the quantum Hall and Josephson effects. As a result, it is possible to create an instrument capable of realizing all three p

Vincent Moreau, Lê Thành Dũng Nguyên

A fundamental theme in automata theory is regular languages of words and trees, and their many equivalent definitions. Salvati has proposed a generalization to regular languages of simply typed $λ$-terms, defined using denotational semantics in finite sets. We provide here some evidence for its robustness. First, we give an equivalent syntactic characterizat

Cristina Gavazzoni, Carolina Brito, Matthieu Wyart

We study the glass transition by exploring a broad class of kinetic rules that can significantly modify the normal dynamics of super-cooled liquids, while maintaining thermal equilibrium. Beyond the usual dynamics of liquids, this class includes dynamics in which a fraction $(1-f_R)$ of the particles can perform pairwise exchange or 'swap moves', whi

Han Liu, Changhao Qin, Georgios Papangelakis, Meng Lon Iu

Entanglement and correlation of quantum light can enhance LiDAR sensitivity in the presence of strong background noise. However, the power of such quantum sources is fundamentally limited to a stream of single photons and cannot compete with the detection range of high-power classical LiDAR transmitters. To circumvent this, we develop and demonstrate a quant

Farhad Nawaz, Tianyu Li, Nikolai Matni, Nadia Figueroa

We propose a Dynamical System (DS) approach to learn complex, possibly periodic motion plans from kinesthetic demonstrations using Neural Ordinary Differential Equations (NODE). To ensure reactivity and robustness to disturbances, we propose a novel approach that selects a target point at each time step for the robot to follow, by combining tools from contro

Amílcar Branquinho, Juan EF Díaz, Ana Foulquié-Moreno, Manuel Mañas

This paper investigates stochastic finite matrices and the corresponding finite Markov chains constructed using recurrence matrices for general families of orthogonal polynomials and multiple orthogonal polynomials. The paper explores the spectral theory of transition matrices, utilizing both orthogonal and multiple orthogonal polynomials. Several properties

Lucas Soster Moriggi, Érison dos Santos Rocha, Magno Valério Trindade Machado

In the present work we investigate the source of azimuthal asymmetry for nuclear collision using a model that contemplates particles produced in the initial hard collisions and the collective effects described by a Blast-Wave like expansion. The latter is described by the relaxation time approximation of the Boltzmann transport equation. The parameters regar

Ruochu Yang, Chad Lembke, Fumin Zhang, Catherine Edwards

Underwater gliders have been widely used in oceanography for a range of applications. However, unpredictable events like shark strikes or remora attachments can lead to abnormal glider behavior or even loss of the instrument. This paper employs an anomaly detection algorithm to assess operational conditions of underwater gliders in the real-world ocean envir

Chowdhury Mohammad Sakib Anwar, Konstantinos Georgalos

Gallice and Monzón (2019) present a natural environment that sustains full co-operation in one-shot social dilemmas among a finite number of self-interested agents. They demonstrate that in a sequential public goods game, where agents lack knowledge of their position in the sequence but can observe some predecessors' actions, full contribution emerges in

Charlie Hou, Kiran Koshy Thekumparampil, Michael Shavlovsky, Giulia Fanti

On tabular data, a significant body of literature has shown that current deep learning (DL) models perform at best similarly to Gradient Boosted Decision Trees (GBDTs), while significantly underperforming them on outlier data. However, these works often study idealized problem settings which may fail to capture complexities of real-world scenarios. We identi

Nacira Agram, Bernt Øksendal, Frank Proske, Olena Tymoshenko

In this paper we study a Pontryagin type stochastic maximum principle for the optimal control of a system, where the state dynamics satisfy a stochastic partial differential equation (SPDE) driven by a two-parameter (time-space) Brownian motion (also called Brownian sheet). We first discuss some properties of a Brownian sheet driven linear SPDE which models

Zhichao Wang, Xin Zhou

We prove the $C^{1,1}$-regularity for stationary $C^{1,α}$ ($α\in(0,1)$) solutions to the multiple membrane problem. This regularity estimate was essentially used in our recent work on Yau's four minimal spheres conjecture.

Tornike Shubitidze, Wesley A. Britton, Luca Dal Negro

Recently, materials with vanishingly small permittivity, known as epsilon-near-zero (ENZ) media, emerged as promising candidates to achieve nonlinear optical effects of unprecedented magnitude on a solid-state platform. In particular, the ENZ behavior of Indium Tin Oxide (ITO) thin films resulted in Kerr-type nonlinearity with non-perturbative refractive ind

Brendon McConnell

The log transformation of the dependent variable is not innocuous when using a difference-in-differences (DD) model. With a dependent variable in logs, the DD term captures an approximation of the proportional difference in growth rates across groups. As I show with both simulations and two empirical examples, if the baseline outcome distributions are suffic

Seyed Samie Alizadeh Darbandi, Alex Fornito, Abdorasoul Ghasemi

Network control theory can be used to model how one should steer the brain between different states by driving a specific region with an input. The needed energy to control a network is often used to quantify its controllability, and controlling brain networks requires diverse energy depending on the selected input region. We use the theory of how input node

Serge Gladkoff, Lifeng Han, Gleb Erofeev, Irina Sorokina

Translation Quality Evaluation (TQE) is an essential step of the modern translation production process. TQE is critical in assessing both machine translation (MT) and human translation (HT) quality without reference translations. The ability to evaluate or even simply estimate the quality of translation automatically may open significant efficiency gains thr

Abdurrahman Elmaghbub, Vincent Immler, Bechir Hamdaoui

Deep learning-based RF fingerprinting offers great potential for improving the security robustness of various emerging wireless networks. Although much progress has been done in enhancing fingerprinting methods, the impact of device hardware stabilization and warm-up time on the achievable fingerprinting performances has not received adequate attention. As s

E. Kun, S. Britzen, S. Frey, K. É. Gabányi

In a previous work, we have identified the spin of the dominant black hole of a binary from its jet properties. Analysing Very Long Baseline Array (VLBA) observations of the quasar S5~1928+738, taken at $15$-GHz during $43$ epochs between $1995.96$ and $2013.06$, we showed that the inclination angle variation of the inner ($<2$~mas) jet symmetry axis natural

Yuta Michimura, Haoyu Wang, Francisco Salces-Carcoba, Christopher Wipf

Crystalline materials are promising candidates as substrates or high-reflective coatings of mirrors to reduce thermal noises in future laser interferometric gravitational wave detectors. However, birefringence of such materials could degrade the sensitivity of gravitational wave detectors, not only because it can introduce optical losses, but also because it

Liran Wang, Xunzhu Tang, Yichen He, Changyu Ren

Commit message generation (CMG) is a challenging task in automated software engineering that aims to generate natural language descriptions of code changes for commits. Previous methods all start from the modified code snippets, outputting commit messages through template-based, retrieval-based, or learning-based models. While these methods can summarize wha

David Gontier, Adechola E. K. Kouande, Éric Séré

In this paper we consider stationary states of the SSH model for infinite polyacetylene chains that are homoclinic or heteroclinic connections between two-periodic dimerized states. We prove that such connections converge exponentially fast to the corresponding asymptotic periodic states.

Sanjay Lall, Calin Cascaval, Martin Izzard, Tammo Spalink

We introduce logical synchrony, a framework that allows distributed computing to be coordinated as tightly as in synchronous systems without the distribution of a global clock or any reference to universal time. We develop a model of events called a logical synchrony network, in which nodes correspond to processors and every node has an associated local cloc

Shahaf Bassan, Guy Amir, Davide Corsi, Idan Refaeli

Deep neural networks (DNNs) are increasingly being used as controllers in reactive systems. However, DNNs are highly opaque, which renders it difficult to explain and justify their actions. To mitigate this issue, there has been a surge of interest in explainable AI (XAI) techniques, capable of pinpointing the input features that caused the DNN to act as it

Chester Holtz, Pengwen Chen, Alexander Cloninger, Chung-Kuan Cheng

Motivated by the need to address the degeneracy of canonical Laplace learning algorithms in low label rates, we propose to reformulate graph-based semi-supervised learning as a nonconvex generalization of a \emph{Trust-Region Subproblem} (TRS). This reformulation is motivated by the well-posedness of Laplacian eigenvectors in the limit of infinite unlabeled

Sinan Allak

This paper presents a comprehensive X-ray and multi-wavelength study of ultraluminous X-ray sources (ULXs) in NGC 1566 using archival Chandra, Swift/XRT, James Webb Space Telescope, JWST, and Hubble Space Telescope, HST observations. The main results are, first, from the hardness ratio diagram, where spectral state transitions from hard to soft as seen in ty

Zohreh Farmani, Nazanin Ghods, Harkirat Singh, Jing Wang

Slowly sheared particulate media like sand and suspensions flow heterogeneously as they yield via shear bands, in which most strain accumulates. Understanding shear band localization from microscopics is still a major challenge. One class of so-called non-local theories identified that the width of the shearing zone should depend on the stress field, in part

Qian Qin

This article studies the convergence properties of trans-dimensional MCMC algorithms when the total number of models is finite. It is shown that, for reversible and some non-reversible trans-dimensional Markov chains, under mild conditions, geometric convergence is guaranteed if the Markov chains associated with the within-model moves are geometrically ergod

Hemn Barzan Abdalla, Awder Ahmed, Bahtiyar Mehmed, Mehdi Gheisari

Online reviews play a crucial role in shaping consumer decisions, especially in the context of e-commerce. However, the quality and reliability of these reviews can vary significantly. Some reviews contain misleading or unhelpful information, such as advertisements, fake content, or irrelevant details. These issues pose significant challenges for recommendat

R. Seutin, O. J. Hernandez, T. Miyagi, S. Bacca

Many-body approaches for atomic nuclei generally rely on a basis expansion of the nuclear states, interactions, and current operators. In this work, we derive the representation of the magnetic dipole operator in plane-wave and harmonic-oscillator basis states, as needed for Faddeev calculations of few-body systems or many-body calculations within, e.g., the

Jeffrey W. Johnston

How to make artificial intelligence (AI) systems safe and aligned with human values is an open research question. Proposed solutions tend toward relying on human intervention in uncertain situations, learning human values and intentions through training or observation, providing off-switches, implementing isolation or simulation environments, or extrapolatin

Dženan Lapandić, Christos K. Verginis, Dimos V. Dimarogonas, Bo Wahlberg

We develop an algorithm to control an underactuated unmanned surface vehicle (USV) using kinodynamic motion planning with funnel control (KDF). KDF has two key components: motion planning used to generate trajectories with respect to kinodynamic constraints, and funnel control, also referred to as prescribed performance control, which enables trajectory trac

Yassine Ghannane, Mohamed S. Abdelfattah

Datacenters are increasingly becoming heterogeneous, and are starting to include specialized hardware for networking, video processing, and especially deep learning. To leverage the heterogeneous compute capability of modern datacenters, we develop an approach for compiler-level partitioning of deep neural networks (DNNs) onto multiple interconnected hardwar

David N. Pham, Fei Ye

Left-invariant Hermitian and Gauduchon connections are studied on an arbitrary Lie group $G$ equipped with an arbitrary left-invariant almost Hermitian structure $(\langle\cdot,\cdot\rangle,J)$. The space of left-invariant Hermitian connections is shown to be in one-to-one correspondence with the space $\wedge^{(1,1)}\mathfrak{g}^\ast\otimes \mathfrak{g}$ of

Bruno Ipaves, João F. Justo, Biplab Sanyal, Lucy V. C. Assali

In the present paper, we investigate the structural, thermodynamic, dynamic, elastic, and electronic properties of doped 2D diamond C$_4$X$_2$ (X = B or N) nanosheets in both AA$&#39;$A$&#39;&#39;$ and ABC stacking configurations, by first-principles calculations. Those systems are composed of 3 diamond-like graphene sheets, with an undoped graphene layer be

Chao Huang, Susan Liang, Yapeng Tian, Anurag Kumar

We propose DAVIS, a Diffusion-based Audio-VIsual Separation framework that solves the audio-visual sound source separation task through generative learning. Existing methods typically frame sound separation as a mask-based regression problem, achieving significant progress. However, they face limitations in capturing the complex data distribution required fo

Stewart N. Ethier, Jiyeon Lee

In a previous paper, we considered several models of the parlor game baccara chemin de fer, including Model B2 (a $2\times2^{484}$ matrix game) and Model B3 (a $2^5\times2^{484}$ matrix game), both of which depend on a positive-integer parameter $d$, the number of decks. The key to solving the game under Model B2 was what we called Foster&#39;s algorithm, wh

Valeri P. Frolov, Jose Pinedo Soto

In the present paper, we discuss a nonlocal modification of the Kerr metric. Our starting point is the Kerr-Schild form of the Kerr metric $g_{μν}=η_{μν}+Φl_μl_μ$. Using Newman&#39;s approach we identify a shear free null congruence $\boldsymbol{l}$ with the generators of the null cone with apex at a point $p$ in the complex space. The Kerr metric is obtaine

Sergey V. Astashkin, Per G. Nilsson

We investigate connections between upper/lower estimates for Banach lattices and the notion of relative s-decomposability, which has roots in interpolation theory. To get a characterization of relatively s-decomposable Banach lattices in terms of the above estimates, we assign to each Banach lattice X two sequence spaces XU and XL that are largely determined

Tatsuya Daniel, Marcell Howard, Morgane König

Cosmological gravitational wave backgrounds (CGWBs) are the conglomeration of unresolved gravitational wave signals from early Universe sources, which make them a promising tool for cosmologists. Because gravitons decouple from the cosmic plasma early on, one can consider interactions between gravitons and any particle species that were present in the very e

Claudio Bonati, Andrea Pelissetto, Ettore Vicari

We study the topological phase transitions occurring in three-dimensional (3D) multicomponent lattice Abelian-Higgs (LAH) models, in which an $N$-component scalar field is minimally coupled with a noncompact Abelian gauge field, with a global SU($N$) symmetry. Their phase diagram presents a high-temperature Coulomb (C) phase, and two low-temperature molecula

Juliana Coelho

We study the gonality of curves $C$ over $\mathbb C$ whose normalization is composed of one or two copies of $\mathbb P^1$. In the first case, $C$ is a nodal curve with $g(C)$ nodes, and in the second case $C$ is a so-called binary curve. In any case we show that the usual bound $\mathrm{gon}(C)\leq\lfloor\frac{g(C)+3}{2}\rfloor$ holds if $g(C)\geq 2$, with

Kacper Błachut, Tomasz Kowalczyk

We show that the Pythagoras number of rings of type $\mathbb{R}[x,y, \sqrt{f(x,y)}]$ is infinite, provided that the polynomial $f(x,y)$ satisfies some mild conditions.

Santiago Rojas-Rojas, Daniel Martínez, Kei Sawada, Luciano Pereira

With the advent of quantum technology, the interest in communication tasks assisted by quantum systems has increased both in academia and industry. Nonetheless, the transmission of a quantum state in real-world scenarios is bounded by environmental noise, so that the quantum channel is an open quantum system. In this work, we study a high-dimensional open qu

Jiuhong Xiao, Gao Zhu, Giuseppe Loianno

Visual Geo-localization (VG) is a critical research area for identifying geo-locations from visual inputs, particularly in autonomous navigation for robotics and vehicles. Current VG methods often learn feature extractors from geo-labeled images to create dense, geographically relevant representations. Recent advances in Self-Supervised Learning (SSL) have d

Francesco Bajardi, Salvatore Capozziello, Tiziana Di Salvo, Francesca Spinnato

We sketch the main features of the Noether Symmetry Approach, a method to reduce and solve dynamics of physical systems by selecting Noether symmetries, which correspond to conserved quantities. Specifically, we take into account the vanishing Lie derivative condition for general canonical Lagrangians to select symmetries. Furthermore, we extend the prescrip

Mehwish Alam, Frank van Harmelen, Maribel Acosta

Embedding based Knowledge Graph (KG) Completion has gained much attention over the past few years. Most of the current algorithms consider a KG as a multidirectional labeled graph and lack the ability to capture the semantics underlying the schematic information. In a separate development, a vast amount of information has been captured within the Large Langu

Robin Kenis, Emanuel Laude, Panagiotis Patrinos

In this paper we derive a moment relaxation for large-scale nonsmooth optimization problems with graphical structure and spherical constraints. In contrast to classical moment relaxations for global polynomial optimization that suffer from the curse of dimensionality we exploit the partially separable structure of the optimization problem to reduce the dimen

Haipeng An, Boye Su, Hanwen Tai, Lian-Tao Wang

The gravitational wave (GW) signal offers a promising window into the dynamics of the early universe. The recent results from the pulsar timing arrays (PTAs) could be the first glimpse of such new physics. In particular, they could point to new details during inflation, which can not be probed by other means. We explore the possibility that the new results c

Arpit Das, Chethan N. Gowdigere, Sunil Mukhi, Jagannath Santara

Studies of modular linear differential equations (MLDE) for the classification of rational CFT characters have been limited to the case where the coefficient functions (in monic form) have no poles, or poles at special points of moduli space. Here we initiate an exploration of the vast territory of MLDEs with two characters and any number of poles at arbitra

Jonathan M. Lilly, Joel Feske, Baylor Fox-Kemper, Jeffrey Early

The familiar divergence and Kelvin-Stokes theorem are generalized by a tensor-valued identity that relates the volume integral of the gradient of a vector field to the integral over the bounding surface of the outer product of the vector field with the exterior normal. The importance of this long-established yet little-known result is discussed. In flat two-

Alexandre Baraviera, Pedro Duarte, Longmei Shu, Maria Joana Torres

Isospectral reduction is an important tool for network/matrix analysis as it reduces the dimension of a matrix/network while preserving its eigenvalues and eigenvectors. The main contribution of this manuscript is a proposed algorithmic scheme to approximate the stationary measure of a stochastic matrix based on isospectral reductions. We run numerical exper

Henrik Beccard, Elke Beyreuther, Benjamin Kirbus, Samuel D. Seddon

For the last decade, conductive domain walls (CDWs) in single crystals of the uniaxial model ferroelectric lithium niobate (LiNbO$_3$, LNO) have shown to reach resistances more than 10 orders of magnitude lower as compared to the surrounding bulk, with charge carriers being firmly confined to sheets of a few nanometers in width. LNO thus currently witnesses

Markus Redeker

Number-conserving cellular automata are discrete dynamical systems that simulate interacting particles like e.g. grains of sand. In an earlier paper, I had already derived a uniform construction for all transition rules of one-dimensional number-conserving automata. Here I describe in greater detail how one can simulate the automata on a computer and how to

Abhijit B. Bendre, Jennifer Schober, Prasun Dhang, Kandaswamy Subramanian

We describe a novel method to compute the components of dynamo tensors from direct magnetohydrodynamic (MHD) simulations. Our method relies upon an extension and generalisation of the standard Högbom CLEAN algorithm widely used in radio astronomy to systematically remove the impact of the strongest beams onto the corresponding image. This generalisation, cal

Efstratios Koukoutsis, Kyriakos Hizanidis, Abhay K. Ram, George Vahala

In dispersive media, dissipation appears in the Schrödinger representation of classical Maxwell equations as a sparse diagonal operator occupying an $r$-dimensional subspace. A first order Suzuki-Trotter approximation for the evolution operator enables us to isolate the non-unitary operators (associated with dissipation) from the unitary operators (associate

Javier de la Bodega, Eduardo de Lorenzo Poza

In arXiv:1911.08213 it was conjectured that the compactly supported cohomology of the $m$-th restricted contact locus of an isolated hypersurface singularity coincides, up to a shift, with the Floer cohomology of the $m$-th iterate of the monodromy of the Milnor fiber. In this paper we give an affirmative answer to this conjecture in the case of plane curves

Ben Kain

Charged Dirac fields minimally coupled to gravity have spherically symmetric wormhole solutions known as Einstein-Dirac-Maxwell (EDM) wormholes. EDM wormholes do not make use of exotic matter and exist in asymptotically flat general relativity. We construct static spherically symmetric EDM wormhole configurations in quantum field theory using semiclassical a

Meredith Stone, Jianwei Lyu, George H. Rieke, Stacey Alberts

We characterize the stellar mass of J2239+0207, a z~6.25 sub-Eddington quasar (M_1450=-24.6), using dedicated JWST/NIRCam medium-band observations of a nearby PSF star to remove the central point source and reveal the underlying galaxy emission. We detect the host galaxy in two bands longward of the Balmer break, obtaining a stellar mass of ~10^10 M_sun, mor

Carl Lian

We consider the problem of enumerating maps $f$ of degree $d$ from a fixed general curve $C$ of genus $g$ to $\mathbb{P}^r$ satisfying incidence conditions of the form $f(p_i)\in X_i$, where $p_i\in C$ are general points and $X_i\subset\mathbb{P}^r$ are general linear spaces. We give a complete answer in the case where the $X_i$ are points, where the counts,

Abhirup Roy Karmakar, A. Taraphder, G. P. Das

The recent discovery of the Weyl semimetal CeAlSi with simultaneous breaking of inversion and time-reversal symmetries has opened up new avenues for research into the interaction between light and topologically protected bands. In this work, we present a comprehensive examination of the shift current and injection current responsible for the circular photoga

Giuseppe Scriva, Nikita Astrakhantsev, Sebastiano Pilati, Guglielmo Mazzola

Quantum enhanced optimization of classical cost functions is a central theme of quantum computing due to its high potential value in science and technology. The variational quantum eigensolver (VQE) and the quantum approximate optimization algorithm (QAOA) are popular variational approaches that are considered the most viable solutions in the noisy-intermedi

Roger Casals, Honghao Gao

We show that each cluster seed in the augmentation variety is inhabited by an embedded exact Lagrangian filling. This resolves the matter of surjectivity of the map from Lagrangian fillings to cluster seeds. The main new technique to produce these Lagrangian fillings is the construction and study of a quiver with potential associated to curve configurations.

Lukas J. Furtak, Ashish K. Meena, Erik Zackrisson, Adi Zitrin

We present JWST/NIRSpec observations of a highly magnified star candidate at a photometric redshift of $z_{\mathrm{phot}}\simeq4.8$, previously detected in JWST/NIRCam imaging of the strong lensing (SL) cluster MACS J0647+7015 ($z=0.591$). The spectroscopic observation allows us to precisely measure the redshift of the host arc at $z_{\mathrm{spec}}=4.758\pm

Alec Martin, Yicheng Guo, Xin Wang, Anton M. Koekemoer

Giant star-forming clumps are a prominent feature of star-forming galaxies (SFGs) and contain important clues on galaxy formation and evolution. However, basic demographics of clumps and their host galaxies remain uncertain. Using the HST/WFC3 F275W images from the Ultraviolet Imaging of the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (UVC

Matthew J. Blacker, Sirui Ning

We solve the Wheeler DeWitt equation for the planar Reissner-Nordström-AdS black hole in a minisuperspace approximation. We construct semiclassical Wheeler DeWitt states from Gaussian wavepackets that are peaked on classical black hole interior solutions. By using the metric component $g_{xx}$ as a clock, these states are evolved through both the exterior an

A. H. Anupam, Chandramouli Chowdhury, Ashoke Sen

We compute logarithmic correction to five dimensional BPS black hole entropy using finite temperature black hole geometry and find perfect agreement with the microscopic results and macroscopic computations based on zero temperature near horizon geometry. We also reproduce the Bekenstein-Hawking term for zero temperature black hole entropy from the correspon

Michele Maltoni

In this note we describe how to complement the neutrino evolution matrix calculated at a given energy and trajectory with additional information which allows to reliably extrapolate it to nearby energies or trajectories without repeating the full computation. Our method works for arbitrary matter density profiles, can be applied to any propagation model desc

Stefano De Angelis, Gauthier Durieux

We present a new on-shell method for the matching of ultraviolet models featuring massive states onto their massless effective field theory. We employ a dispersion relation in the space of complex momentum dilations to capture, in a single variable, the relevant analytic structure of scattering amplitudes at any multiplicity. Multi-variate complex analysis a

Diego Guadagnoli, Camille Normand, Silvano Simula, Ludovico Vittorio

$B_s \to μ^+ μ^- γ$, measured at high $q^2$ as a partially reconstructed decay, can probe the origin of the existing discrepancies in semi-leptonic $b \to s$ and $b \to c$ decays. We perform a complete study of this possibility. We start by reassessing the alleged discrepancies, with a focus on a unified EFT description. Using the SMEFT, we find that the tau

Vladimir Rosenhaus, Gregory Falkovich

We consider turbulence of waves that interact weakly via four-wave scattering (sea waves, plasma waves, spin waves, and many others). In the first non-vanishing order in the interaction, the occupation number of waves satisfy a closed kinetic equation which has stationary solutions describing turbulent cascades. We show that a straightforward perturbation th

Giorgio Franceschelli, Mirco Musolesi

Generative Artificial Intelligence (AI) is one of the most exciting developments in Computer Science of the last decade. At the same time, Reinforcement Learning (RL) has emerged as a very successful paradigm for a variety of machine learning tasks. In this survey, we discuss the state of the art, opportunities and open research questions in applying RL to g

Daniel Junghans

It has been proposed that flux compactifications of supercritical string theories (i.e., with spacetime dimension $D>10$) have dS vacua, with large $D$ acting as a control parameter for corrections to the classical spacetime effective action. In this paper, we provide a detailed analysis of the self-consistency of such models, focussing on $α^\prime$ and bac

Alessandro Candido, Stefano Forte, Tommaso Giani, Felix Hekhorn

We revisit our argument that shows that parton distribution Functions (PDFs) in the MSbar{ scheme are non-negative in the perturbative region, with the main goals of elucidating its domain of validity and clarifying its theoretical underpinnings. We specifically discuss recent results proving that PDFs can turn negative at sufficiently low scale, we clarify

Paul Caucal, Farid Salazar, Björn Schenke, Tomasz Stebel

We compute the back-to-back dijet cross-section in deep inelastic scattering (DIS) at small $x$ to next-to-leading order (NLO) in the Color Glass Condensate effective field theory. Our result can be factorized into a convolution of the Weizsäcker-Williams gluon transverse momentum dependent distribution function (WW gluon TMD) with a universal soft factor an

Vojtěch Witzany, Gabriel Andres Piovano

Rapidly rotating bodies moving in curved space-time experience the so-called spin-curvature force, which becomes important for the motion of compact objects in gravitational-wave inspirals. As a first approximation, this effect is captured in the motion of a spinning test particle. We solve the equations motion of a spinning particle to leading order in spin

James E. Owen, Hilke E. Schlichting

Understanding atmospheric escape in close-in exoplanets is critical to interpreting their evolution. We map out the parameter space over which photoevaporation and core-powered mass loss dominate atmospheric escape. Generally, the transition between the two regimes is determined by the location of the Bondi radius (i.e. the sonic point of core-powered outflo

Miguel P. Bento, Joao P. Silva, Andreas Trautner

The flavor puzzle of the Standard Model quark sector is formulated in a non-perturbative way, using basis invariants that are independent of the choice of quark field basis. To achieve this, we first derive the algebraic ring of 10 CP even (primary) and 1 CP odd (secondary) basis invariants, using the Hilbert series and plethystic logarithm. An orthogonal ba

Cheng-You Lu, Peisen Zhou, Angela Xing, Chandradeep Pokhariya

Advances in neural fields are enabling high-fidelity capture of the shape and appearance of dynamic 3D scenes. However, their capabilities lag behind those offered by conventional representations such as 2D videos because of algorithmic challenges and the lack of large-scale multi-view real-world datasets. We address the dataset limitation with DiVa-360, a r

Theron Guo, Ondřej Rokoš, Karen Veroy

In recent years, there has been a growing interest in understanding complex microstructures and their effect on macroscopic properties. In general, it is difficult to derive an effective constitutive law for such microstructures with reasonable accuracy and meaningful parameters. One numerical approach to bridge the scales is computational homogenization, in

Amir Bar, Florian Bordes, Assaf Shocher, Mahmoud Assran

Masked Image Modeling (MIM) is a promising self-supervised learning approach that enables learning from unlabeled images. Despite its recent success, learning good representations through MIM remains challenging because it requires predicting the right semantic content in accurate locations. For example, given an incomplete picture of a dog, we can guess tha

Sinéad M. Griffin

A recent report of room temperature superconductivity at ambient pressure in Cu-substituted apatite (`LK99&#39;) has invigorated interest in the understanding of what materials and mechanisms can allow for high-temperature superconductivity. Here I perform density functional theory calculations on Cu-substituted lead phosphate apatite, identifying correlated

Jessy Lin, Yuqing Du, Olivia Watkins, Danijar Hafner

To interact with humans and act in the world, agents need to understand the range of language that people use and relate it to the visual world. While current agents can learn to execute simple language instructions, we aim to build agents that leverage diverse language -- language like &#34;this button turns on the TV&#34; or &#34;I put the bowls away&#34;

Stephen Kelly, Daniel S. Park, Xingyou Song, Mitchell McIntire

Autonomous robots deployed in the real world will need control policies that rapidly adapt to environmental changes. To this end, we propose AutoRobotics-Zero (ARZ), a method based on AutoML-Zero that discovers zero-shot adaptable policies from scratch. In contrast to neural network adaptation policies, where only model parameters are optimized, ARZ can buil

Jun Yan, Vikas Yadav, Shiyang Li, Lichang Chen

Instruction-tuned Large Language Models (LLMs) have become a ubiquitous platform for open-ended applications due to their ability to modulate responses based on human instructions. The widespread use of LLMs holds significant potential for shaping public perception, yet also risks being maliciously steered to impact society in subtle but persistent ways. In

Sanjay Pant, Debanjan Karan

We perform a holographic study of the high and low temperature behaviours of logarithmic negativity (LN) and entanglement wedge cross section (EWCS) in a large $N$ strongly coupled thermal field theory with critical point having a well defined gravity dual known as 1RC black hole. The critical point is defined via $ξ\to 2$ limit where, $ξ$ is dimensionless p

Mohammad Alminawi, Ilaria Brivio, Joe Davighi

For scalar field theories, such as those EFTs describing the Higgs, it is well-known that the 2-derivative Lagrangian is captured by geometry. That is, the set of operators with exactly 2 derivatives can be obtained by pulling back a metric from a field space manifold $M$ to spacetime $Σ$. We here generalise this geometric understanding of scalar field theor

Vittorio Vitale, Aniket Rath, Petar Jurcevic, Andreas Elben

We present the experimental measurement, on a quantum processor, of a series of polynomial lower bounds that converge to the quantum Fisher information (QFI), a fundamental quantity for certifying multipartite entanglement that is useful for metrological applications. We combine advanced methods of the randomized measurement toolbox to obtain estimators that

John M. Ball

We make some remarks on the linear wave equation concerning the existence and uniqueness of weak solutions, satisfaction of the energy equation, growth properties of solutions, the passage from bounded to unbounded domains, and reconciliation of different representations of solutions.

Mengping Yang, Zhe Wang

Deep generative models, which target reproducing the given data distribution to produce novel samples, have made unprecedented advancements in recent years. Their technical breakthroughs have enabled unparalleled quality in the synthesis of visual content. However, one critical prerequisite for their tremendous success is the availability of a sufficient num

G. M. Shahariar, Tahmid Hasan, Anindya Iqbal, Gias Uddin

We present a novel approach - CLAA - for API aspect detection in API reviews that utilizes transformer models trained with a supervised contrastive loss objective function. We evaluate CLAA using performance and impact analysis. For performance analysis, we utilized a benchmark dataset on developer discussions collected from Stack Overflow and compare the re

Vaibhav Adlakha, Parishad BehnamGhader, Xing Han Lu, Nicholas Meade

Retriever-augmented instruction-following models are attractive alternatives to fine-tuned approaches for information-seeking tasks such as question answering (QA). By simply prepending retrieved documents in its input along with an instruction, these models can be adapted to various information domains and tasks without additional fine-tuning. While the mod

Haijin Ding, Nina H. Amini, Guofeng Zhang, John E. Gough

In this paper, we show that quantum feedback control may be applied to generate desired states for atomic and photonic systems based on a semi-infinite waveguide coupled with multiple two-level atoms. In this set-up, an initially excited atom can emit one photon into the waveguide, which can be reflected by the terminal mirror or other atoms to establish dif

Arnav Hiray, Pratvi Shah, Vishwa Shah, Agam Shah

Over the last decade, the cryptocurrency market has experienced unprecedented growth, emerging as a prominent financial market. As this market rapidly evolves, it necessitates re-evaluating which cryptocurrencies command the market and steer the direction of blockchain technology. We implement a network-based cryptocurrency market analysis to investigate thi

Xing-Zhou Qu, Dai-Wei Qu, Jialin Chen, Congjun Wu

The recently discovered nickelate superconductor La$_3$Ni$_2$O$_7$ has a high transition temperature near 80 K under pressure, which offers additional avenues of unconventional superconductivity. Here with state-of-the-art tensor-network methods, we study a bilayer $t$-$J$-$J_\perp$ model for La$_3$Ni$_2$O$_7$ and find a robust $s$-wave superconductive (SC)

Alessandro Bondi, Enrico Priola

Given a Brownian motion $W$ and a stationary Poisson point process $p$ with values in ${\mathbb R}^d$, we prove a Dynamic Programming Principle (DPP) in a strong formulation for a stochastic control problem involving controlled SDEs of the form \begin{align} \label{ci1} \nonumber dX_{t}=&\,b(t, X_{t}, a_t) dt + α\left(t, X_{t}, a_t \right) dW_t+ \! \! \int_{

K. Mouloudakis, J. Kong, A. Sierant, E. Arkin

We perform spin-noise spectroscopy on an unpolarized $^{87}\mathrm{Rb}$ vapor in the spin-exchange-relaxation-free (SERF) regime. We observe noise spectral distributions that deviate strongly from Lorentzian models that accurately describe lower-density regimes. For example, at magnetic fields of $\sim 1 \mathrm{μT}$ and $^{87}\mathrm{Rb}$ densities $\gtrsim

Reza Gheissari, Eyal Lubetzky

We study Glauber dynamics for the low temperature $(2+1)$D Solid-On-Solid model on a box of side-length $n$ with a floor at height $0$ (inducing entropic repulsion) and a competing bulk external field $λ$ pointing down (the prewetting problem). In 1996, Cesi and Martinelli showed that if the inverse-temperature $β$ is large enough, then along a decreasing se