April 2024 arXiv papers — page 118

Kang Lyu, Chuanfu Yang

We consider the Dirac equation on $L^2(\mathbb{R})\oplus L^2(\mathbb{R})$ \begin{align} Ly= \begin{pmatrix} 0&-1 1&0 \end{pmatrix} \begin{pmatrix} y_1 y_2 \end{pmatrix}'+ \begin{pmatrix} p&q q&-p \end{pmatrix}\begin{pmatrix} y_1 y_2 \end{pmatrix}+ V\begin{pmatrix} y_1 y_2 \end{pmatrix}=\lambda y,\nonumber \end{align} where $y=y(x,\lambda)=\tbinom{y_1(x,\lamb

Z. H. Chen, X. H. Yang, G. B. Zhang, Y. Y. Ma

Ablative Rayleigh-Taylor instability (ARTI) and nonlocal heat transport are the critical problems in laser-driven inertial confinement fusion, while their coupling with each other is not completely understood yet. Here the ARTI in the presence of nonlocal heat transport is studied self-consistently for the first time theoretically and by using radiation hydr

S. J. Yue, Qing Liu, Shengyuan A. Yang, Y. X. Zhao

Real topological phases protected by the spacetime inversion (P T) symmetry are a current research focus. The basis is that the P T symmetry endows a real structure in momentum space, which leads to Z2 topological classifications in 1D and 2D. Here, we provide solutions to two outstanding problems in the diagnosis of real topology. First, based on the stable

Si-Wen He, Zhi-Jiao Deng, Yi Xie, Yan-Yi Wang

The entanglement properties of quantum synchronization, based on a single-ion phonon laser subjected to an external drive, have been studied. It is found that the maximum value of steady-state entanglement between the ion's internal and external states occurs near the noiseless boundary from synchronization to unsynchronization, accompanied by noticeable osc

Jaewook Lee, Jun Wang, Elizabeth Brown, Liam Chu

Voice assistants (VAs) like Siri and Alexa are transforming human-computer interaction; however, they lack awareness of users' spatiotemporal context, resulting in limited performance and unnatural dialogue. We introduce GazePointAR, a fully-functional context-aware VA for wearable augmented reality that leverages eye gaze, pointing gestures, and conversatio

Hika Barki, Wan-Young Chung

Mental stress is a prevalent condition that can have negative impacts on one's health. Early detection and treatment are crucial for preventing related illnesses and maintaining overall wellness. This study presents a new method for identifying mental stress using a wearable biosensor worn in the ear. Data was gathered from 14 participants in a controlled en

Xu-Tao Wan, Chao Gao, Zhe-Yu Shi

The translation symmetry of a lattice is greatly modified when subjected to a perpendicular magnetic field [Zak, Phys. Rev. \textbf{134}, A1602 (1964)]. This change in symmetry can lead to magnetic unit cells that are substantially larger than the original ones. Similarly, the translation properties of a double-layered lattice alters drastically while two mo

Ching Hong Tam, Frederik Geth, Nadarajah Mithulananthan

In recent years, with the increase in renewable energy and storage penetration, power flow studies in low-voltage networks have become of interest in both industry and academia. Many studies use impedance represented by sequence components due to the lack of datasets with fully parameterized impedance matrices. This assumes that the network impedance is bala

Zongbin Chen

For the group $\mathrm{GL}_{d}$, we confirm a conjecture of Goresky, Kottwitz and MacPherson, which states that the cohomology of the affine Springer fibers depend only on the root valuation datum of their defining elements. The proof relies on a microlocal analysis of the intermediate extensions appearing in Ng\^o's support theorem, and a Whitney regularity

Jie Zhu, Bojing Liao

The transformation of urban environments to accommodate growing populations has profoundly impacted public health and well-being. This paper addresses the critical challenge of estimating the impact of urban design interventions on diverse populations. Traditional approaches, reliant on questionnaires and stated preference techniques, are limited by recall b

Liangyu Chen, Baoyuan Mu, Huajia Wang, Pengfei Zhang

The growth of simple operators is essential for the emergence of chaotic dynamics and quantum thermalization. Recent studies have proposed different measures, including the out-of-time-order correlator and Krylov complexity. It is established that the out-of-time-order correlator serves as the signature of quantum many-body chaos, while the Krylov complexity

Junhua Dong, Sihao Zhang, Huan He, Huanan Li

Photonic time crystals (PTCs) host momentum bandgaps enabling intriguing non-resonant light amplification in propagating waves, but opening substantial bandgaps demands refractive index changes too extreme for conventional nonlinear optics. Here, we introduce momentum bandgaps for non-uniform waves, including evanescent and ghost types, by extending PTCs to

Héctor Novales-Sánchez, Mónica Salinas, Humberto Vázquez-Castro

The experimental confirmation of neutrino mass and mixing disagrees with the picture of the Standard Model, and thus provides a good motivation to look for unknown physics. A seesaw variant in which neutrino masses are radiatively generated, with neutrinos characterized by Majorana fields and where a set of three hypothetical neutral heavy leptons are presen

Dasen Ye, Sangyong Jeon, Charles Gale

In this work, we first derive the evolution equation for the general energy-momentum moment of $\delta f$, where $\delta f$ is the deviation from the local equilibrium phase space density. We then introduce a relativistic extension of regularized hydrodynamics developed in the non-relativistic case by Struchtrup and Torrilhon that combines the method of mome

Wei Zhang, H. Z. Shen

We investigate the generation of the frequency components at the second-order sidebands based on a spinning resonator containing a degenerate optical parametric amplifier (OPA). We show an OPA driven by different pumping frequencies inside a cavity can enhance and modulate the amplitude of the second-order sideband with different influences. We find that bot

T. Z. Luan, H. Z. Shen, X. X. Yi

Shortcuts to adiabaticity are alternative fast processes which reproduce the same final state as the adiabatic process in a finite or even shorter time, which have been extended from Hermitian systems to non-Hermitian systems in recent years, but they are barely explored for general non-Hermitian systems where off-diagonal elements of the Hamiltonian are not

Yizhi Pan, Junyi Xin, Tianhua Yang, Teeradaj Racharak

In medical imaging, accurate image segmentation is crucial for quantifying diseases, assessing prognosis, and evaluating treatment outcomes. However, existing methods lack an in-depth integration of global and local features, failing to pay special attention to abnormal regions and boundary details in medical images. To this end, we present a novel deep lear

Paula Belzig

If a sender and a receiver lack precise knowledge about the communication line that connects them, designing a scheme to reliably transmit information becomes more challenging. This has been studied in classical and quantum information theory in the context of compound channel models and arbitrarily varying channel models. However, a fully quantum version of

Siqi Han, Chao Zhang, Jiaxin Lei, Qingquan Han

This paper proposes to use cepstrum for artifact detection, recognition and removal in prefrontal EEG. This work focuses on the artifact caused by eye movement. A database containing artifact-free EEG and eye movement contaminated EEG from different subjects is established. A cepstral analysis-based feature extraction with support vector machine (SVM) based

Tao Wang, Xin Chen, Yu Zhang

The Cd puzzle implies that the phonon excitation of a spherical nucleus should be questioned and refuted. For understanding this spherical-like $\gamma$-soft mode newly found experimentally, a possible answer was proposed recently in the SU3-IBM. In this paper, the evolutions of the normal states in $^{108-120}$Cd are investigated and compared with the exper

Zichao Li, Cihang Xie, Ekin Dogus Cubuk

This paper investigates the performance of the Contrastive Language-Image Pre-training (CLIP) when scaled down to limited computation budgets. We explore CLIP along three dimensions: data, architecture, and training strategies. With regards to data, we demonstrate the significance of high-quality training data and show that a smaller dataset of high-quality

Yubo Duan, Yawei Wei

In this paper, we consider the nonlinear equation involving the fractional p-Laplacian with sign-changing potential. This model draws inspiration from De Giorgi Conjecture. There are two main results in this paper. Firstly, we obtain that the solution is radially symmetric within the bounded domain, by applying the moving plane method. Secondly, by exploitin

Zhiwei Yang, Yucong Meng, Kexue Fu, Shuo Wang

Weakly supervised semantic segmentation (WSSS) with image-level labels intends to achieve dense tasks without laborious annotations. However, due to the ambiguous contexts and fuzzy regions, the performance of WSSS, especially the stages of generating Class Activation Maps (CAMs) and refining pseudo masks, widely suffers from ambiguity while being barely not

Brennan Benfield, Oliver Lippard

A $K$-Fibonacci sequence is a binary recurrence sequence where $F_0=0$, $F_1=1$, and $F_n=K\cdot F_{n-1}+F_{n-2}$. These sequences are known to be periodic modulo every positive integer greater than $1$. If the length of one shortest period of a $K$-Fibonacci sequence modulo a positive integer is equal to the modulus, then that positive integer is called a $

Brennan Benfield, Oliver Lippard

The generalized Waring problem asks exactly which positive integers cannot be expressed as the sum of $j$ positive $k$-th powers? Using computational techniques, this paper refines an approach introduced by Zenkin, establishes results for the individual cases $5 \le k \le 9$, and resolves conjectures of Zenkin and the OEIS. This paper further establishes the

Yiming Jiang, Yawei Wei, Yiyun Yang

We study the wellposedness of the master equation for a second-order mean field games with the Grushin type diffusion. In order to do this, we obtain the properties of its solution by investigating a degenerate mean field games system for which there exists an equivalent characterization with the master equation. The crucial points of this paper are to explo

Leandro Rodrigues de Souza, Thales Sales Almeida, Roberto Lotufo, Rodrigo Nogueira

Multilingual pretraining has been a successful solution to the challenges posed by the lack of resources for languages. These models can transfer knowledge to target languages with minimal or no examples. Recent research suggests that monolingual models also have a similar capability, but the mechanisms behind this transfer remain unclear. Some studies have

Brennan Benfield, Oliver Lippard, Arindam Roy

Generalized taxicab numbers are the smallest positive integers that are the sum of exactly $j$, positive $k$-th powers in exactly $m$ distinct ways. This paper is considers for which values of $m$ does a smallest such integer exist as $j$ gets large. There appear to be only two possible outcomes, leading to curious results like there is no positive integer t

Patrice Béchard, Orlando Marquez Ayala

A common and fundamental limitation of Generative AI (GenAI) is its propensity to hallucinate. While large language models (LLM) have taken the world by storm, without eliminating or at least reducing hallucinations, real-world GenAI systems may face challenges in user adoption. In the process of deploying an enterprise application that produces workflows ba

Fuwang Dong, Fan Liu, Shihang Liu, Yifeng Xiong

In this paper, we introduce a novel communication-assisted sensing (CAS) framework that explores the potential coordination gains offered by the integrated sensing and communication technique. The CAS system endows users with beyond-line-of-the-sight sensing capabilities, supported by a dual-functional base station that enables simultaneous sensing and commu

Ryan Griffiths, Donald G. Dansereau

The majority of image processing approaches assume images are in or can be rectified to a perspective projection. However, in many applications it is beneficial to use non conventional cameras, such as fisheye cameras, that have a larger field of view (FOV). The issue arises that these large-FOV images can't be rectified to a perspective projection without s

Morteza Maleki

The COVID-19 pandemic has presented unprecedented challenges worldwide, with its impact varying significantly across different geographic and socioeconomic contexts. This study employs a clustering analysis to examine the diversity of responses to the pandemic within the United States, aiming to provide nuanced insights into the effectiveness of various stra

Muhammad Zeeshan, Richard O'Shaughnessy

Gravitational waves (GW), emanating from binary black holes (BBH), encode vital information about their source. GW signals enable us to deduce key properties of the BBH population across the universe, including mass, spin, and eccentricity distribution. While the masses and spins of binary components are already recognized for their insights into formation,

Nathan Vance, Patrick Flynn

Domain shift differences between training data for deep learning models and the deployment context can result in severe performance issues for models which fail to generalize. We study the domain shift problem under the context of remote photoplethysmography (rPPG), a technique for video-based heart rate inference. We propose metrics based on model similarit

Tài Huy Hà, Takayuki Hibi, Fabrizio Zanello

The pure $O$-sequences of the form $(1,a,a,\ldots)$ are classified.

Changying Ding

We show that if $\Gamma\curvearrowright (X^\Gamma,\mu^\Gamma)$ is a Bernoulli action of an i.c.c. nonamenable group $\Gamma$ which is weakly amenable with Cowling-Haagerup constant $1$, and $\Lambda\curvearrowright(Y,\nu)$ is a free ergodic p.m.p. algebraic action of a group $\Lambda$, then the isomorphism $L^\infty(X^\Gamma)\rtimes\Gamma\cong L^\infty(Y)\rt

Sina Hajimiri, Ismail Ben Ayed, Jose Dolz

Despite the significant progress in deep learning for dense visual recognition problems, such as semantic segmentation, traditional methods are constrained by fixed class sets. Meanwhile, vision-language foundation models, such as CLIP, have showcased remarkable effectiveness in numerous zero-shot image-level tasks, owing to their robust generalizability. Re

Guowei Ren, Mouyuan Sun, Jun-Xian Wang, Zhen-Yi Cai

Magnetohydrodynamics (MHD) turbulence can drive significant temperature fluctuations in the accretion disk of an active galactic nucleus (AGN). As a result, the disk can be highly inhomogeneous and has a half-light radius larger than the static Shakura \& Sunyaev Disk (SSD), in agreement with quasar microlensing observations. Meanwhile, the accretion-disk si

Joshua A. Fisher, Fernando Rochaix

This paper outlines the Clarkston AR Gateways Project, a speculative process and artifact entering its second phase, where Augmented Reality (AR) will be used to amplify the diverse narratives of Clarkston, Georgia's refugee community. Focused on anchoring their stories and presence into the town's physical and digital landscapes, the project employs a parti

Aaresh Bhathena, Salar Fattahi, Andrés Gómez, Simge Küçükyavuz

This paper investigates convex quadratic optimization problems involving $n$ indicator variables, each associated with a continuous variable, particularly focusing on scenarios where the matrix $Q$ defining the quadratic term is positive definite and its sparsity pattern corresponds to the adjacency matrix of a tree graph. We introduce a graph-based dynamic

Kevin J. U. Vidarte, Felipe Pérez Riffo, Eric Suárez Morell, Caio Lewenkopf

We present a theoretical investigation of the magnetic properties exhibited by twisted bilayer graphene (TBG) systems with small twist angles, where the appearance of flat minibands strongly enhances electron-electron interaction effects. We show that, at three-quarters filling of the conduction miniband, the Stoner mechanism induces a ferromagnetic polariza

Masako Kishida, Shunsuke Ono

This extended abstract introduces a class of graph learning applicable to cases where the underlying graph has polytopic uncertainty, i.e., the graph is not exactly known, but its parameters or properties vary within a known range. By incorporating this assumption that the graph lies in a polytopic set into two established graph learning frameworks, we find

Adarsh Salagame, Kruthika Gangaraju, Harin Kumar Nallaguntla, Eric Sihite

Object manipulation has been extensively studied in the context of fixed base and mobile manipulators. However, the overactuated locomotion modality employed by snake robots allows for a unique blend of object manipulation through locomotion, referred to as loco-manipulation. The following work presents an optimization approach to solving the loco-manipulati

Hyeonjin Kim, Yi Hu, Kai Ye, Ning Lu

This paper introduces ViT4LPA, an innovative Vision Transformer (ViT) based approach for Load Profile Analysis (LPA). We transform time-series load profiles into load images. This allows us to leverage the ViT architecture, originally designed for image processing, as a pre-trained image encoder to uncover latent patterns within load data. ViT is pre-trained

Adarsh Salagame, Kruthika Gangaraju, Harin Kumar Nallaguntla, Eric Sihite

Object manipulation has been extensively studied in the context of fixed base and mobile manipulators. However, the overactuated locomotion modality employed by snake robots allows for a unique blend of object manipulation through locomotion, referred to as loco-manipulation. The following work presents an optimization approach to solving the loco-manipulati

Jaehyun Koo

The celebrated Floyd-Warshall algorithm efficiently computes the all-pairs shortest path, and its simplicity made it a staple in computer science classes. Frequently, students discover a variant of this Floyd-Warshall algorithm by mixing up the loop order, ending up with the incorrect APSP matrix. This paper considers a computational problem of computing thi

Farhad Farokhi

Optimal encoding of classical data for statistical inference using quantum computing is investigated. A universal encoder is sought that is optimal for a wide array of statistical inference tasks. Accuracy of any statistical inference is shown to be upper bounded by a term that is proportional to maximal quantum leakage from the classical data, i.e., the inp

Duy Phuong Nguyen, J. Pablo Munoz, Ali Jannesari

In the rapidly evolving field of artificial intelligence, multimodal models, e.g., integrating vision and language into visual-language models (VLMs), have become pivotal for many applications, ranging from image captioning to multimodal search engines. Among these models, the Contrastive Language-Image Pre-training (CLIP) model has demonstrated remarkable p

Jinling Zhou, Jiawang Nie, Zheng Peng, Guangming Zhou

This paper studies the rank-$1$ tensor completion problem for cubic tensors. First of all, we show that this problem is equivalent to a special rank-$1$ matrix recovery problem. When the tensor is strongly rank-$1$ completable, we show that the problem is equivalent to a rank-$1$ matrix completion problem and it can be solved by an iterative formula. For oth

Jingwei Liu, Fulvio Melia

The absence of large-angle correlations in the temperature of the cosmic microwave background (CMB), confirmed by three independent satellite missions, creates significant tension with the standard model of cosmology. Previous work has shown, however, that a truncation, $k_{min}$, of the primordial power spectrum comprehensively resolves the anomaly and the

Wei Du, Jan Hannig, Thomas C. M. Lee, Yi Su

The concept of fiducial inference was introduced by R. A. Fisher in the 1930s to address the perceived limitations of Bayesian inference, particularly the need for subjective prior distributions in cases with limited prior information. However, Fisher's fiducial approach lost favor due to complications, especially in multi-parameter problems. With renewed in

Etash Guha, Shlok Natarajan, Thomas Möllenhoff, Mohammad Emtiyaz Khan

Conformal prediction (CP) for regression can be challenging, especially when the output distribution is heteroscedastic, multimodal, or skewed. Some of the issues can be addressed by estimating a distribution over the output, but in reality, such approaches can be sensitive to estimation error and yield unstable intervals.~Here, we circumvent the challenges

Shuang-Tao Wang, Su-Yan Pei, Tianhong Wang, Guo-Li Wang

In 2021, a new charm-strange meson, $D_{s0}(2590)^+$, has been discovered, it is believed to be the $D_s^+(2^1S_0)$. However, its low mass and wide width are challenged by theoretical results. Given the small branching ratio of the current production channel, resulting in a small number of events and large errors. We suggest to search for the $D_{s0}(2590)^+

Shaun Gallagher, Jessica Kline, Farzaneh Jahanbakhshi, James C. Sadighian

Photoluminescence intermittency remains one of the biggest challenges to realizing perovskite quantum dots (QDs) as scalable single photon emitters. We compare CsPbBr3 QDs capped with different ligands, lecithin, and a combination of oleic acid and oleylamine, to elucidate the role of surface chemistry on photoluminescence intermittency. We employ widefield

Jonathan Cook, Sabih ur Rehman, M. Arif Khan

Rapid growth in the number of small sensor devices known as the Internet of Things (IoT) has seen the development of lightweight encryption algorithms. Two well-known lightweight algorithms are SIMON and SIMECK which have been specifically designed for use on resource-constrained IoT devices. These lightweight encryption algorithms are based on the efficient

Haoting Zhang, Jinghai He, Rhonda Righter, Zeyu Zheng

With the advancement in generative language models, the selection of prompts has gained significant attention in recent years. A prompt is an instruction or description provided by the user, serving as a guide for the generative language model in content generation. Despite existing methods for prompt selection that are based on human labor, we consider faci

Robert Hernandez, Linn Carothers

The following is a write up of the progress of modeling data from the K12 organization \cite{Riedman_2023}. Data was characterized and investigated for statistically significant factors. The incident data was spilt into three sets: the entire set of incidents, incidents from 1966 - 2017, and incidents from 2018 - 2023. This was done in an attempt to discern

Mehdi Jokar, Siddharth Nair, Fabio Semperlotti

This paper extends the finite element network analysis (FENA) to include a dynamic time-transient formulation. FENA was initially formulated in the context of the linear static analysis of 1D and 2D elastic structures. By introducing the concept of super finite network element, this paper provides the necessary foundation to extend FENA to linear time-transi

Hassan Alnatah, Qi Yao, Jonathan Beaumariage, Shouvik Mukherjee

We have created a spatially homogeneous polariton condensate in thermal equilibrium, up to very high condensate fraction. Under these conditions, we have measured the coherence as a function of momentum, and determined the total coherent fraction of this boson system from very low density up to density well above the condensation transition. These measuremen

Jiasen Yang, Xiao Wang, Chuanhai Liu

Inferential models have been proposed for valid and efficient prior-free probabilistic inference. As it gradually gained popularity, this theory is subject to further developments for practically challenging problems. This paper considers the many-normal-means problem with the means constrained to be in the neighborhood of each other, formally represented by

Bhakti Shah, Willam Spencer, Laura Zielinski, Ben Caldwell

We present ViCAR, a library for working with monoidal categories in the Coq proof assistant. ViCAR provides definitions for categorical structures that users can instantiate with their own verification projects. Upon verifying relevant coherence conditions, ViCAR gives a set of lemmas and tactics for manipulating categorical structures. We also provide a vis

George Giakkoupis, Marcos Kiwi, Dimitrios Los

We study sorting in the evolving data model, introduced by [AKMU11], where the true total order changes while the sorting algorithm is processing the input. More precisely, each comparison operation of the algorithm is followed by a sequence of evolution steps, where an evolution step perturbs the rank of a random item by a "small" random value. The goal is

Farajollah Tahernezhad-Javazm, Debbie Rankin, Naomi Du Bois, Alice E. Smith

Choosing an appropriate optimization algorithm is essential to achieving success in optimization challenges. Here we present a new evolutionary algorithm structure that utilizes a reinforcement learning-based agent aimed at addressing these issues. The agent employs a double deep q-network to choose a specific evolutionary operator based on feedback it recei

Annapurna Pradhan, Susmita Das, Md. Jalil Piran, Zhu Han

Ultra-reliable low latency communication (URLLC) is an innovative service offered by fifth-generation (5G) wireless systems. URLLC enables various mission-critical applications by facilitating reliable and low-latency signal transmission to support extreme Quality of Service (QoS) requirements. Apart from reliability and latency, ensuring secure data transmi

Henry Purcell, Sherwood Richers, Amol V. Patwardhan, Francois Foucart

In the presence of anisotropic neutrino and antineutrino fluxes, the quantum kinetic equations drive coherent oscillations in neutrino helicity, frequently referred to as spin oscillations. These oscillations depend directly on the absolute mass scale and Majorana phase, but are usually too transient to produce important effects. In this paper we present a f

Liming Xu, Dave Towey, Andrew P. French, Steve Benford

The recent release of the Apple Vision Pro has reignited interest in the metaverse, showcasing the intensified efforts of technology giants in developing platforms and devices to facilitate its growth. As the metaverse continues to proliferate, it is foreseeable that everyday environments will become increasingly saturated with its presence. Consequently, un

Tom Gur, Mohammad Mahdi Jahanara, Mohammad Mahdi Khodabandeh, Ninad Rajgopal

We continue the study of doubly-efficient proof systems for verifying agnostic PAC learning, for which we obtain the following results. - We construct an interactive protocol for learning the $t$ largest Fourier characters of a given function $f \colon \{0,1\}^n \to \{0,1\}$ up to an arbitrarily small error, wherein the verifier uses $\mathsf{poly}(t)$ rando

Abhay Singh Bhadoriya, Deepjyoti Deka, Kaarthik Sundar

The Multiple Traveling Salesman Problem (MTSP) extends the traveling salesman problem by assigning multiple salesmen to visit a set of targets from a common depot, with each target visited exactly once while minimizing total tour length. A common variant, the min-max MTSP, focuses on workload balance by minimizing the longest tour, but it is difficult to sol

Md Messal Monem Miah, Ulie Schnaithmann, Arushi Raghuvanshi, Youngseo Son

Detecting dialogue breakdown in real time is critical for conversational AI systems, because it enables taking corrective action to successfully complete a task. In spoken dialog systems, this breakdown can be caused by a variety of unexpected situations including high levels of background noise, causing STT mistranscriptions, or unexpected user flows. In pa

Amin Hosseiny Marani, Ulie Schnaithmann, Youngseo Son, Akil Iyer

Current Conversational AI systems employ different machine learning pipelines, as well as external knowledge sources and business logic to predict the next action. Maintaining various components in dialogue managers' pipeline adds complexity in expansion and updates, increases processing time, and causes additive noise through the pipeline that can lead to i

Runqi Lin, Chaojian Yu, Tongliang Liu

Single-step adversarial training (SSAT) has demonstrated the potential to achieve both efficiency and robustness. However, SSAT suffers from catastrophic overfitting (CO), a phenomenon that leads to a severely distorted classifier, making it vulnerable to multi-step adversarial attacks. In this work, we observe that some adversarial examples generated on the

N. Vidal-Silva, Francisco J. Peña, Roberto E. Troncoso, Patricio Vargas

We propose a magnon-based thermal machine in two-dimensional (2D) magnetic insulators. The thermodynamical cycles are engineered by exposing a magnon spin system to thermal baths at different temperatures and tuning the Dzyaloshinskii-Moriya (DM) interaction. We find for the Otto cycle that a thermal gas of magnons converts a fraction of heat into energy in

Madison Brigham, Joël Porquet-Lupine

The COVID-19 pandemic significantly altered how post-secondary students receive their education. Namely, the transition from an in-person to an online class format changed how students interact with their instructors and their classmates. In this paper, we use student participation scores from two core computer science classes across ten in-person and three

Tuan Minh Pham, Thomas Peron, Fernando L. Metz

We derive exact equations for the spectral density of sparse networks with an arbitrary distribution of the number of single edges and triangles per node. These equations enable a systematic investigation of the effect of clustering on the spectral properties of the network adjacency matrix. In the case of heterogeneous networks, we demonstrate that the spec

Rabimba Karanjai, Lei Xu, Lin Chen, Nour Diallo

Function-as-a-Service (FaaS) offers a streamlined cloud computing paradigm, but existing centralized systems suffer from vendor lock-in and single points of failure. We propose DeFaaS, a decentralized FaaS system leveraging blockchain technology and decentralized API management. DeFaaS addresses these limitations by establishing a secure, transparent registr

Ian Charlesworth, Rolando de Santiago, Ben Hayes, David Jekel

We undertake a comprehensive study of structural properties of graph products of von Neumann algebras equipped with faithful, normal states, as well as properties of the graph products relative to subalgebras coming from induced subgraphs. Among the technical contributions in this paper include a complete bimodule calculation for subalgebras arising from sub

Behrooz Mosallaei, Sepideh Farivar, Farzaneh Ghanbari, Vahid Nourozi

This paper presents a formula for $a$-number of certain maximal curves characterized by the equation $y^{\frac{q+1}{2}} = x^m + x$ over the finite field $\mathbb{F}_{q^2}$. $a$-number serves as an invariant for the isomorphism class of the $p$-torsion group scheme. Utilizing the action of the Cartier operator on $H^0(\mathcal{X}, \Omega^1)$, we establish a c

Jierui Li, Raymond Mooney

Distilling explicit chain-of-thought reasoning paths has emerged as an effective method for improving the reasoning abilities of large language models (LLMs) across various tasks. However, when tackling complex tasks that pose significant challenges for state-of-the-art models, this technique often struggles to produce effective chains of thought that lead t

Scott Wesley

As quantum computing evolves, many important questions emerge, such as how best to represent quantum programs, and how to promote interoperability between quantum program analysis tools. These questions arise naturally in the design of quantum transpilers, which translate between quantum programming languages. In this paper, we take a step towards answering

Gabriel Lacerda, Sergio Romaña

Given $X$ a compact metric space and $T: X \to X$ a continuous map, the induced hyperspace map $T_\mathcal{K}$ acts on the hyperspace $\mathcal{K}(X)$ of closed and nonempty subsets of $X$, and on the continuum hyperspace $\mathcal{C}(X) \subset \mathcal{K}(X)$ of connected sets. This work studies the mean dimension explosion phenomenon: when the base system

Haozhi Sha, Yixuan Zhang, Yunpeng Ma, Wei Li

Polar topologies, such as vortex and skyrmion, have attracted significant interest due to their unique physical properties and promising applications in high-density memory devices. Currently, most polar vortices are observed in heterostructures containing ferroelectric materials and constrained by substrates. In this study, we unravel arrays of polar vortic

Richard Fang, Rohan Bindu, Akul Gupta, Daniel Kang

LLMs have becoming increasingly powerful, both in their benign and malicious uses. With the increase in capabilities, researchers have been increasingly interested in their ability to exploit cybersecurity vulnerabilities. In particular, recent work has conducted preliminary studies on the ability of LLM agents to autonomously hack websites. However, these s

Yasasi Abeysinghe, Bhanuka Mahanama, Gavindya Jayawardena, Yasith Jayawardana

Understanding how individuals focus and perform visual searches during collaborative tasks can help improve user engagement. Eye tracking measures provide informative cues for such understanding. This article presents A-DisETrac, an advanced analytic dashboard for distributed eye tracking. It uses off-the-shelf eye trackers to monitor multiple users in paral

Kurt Schmidt, Robert Buckingham

The generalized Hastings-McLeod solutions to the inhomogeneous Painlev\'{e}-II equation arise in multi-critical unitary random matrix ensembles, the chiral two-matrix model for rectangular matrices, non-intersecting squared Bessel paths, and non-intersecting Brownian motions on the circle. We establish the leading-order asymptotic behavior of the generalized

Kohei Motegi, Ryo Ohkawa

Source identities are fundamental identities between multivariable special functions. We give a geometric derivation of rational and trigonometric source identities. We also give a systematic derivation and extension of various determinant representations for source functions which appeared in previous literature as well as introducing the elliptic version o

Evgueni Doubtsov

Let $\varphi: B_d\to\mathbb{D}$, $d\ge 1$, be a holomorphic function, where $B_d$ denotes the open unit ball of $\mathbb{C}^d$ and $\mathbb{D}= B_1$. Let $\Theta: \mathbb{D} \to \mathbb{D}$ be an inner function and let $K^p_\Theta$ denote the corresponding model space. For $p>1$, we characterize the compact composition operators $C_\varphi: K^p_\Theta \to H^

Peter Bonart

We introduce dependent adders. A dependent adder $A$ has for every $x \in A$ a way of adding together $x$ many elements of $A$. We provide examples from many disparate branches of mathematics. Examples include the field with one element $\mathbb{F}_1$, the real numbers with integrals as sums, the category of categories with oplax colimits as sums. We also co

Mark Dodici, Scott Tremaine

Using the equations of motion from Hill's problem, with added accelerations for different forms of dynamical friction, we provide the (to-date) broadest scale-free study of friction-driven binary formation in gaseous disks and stellar clusters. We focus mainly on binary formation between stellar-mass black holes in active galactic nuclei (AGNi), considering

Marwah Alaofi, Negar Arabzadeh, Charles L. A. Clarke, Mark Sanderson

In this chapter, we consider generative information retrieval evaluation from two distinct but interrelated perspectives. First, large language models (LLMs) themselves are rapidly becoming tools for evaluation, with current research indicating that LLMs may be superior to crowdsource workers and other paid assessors on basic relevance judgement tasks. We re

Xu Yan, Weimin Wang, MingXuan Xiao, Yufeng Li

Gastric cancer and Colon adenocarcinoma represent widespread and challenging malignancies with high mortality rates and complex treatment landscapes. In response to the critical need for accurate prognosis in cancer patients, the medical community has embraced the 5-year survival rate as a vital metric for estimating patient outcomes. This study introduces a

Eric Luxenberg, Stephen Boyd

An exponentially weighted moving model (EWMM) for a vector time series fits a new data model each time period, based on an exponentially fading loss function on past observed data. The well known and widely used exponentially weighted moving average (EWMA) is a special case that estimates the mean using a square loss function. For quadratic loss functions EW

Jamie Menjay Lin, Jisoo Jeong, Hong Cai, Risheek Garrepalli

Optical flow estimation is crucial to a variety of vision tasks. Despite substantial recent advancements, achieving real-time on-device optical flow estimation remains a complex challenge. First, an optical flow model must be sufficiently lightweight to meet computation and memory constraints to ensure real-time performance on devices. Second, the necessity

Eugene Yang, Dawn J. Lawrie, Paul McNamee, James Mayfield

This paper describes the submission runs from the HLTCOE team at the CIRAL CLIR tasks for African languages at FIRE 2023. Our submissions use machine translation models to translate the documents and the training passages, and ColBERT-X as the retrieval model. Additionally, we present a set of unofficial runs that use an alternative training procedure with a

Belle, Belle II Collaborations, :, I. Adachi

We present the results of a search for the $b \to d\ell^+\ell^-$ flavor-changing neutral-current rare decays $B^{+, 0} \to (\eta, \omega, \pi^{+,0}, \rho^{+, 0}) e^+e^-$ and $B^{+, 0} \to (\eta, \omega, \pi^{0}, \rho^{+}) \mu^+\mu^-$ using a $711$ fb$^{-1}$ data sample that contains $772 \times 10^{6}$ $B\overline{B}$ events. The data were collected at the $

Behrooz Mosallaei, Farzaneh Ghanbari, Sepideh Farivar, Vahid Nourozi

In this paper, we study some codes of algebraic geometry related to certain maximal curves. Quantum stabilizer codes obtained through the self orthogonality of Hermitian codes of this error correcting do not always have good parameters. However, appropriate parameters found that the Hermitian self-orthogonal code quantum stabilizer code has good parameters.

Wojciech Czaja, Sanghoon Na

We present a post-training quantization algorithm with error estimates relying on ideas originating from frame theory. Specifically, we use first-order Sigma-Delta ($\Sigma\Delta$) quantization for finite unit-norm tight frames to quantize weight matrices and biases in a neural network. In our scenario, we derive an error bound between the original neural ne

Alex Fedoseyev

The analytical solution for turbulent flow in channel presented in Fedoseyev (2023), described the mean turbulent flow velocity as a superposition of the laminar (parabolic) and turbulent (superexponential) solutions. In this study, the coefficients of superposition are proposed to obtain through the minimization principle, the principle of minimum viscous d

Nicola Borri, Denis Chetverikov, Yukun Liu, Aleh Tsyvinski

We propose a new non-linear single-factor asset pricing model $r_{it}=h(f_{t}\lambda_{i})+\epsilon_{it}$. Despite its parsimony, this model represents exactly any non-linear model with an arbitrary number of factors and loadings -- a consequence of the Kolmogorov-Arnold representation theorem. It features only one pricing component $h(f_{t}\lambda_{I})$, com

Kaiyuan Hua, Hwanhee Hong, Xiaofei Wang

Multi-regional clinical trials (MRCTs) play an increasingly crucial role in global pharmaceutical development by expediting data gathering and regulatory approval across diverse patient populations. However, differences in recruitment practices and regional demographics often lead to variations in study participant characteristics, potentially biasing treatm

Markus R. Ernst, Francisco M. López, Arthur Aubret, Roland W. Fleming

Color constancy (CC) describes the ability of the visual system to perceive an object as having a relatively constant color despite changes in lighting conditions. While CC and its limitations have been carefully characterized in humans, it is still unclear how the visual system acquires this ability during development. Here, we present a first study showing