May 2024 arXiv papers — page 125

Shovan Dutta, Shu Zhang, Masudul Haque

Among the most iconic features of classical dissipative dynamics are persistent limit-cycle oscillations and critical slowing down at the onset of such oscillations, where the system relaxes purely algebraically in time. On the other hand, quantum systems subject to generic Markovian dissipation decohere exponentially in time, approaching a unique steady sta

Estanis Utrilla Ginés, Dion Noordhuis, Christoph Weniger, Samuel J. Witte

Many present-day axion searches attempt to probe the mixing of axions and photons, which occurs in the presence of an external magnetic field. While this process is well-understood in a number of simple and idealized contexts, a strongly varying or highly inhomogeneous background can impact the efficiency and evolution of the mixing in a non-trivial manner.

R. Rehm, J. S. G. Mombarg, C. Aerts, M. Michielsen

Numerical computations of stellar oscillations for models representative of B-type stars predict fewer modes to be excited than observations reveal from modern space-based photometric data. One shortcoming of state-of-the-art evolution models of B-type stars that may cause a lack of excited modes is the absence of microscopic diffusion in most such models. W

Joseph Tooby-Smith

We introduce HepLean, an open-source project to digitalise definitions, theorems, proofs, and calculations in high energy physics using the interactive theorem prover Lean 4. HepLean has the potential to benefit the high energy physics community in four ways: making it easier to find existing results, allowing the creation of new results using artificial int

Astrid Eichhorn, Andreas Odgaard Pedersen, Marc Schiffer

Positivity bounds are bounds on the Wilson coefficients of an effective field theory. They hold, if the ultraviolet completion satisfies unitarity, microcausality, locality and Lorentz symmetry; accordingly their violation signals a violation of at least one of these properties of the ultraviolet completion. We explore whether positivity bounds on four-photo

María Benito, Konstantin Karchev, Rebecca K. Leane, Sven Põder

Dark Matter (DM) can become captured, deposit annihilation energy, and hence increase the heat flow in exoplanets and brown dwarfs. Detecting such a DM-induced heating in a population of exoplanets in the inner kpc of the Milky Way thus provides potential sensitivity to the galactic DM halo parameters. We develop a Bayesian Hierarchical Model to investigate

Hyunsoo Ha, Akshat Pandey, Sarang Gopalakrishnan, David A. Huse

The competition between scrambling and projective measurements can lead to measurement-induced entanglement phase transitions (MIPT). In this work, we show that the universality class of the MIPT is drastically altered when the system is coupled to a diffusing conserved density. Specifically, we consider a 1+1d random Clifford circuit locally monitored by cl

Benjamin Knorr, Alessia Platania

We compute the asymptotic safety landscape stemming from ultraviolet-complete photon-graviton flows in a field theoretic setup, and we confront it with the weak gravity conjecture and, for the first time, with positivity bounds. At fourth order in derivatives, we find two gravitational fixed points providing viable ultraviolet completions for the theory. One

Yuichiro Tada, Masaki Yamada

We revisit the hybrid inflation model within the framework of the Grand Unified Theory (GUT), focusing on cases where the waterfall phase transition extends over several e-foldings to dilute monopoles. Considering the stochastic effects of quantum fluctuations, we demonstrate that the waterfall fields (i.e., GUT Higgs) maintain a nonzero vacuum expectation v

Rodolfo Capdevilla, Federico Meloni, Jose Zurita

Minimal Dark Matter models feature one neutral particle that serves as a thermal relic dark matter candidate, as well as quasi-degenerate charged states with TeV masses. When the charged states are produced at colliders, they can decay into dark matter and a low-momentum (soft) charged particle, which is challenging to reconstruct at hadron colliders. We dem

Michele Vallisneri, Marco Crisostomi, Aaron D. Johnson, Patrick M. Meyers

In the gravitational-wave analysis of pulsar-timing-array datasets, parameter estimation is usually performed using Markov Chain Monte Carlo methods to explore posterior probability densities. We introduce an alternative procedure that relies instead on stochastic gradient-descent Bayesian variational inference, whereby we obtain the weights of a neural-netw

Yohei Ema, Ting Gao, Maxim Pospelov, Adam Ritz

We revisit the chiral properties of nucleon interpolating currents, and show that of the two leading order currents $j_1$ and $j_2$, only two linear combinations $j_1\pm j_2$ transform covariantly under the anomalous $U(1)_A$ symmetry. As a result, calculations of quantities which vanish by symmetry in the chiral limit may produce unphysical results if carri

Jason T. Hinkle, Benjamin J. Shappee, Katie Auchettl, Christopher S. Kochanek

We present the class of extreme nuclear transients (ENTs), including the most energetic single transient yet discovered, Gaia18cdj. Each ENT is coincident with its host-galaxy nucleus and exhibits a smooth ($<$$10$% excess variability), luminous ($2\times$$10^{45}$ to $7\times$$10^{45}$ erg s$^{-1}$), and long-lived ($>$$150$ days) flare. ENTs are extremely

Lingdong Kong, Shaoyuan Xie, Hanjiang Hu, Yaru Niu

In the realm of autonomous driving, robust perception under out-of-distribution conditions is paramount for the safe deployment of vehicles. Challenges such as adverse weather, sensor malfunctions, and environmental unpredictability can severely impact the performance of autonomous systems. The 2024 RoboDrive Challenge was crafted to propel the development o

Zihao Wei, Zixuan Pan, Andrew Owens

We propose a simple strategy for masking image patches during visual-language contrastive learning that improves the quality of the learned representations and the training speed. During each iteration of training, we randomly mask clusters of visually similar image patches, as measured by their raw pixel intensities. This provides an extra learning signal,

Cian C. Reeves, Gaurav Harsha, Avijit Shee, Yuanran Zhu

Theoretical descriptions of non equilibrium dynamics of quantum many-body systems essentially employ either (i) explicit treatments, relying on truncation of the expansion of the many-body wave function, (ii) compressed representations of the many-body wave function, or (iii) evolution of an effective (downfolded) representation through Green's functions. In

Ruchit Rawal, Khalid Saifullah, Miquel Farré, Ronen Basri

Current datasets for long-form video understanding often fall short of providing genuine long-form comprehension challenges, as many tasks derived from these datasets can be successfully tackled by analyzing just one or a few random frames from a video. To address this issue, we present a novel dataset and benchmark, CinePile, specifically designed for authe

Ernest Fontich, Antonio Garijo, Xavier Jarque

In this paper we give analytic proofs of the existence of transversal homoclinic points for a family of non-globally smooth diffeomorphisms having the origin as a fixed point which come out as a truncated map governing the local dynamics near a critical period three cycle associated to the Secant map. Using Moser's version of Birkhoff-Smale's Theorem, we pro

Ali Javadi-Abhari, Matthew Treinish, Kevin Krsulich, Christopher J. Wood

We describe Qiskit, a software development kit for quantum information science. We discuss the key design decisions that have shaped its development, and examine the software architecture and its core components. We demonstrate an end-to-end workflow for solving a problem in condensed matter physics on a quantum computer that serves to highlight some of Qisk

Ethan Torres

In \cite{Garcia-Etxebarria:2017crf}, it was found that the system of $k$ D7-branes probing an $O7^+$-plane suffers from an $\mathfrak{sp}(k)$ gauge anomaly when $k>1$. These authors then conjectured that this 8D $\mathcal{N}=1$ gauge theory couples to an 8D topological field theory (TFT) such that the total system is anomaly-free, thus acting as a "topologic

Antoine Rignon-Bret, Simone Speziale

We propose a new set of BMS charges at null infinity, characterized by a super-translation flux that contains only the `hard' term. This is achieved with a specific corner improvement of the symplectic 2-form, and we spell the conditions under which it is unique. The charges are associated to a Wald-Zoupas symplectic potential, and satisfy all standard crite

Jonathan Roberts, Kai Han, Neil Houlsby, Samuel Albanie

Large multimodal models (LMMs) have proven flexible and generalisable across many tasks and fields. Although they have strong potential to aid scientific research, their capabilities in this domain are not well characterised. A key aspect of scientific research is the ability to understand and interpret figures, which serve as a rich, compressed source of co

Zhehao Zhang, Thomas S. Richardson

We revisit the following problem, proposed by Kolmogorov: given prescribed marginal distributions $F$ and $G$ for random variables $X,Y$ respectively, characterize the set of compatible distribution functions for the sum $Z=X+Y$. Bounds on the distribution function for $Z$ were first given by Markarov (1982) and R\"uschendorf (1982) independently. Frank et a

Giacomo Ascione, Atsuhide Ishida, József Lőrinczi

We propose a counterpart of the classical Rollnik-class of potentials for fractional and massive relativistic Laplacians, and describe this space in terms of appropriate Riesz potentials. These definitions rely on precise resolvent estimates. We show that Coulomb-type potentials are elements of fractional Rollnik-class up to but not including the critical si

He Jia, Eliot Quataert, Alexandru Lupsasca, George N. Wong

We calculate the interferometric signatures of black hole photon rings beyond the universal regime by perturbatively including the effects of finite ring width. Our approach first slices a thick ring into a series of thin rings, each of which falls within the universal regime. We thus calculate the visibility of the thick ring by aggregating the contribution

Kevin Hu, Kavita Ramanan, William Salkeld

In this paper, we prove a mimicking theorem for stochastic processes with an additive Gaussian noise along with some entropy and transport type estimates. As an application of these results, we prove sharp quantitative propagation of chaos result and derive a formula for the marginal dynamics of collections of locally interacting stochastic differential equa

Haozhe Wang, Haidong Zhou, Weiwei Xie

A recent $J. Am. Chem. Soc.$ Article (DOI: 10.1021/jacs.3c13094) details a pressure-temperature ($P$-$T$) phase diagram for the Ruddlesden-Popper bilayer nickelate La$_3$Ni$_2$O$_7$ (LNO-2222) using synchrotron X-ray diffraction. This study identifies a phase transition from $Amam$ (#63) to $Fmmm$ (#69) within the temperature range of 104 K to 120 K under in

Jamie Heredge, Niraj Kumar, Dylan Herman, Shouvanik Chakrabarti

Ensuring data privacy in machine learning models is critical, particularly in distributed settings where model gradients are typically shared among multiple parties to allow collaborative learning. Motivated by the increasing success of recovering input data from the gradients of classical models, this study addresses a central question: How hard is it to re

Tianwei Xia, Zhe Yu, Kai Sun, Di Shi

In a power system, when the participation factors of generators are computed to rank their participations into an oscillatory mode, a model-based approach is conventionally used on the linearized system model by means of the corresponding right and left eigenvectors. This paper proposes a new approach for estimating participation factors directly from measur

Shay Ben-Moshe

We show that the Yoneda embedding extends to an $(\infty,2)$-natural transformation. Furthermore, as such, it is uniquely determined by its value at the trivial $\infty$-category. We also study the naturality of the Yoneda lemma in its arguments, showing that it is an isomorphism of $(\infty,2)$-natural transformations.

Cory Hargus, Alhad Deshpande, Ahmad K. Omar, Kranthi K. Mandadapu

Onsager's regression hypothesis makes a fundamental connection between macroscopic transport phenomena and the average relaxation of spontaneous microscopic fluctuations. This relaxation, however, is agnostic to odd transport phenomena, in which fluxes run orthogonal to the gradients driving them. To account for odd transport, we generalize the regression hy

Eduard Inozemtsev, Andrey Kupavskii

In this paper, we investigate two questions on Kneser graphs $KG_{n,k}$. First, we prove that the union of $s$ intersecting families in ${[n]\choose k}$ has size at most ${n\choose k}-{n-s\choose k}$ for all sufficiently large $n$ that satisfy $n>(2+\epsilon)k^2+s$ with $\epsilon>0$. We provide an example that shows that this result is essentially tight for

Tomasz Strzalecki

I show how variational Bayes can be used as a microfoundation for a popular model of non-Bayesian updating.

Kevin Hu, Kavita Ramanan, William Salkeld

We consider collections of SDEs indexed by a graph. Each SDE is driven by an additive Gaussian noise and each drift term interacts with all other SDEs within the graph neighbourhood. We derive the fundamental martingale for a class of Gaussian processes and use this to prove a Girsanov type theorem. Further, we use this to construct a clique factorisation to

Luisa Schwirten, Jannes Scholz, Daniel Kondermann, Janis Keuper

Datasets labelled by human annotators are widely used in the training and testing of machine learning models. In recent years, researchers are increasingly paying attention to label quality. However, it is not always possible to objectively determine whether an assigned label is correct or not. The present work investigates this ambiguity in the annotation o

Kyunghyun Cho

This is a lecture note produced for DS-GA 3001.003 "Special Topics in DS - Causal Inference in Machine Learning" at the Center for Data Science, New York University in Spring, 2024. This course was created to target master's and PhD level students with basic background in machine learning but who were not exposed to causal inference or causal reasoning in ge

Edison Jair Bejarano Sepulveda, Nicolai Potes Hector, Santiago Pineda Montoya, Felipe Ivan Rodriguez

This paper explores the potential of large language models (LLMs) to make the Aeronautical Regulations of Colombia (RAC) more accessible. Given the complexity and extensive technicality of the RAC, this study introduces a novel approach to simplifying these regulations for broader understanding. By developing the first-ever RAC database, which contains 24,47

Ernest Fontic, Antonio Garijo, Xavier Jarque

We consider the secant method $S_p$ applied to a real polynomial $p$ of degree $d+1$ as a discrete dynamical system on $\mathbb R^2$. If the polynomial $p$ has a local extremum at a point $\alpha$ then the discrete dynamical system generated by the iterates of the secant map exhibits a critical periodic orbit of period 3 or three-cycle at the point $(\alpha,

Cristian J. Vaca-Rubio, Luis Blanco, Roberto Pereira, Màrius Caus

This paper introduces a novel application of Kolmogorov-Arnold Networks (KANs) to time series forecasting, leveraging their adaptive activation functions for enhanced predictive modeling. Inspired by the Kolmogorov-Arnold representation theorem, KANs replace traditional linear weights with spline-parametrized univariate functions, allowing them to learn acti

Lars Fritsche, Alexander Lauer, Maximilian Kratz, Andy Schürr

When using graphs and graph transformations to model systems, consistency is an important concern. While consistency has primarily been viewed as a binary property, i.e., a graph is consistent or inconsistent with respect to a set of constraints, recent work has presented an approach to consistency as a graduated property. This allows living with inconsisten

Nicholas Harvey, Arvin Sahami

Orthogonal arrays are a type of combinatorial design that were developed in the 1940s in the design of statistical experiments. In 1947, Rao proved a lower bound on the size of any orthogonal array, and raised the problem of constructing arrays of minimum size. Kuperberg, Lovett and Peled (2017) gave a non-constructive existence proof of orthogonal arrays wh

Tiantian Zhang, Manxi Lin, Hongda Guo, Xiaofan Zhang

The Prostate Imaging Reporting and Data System (PI-RADS) is pivotal in the diagnosis of clinically significant prostate cancer through MRI imaging. Current deep learning-based PI-RADS scoring methods often lack the incorporation of common PI-RADS clinical guideline~(PICG) utilized by radiologists, potentially compromising scoring accuracy. This paper introdu

Margaret Z. Buhariwalla, L. C. Gallo, J. Mao, J. Jiang

Previous X-ray works on Mrk 1239 have revealed a complex Narrow Line Seyfert 1 (NLS1) that exhibits substantial absorption and strong emission from both collisional (CIE) and photoionized (PIE) plasmas. Here, we report on deep-pointed observations with $XMM{\rm -}Newton$ and $NuSTAR$, along with $Swift$ monitoring, to understand the $0.3-30$ keV continuum em

Aehong Min, Xuan Wang, Rion Brattig Correia, Jordan Rozum

We used a dictionary built from biomedical terminology extracted from various sources such as DrugBank, MedDRA, MedlinePlus, TCMGeneDIT, to tag more than 8 million Instagram posts by users who have mentioned an epilepsy-relevant drug at least once, between 2010 and early 2016. A random sample of 1,771 posts with 2,947 term matches was evaluated by human anno

Qiang Ma, Kaili Liang, Liu Li, Saga Masui

The Developing Human Connectome Project (dHCP) aims to explore developmental patterns of the human brain during the perinatal period. An automated processing pipeline has been developed to extract high-quality cortical surfaces from structural brain magnetic resonance (MR) images for the dHCP neonatal dataset. However, the current implementation of the pipel

Sergio Grancagnolo

Several theories beyond the Standard Model (BSM) predict heavy neutral leptons, or long-lived particles with unique signatures which are difficult to reconstruct. Another area of interest are vector-like quarks which lie at the heart of many extensions to the Standard Model seeking to address the Hierarchy Problem, as they can naturally cancel the mass diver

Italo J. Dejter

Let $2\le k\in\mathbb{Z}$. A total coloring of a $k$-regular simple graph via $k+1$ colors is an {\it efficient total coloring} if each color yields an efficient dominating set, where the efficient domination condition applies to the restriction of each color class to the vertex set. In this work, focus is set upon graphs of girth $k+1$. Efficient total colo

Gregory Holste, Mingquan Lin, Ruiwen Zhou, Fei Wang

Deep learning has enabled breakthroughs in automated diagnosis from medical imaging, with many successful applications in ophthalmology. However, standard medical image classification approaches only assess disease presence at the time of acquisition, neglecting the common clinical setting of longitudinal imaging. For slow, progressive eye diseases like age-

Lien T. P. Ta, Huong T. T. Tran

Most Mahonian statistics can be expressed as a linear combination of vincular patterns. This is not only true with statistics on the permutation set, but it can also be applied for statistics on the permutation with repetition set. By following the method extending the vincular patterns combinations presented by Kitaev and Vajnovszki, we discover 8 vincular-

G. L. Smith, C. D. Hoyle, J. H. Gundlach, E. G. Adelberger

We tested the equivalence principle at short length scales by rotating a 3-ton $^{238}$U attractor around a compact torsion balance containing Cu and Pb test bodies. The observed differential acceleration of the test bodies toward the attractor, $a_{\text{Cu}}-a_{\text{Pb}} =(1.0\pm2.8)\times 10^{-13}$ cm/s$^2$, should be compared to the corresponding gravit

Wanqi Zhou, Shuanghao Bai, Shujian Yu, Qibin Zhao

With the advancement of neural networks, diverse methods for neural Granger causality have emerged, which demonstrate proficiency in handling complex data, and nonlinear relationships. However, the existing framework of neural Granger causality has several limitations. It requires the construction of separate predictive models for each target variable, and t

Sean Dawson, Holger Dullin

We study the family of quantum integrable systems that arise from separating the Schr\"odinger equation in all 6 separable orthogonal coordinates on the 3 sphere: ellipsoidal, prolate, oblate, Lam\'{e}, spherical and cylindrical. On the one hand each separating coordinate system gives rise to a quantum integrable system on S2 x S2, on the other hand it also

Ludovica Serricchio, Dario Bocchi, Claudio Chilin, Raffaele Marino

To improve the storage capacity of the Hopfield model, we develop a version of the dreaming algorithm that perpetually reinforces the patterns to be stored (as in the Hebb rule), and erases the spurious memories (as in dreaming algorithms). For this reason, we called it Daydreaming. Daydreaming is not destructive and it converges asymptotically to stationary

Nancy Hada, Aditya Singh, Kavita Vemuri

Indian folk paintings have a rich mosaic of symbols, colors, textures, and stories making them an invaluable repository of cultural legacy. The paper presents a novel approach to classifying these paintings into distinct art forms and tagging them with their unique salient features. A custom dataset named FolkTalent, comprising 2279 digital images of paintin

Pouria Abbasalinejad, Hamid Tebyanian

This paper presents an alternative approach to quantum entanglement, one that effectively resolves the logical inconsistencies without leading to logical contradictions. By addressing some of the inconsistencies within quantum mechanics, such as state superposition and non-locality, that challenge classical causal explanations, our method is constructed on t

A. C. L. Santos, R. V. Maluf, C. R. Muniz

This work presents a new wormhole solution in General Relativity supported by the quantum vacuum fluctuations of the Casimir effect between perfect chromometallic mirrors in $(3+1)$ dimensions, which was recently fitted using first-principle numerical simulations. Initially, we employ a perturbative approach for $x = m r \ll 1$, where $m$ represents the Casi

Aditya Raghavan, Rohit Pant, Ichiro Takeuchi, Eugene A. Eliseev

Combinatorial spread libraries offer a unique approach to explore evolution of materials properties over the broad concentration, temperature, and growth parameter spaces. However, the traditional limitation of this approach is the requirement for the read-out of functional properties across the library. Here we demonstrate the application of automated Piezo

Sergio Ferrando Solera, Antonio Pich, Luiz Vale Silva

While the third run of the Large Hadron Collider (LHC) is ongoing, the underlying theory that extends the Standard Model remains so far unknown. Left-Right Models (LRMs) introduce a new gauge sector, and can restore parity symmetry at high enough energies. If LRMs are indeed realized in nature, the mediators of the new weak force can be searched for in colli

Javier A. Lemus, Benjamin Herrmann

The sparse identification of nonlinear dynamics (SINDy) has been established as an effective technique to produce interpretable models of dynamical systems from time-resolved state data via sparse regression. However, to model parameterized systems, SINDy requires data from transient trajectories for various parameter values over the range of interest, which

Jan Glaubitz, Jan Nordström, Philipp Öffner

We introduce a novel construction procedure for one-dimensional summation-by-parts (SBP) operators. Existing construction procedures for FSBP operators of the form $D = P^{-1} Q$ proceed as follows: Given a boundary operator $B$, the norm matrix $P$ is first determined and then in a second step the complementary matrix $Q$ is calculated to finally get the FS

Young-Hwan Hyun, Boris Latosh, Miok Park

We investigate scalar field perturbations of the hairy black holes involved with spontaneous symmetry breaking of the global U(1) symmetry in Einstein-scalar-Gauss-Bonnet theory for asymptotically flat spacetimes. We consider the mechanism that black holes without hairs become unstable at the critical point of the coupling constant and undergo a phase transi

Yulin Wang, Yang Yue, Rui Lu, Yizeng Han

The superior performance of modern visual backbones usually comes with a costly training procedure. We contribute to this issue by generalizing the idea of curriculum learning beyond its original formulation, i.e., training models using easier-to-harder data. Specifically, we reformulate the training curriculum as a soft-selection function, which uncovers pr

Marcelo Barbosa, Horatiu Nastase, Carlos Nunez, Ricardo Stuardo

In this paper we consider the Penrose limit in the case of two gravity duals. One of them, consists of compactified I-branes (intersecting sets of D5-branes over $(1+1)$ dimensions). The second consists of D5-branes compactified on a circle. Both compactifications preserve SUSY. We find a match of the oscillators and masses of string modes on the resulting p

Claus Hofmann, Simon Schmid, Bernhard Lehner, Daniel Klotz

Out-of-distribution (OOD) detection is critical when deploying machine learning models in the real world. Outlier exposure methods, which incorporate auxiliary outlier data in the training process, can drastically improve OOD detection performance compared to approaches without advanced training strategies. We introduce Hopfield Boosting, a boosting approach

Jie Zhang, Yuhan Li, Yude Wang, Stephen Lin

Few-shot segmentation (FSS) aims to train a model which can segment the object from novel classes with a few labeled samples. The insufficient generalization ability of models leads to unsatisfactory performance when the models lack enough labeled data from the novel classes. Considering that there are abundant unlabeled data available, it is promising to im

Holt Bodish

We study a family of $(1,1)$-pattern knots that generalize the Mazur pattern, and compute the concordance invariants $\tau$ and $\epsilon$ of $n$-twisted satellites formed from these patterns. We show that none of the $n$-twisted patterns from this family act surjectively on the smooth or rational concordance group. We also determine when the $n$-twisted gen

Greg Tystahl, Yasemin Acar, Michel Cukier, William Enck

Supply chain security has become a very important vector to consider when defending against adversary attacks. Due to this, more and more developers are keen on improving their supply chains to make them more robust against future threats. On March 7th, 2024 researchers from the Secure Software Supply Chain Center (S3C2) gathered 14 industry leaders, develop

Enrique Bello-Benítez, Alberto Marín-Cebrián, Eduardo Ahedo

The electron-cyclotron drift instability (ECDI) has been proposed as one of the main actors behind the anomalous transport of electrons in Hall plasmas. In this work, we revisit the classical theory of this instability [Forslund et al., Phys. Rev. Lett. 25, 1266 (1970)] and perform two-dimensional kinetic simulations under several conditions to analyze the n

Akhila Yerukola, Saujas Vaduguru, Daniel Fried, Maarten Sap

Humans often express their communicative intents indirectly or non-literally, which requires their interlocutors -- human or AI -- to understand beyond the literal meaning of words. While most existing work has focused on discriminative evaluations, we present a new approach to generatively evaluate large language models' (LLMs') intention understanding by e

Jiayue Wang, Ben Boukai

In this paper, we propose an optimal sequential procedure for the early detection of potential side effects resulting from the administration of some treatment (e.g. a vaccine, say). The results presented here extend previous results obtained in Wang and Boukai (2024) who study the single side effect case to the case of two (or more) side effects. While the

Chandrachur Chakraborty, Sudip Bhattacharyya, Pankaj S. Joshi

Near-solar mass black holes (BHs) could have been involved in the two recent gravitational wave events, GW190425 and GW190814. Since such a low mass BH cannot be formed via stellar evolution, a model has been proposed based on the core collapse of a neutron star initiated by a certain number of dark matter (DM) particles. In this process, the accumulated DM

Eddye Bustamante, José Jiménez Urrea, Jorge Mejía

In this work we prove that the initial-boundary value problem (IBVP) for the fifth order Korteweg-de Vries equation \begin{align*} \left. \begin{array}{rlr} u_t+\partial_x^5 u+u\partial_x u&\hspace{-2mm}=0,&\quad x\in\mathbb R^+,\; t\in\mathbb R^+,\\ u(x,0)&\hspace{-2mm}=g(x),&\\ u(0,t)=h_1(t),\, \partial_x u(0,t)&\hspace{-2mm}=h_2(t),\,\partial_x^2 u(0,t)=h

Matt Pharr, Bartlomiej Wronski, Marco Salvi, Marcos Fajardo

2D texture maps and 3D voxel arrays are widely used to add rich detail to the surfaces and volumes of rendered scenes, and filtered texture lookups are integral to producing high-quality imagery. We show that applying the texture filter after evaluating shading generally gives more accurate imagery than filtering textures before BSDF evaluation, as is curren

Samuel Tesfazgi, Leonhard Sprandl, Armin Lederer, Sandra Hirche

Learning from expert demonstrations to flexibly program an autonomous system with complex behaviors or to predict an agent's behavior is a powerful tool, especially in collaborative control settings. A common method to solve this problem is inverse reinforcement learning (IRL), where the observed agent, e.g., a human demonstrator, is assumed to behave accord

Syed Mhamudul Hasan, Alaa M. Alotaibi, Sajedul Talukder, Abdur R. Shahid

With the proliferation of edge devices, there is a significant increase in attack surface on these devices. The decentralized deployment of threat intelligence on edge devices, coupled with adaptive machine learning techniques such as the in-context learning feature of Large Language Models (LLMs), represents a promising paradigm for enhancing cybersecurity

Urvij Saroliya, Eishi Arima, Dai Liu, Martin Schulz

GPU-based heterogeneous architectures are now commonly used in HPC clusters. Due to their architectural simplicity specialized for data-level parallelism, GPUs can offer much higher computational throughput and memory bandwidth than CPUs in the same generation do. However, as the available resources in GPUs have increased exponentially over the past decades,

Erwin Bolthausen, Wolfgang Koenig, Chiranjib Mukherjee

We consider a model of $d$-dimensional interacting quantum Bose gas, expressed in terms of an ensemble of interacting Brownian bridges in a large box and undergoing the influence of all the interactions between the legs of each of the Brownian bridges. We study the thermodynamic limit of the system and give an explicit formula for the limiting free energy an

Samuel Ameyaw, Lin Lin, Bo Zhao, Hamish Carr Delgado

High Q phase gradient metasurfaces are becoming promising elements for revolutionizing light manipulation but near-field coupling typically forces a trade-off between quality factor and resolution. Here, we show a strategy for not just reducing but eliminating coupling-based nonlocal effects in wave shaping metasurfaces composed of meta-pixels with arbitrari

Waqas Riaz

Effective Field Theory (EFT) stands as a cornerstone in modern theoretical physics, offering a powerful framework for describing the dynamics of physical systems across a wide range of energy scales. This article provides an in-depth exploration of EFT and its diverse applications in various branches of physics. Beginning with a foundational overview of EFT

Alapan Kuila, Sudeshna Sarkar

Navigating the complex landscape of news articles involves understanding the various actors or entities involved, referred to as news stakeholders. These stakeholders, ranging from policymakers to opposition figures, citizens, and more, play pivotal roles in shaping news narratives. Recognizing their stakeholder types, reflecting their roles, political align

Simone Zoia

I present the computation of the two-loop amplitudes for the scattering of a lepton pair with an off-shell and an on-shell photon in massless QED. We apply modern techniques developed to tackle QCD amplitudes with many scales: we express the Feynman integrals in terms of a basis of special functions, and reconstruct the amplitudes from numerical finite-field

Jiangyong Jia, Chunjian Zhang, Shengli Huang

Ultrarelativistic collisions of atomic nuclei produce the quark--gluon plasma (QGP), an extremely hot, dense state of matter. The QGP behaves like a nearly perfect fluid, so its final-state momentum distributions can be inverted to reveal its initial-state geometry. This programme has succeeded in the transverse plane but made less progress along the beam, w

Zhimin Li, Jianwei Zhang, Qin Lin, Jiangfeng Xiong

We present Hunyuan-DiT, a text-to-image diffusion transformer with fine-grained understanding of both English and Chinese. To construct Hunyuan-DiT, we carefully design the transformer structure, text encoder, and positional encoding. We also build from scratch a whole data pipeline to update and evaluate data for iterative model optimization. For fine-grain

Yann Issartel, Christophe Giraud, Nicolas Verzelen

We consider the seriation problem, whose goal is to recover a hidden ordering from a noisy observation of a permuted Robinson matrix. We establish sharp minimax rates under average-Lipschitz conditions that strictly extend the bi-Lipschitz framework of [Giraud et al., 2023]. We further design a polynomial-time algorithm that attains these optimal rates, ther

Louis Boucherie, Benjamin F. Maier, Sune Lehmann

Driven by access to large volumes of movement data, the study of human mobility has grown rapidly over the past decades. The field has shown that human mobility is scale-free, proposed models to generate scale-free moving distance distributions, and explained how the scale-free distribution arises. It has not, however, explicitly addressed how mobility is st

Wei Sun, Linhan Cao, Jun Jia, Zhichao Zhang

Blind video quality assessment (BVQA) is a highly challenging task due to the intrinsic complexity of video content and visual distortions, especially given the high popularity of social media videos, which originate from a wide range of sources, and are often processed by various compression and enhancement algorithms. While recent BVQA and blind image qual

Douglas Edmonds, Joshua Erlich, Djordje Minic, Tatsu Takeuchi

Observations of velocity dispersions of galactic structures over a wide range of scales point to the existence of a universal acceleration scale $a_0\sim 10^{-10}$ m/s$^2$. Focusing on the fuzzy dark matter paradigm, which proposes ultralight dark matter with mass around $10^{-22}$ eV and de Broglie wavelength $\lambda\sim {\rm few}\times10^{2}$ parsecs, we

Nicolas Gigena, Ekta Panwar, Giovanni Scala, Mateus Araújo

The degree of experimentally attainable nonlocality, as gauged by the loophole-free or effective violation of Bell inequalities, remains severely limited due to inefficient detectors. We address an experimentally motivated question: Which quantum strategies attain the maximal loophole-free nonlocality in the presence of inefficient detectors? For any Bell in

Yicheng Hsu, Mingsian R. Bai

Binaural Audio Telepresence (BAT) aims to encode the acoustic scene at the far end into binaural signals for the user at the near end. BAT encompasses an immense range of applications that can vary between two extreme modes of Immersive BAT (I-BAT) and Enhanced BAT (E-BAT). With I-BAT, our goal is to preserve the full ambience as if we were at the far end, w

Maximilien Gadouleau, Luca Mariot, Federico Mazzone

We consider the construction of maximal families of polynomials over the finite field $\mathbb{F}_q$, all having the same degree $n$ and a nonzero constant term, where the degree of the GCD of any two polynomials is $d$ with $1 \le d\le n$. The motivation for this problem lies in a recent construction for subspace codes based on cellular automata. More preci

Zifeng Zhuang, Dengyun Peng, Jinxin Liu, Ziqi Zhang

As a data-driven paradigm, offline reinforcement learning (RL) has been formulated as sequence modeling that conditions on the hindsight information including returns, goal or future trajectory. Although promising, this supervised paradigm overlooks the core objective of RL that maximizes the return. This overlook directly leads to the lack of trajectory sti

Craig E. DeForest, Daniel B. Seaton, Amir Caspi, Matt Beasley

We present the design of a portable coronagraph, CATEcor, that incorporates a novel "shaded truss" style of external occultation and serves as a proof-of-concept for that family of coronagraphs. The shaded truss design style has the potential for broad application in various scientific settings. We conceived CATEcor itself as a simple instrument to observe t

Alec McClean, Zach Branson, Edward H. Kennedy

In causal inference, sensitivity models assess how unmeasured confounders could alter causal analyses, but the sensitivity parameter -- which quantifies the degree of unmeasured confounding -- is often difficult to interpret. For this reason, researchers sometimes compare the sensitivity parameter to an estimate of measured confounding. This is known as cali

Thomas Blommel, David J. Gardner, Carol S. Woodward, Emanuel Gull

The non-equilibrium Green's function gives access to one-body observables for quantum systems. Of particular interest are quantities such as density, currents, and absorption spectra which are important for interpreting experimental results in quantum transport and spectroscopy. We present an integration scheme for the Green's function's equations of motion,

Oday Hazaimah

In this paper we consider a class of second order singular homogeneous differential equations called the Lane-Emden-type with time singularity in the drift coefficient. Lane-Emden equations are singular initial value problems that model phenomena in astrophysics such as stellar structure and are governed by polytropics with applications in isothermal gas sph

Stacey R. Smith?, Tyler Meadows, Gail S. K. Wolkowicz

Self-cycling fermentation is an automated process used for culturing microorganisms. We consider a model of $n$ distinct species competing for a single non-reproducing nutrient in a self-cycling fermentor in which the nutrient level is used as the decanting condition. The model is formulated in terms of impulsive ordinary differential equations. We prove tha

Bogdan Nica

Consider a graph on the non-singular matrices over a finite field, in which two distinct non-singular matrices are joined by an edge whenever their sum is singular. We prove an upper bound for the independence number of this graph. As a consequence, we obtain a lower bound for its chromatic number that significantly improves a previous result of Tomon.

Zichen Wang, Xi Deng, Ziyi Zhang, Wenzel Jakob

We present a simple algorithm for differentiable rendering of surfaces represented by Signed Distance Fields (SDF), which makes it easy to integrate rendering into gradient-based optimization pipelines. To tackle visibility-related derivatives that make rendering non-differentiable, existing physically based differentiable rendering methods often rely on ela

Derya Malak, Mohammad Reza Deylam Salehi, Berksan Serbetci, Petros Elia

The work here studies the communication cost for a multi-server multi-task distributed computation framework, and does so for a broad class of functions and data statistics. Considering the framework where a user seeks the computation of multiple complex (conceivably non-linear) tasks from a set of distributed servers, we establish communication cost upper b

William Yang, Michael Posa

Non-prehensile manipulation enables fast interactions with objects by circumventing the need to grasp and ungrasp as well as handling objects that cannot be grasped through force closure. Current approaches to non-prehensile manipulation focus on static contacts, avoiding the underactuation that comes with sliding. However, the ability to control sliding con