November 2024 arXiv papers — page 123

Arthur Goemans, Marie Davidsen Buhl, Jonas Schuett, Tomek Korbak

Frontier artificial intelligence (AI) systems pose increasing risks to society, making it essential for developers to provide assurances about their safety. One approach to offering such assurances is through a safety case: a structured, evidence-based argument aimed at demonstrating why the risk associated with a safety-critical system is acceptable. In thi

Xiangtian Li, Han Cao, Zhaoyang Zhang, Jiacheng Hu

The works of Gatys et al. demonstrated the capability of Convolutional Neural Networks (CNNs) in creating artistic style images. This process of transferring content images in different styles is called Neural Style Transfer (NST). In this paper, we re-implement image-based NST, fast NST, and arbitrary NST. We also explore to utilize ResNet with activation s

Eleonora Mancini, Francesco Paissan, Paolo Torroni, Mirco Ravanelli

Speech impairments in Parkinson's disease (PD) provide significant early indicators for diagnosis. While models for speech-based PD detection have shown strong performance, their interpretability remains underexplored. This study systematically evaluates several explainability methods to identify PD-specific speech features, aiming to support the development

Alejandro Ibarra, Nicholas Leister, Di Zhang

We calculate the renormalization group equation (RGE) of the lepton-number-violating Weinberg operator with the particle content of the Standard Model (SM), thus completing the set of two-loop RGEs of the SM effective field theory up to dimension 5. We identify new diagrams that could increase the rank of the Wilson coefficient of the Weinberg operator, and

Ricardo G. Rodrigues, Thiago S. Pereira, Miguel Quartin

Cosmological data collected on a sphere, such as CMB anisotropies, are typically represented by the spherical harmonic coefficients, denoted as $a_{\ell m}$. The angular power spectrum, or $C_\ell$, serves as the fundamental estimator of the variance in this data. Alternatively, spherical data and their variance can also be characterized using Multipole Vect

Marzia Riso, Giuseppe Vecchio, Fabio Pellacini

Recent advances in diffusion models have significantly improved the synthesis of materials, textures, and 3D shapes. By conditioning these models via text or images, users can guide the generation, reducing the time required to create digital assets. In this paper, we address the synthesis of structured, stationary patterns, where diffusion models are genera

Melody A. Owen, Geoffrey M. Curran, Justin D. Smith, Yacob Tedla

Hybrid studies allow investigators to simultaneously study an intervention effectiveness outcome and an implementation research outcome. In particular, type 2 hybrid studies support research that places equal importance on both outcomes rather than focusing on one and secondarily on the other (i.e., type 1 and type 3 studies). Hybrid 2 studies introduce the

Joshua Tint, Som Sagar, Aditya Taparia, Kelly Raines

Human communication is often implicit, conveying tone, identity, and intent beyond literal meanings. While large language models have achieved strong performance on explicit tasks such as summarization and reasoning, their capacity for expressivity, or implicit communication, remains underexplored. We introduce \textbf{ExpressivityBench}, a framework for eva

Grigori Avramidi, Boris Okun, Kevin Schreve

If $L$ is a flag triangulation of $S^{n-1}$, then the Davis complex $\Sigma_L$ for the associated right-angled Coxeter group $W_L$ is a contractible $n$-manifold. A special case of a conjecture of Singer predicts that the $L^2$-homology of such $\Sigma_L$ vanishes outside the middle dimension. We give conditions which guarantee this vanishing is preserved un

Darlayne Addabbo, Christoph A. Keller

It is known from Zhu's results that under modular transformations, correlators of rational $C_2$-cofinite vertex operator algebras transform like Jacobi forms. We investigate the modular transformation properties of VOA correlators that have zero modes inserted. We derive recursion relations for such correlators and use them to establish modular transformati

Guilherme Grams, Nikolai N. Shchechilin, Adrian Sanchez-Fernandez, Wouter Ryssens

Providing reliable data on the properties of atomic nuclei and infinite nuclear matter to astrophysical applications remains extremely challenging, especially when treating both properties coherently within the same framework. Methods based on energy density functionals (EDFs) enable manageable calculations of nuclear structure throughout the entire nuclear

Ruben A. Hidalgo

Let $\chi$ be a (right) action of ${\rm PSL}_{2}({\mathbb L})$ on the space ${\mathbb L}(z)$ of rational maps defined over an algebraically closed field ${\mathbb L}$. If $R \in {\mathbb L}(z)$ and ${\mathcal M}_{R}^{\chi}$ is its $\chi$-field of moduli, then the parameter ${\rm FOD/FOM}_{\chi}(R)$ is the smallest integer $n \geq 1$ such that there is a $\ch

Noriyuki Sogabe, Yi Yin

We explore the interplay between Berry curvature and topological properties in single-flavor color superconductors, where quarks form spin-one Cooper pairs. By deriving a new relation, we connect the topological nodal structure of the gap function in momentum space to the (nonabelian) Berry flux associated with paired quarks. This generalizes the early work

V. V. Bavula

The class of semiprime left Goldie rings is a huge class of rings that contains many large subclasses of rings -- semiprime left Noetherian rings, semiprime rings with Krull dimension, rings of differential operators on affine algebraic varieties and universal enveloping algebras of finite dimensional Lie algebras to name a few. In the paper, `Ring endomorph

Manuel Cebrian, Andres Abeliuk, Jan Arne Telle

Attributing outputs from Large Language Models (LLMs) in adversarial settings-such as cyberattacks and disinformation campaigns-presents significant challenges that are likely to grow in importance. We approach this attribution problem from both a theoretical and an empirical perspective, drawing on formal language theory (identification in the limit) and da

Alexandros Chatzinikolaou, Ivan G. Todorov, Lyudmila Turowska

We characterise absolutely dilatable completely positive maps on the space of all bounded operators on a Hilbert space that are also bimodular over a given von Neumann algebra as rotations by a suitable unitary on a larger Hilbert space followed by slicing along the trace of an additional ancilla. We define the local, quantum and approximately quantum types

Shaluka Senevirathna, Anna Zemlyanova, Shaina A. Kelly, Qinhong Hu

Spontaneous imbibition (SI) is a process by which liquid is drawn into partially saturated porous media by capillary forces, relevant for subsurface processes like underground fluid storage and withdrawal. Accurate modeling and scaling of counter-current SI have long been challenging. In this study, we proposed a generalized fractional flow theory (GFFT) usi

Lilianne Tapia, Monserrat Aguayo, Andrés Anabalón, Dumitru Astefanesei

In this paper, we analyze the scalar field (quasi-)normal modes of recently derived rotating black holes within the framework of Einstein-Gauss-Bonnet theory at the Chern-Simons point in five dimensions. We also examine the mode spectrum of these probes on new static gravitational solitons. These solitons, featuring a regular center, are constructed from sta

Luis M. Briceño-Arias, Cristóbal Vivar-Vargas

In this paper we provide an efficient computation of the projection onto the cone generated by the epigraph of the perspective of any convex lower semicontinuous function. Our formula requires solving only two scalar equations involving the proximity operator of the function. This enables the computation of projections, for instance, onto exponential and pow

Paul Noël, Emir Karadža, Richard Schlitz, Pol Welter

We present a comprehensive set of harmonic resistance measurements of the dampinglike (DL) and fieldlike (FL) torques in Pt/CoFeB, Pt/Co, W/CoFeB, W/Co, and YIG/Pt bilayers complemented by measurements of the DL torque using the magneto-optical Kerr effect and calibrated by nitrogen vacancy magnetometry on the same devices. The magnon creation-annihilation m

Jeremy W. Hopwood, Craig A. Woolsey

A symmetry-preserving, reduced-order state observer is presented for the unmeasured part of a system's state, where the nonlinear system dynamics exhibit symmetry under the action of a Lie group. Leveraging this symmetry with a moving frame, the observer dynamics are constructed such that they are invariant under the Lie group's action. Sufficient conditions

Botao Du, Qihao Guo, Santiago López, Ruichao Ma

We demonstrate tunneling spectroscopy of synthetic quantum matter in superconducting circuit lattices. We measure site-resolved excitation spectra by coupling the lattice to engineered driven-dissipative particle baths that serve as local tunneling probes. Using incoherent particle source and drain, we independently extract quasi-particle and quasi-hole spec

Victor Babiano-Suarez, Javier Balibrea-Correa, Ion Ladarescu, Jorge Lerendegui-Marco

Nuclear energy production is inherently tied to the management and disposal of radioactive waste. Enhancing classification and monitoring tools is therefore crucial, with significant socioeconomic implications. This paper reports on the applicability and performance of a high-efficiency, cost-effective and portable Compton camera for detecting and visualizin

Nilay Bostan, Canan Karahan, Ozan Sargın

In this paper, we employ the Palatini formalism to investigate the dynamics of large-field inflation using a renormalizable polynomial inflaton potential in the context of $f(R,\phi)$ gravity. Assuming instant reheating, we make a comparative analysis of large-field polynomial inflation (PI). We first consider the minimal and non-minimal coupling of inflaton

The MEG II collaboration, K. Afanaciev, A. M. Baldini, S. Ban

The observation of a resonance structure in the opening angle of the electron-positron pairs in the $^{7}$Li(p,\ee) $^{8}$Be reaction was claimed and interpreted as the production and subsequent decay of a hypothetical particle (X17). Similar excesses, consistent with this particle, were later observed in processes involving $^{4}$He and $^{12}$C nuclei with

Michael A. Kouritzin, Ian Zhang, Jyoti Bhadana, Seoyeon Park

New and existing methods for generating, and especially detecting, deepfakes are investigated and compared on the simple problem of authenticating coin flip data. Importantly, an alternative approach to deepfake generation and detection, which uses a Markov Observation Model (MOM) is introduced and compared on detection ability to the traditional Generative

Morteza Heydari, Feng Liang, Hui-Hai Liu, Behzad Ghanbarian

Improving hydrocarbon production with hydraulic fracturing from unconventional reservoirs requires investigating transport phenomena at the single fracture level. In this study, we simulated geomechanical deformation, fluid flow, and reactive transport to understand the effect of hydraulic fracturing treatment on permeability evolution in shale rough-walled

Paul Noël, Richard Schlitz, Emir Karadža, Charles-Henri Lambert

Charge-spin conversion phenomena such as the spin Hall effect allow for the excitation of magnons in a magnetic layer by passing an electric current in an adjacent nonmagnetic conductor. We demonstrate that this current-induced modification of the magnon density generates an additional nonlinear longitudinal and transverse magnetoresistance for every magneto

Valentin Hofmann, Leonie Weissweiler, David Mortensen, Hinrich Schütze

What mechanisms underlie linguistic generalization in large language models (LLMs)? This question has attracted considerable attention, with most studies analyzing the extent to which the language skills of LLMs resemble rules. As of yet, it is not known whether linguistic generalization in LLMs could equally well be explained as the result of analogical pro

Jiajia Yu, Xiuyuan Cheng, Jian-Guo Liu, Hongkai Zhao

A mean-field game (MFG) seeks the Nash Equilibrium of a game involving a continuum of players, where the Nash Equilibrium corresponds to a fixed point of the best-response mapping. However, simple fixed-point iterations do not always guarantee convergence. Fictitious play is an iterative algorithm that leverages a best-response mapping combined with a weight

Celine Peroux, Dylan Nelson

These are exciting times for studies of galaxy formation and the growth of structures. New observatories and advanced simulations are revolutionising our understanding of the cycling of matter into, through, and out of galaxies. This chapter first describes why baryons are essential for galaxy evolution, providing a key test of Lambda-Cold Dark Matter cosmol

Priyanka Boora, Dinesh Kumar, Kavita Lalwani

We extend the Standard Model with the general effective Hamiltonian for the quark level transition $c \to s \ell \nu$ with a complete set of four fermion operators including right-handed neutrinos. The current experimental measurements in charm decays are compatible with the Standard Model predictions and are used to constrain the new physics. With the avail

Oskar Henriksson, Carlos Améndola, Jose Israel Rodriguez, Polly Y. Yu

A fundamental question in the field of molecular computation is what computational tasks a biochemical system can carry out. In this work, we focus on the problem of finding the maximum likelihood estimate (MLE) for log-affine models. We revisit a construction due to Gopalkrishnan of a mass-action system with the MLE as its unique positive steady state, whic

Naga VS Raviteja Chappa, Charlotte McCormick, Susana Rodriguez Gongora, Page Daniel Dobbs

The Public Health Advocacy Dataset (PHAD) is a comprehensive collection of 5,730 videos related to tobacco products sourced from social media platforms like TikTok and YouTube. This dataset encompasses 4.3 million frames and includes detailed metadata such as user engagement metrics, video descriptions, and search keywords. This is the first dataset with the

Julian Galliano, Ross J. Kang

For a subfamily ${F}\subseteq 2^{[n]}$ of the Boolean lattice, consider the graph $G_{F}$ on ${F}$ based on the pairwise inclusion relations among its members. Given a positive integer $t$, how large can ${F}$ be before $G_{F}$ must contain some component of order greater than $t$? For $t=1$, this question was answered exactly almost a century ago by Sperner

Ryan Yee, Soham Ghosh, Sameer K. Deshpande

Although it is an extremely effective, easy-to-use, and increasingly popular tool for nonparametric regression, the Bayesian Additive Regression Trees (BART) model is limited by the fact that it can only produce discontinuous output. Initial attempts to overcome this limitation were based on regression trees that output Gaussian Processes instead of constant

Ben Fauber

We demonstrate that Gini coefficients can be used as unified metrics to evaluate many-versus-many (all-to-all) similarity in vector spaces. Our analysis of various image datasets shows that images with the highest Gini coefficients tend to be the most similar to one another, while images with the lowest Gini coefficients are the least similar. We also show t

David Georg Reichelt, Malte Hansen, Shinhyung Yang, Wilhelm Hasselbring

While the observability framework Kieker has a low overhead for tracing, its results currently cannot be used in most analysis tools due to lack of interoperability of the data formats. The OpenTelemetry standard aims for standardizing observability data. In this work, we describe how to export Kieker distributed tracing data to OpenTelemetry. This is done u

Michael Zheng

We establish an upper bound on the minimum codegree necessary for the existence of spanning, fractional Steiner triple systems in $3$-uniform hypergraphs. This improves upon a result by Lee in 2023. In particular, together with results from Lee's paper, our results imply that if $n$ is sufficiently large and satisfies some necessary divisibility conditions,

A. Kehagias, A. Riotto

The nonlinear nature of general relativity manifests prominently throughout the merger of two black holes, from the inspiral phase to the final ringdown. Notably, the quasi-normal modes generated during the ringdown phase display significant nonlinearities. We show that these nonlinear effects can be effectively captured by zooming in on the photon ring thro

Davide Buffelli, Jamie McGowan, Wangkun Xu, Alexandru Cioba

Second-order optimization has been shown to accelerate the training of deep neural networks in many applications, often yielding faster progress per iteration on the training loss compared to first-order optimizers. However, the generalization properties of second-order methods are still being debated. Theoretical investigations have proved difficult to carr

Masahiro Kato

This note introduces a doubly robust (DR) estimator for regression discontinuity (RD) designs. RD designs provide a quasi-experimental framework for estimating treatment effects, where treatment assignment depends on whether a running variable surpasses a predefined cutoff. A common approach in RD estimation is the use of nonparametric regression methods, su

Xiao Li, Cheng Li, Houjun Mo

We investigate the driving mechanisms for the HI gas content in star-forming central galaxies at low redshift, by examining the HI-to-stelalr mass ratio ($M_{\rm HI}/M_\ast$) in both the state-of-the-art hydrodynamic simulations, IllustrisTNG (TNG) and EAGLE, and the xGASS sample. We quantify the correlations of $M_{\rm HI}/M_\ast$ with a variety of galaxy p

Mahmut S. Gokmen, Caner Ozcan, Moneera N. Haque, Steve W. Leung

Coronary artery disease (CAD), one of the leading causes of mortality worldwide, necessitates effective risk assessment strategies, with coronary artery calcium (CAC) scoring via computed tomography (CT) being a key method for prevention. Traditional methods, primarily based on UNET architectures implemented on pre-built models, face challenges like the scar

Yiyang Ma, Xingchao Liu, Xiaokang Chen, Wen Liu

We present JanusFlow, a powerful framework that unifies image understanding and generation in a single model. JanusFlow introduces a minimalist architecture that integrates autoregressive language models with rectified flow, a state-of-the-art method in generative modeling. Our key finding demonstrates that rectified flow can be straightforwardly trained wit

Rolf-Peter Kudritzki, Miguel A. Urbaneja, Fabio Bresolin, Lucas M. Macri

A quantitative spectroscopic study of blue supergiant stars in the Hubble constant anchor galaxy NGC 4258 is presented. The non-LTE analysis of Keck I telescope LRIS spectra yields a central logarithmic metallicity (in units of the solar value) of [Z] = -0.05\pm0.05 and a very shallow gradient of -(0.09\pm0.11)r/r25 with respect to galactocentric distance in

Maggie L. Li, Anna Y. Q. Ho, Geoffrey Ryan, Daniel A. Perley

In the past few years, the improved sensitivity and cadence of wide-field optical surveys have enabled the discovery of several afterglows without associated detected gamma-ray bursts (GRBs). We present the identification, observations, and multiwavelength modeling of a recent such afterglow (AT2023lcr), and model three literature events (AT2020blt, AT2021an

Tom Gur, Jack O'Connor, Nicholas Spooner

We show that for every polynomial q* there exist polynomial-size, constant-query, non-adaptive PCPs for NP which are perfect zero knowledge against (adaptive) adversaries making at most q* queries to the proof. In addition, we construct exponential-size constant-query PCPs for NEXP with perfect zero knowledge against any polynomial-time adversary. This impro

Isaac Ronald Ward, Dylan M. Asmar, Mansur Arief, Jana Krystofova Mike

Deciding on appropriate mechanical ventilator management strategies significantly impacts the health outcomes for patients with respiratory diseases. Acute Respiratory Distress Syndrome (ARDS) is one such disease that requires careful ventilator operation to be effectively treated. In this work, we frame the management of ventilators for patients with ARDS a

Cheng Zhao, Song Huang, Mengfan He, Paulo Montero-Camacho

The MUltiplexed Survey Telescope (MUST) is a 6.5-meter telescope under development. Dedicated to highly-multiplexed, wide-field spectroscopic surveys, MUST observes over 20,000 targets simultaneously using 6.2-mm pitch positioning robots within a ~5 deg$^2$ field of view. MUST aims to conduct the first Stage-V spectroscopic survey in the 2030s, mapping the 3

Dalibor Djukanovic, Georg von Hippel, Simon Kuberski, Harvey B. Meyer

We present our lattice QCD result for the long-distance part of the hadronic vacuum polarization contribution, $(a_\mu^{\rm hvp})^{\rm LD}$, to the muon $g-2$ in the time-momentum representation. This is the numerically dominant, and at the same time the most challenging part regarding statistical precision. Our calculation is based on ensembles with dynamic

Abigail Nolin, Chun-Yuan Lo, Laure V. Kayser, Charles B. Dhong

Most tactile actuators create tactile sensations through vibrations or the mechanical and electrochemical formation of bumps. However, tactile sensations of real objects arise from friction which is derived not only from physical topography, but also surface chemistry. Here, we show that molecular rearrangement can be leveraged to create new classes of tacti

Hossein Vaziri, Mohammad Reza Shojaei

By introducing ansatz and using a PDF at the $N^3LO$ approximation in this paper, we have studied the structure of the nucleons in generalized parton distributions (GPDs). For this purpose, the form factors and the electric radius of nucleons, as well as the quark's form factors, are calculated in this paper. These calculations give important new information

Albert Atserias, Iddo Tzameret

The Schwartz-Zippel Lemma states that if a low-degree multivariate polynomial with coefficients in a field is not zero everywhere in the field, then it has few roots on every finite subcube of the field. This fundamental fact about multivariate polynomials has found many applications in algorithms, complexity theory, coding theory, and combinatorics. We give

Chuyi Kong, Ziyang Luo, Hongzhan Lin, Zhiyuan Fan

The advanced role-playing capabilities of Large Language Models (LLMs) have enabled rich interactive scenarios, yet existing research in social interactions neglects hallucination while struggling with poor generalizability and implicit character fidelity judgments. To bridge this gap, motivated by human behaviour, we introduce a generalizable and explicit p

Shashank Manjunath, Hau-Tieng Wu, Aarti Sathyanarayana

Sleep staging is a challenging task, typically manually performed by sleep technologists based on electroencephalogram and other biosignals of patients taken during overnight sleep studies. Recent work aims to leverage automated algorithms to perform sleep staging not based on electroencephalogram signals, but rather based on the airflow signals of subjects.

Mariam Hegazy, Aliaa Rafaat, Niseem Magdy, Wenliang Li

In this work, we investigate the feasibility of defining centrality in electron-ion collisions at the Electron-Ion Collider (EIC) by examining the correlation between the impact parameter and several observables, including total energy, total transverse momentum, and total number of particles. Using the BeAGLE Monte Carlo generator, we simulate e+Au and e+Ru

Olivia Beckwith, Andreas Mono

In a recent preprint, we constructed a sesquiharmonic Maass form $\mathcal{G}$ of weight $\frac{1}{2}$ and level $4N$ with $N$ odd and squarefree. Extending seminal work by Duke, Imamo\={g}lu, and T\'{o}th, $\mathcal{G}$ maps to Zagier's non-holomorphic Eisenstein series and a linear combination of Pei and Wang's generalized Cohen--Eisenstein series under th

Marco Matone, Nikolaos Dimakis

We demonstrate that the recently introduced linear equation, reformulating the first Friedmann equation, is the first-order WKB expansion of a quantum cosmological equation. This result shows a deeper underlying connection between General Relativity and Quantum Mechanics, pointing towards a unified framework. Solutions of this equation are built in terms of

Christos Giamouzis, Dimitrios Garyfallou, Nestor Evmorfopoulos, George Stamoulis

Model order reduction (MOR) is essential in integrated circuit design, particularly when dealing with large-scale electromagnetic models extracted from complex designs. The numerous passive elements introduced in these models pose significant challenges in the simulation process. MOR methods based on balanced truncation (BT) help address these challenges by

Micah Nichols, Christopher D. Barrett, Doyl E. Dickel, Mashroor S. Nitol

The microstructure of the Ti-Al binary system is an area of great interest as it affects material properties and plasticity. Phase transformations induce microstructural changes; therefore, accurately modeling the phase transformations of the Ti-Al system is necessary to describe plasticity. Interatomic potentials can be a powerful tool to model how material

Satish Kumar Keshri, Nazreen Shah, Ranjitha Prasad

The holy grail of machine learning is to enable Continual Federated Learning (CFL) to enhance the efficiency, privacy, and scalability of AI systems while learning from streaming data. The primary challenge of a CFL system is to overcome global catastrophic forgetting, wherein the accuracy of the global model trained on new tasks declines on the old tasks. I

J. Salvador-Sánchez, A. Pérez-Rodriguez, V. Clericò, O. Zheliuk

In a twisted graphene on hexagonal Boron Nitride, the presence of a gap and the breaking of the symmetry between carbon sublattices leads to multicomponent fractional quantum Hall effect (FQHE) due to the electrons correlation. We report on the FQHE at filling factors nu = k/2 and nu = k/3 with nu > 1, and on the composite fermions at in the nu < 1 lowest la

Arthur P. Guillaumin, Natalia Efremova

This paper addresses non-Gaussian regression with neural networks via the use of the Tukey g-and-h distribution.The Tukey g-and-h transform is a flexible parametric transform with two parameters $g$ and $h$ which, when applied to a standard normal random variable, introduces both skewness and kurtosis, resulting in a distribution commonly called the Tukey g-

Laura Dominé, Ankit Biswas, Richard Cloete, Alex Delacroix

To date there is little publicly available scientific data on Unidentified Aerial Phenomena (UAP) whose properties and kinematics purportedly reside outside the performance envelope of known phenomena. To address this deficiency, the Galileo Project is designing, building, and commissioning a multi-modal ground-based observatory to continuously monitor the s

William Yue, Bo Liu, Peter Stone

In Partially Observable Markov Decision Processes, integrating an agent's history into memory poses a significant challenge for decision-making. Traditional imitation learning, relying on observation-action pairs for expert demonstrations, fails to capture the expert's memory mechanisms used in decision-making. To capture memory processes as demonstrations,

Kaihua Ji, Mingwang Zhong, Alain Karma

We further develop a recently introduced phase-field model of rapid alloy solidification [Ji et al., PRL 2023]. This model utilizes enhanced solute diffusivity within the spatially diffuse interface region to quantitatively capture solute trapping with a larger interface width, thereby making simulations on experimentally relevant length and time scales comp

Yechan Park, Yuya Sasaki

Since LaLonde's (1986) seminal paper, there has been ongoing interest in estimating treatment effects using pre- and post-intervention data. Scholars have traditionally used experimental benchmarks to evaluate the accuracy of alternative econometric methods, including Matching, Difference-in-Differences (DID), and their hybrid forms (e.g., Heckman et al., 19

Eric Schwitzgebel, Jeremy Pober

On broadly Copernican grounds, we are entitled to assume that apparently behaviorally sophisticated extraterrestrial entities ("aliens") would be conscious. Otherwise, we humans would be inexplicably, implausibly lucky to have consciousness, while similarly behaviorally sophisticated entities elsewhere would be mere shells, devoid of consciousness. However,

Antonio J. Fernández, María Medina, Angela Pistoia

We study the critical system of $m\geq 2$ equations \begin{equation*} -\Delta u_i = u_i^5 + \sum_{j = 1,\,j\neq i}^m \beta_{ij} u_i^2 u_j^3\,, \quad u_i \gneqq 0 \quad \mbox{in } \mathbb{R}^3\,, \quad i \in \{1, \ldots, m\}\,, \end{equation*} where $\beta_{\kappa\ell} =\alpha\in\mathbb{R}$ if $\kappa\neq\ell$, and $\beta_{\ell m}=\beta_{m \kappa} =\beta<0$,

Pramod Sharma, Biswajit Das, Ambresh Shivaji

Properties of the Higgs boson ($H$) at current and future particle colliders are crucial to explore new physics beyond the standard model. In particular, experimental and theoretical outlooks at future colliders drive interest in Higgs to gauge boson couplings. Single Higgs production via vector-boson fusion allows probing Higgs couplings with massive vector

Chutian Ma, Paul Smith

We consider a simplified model for optimizing a single-asset portfolio in the presence of transaction costs given a signal with a certain autocorrelation and cross-correlation structure. In our setup, the portfolio manager is given two one-parameter controls to influence the construction of the portfolio. The first is a linear filtering parameter that may in

Peter B. Rau, Ira Wasserman

In magnetar crusts, magnetic fields are sufficiently strong to confine electrons into a small to moderate number of quantized Landau levels. This can have a dramatic effect on the crust's thermodynamic properties, generating field-dependent de Haas--van Alphen oscillations. We previously argued that the large-amplitude oscillations of the magnetic susceptibi

Ali Abdollahi

This study investigates a system comprising a linear oscillator (LO) equipped with a Vibro-Impact Nonlinear Energy Sink (VI-NES) and a coil. The LO's damping and stiffness coefficients are represented by ( C ) and ( k ), respectively, while a ball inside the LO moves within a cavity, colliding with the walls at both ends. The primary focus is on optimizing t

Ritwik Sadhu, Ziv Goldfeld, Kengo Kato

Entropic optimal transport offers a computationally tractable approximation to the classical problem. In this note, we study the approximation rate of the entropic optimal transport map (in approaching the Brenier map) when the regularization parameter $\varepsilon$ tends to zero in the semidiscrete setting, where the input measure is absolutely continuous w

Martin Lefebvre, David Bol

Recent advances in artificial intelligence have prompted the search for enhanced algorithms and hardware to support the deployment of machine learning at the edge. More specifically, in the context of the Internet of Things (IoT), vision chips must be able to fulfill tasks of low to medium complexity, such as feature extraction or region-of-interest (RoI) de

Peijun Bao, Alex C. Kot

This paper presents SimBase, a simple yet effective baseline for temporal video grounding. While recent advances in temporal grounding have led to impressive performance, they have also driven network architectures toward greater complexity, with a range of methods to (1) capture temporal relationships and (2) achieve effective multimodal fusion. In contrast

Kang Zhou

In this paper, we propose new understandings for recently discovered hidden zeros and novel splittings, by utilizing Feynman diagrams. The study focus on ordered tree level amplitudes of three theories, which are ${\rm Tr}(\phi^3)$, Yang-Mills, and non-linear sigma model. We find three universal ways of cutting Feynman diagrams, which are valid for any diagr

Harry Dong, Tyler Johnson, Minsik Cho, Emad Soroush

Tensor parallelism provides an effective way to increase server large language model (LLM) inference efficiency despite adding an additional communication cost. However, as server LLMs continue to scale in size, they will need to be distributed across more devices, magnifying the communication cost. One way to approach this problem is with quantization, but

Zhaoxi Zhang, Yueliang Ying

Computed tomography (CT) provides highly detailed three-dimensional (3D) medical images but is costly, time-consuming, and often inaccessible in intraoperative settings (Organization et al. 2011). Recent advancements have explored reconstructing 3D chest volumes from sparse 2D X-rays, such as single-view or orthogonal double-view images. However, current mod

Mélanie Roschewitz, Raghav Mehta, Charles Jones, Ben Glocker

Shifts in data distribution can substantially harm the performance of clinical AI models and lead to misdiagnosis. Hence, various methods have been developed to detect the presence of such shifts at deployment time. However, the root causes of dataset shifts are diverse, and the choice of shift mitigation strategies is highly dependent on the precise type of

Humberto Gomez, Renann Lipinski Jusinskas, Cristhiam Lopez-Arcos, Alexander Quintero Velez

In this work we propose a simple algebraic recursion for the complete one-loop integrands of $N$-graviton correlators. This formula automatically yields the correct symmetry factors of individual diagrams, taking into account both the graviton and the ghost loop, and seamlessly controlling the related combinatorics.

Dmitry Shishkin, Noam Soker

We identify a point-symmetrical morphology comprised of seven pairs of opposite bays in the core-collapse supernova (CCSN) remnant Crab Nebula, which is consistent with the jittering jets explosion mechanism (JJEM) of CCSNe. We use a recently published infrared image of the Crab Nebula and apply image analysis to fit seven pairs of bays in the Crab, each pai

Najib Khachiaa

This paper aims to explore the concept of continuous \( K \)-frames in quaternionic Hilbert spaces. First, we investigate \( K \)-frames in a single quaternionic Hilbert space \( \mathcal{H} \), where \( K \) is a right $\mathbb{H}$-linear bounded operator acting on \( \mathcal{H} \). Then, we extend the research to two quaternionic Hilbert spaces, \( \mathc

Ziyu Shan, Yujie Zhang, Yipeng Liu, Yiling Xu

No-Reference Point Cloud Quality Assessment (NR-PCQA) aims to objectively assess the human perceptual quality of point clouds without relying on pristine-quality point clouds for reference. It is becoming increasingly significant with the rapid advancement of immersive media applications such as virtual reality (VR) and augmented reality (AR). However, curre

Mushtaq A. Bhat, Peer Abdul Manan

Let $D$ be a digraph of order $n$ with adjacency matrix $A(D)$. For $\alpha\in[0,1)$, the $A_{\alpha}$ matrix of $D$ is defined as $A_{\alpha}(D)=\alpha {\Delta}^{+}(D)+(1-\alpha)A(D)$, where ${\Delta}^{+}(D)=\mbox{diag}~(d_1^{+},d_2^{+},\dots,d_n^{+})$ is the diagonal matrix of vertex outdegrees of $D$. Let $\sigma_{1\alpha}(D),\sigma_{2\alpha}(D),\dots,\si

Yixiu Mao, Qi Wang, Yun Qu, Yuhang Jiang

Offline Reinforcement Learning (RL) suffers from the extrapolation error and value overestimation. From a generalization perspective, this issue can be attributed to the over-generalization of value functions or policies towards out-of-distribution (OOD) actions. Significant efforts have been devoted to mitigating such generalization, and recent in-sample le

Yifei Gao, Harun Yetkin, McMahon James, Daniel J. Stilwell

Cooperating autonomous underwater vehicles (AUVs) often rely on acoustic communication to coordinate their actions effectively. However, the reliability of underwater acoustic communication decreases as the communication range between vehicles increases. Consequently, teams of cooperating AUVs typically make conservative assumptions about the maximum range a

Seongmin Kim

The Khintchine-Groshev theorem in Diophantine approximation theory says that there is a dichotomy of the Lebesgue measure of sets of $\psi$-approximable numbers, given a monotonic function $\psi$. Allen and Ram\'irez removed the monotonicity condition from the inhomogeneous Khintchine-Groshev theorem for cases with $nm\geq3$ and conjectured that it also hold

Kiryl Asheichyk

We develop a theoretical formalism for time-dependent radiative heat flux from one object to another in the case where the former starts radiating at a certain time. The time dependence is demonstrated for the heat flux between two isolated nanoparticles. After one particle starts radiating, the emitted energy first reaches the other one with a delay accordi

Linxuan Li, Wenjia Wei, Luyao Yang, Wenwen Zhang

Low-dose CT (LDCT) significantly reduces the radiation dose received by patients, however, dose reduction introduces additional noise and artifacts. Currently, denoising methods based on convolutional neural networks (CNNs) face limitations in long-range modeling capabilities, while Transformer-based denoising methods, although capable of powerful long-range

A. Muñoz de las Heras, D. Porras, A. González-Tudela

Photonic quantum metrology enables the measurement of physical parameters with precision surpassing classical limits by using quantum states of light. However, generating states providing a large metrological advantage is hard because standard probabilistic methods suffer from low generation rates. Deterministic protocols using non-linear interactions offer

Klaus Mosegaard, Andrew Curtis

Bayesian inference is used to estimate continuous parameter values given measured data in many fields of science. The method relies on conditional probability densities to describe information about both data and parameters, yet the notion of conditional densities is inadmissible: probabilities of the same physical event, computed from conditional densities

A. Deltuva, D. Jurčiukonis

Deuteron breakup in collision with a ${}^{24}\mathrm{Mg}$ nucleus is studied using rigorous three-body scattering equations, extended to include also the excitation of the nucleus. Predictions based on local and nonlocal nucleon-nucleus optical potentials with rotational quadrupole deformation enabling the excitation of the ${}^{24}\mathrm{Mg}(2^+)$ state ar

Raffaele Romagnoli

Chimeric antigen receptor (CAR) T cell therapy is revolutionizing the treatment of blood cancers. Mathematical models that can predict the effectiveness of immunotherapies such as CAR T are of increasing interest due to their ability to reduce the number of experiments performed and to guide the theoretical development of new therapeutic strategies. {Followi

Martin Nørgaard, Torgom Yezekyan, Stefan Rolfs, Christian Frydendahl

Common techniques for measuring refractive indices, such as ellipsometry and goniometry, are ineffective for van der Waals crystal flakes because of their high anisotropy and small, micron-scale, lateral size. To address this, we employ near-field optical microscopy to analyze the guided optical modes within these crystals. By probing these modes in MoS$_2$

Chengchao Yuan, Walter Winter, B. Theodore Zhang, Kohta Murase

We investigate the external reverse shock region of relativistic jets as the origin of X-ray afterglows of jetted tidal disruption events (TDEs) that exhibit luminous jets accompanied by fast-declining non-thermal X-ray emissions. We model the dynamics of jet propagating within an external density medium, accounting for continuous energy injection driven by

H. S. Karthik, S. Gómez, F. M. Quinteros, Akshata Shenoy H.

A $n^d \xrightarrow{p} 1$ Quantum Random Access Code (QRAC) is a communication task where Alice encodes $n$ classical bits into quantum states of dimension $d$ and transmits them to Bob, who performs appropriate measurements to recover the required bit with probability $p$. In the presence of a noisy environment, the performance of a QRAC is degraded, losing

J. M. Marcos, J. J. Melendez, R. Cuerno, J. J. Ruiz-Lorenzo

We study numerically the kinetic roughening properties of the precursor fronts of nonvolatile liquid droplets spreading on solid substrates, for the case of circular droplets, more frequently addressed in experiments. To this end, we perform kinetic Monte Carlo (kMC) simulations of a lattice gas model whose kinetic roughening behavior has been recently asses

Ryan Boukrouche, Rodrigo Caballero, Markus Janson

Non-transiting terrestrial planets will be accessible by upcoming observatories of which LIFE is an example. Planet b orbiting Teegarden's Star is one of the optimal targets for such missions. We use a one-dimensional atmospheric model with real-gas radiation, a multi-species pseudo-adiabatic convection-condensation scheme, and a water cloud scheme, to estim