February 2024 arXiv papers — page 94

Yiming Bian, Yan Pan, Xuesong Xu, Liang Zhao

Quantum key distribution, which ensures information-theoretically secret key generation, is currently advancing through photonic integration to achieve high performance, cost reduction and compact size, thereby facilitating the large-scale deployment. Continuous-variable quantum key distribution is an attractive approach for photonic integrations due to its

M. Sharif, M. Sallah

This paper uses the gravitational decoupling through the minimal geometric deformation approach and extends a known isotropic solution for a self-gravitating interior to two types of anisotropic spherical solutions in Rastall gravity in the presence of electromagnetic field. By deforming only the radial metric component, the field equations are decoupled int

Joseph E. Lawrence, Imaad M. Ansari, Jonathan R. Mannouch, Meghna A. Manae

In response to a community prediction challenge, we simulate the nonadiabatic dynamics of cyclobutanone using the mapping approach to surface hopping (MASH). We consider the first 500 fs of relaxation following photo-excitation to the S2 state and predict the corresponding time-resolved electron-diffraction signal that will be measured by the planned experim

Jun Zhuang, Casey Kennington

As new research on Large Language Models (LLMs) continues, it is difficult to keep up with new research and models. To help researchers synthesize the new research many have written survey papers, but even those have become numerous. In this paper, we develop a method to automatically assign survey papers to a taxonomy. We collect the metadata of 144 LLM sur

Ying Li, Yue Sun, Zhi-Tian Zou

Within QCD factorization approach, we employ the new results of form factors of $B_s \to \phi$ and calculate the branching fractions, CP asymmetries (CPAs) and polarization fractions of the decay modes $B_s \to \phi (\rho^0, \omega)$ in both the standard model (SM) and the family non-universal $Z^\prime$ model. We find that in SM the above observables are re

Peijun Li, Jue Wang

This paper presents a thorough investigation into nonradiating sources of Maxwell's equations. Various characterizations are developed to clarify the properties of nonradiating sources, considering their varying degrees of regularity. Furthermore, the characterizations are examined on far-field patterns and near-field data of the electric field, along with t

Yang Guo, Hao Xie, Yan-Gang Miao

We discuss the intrinsic relations between thermodynamic phase transitions and quasinormal modes in regular AdS black holes, specifically in the Bardeen and Hayward AdS classes. To this end, we calculate the quasinormal modes of massless scalar field perturbations around small and large black holes via the Horowitz-Hubeny method. By investigating the isobari

Xueping Zhao, Susanne Liese, Alf Honigmann, Frank Jülicher

Biomolecules, such as proteins and RNAs, can phase separate in the cytoplasm of cells to form biomolecular condensates. Such condensates are liquid-like droplets that can wet biological surfaces such as membranes. Many molecules that participate in phase separation can also reversibly bind to membrane surfaces. When a droplet wets a surface, molecules can di

Ji-Hoon Park, Yeong-Joon Ju, Seong-Whan Lee

Diffusion models have demonstrated remarkable performance in generation tasks. Nevertheless, explaining the diffusion process remains challenging due to it being a sequence of denoising noisy images that are difficult for experts to interpret. To address this issue, we propose the three research questions to interpret the diffusion process from the perspecti

Jun-Jie Zhang, Deyu Meng

Neural networks demonstrate inherent vulnerability to small, non-random perturbations, emerging as adversarial attacks. Such attacks, born from the gradient of the loss function relative to the input, are discerned as input conjugates, revealing a systemic fragility within the network structure. Intriguingly, a mathematical congruence manifests between this

Jin-Hwa Kim

Recent advancements in visualizing deep neural networks provide insights into their structures and mesh extraction from Continuous Piecewise Affine (CPWA) functions. Meanwhile, developments in neural surface representation learning incorporate non-linear positional encoding, addressing issues like spectral bias; however, this poses challenges in applying mes

Takuya Ikeda

The maximum hands-off control is the optimal solution to the L0 optimal control problem. It has the minimum support length among all feasible control inputs. To avoid computational difficulties arising from its combinatorial nature, the convex approximation method that replaces the L0 norm by the L1 norm in the cost function has been employed on standard. Ho

Hae Jin Song, Mahyar Khayatkhoei, Wael AbdAlmageed

Recent works have shown that generative models leave traces of their underlying generative process on the generated samples, broadly referred to as fingerprints of a generative model, and have studied their utility in detecting synthetic images from real ones. However, the extend to which these fingerprints can distinguish between various types of synthetic

Sergio Servantez, Joe Barrow, Kristian Hammond, Rajiv Jain

Rule-based reasoning, a fundamental type of legal reasoning, enables us to draw conclusions by accurately applying a rule to a set of facts. We explore causal language models as rule-based reasoners, specifically with respect to compositional rules - rules consisting of multiple elements which form a complex logical expression. Reasoning about compositional

Jess Stephenson, Nathan T. Duncan, Melissa Greeff

Heterogeneous autonomous robot teams consisting of multirotor and uncrewed surface vessels (USVs) have the potential to enable various maritime applications, including advanced search-and-rescue operations. A critical requirement of these applications is the ability to land a multirotor on a USV for tasks such as recharging. This paper addresses the challeng

Haiyang Liu, Yang Zhang, Vidya Saikrishna, Quanquan Tian

Code smells indicate the potential problems of software quality so that developers can identify refactoring opportunities by detecting code smells. State-of-the-art approaches leverage heuristics, machine learning, and deep learning to detect code smells. However, existing approaches have not fully explored the potential of large language models (LLMs). In t

Yuuki Yamanaka, Tomokatsu Takahashi, Takuya Minami, Yoshiaki Nakajima

System logs are some of the most important information for the maintenance of software systems, which have become larger and more complex in recent years. The goal of log-based anomaly detection is to automatically detect system anomalies by analyzing the large number of logs generated in a short period of time, which is a critical challenge in the real worl

Yingjie Ma, Xi Gao, Chao Liu, Jie Li

Feasible path algorithms have been widely used for process optimisation due to its good convergence. The sequential quadratic programming (SQP) algorithm is usually used to drive the feasible path algorithms towards optimality. However, existing SQP algorithms may suffer from inconsistent quadratic programming (QP) subproblems and numerical noise, especially

Emanuele Parisi, Alberto Musa, Maicol Ciani, Francesco Barchi

RISC-V open-source systems are emerging in deployment scenarios where safety and security are critical. OpenTitan is an open-source silicon root-of-trust designed to be deployed in a wide range of systems, from high-end to deeply embedded secure environments. Despite the availability of various cryptographic hardware accelerators that make OpenTitan suitable

Long Ma, Zhe Liu, Bowen Ai, Jia Man

Short nanopores find extensive applications capitalizing on their high throughput and detection resolution. Ionic behaviors through long nanopores are mainly determined by charged inner-pore walls. When pore lengths decrease to sub-200 nm, charged exterior surfaces provide considerable modulation to ion current. We find that the charge status of inner-pore w

Leonard M. Adleman

Living things, computers, societies, and even books are part of a grand evolutionary struggle to survive. That struggle shapes nature, nations, religions, art, science, and you. What you think, feel, and do is determined by it. Darwinian evolution does not apply solely to the genes that are stored in DNA. Using the insights of Alan Turing and Richard Dawkins

Yimu Wang, He Zhao, Ruizhi Deng, Frederick Tung

Pretext training followed by task-specific fine-tuning has been a successful approach in vision and language domains. This paper proposes a self-supervised pretext training framework tailored to event sequence data. We introduce a novel alignment verification task that is specialized to event sequences, building on good practices in masked reconstruction and

Fumika Suzuki, S. A. Shah, Diego A. R. Dalvit, Markus Arndt

We theoretically investigate the influence of chiral Casimir-Polder (CP) forces in Talbot-Lau interferometry, based on three nanomechanical gratings. We study scenarios where the second grating is either directly written into a chiral material or where the nanomask is coated with chiral substances. We show requirements for probing enantiospecific effects in

Hai-Bin Hu, Hai-Qin Wang, Rui Xue, Fang-Kun Peng

Previous studies on the fitting of spectral energy distributions (SEDs) often apply the external-Compton process to interpret the high-energy peak of low-synchrotron-peaked (LSP) BL Lac objects (LBLs), despite the lack of strong broad emission lines observed for LBLs. In this work, we collect quasi-simultaneous multi-wavelength data of 15 LBLs from the Fermi

Maha Ali Allouzi, Javed Khan

Internet of Medical Things (IoMT) deals with a patient-data-rich segment, which makes security and privacy a severe concern for patients. Therefore, access control is a significant aspect of ensuring trust in the IoMT. However, deploying existing authentication and authorization solutions to the Internet of Medical Things (IoMT) is not straightforward becaus

Azfar Adib, Wei-Ping Zhu, M. Omair Ahmad

Age verification, which is a mandatory legal requirement for delivering certain age-appropriate services or products, has recently been emphasized around the globe to ensure online safety for children. The rapid advancement of artificial intelligence has facilitated the recent development of some cutting-edge age-verification technologies, particularly using

Peter Eckmann, Dongxia Wu, Germano Heinzelmann, Michael K Gilson

Current generative models for drug discovery primarily use molecular docking to evaluate the quality of generated compounds. However, such models are often not useful in practice because even compounds with high docking scores do not consistently show experimental activity. More accurate methods for activity prediction exist, such as molecular dynamics based

Gurjot Singh Bhatia, Yoann Corre, Thierry Tenoux, M. Di Renzo

Reconfigurable Intelligent Surfaces (RISs) have risen to the forefront of wireless communications research due to their proactive ability to alter the wireless environment intelligently, promising improved wireless network capacity and coverage. Thus, RISs are a pivotal technology in evolving next-generation communication networks. This paper demonstrates a

Tanmoy Biswas, Marcin Łobejko, Paweł Mazurek, Michał Horodecki

We consider a model of heat engine operating in the microscopic regime: the two-stroke engine. It produces work and exchanges heat in two discrete strokes that are separated in time. The working body of the engine consists of two $d$-level systems initialized in thermal states at two distinct temperatures. Additionally, an auxiliary non-equilibrium system ca

Fabrizio Colombo, Peter Schlosser

In contrast to the classical complex spectral theory, where the spectrum is related to the invertibility of $\lambda-A:D(A)\subseteq X_\mathbb{C}\rightarrow X_\mathbb{C}$, in the noncommutative quaternionic $S$-spectral theory one uses the invertibility of the second order polynomial $Q_s(T):=T^2-2\text{Re}(s)T+|s|^2:D(T^2)\subseteq X\rightarrow X$ to define

Tess Van Daele, Akhil Iyer, Yuning Zhang, Jalyn C. Derry

Short videos on platforms such as TikTok, Instagram Reels, and YouTube Shorts (i.e. short-form videos) have become a primary source of information and entertainment. Many short-form videos are inaccessible to blind and low vision (BLV) viewers due to their rapid visual changes, on-screen text, and music or meme-audio overlays. In our formative study, 7 BLV v

Yan Kang, Hao Lin, Mingjian Yang, Shin-Jye Lee

The rapid advancement of high-quality image generation models based on AI has generated a deluge of anime illustrations. Recommending illustrations to users within massive data has become a challenging and popular task. However, existing anime recommendation systems have focused on text features but still need to integrate image features. In addition, most m

Ajay Patel, Colin Raffel, Chris Callison-Burch

Large language models (LLMs) have become a dominant and important tool for NLP researchers in a wide range of tasks. Today, many researchers use LLMs in synthetic data generation, task evaluation, fine-tuning, distillation, and other model-in-the-loop research workflows. However, challenges arise when using these models that stem from their scale, their clos

Abdelilah Karara, Mohamed Rossafi

In this paper, we will introduce the new concept of K-bi-g-frames for Hilbert spaces. Then, we examine some characterizations with the help of a biframe operator. Finally, we investigate several results about the stability of K-bi-g-frames are produced via the use of frame theory methods.

George F. Seelinger, Wenhua Zhao

Let $F$ be an algebraically closed field and let $n\geq 3$. Consider $V=F^n$ with standard basis $\{\vec{e}_1,\ldots,\vec{e}_n\}$ and its dual space $V^*= {\mathrm{Hom}}_{F-{\mathrm{lin}}}(V,F)$ with dual basis $\{y_1,\ldots,y_n\}\subseteq V^*$ and let $\vec{y} = \sum_i y_i\otimes \vec{e}_i\in V^*\otimes V$. Let $d<n$ and consider the vectors $\vec{q}_1,\ldo

Estevan Luiz da Silva, João Marcos do Ó

Global pointwise estimates are obtained for quasilinear Lane-Emden-type systems involving measures in the "sublinear growth" rate. We give necessary and sufficient conditions for existence expressed in terms of Wolff's potential. Our approach is based on recent advances due to Kilpel\"{a}inen and Mal\'{y} in the potential theory. This method enables us to tr

Usha Bhalla, Alex Oesterling, Suraj Srinivas, Flavio P. Calmon

CLIP embeddings have demonstrated remarkable performance across a wide range of multimodal applications. However, these high-dimensional, dense vector representations are not easily interpretable, limiting our understanding of the rich structure of CLIP and its use in downstream applications that require transparency. In this work, we show that the semantic

Junhyun Lee, Wooseong Yang, Jaewoo Kang

In the evolving landscape of machine learning, the adaptation of pre-trained models through prompt tuning has become increasingly prominent. This trend is particularly observable in the graph domain, where diverse pre-training strategies present unique challenges in developing effective prompt-based tuning methods for graph neural networks. Previous approach

Ludovick Bouthat

Riemann sums, a classical method for approximating the definite integral of a function, have been extensively studied in the past. However, their monotonic properties, while still of great importance, particularly in approximation theory and interpolation theory, remain somewhat obscure. This paper is dedicated to proving general theorems about the monotonic

Patrick van Meurs, Kenkichi Tsunoda, Lu Xu

We establish the incompressible limit of weakly asymmetric simple exclusion processes coupled through particle collisions. The incompressible limit depends on various parameters in the particle system and is linked to fluid dynamics equations. Our main contributions to previous results are the extension of the parameter space and the focus on local particle

Taisuke Kobayashi

Experience replay (ER) used in (deep) reinforcement learning is considered to be applicable only to off-policy algorithms. However, there have been some cases in which ER has been applied for on-policy algorithms, suggesting that off-policyness might be a sufficient condition for applying ER. This paper reconsiders more strict "experience replayable conditio

Yanis Labrak, Adrien Bazoge, Emmanuel Morin, Pierre-Antoine Gourraud

Large Language Models (LLMs) have demonstrated remarkable versatility in recent years, offering potential applications across specialized domains such as healthcare and medicine. Despite the availability of various open-source LLMs tailored for health contexts, adapting general-purpose LLMs to the medical domain presents significant challenges. In this paper

Mark Mandelkern

A long-standing, unanswered question regarding Euclid's Elements concerns the absence of a theorem for the concurrence of the altitudes of a triangle, and the possible reasons for this omission. In the centuries following Euclid, a remarkable number of proofs have been put forward; this suggests a search for the most elementary and direct proof. This paper p

Tyler Toner, Vahidreza Molazadeh, Miguel Saez, Dawn M. Tilbury

Robotic manipulation of deformable linear objects (DLOs) is an active area of research, though emerging applications, like automotive wire harness installation, introduce constraints that have not been considered in prior work. Confined workspaces and limited visibility complicate prior assumptions of multi-robot manipulation and direct measurement of DLO co

Nicole Rodriguez Cavero

The Imaging X-ray Polarimetry Explorer (IXPE), launched on December 9, 2021, enables X-ray polarimetric observations with unprecedented sensitivity in the 2-8 keV energy range. X-ray polarization allows us to test accretion disk, corona, and emission models of stellar-mass black holes in X-ray binaries found predominantly in soft and hard states of accretion

Chris Lowder, Chris Gilly, Craig DeForest

We describe a novel method for modeling the global, steady solar wind using photospheric magnetic fields as a driving boundary condition. Prior wind models in this class include both rapid heuristic methods that use potential field extrapolation and variants thereof, trading rigor for computation speed, and detailed 3D magnetohydrodynamic (MHD) models that a

Nikolay Grantcharov

Given a semisimple reductive group $G$ and a smooth projective curve $X$ over an algebraically closed field $k$ of arbitrary characteristic, let $\text{Bun}_G$ denote the moduli space of principal $G$-bundles over $X$. For a bundle $P\in\text{Bun}_G$ without infinitesimal symmetries, we provide a description of all divided-power infinitesimal jet spaces, $J_

Diego A. Sousa, Fco. Rafael M. Lima, Victor F. Monteiro, Tarcisio F. Maciel

Millimeter wave (mmWave) and sub-THz communications, foreseen for sixth generation (6G), suffer from high propagation losses which affect the network coverage. To address this point, smart entities such as network-controlled repeaters (NCRs) have been considered as cost-efficient solutions for coverage extension. NCRs, which have been standardized in 3rd gen

Zhan Li, Jiayang Chen, Zhaohui Ma, Chao Tang

We demonstrate parametric all-optical modulation in a periodically-poled lithium niobate microring resonator on chip. It employs quantum Zeno blockade between two distinct waves, a signal and a pump, through their sum-frequency generation at a large per-photon efficiency of 8.2 MHz. With nanosecond pump pulses at 6 mW peak power, 85.7% modulation extinction

Alex Xu

We construct infinitely many examples of finite volume 4-manifolds with $T^3$ ends that do not admit any cusped asymptotically hyperbolic Einstein metrics yet satisfy a strict logarithmic version of the Hitchin-Thorpe inequality due to Dai-Wei. This is done by using estimates from Seiberg-Witten theory due to LeBrun as well as a method for constructing solut

Robert Kosk, Richard Southern, Lihua You, Shaojun Bian

With the rising popularity of virtual worlds, the importance of data-driven parametric models of 3D meshes has grown rapidly. Numerous applications, such as computer vision, procedural generation, and mesh editing, vastly rely on these models. However, current approaches do not allow for independent editing of deformations at different frequency levels. They

M. Khamsi, J. Lang, O. Mendez, A. Nekvinda

We prove the solvability of the Dirichlet problem for the variable exponent $p$-Laplacian with boundary data in $W^{1,p(x)}(\Omega)$ on a bounded, smooth domain $\Omega \subset {\mathbb R}^n$. Our main focus will be on an a.e. finite variable exponent $p(\cdot)$ with $n < \inf\limits_{x\in \Omega}p(x)$ and $\sup\limits_{x\in \Omega}p(x) = \infty$ under the s

Myeonggi Kwon, Takahiro Oba

We prove the uniqueness, up to diffeomorphism, of symplectically aspherical fillings of the unit cotangent bundle of odd-dimensional spheres. As applications, we first show the non-existence of exact symplectic cobordisms between some 5-dimensional Brieskorn manifolds. We also determine the diffeomorphism types of closed symplectic 6-manifolds with certain c

Kasra Hejazi, Modjtaba Shokrian Zini, Juan Miguel Arrazola

Product formulas are one of the main approaches for quantum simulation of the Hamiltonian dynamics of a quantum system. Their implementation cost is computed based on error bounds which are often pessimistic, resulting in overestimating the total runtime. In this work, we rigorously consider the error induced by product formulas when the state undergoing tim

T. T. H. Bui, P. van Heijster, R. Marangell

We establish spectral, linear, and nonlinear stability of the vanishing and slow-moving travelling waves that arise as time asymptotic solutions to the Fisher-Stefan equation. Nonlinear stability is in terms of the limiting equations that the asymptotic waves satisfy.

Julian Asilis, Siddartha Devic, Shaddin Dughmi, Vatsal Sharan

We demonstrate a compactness result holding broadly across supervised learning with a general class of loss functions: Any hypothesis class $H$ is learnable with transductive sample complexity $m$ precisely when all of its finite projections are learnable with sample complexity $m$. We prove that this exact form of compactness holds for realizable and agnost

Zheyuan Liu, Xiaoxin He, Yijun Tian, Nitesh V. Chawla

Graph plays an important role in representing complex relationships in real-world applications such as social networks, biological data and citation networks. In recent years, Large Language Models (LLMs) have achieved tremendous success in various domains, which makes applying LLMs to graphs particularly appealing. However, directly applying LLMs to graph m

Oscar Trull, J. Carlos García-Díaz, Angel Peiró-Signes

Transmission system operators have a growing need for more accurate forecasting of electricity demand. Current electricity systems largely require demand forecasting so that the electricity market establishes electricity prices as well as the programming of production units. The companies that are part of the electrical system use exclusive software to obtai

Sahitya V. Vegesna, Venkata Rao Rayapati, Heidemarie Schmidt

Interface-type, analog memristors have quite a reputation for real-time applications in edge sensorics, edge computing, and neuromorphic computing. The n-type conducting BiFeO3 (BFO) is such an interface-type, analog memristor which is also nonlinear and can therefore not only store, but also process data in the same memristor cell without data transfer betw

Xiang Cheng, Jingzhao Zhang, Suvrit Sra

We study the task of efficiently sampling from a Gibbs distribution $d \pi^* = e^{-h} d {vol}_g$ over a Riemannian manifold $M$ via (geometric) Langevin MCMC; this algorithm involves computing exponential maps in random Gaussian directions and is efficiently implementable in practice. The key to our analysis of Langevin MCMC is a bound on the discretization

Malcolm A. Kealey, Philip A. LeMaitre, Russell B. Thompson

A mapping is made between fermion exchange and excluded volume in the quantum-classical isomorphism using polymer self-consistent field theory. Apart from exchange, quantum particles are known to be exactly representable in classical statistical mechanics as ring polymers, with contours that are parametrized by the inverse thermal energy, often called the im

Shabnam Akhtari, Jennifer Park, Marta Pieropan, Soumya Sankar

In this expository article, we compare Malle's conjecture on counting number fields of bounded discriminant with recent conjectures of Ellenberg--Satriano--Zureick-Brown and Darda--Yasuda on counting points of bounded height on classifying stacks. We illustrate the comparisons via the classifying stacks $B(\mathbb{Z}/n\mathbb{Z})$ and $B{\mu_n}$.

Jock McOrist, Sebastien Picard, Eirik Eik Svanes

We consider N=1, d=4 vacua of heterotic theories in the large radius limit in which alpha' << 1. We construct a real differential operator $\mathcal{D}= D+\bar{D}$ on an extension bundle $(Q, \mathcal{D})$ with underlying topology $Q=(T^{1,0}X)^* \oplus {\rm End} \, E \oplus T^{1,0} X$ whose curvature is holomorphic and Hermitian-Yang-Mills with respect to t

Kang He, Yinghan Long, Kaushik Roy

Prompt-based learning is susceptible to intrinsic bias present in pre-trained language models (LMs), leading to sub-optimal performance in prompt-based zero/few-shot settings. In this work, we propose a null-input prompting method to calibrate intrinsic bias encoded in pre-trained LMs. Different from prior efforts that address intrinsic bias primarily for so

Vedant Sawal, Hiu Yung Wong

In this paper, we study the inference accuracy of the Resistive Random Access Memory (ReRAM) neuromorphic circuit due to stuck-at faults (stuck-on, stuck-off, and stuck at a certain resistive value). A simulation framework using Python is used to perform supervised machine learning (neural network with 3 hidden layers, 1 input layer, and 1 output layer) of h

Alex Saad-Falcon, Brighton Ancelin, Justin Romberg

Tracking signals in dynamic environments presents difficulties in both analysis and implementation. In this work, we expand on a class of subspace tracking algorithms which utilize the Grassmann manifold -- the set of linear subspaces of a high-dimensional vector space. We design regularized least squares algorithms based on common manifold operations and in

Noel Arteche, Gaia Carenini, Matthew Gray

We prove the first hardness results against efficient proof search by quantum algorithms. We show that under Learning with Errors (LWE), the standard lattice-based cryptographic assumption, no quantum algorithm can weakly automate $\mathbf{TC}^0$-Frege. This extends the line of results of Kraj\'i\v{c}ek and Pudl\'ak (Information and Computation, 1998), Bonet

Jing Su, Chufeng Jiang, Xin Jin, Yuxin Qiao

This systematic literature review comprehensively examines the application of Large Language Models (LLMs) in forecasting and anomaly detection, highlighting the current state of research, inherent challenges, and prospective future directions. LLMs have demonstrated significant potential in parsing and analyzing extensive datasets to identify patterns, pred

Dmitry V. Makhov, Adam Kirrander, Dmitrii V. Shalashilin

We present the result of our calculations of ultrafast electron diffraction (UED) for cyclobutanone excited into $S_2$ electronic state, which are based on the non-adiabatic dynamics simulations with \textit{Ab Initio} Multiple Cloning (AIMC) method with the electronic structure calculated at the SA(3)-CASSCF(12,12)/aug-cc-pVDZ level of theory. The key featu

Xiaoyu Mao, Rajeev Jaiman

Using a fixed Eulerian mesh, the phase-field method has been successfully utilized for a broad range of moving boundary problems involving multiphase fluids and single-phase fluid-structure interaction. Nevertheless, multiphase fluids interacting with multiple solids are rarely explored, especially for large-scale finite element simulations with contact dyna

Stephan Wong, Terry A. Loring, Alexander Cerjan

In the recent years, photonic Chern materials have attracted substantial interest as they feature topological edge states that are robust against disorder, promising to realize defect-agnostic integrated photonic crystal slab devices. However, the out-of-plane radiative losses in those photonic Chern slabs has been previously neglected, yielding limited accu

Helmut Harbrecht, Christoph Schwab, Marco Zank

On a finite time interval $(0,T)$, we consider the multiresolution Galerkin discretization of a modified Hilbert transform $\mathcal H_T$ which arises in the space-time Galerkin discretization of the linear diffusion equation. To this end, we design spline-wavelet systems in $(0,T)$ consisting of piecewise polynomials of degree $\geq 1$ with sufficiently man

Chun-Wei Chen, Kabish Wisal, Mathias Fink, A. Douglas Stone

Time-reversal symmetry enables shaping input waves to control output waves in many linear and nonlinear systems; however energy dissipation violates such symmetry. We consider a saturated multimode fiber amplifier in which light generates heat flow and suffers nonlinear thermo-optical scattering, breaking time-reversal symmetry. We identify a spacetime symme

Allison Chen, Ilia Sucholutsky, Olga Russakovsky, Thomas L. Griffiths

Does language help make sense of the visual world? How important is it to actually see the world rather than having it described with words? These basic questions about the nature of intelligence have been difficult to answer because we only had one example of an intelligent system -- humans -- and limited access to cases that isolated language or vision. Ho

Muhammad Arbab Arshad, Talukder Jubery, James Afful, Anushrut Jignasu

We evaluate different Neural Radiance Fields (NeRFs) techniques for the 3D reconstruction of plants in varied environments, from indoor settings to outdoor fields. Traditional methods usually fail to capture the complex geometric details of plants, which is crucial for phenotyping and breeding studies. We evaluate the reconstruction fidelity of NeRFs in thre

Jialu Hu, László Kozma

The Bellman-Ford algorithm for single-source shortest paths repeatedly updates tentative distances in an operation called relaxing an edge. In several important applications a non-adaptive (oblivious) implementation is preferred, which means fixing the entire sequence of relaxations upfront, independently of the edge-weights. Such an implementation performs,

Yihan Du, Anna Winnicki, Gal Dalal, Shie Mannor

Reinforcement Learning from Human Feedback (RLHF) has achieved impressive empirical successes while relying on a small amount of human feedback. However, there is limited theoretical justification for this phenomenon. Additionally, most recent studies focus on value-based algorithms despite the recent empirical successes of policy-based algorithms. In this w

Amit Acharya

The mid-surface scaling invariance of bending strain measures proposed in [Acharya (2000)] is discussed in light of the work of [arXiv:2010.14308].

Logan J. Prust, Hila Glanz, Lars Bildsten, Hagai B. Perets

We carry out three-dimensional computations of the accretion rate onto an object (of size $R_{\rm sink}$ and mass $m$) as it moves through a uniform medium at a subsonic speed $v_{\infty}$. The object is treated as a fully-absorbing boundary (e.g. a black hole). In contrast to early conjectures, we show that when $R_{\rm sink}\ll R_{A}=2Gm/v^2$ the accretion

Xiyang Wu, Souradip Chakraborty, Ruiqi Xian, Jing Liang

In this work, we highlight vulnerabilities in robotic systems integrating large language models (LLMs) and vision-language models (VLMs) due to input modality sensitivities. While LLM/VLM-controlled robots show impressive performance across various tasks, their reliability under slight input variations remains underexplored yet critical. These models are hig

Hugo Silva, Martha White

Oftentimes, machine learning applications using neural networks involve solving discrete optimization problems, such as in pruning, parameter-isolation-based continual learning and training of binary networks. Still, these discrete problems are combinatorial in nature and are also not amenable to gradient-based optimization. Additionally, classical approache

Nakul S. Deshpande, Paulo E. Arratia, Douglas J. Jerolmack

Creep is a generic descriptor of slow motions -- in the context of materials, it describes quasi-static deformation of a solid when subjected to stresses below the global yield, at which all rigidity collapses and the material flows. Here, we experimentally investigate creep, flow, and the transition between the two states in a granular heap flow. Within the

Shenming Fu, Ian Dell'Antonio, Zacharias Escalante, Jessica Nelson

The Local Volume Complete Cluster Survey (LoVoCCS) is an on-going program to observe nearly a hundred low-redshift X-ray-luminous galaxy clusters (redshifts $0.03<z<0.12$ and X-ray luminosities in the 0.1-2.4 keV band $L_{{\rm X500c}}>10^{44}$ erg/s) with the Dark Energy Camera (DECam), capturing data in $u,g,r,i,z$ bands with a $5\sigma$ point source depth

Ericka Roy Miller, Sean J. Hoehn, Abhijith Kumar, Dehua Jiang

We simulate the photodynamics of gas-phase cyclobutanone excited to the S$_2$ state using fewest switches surface hopping (FSSH) dynamics powered by time-dependent density functional theory (TDDFT). We predict a total C3+C2 photoproduct yield of 9%, with a C3:C2 product ratio of 1:8. Two primary S$_2$$\rightarrow$S$_1$ conical intersections are identified: $

Matthias Bentert, Alex Crane, Pål Grønås Drange, Felix Reidl

We explore Cluster Editing and its generalization Correlation Clustering with a new operation called permissive vertex splitting which addresses finding overlapping clusters in the face of uncertain information. We determine that both problems are NP-hard, yet they exhibit significant differences in parameterized complexity and approximability. For Cluster E

Ankan Dash, Jingyi Gu, Guiling Wang

Inpainting involves filling in missing pixels or areas in an image, a crucial technique employed in Mixed Reality environments for various applications, particularly in Diminished Reality (DR) where content is removed from a user's visual environment. Existing methods rely on digital replacement techniques which necessitate multiple cameras and incur high co

José Aliste-Prieto, Jeremy L. Martin, Jennifer D. Wagner, José Zamora

Stanley asked whether a tree is determined up to isomorphism by its chromatic symmetric function. We approach Stanley's problem by studying the relationship between the chromatic symmetric function and other invariants. First, we prove Crew's conjecture that the chromatic symmetric function of a tree determines its generalized degree sequence, which enumerat

Henry W. Sprueill, Carl Edwards, Khushbu Agarwal, Mariefel V. Olarte

The discovery of new catalysts is essential for the design of new and more efficient chemical processes in order to transition to a sustainable future. We introduce an AI-guided computational screening framework unifying linguistic reasoning with quantum-chemistry based feedback from 3D atomistic representations. Our approach formulates catalyst discovery as

Matthew Stoffregen, Michael Willis

We construct and study a lift of Jones-Wenzl projectors to the setting of Khovanov spectra, and provide a realization of such lifted projectors via a Cooper-Krushkal-like sequence of maps. We also give a polynomial action on the 3-strand spectral projector allowing a complete computation of the 3-colored Khovanov spectrum of the unknot, proving a conjecture

Ilya Chevyrev

The theory of rough paths arose from a desire to establish continuity properties of ordinary differential equations involving terms of low regularity. While essentially an analytic theory, its main motivation and applications are in stochastic analysis, where it has given a new perspective on It\^o calculus and a meaning to stochastic differential equations

Utkan Güngördü, Rusko Ruskov, Silas Hoffman, Kyle Serniak

Josephson junctions constructed from superconductor-semiconductor-superconductor heterostructures have been used to realize a variety of voltage-tunable superconducting quantum devices, including qubits and parametric amplifiers. To date theoretical descriptions of these systems have been restricted to small quantum fluctuations of the junction phase, making

Cheng Chi, Zhenjia Xu, Chuer Pan, Eric Cousineau

We present Universal Manipulation Interface (UMI) -- a data collection and policy learning framework that allows direct skill transfer from in-the-wild human demonstrations to deployable robot policies. UMI employs hand-held grippers coupled with careful interface design to enable portable, low-cost, and information-rich data collection for challenging biman

Taygun R. Gungor, Yvan Maciel, Ayse G. Gungor

Two direct numerical simulation (DNS) databases are investigated to understand the effect of the outer-layer turbulence on the inner layer's structures and energy transfer mechanisms. The first DNS database is the non-equilibrium adverse-pressure-gradient (APG) turbulence boundary layer (TBL) of Gungor et al. (2022). Its Reynolds number and the inner-layer p

Andrey Yu. Starikovskiy, Mikhail N. Shneider

In this paper, the Rayleigh scattering method is used to study the formation of cavitation in water in a pulsed inhomogeneous electric field when a nanosecond high voltage pulse is applied to a needle-like electrode. The observational results confirm the theoretical picture of cavitation development under the action of electrostrictive ponderomotive forces.

Harbir Antil

The report describes the discussions from the Workshop on Mathematical Opportunities in Digital Twins (MATH-DT) from December 11-13, 2023, George Mason University. It illustrates that foundational Mathematical advances are required for Digital Twins (DTs) that are different from traditional approaches. A traditional model, in biology, physics, engineering or

O. G. Finnerud, C. A. Lindstrøm, J. B. B. Chen, E. Adli

We discuss plans for the E302 instability-efficiency experiment, starting in 2024 at the recently upgraded FACET-II facility at SLAC National Accelerator Laboratory. The beam-breakup instability will be the main area of study for the E302 experiment. With the imaging spectrometer at FACET-II, we introduce a novel technique for observing and quantifying the a

Rajiv Thummala, Gregory Falco

In March of 2022, Network battalion 65 (NB65), a hacktivist affiliate of Anonymous, publicly asserted its successful breach of ROSCOSMOS's satellite imaging capabilities in response to Russia's invasion of Ukraine. NB65 disseminated a series of primary sources as substantiation, proclaiming the incapacitation of ROSCOSMOS's space-based vehicle monitoring sys

Babak Akbari, Melissa Greeff

Neglecting complex aerodynamic effects hinders high-speed yet high-precision multirotor autonomy. In this paper, we present a computationally efficient learning-based model predictive controller that simultaneously optimizes a trajectory that can be tracked within the physical limits (on thrust and orientation) of the multirotor system despite unknown aerody

Jane Ivy Coons, Shelby Cox, Aida Maraj, Ikenna Nometa

A Brownian motion tree (BMT) model is a Gaussian model whose associated set of covariance matrices is linearly constrained according to common ancestry in a phylogenetic tree. We study the complexity of inferring the maximum likelihood (ML) estimator for a BMT model by computing its ML-degree. Our main result is that the ML-degree of the BMT model on a star

Alexander Krawciw, Sven Lilge, Timothy D. Barfoot

This paper presents an approach for applying camera perception techniques to spinning LiDAR data. To improve the robustness of long-term change detection from a 3D LiDAR, range and intensity information are rendered into virtual perspectives using a pinhole camera model. Hue-saturation-value image encoding is used to colourize the images by range and near-IR