December 2024 arXiv papers — page 195

Abdullah Al Mamun, Abyad Enan, Debbie A. Indah, Judith Mwakalonge

This study investigates crash severity risk modeling strategies for work zones involving large vehicles (i.e., trucks, buses, and vans) under crash data imbalance between low-severity (LS) and high-severity (HS) crashes. We utilized crash data involving large vehicles in South Carolina work zones from 2014 to 2018, which included four times more LS crashes t

Carlos Villanueva, Pengfei Zhang

We investigate the fundamental properties of Minkowski billiards and introduce a new coordinate system $(s,u)$ on the phase space $\mathcal{M}$. In this coordinate system, the Minkowski billiard map $\mathcal{T}$ preserves the standard area form $\omega = ds \wedge du$. We then classify the periodic orbits of Minkowski billiards with period $2$ and derive fo

Makoto Uemura, Yuzuki Koga, Ryosuke Sazaki, Tomoya Yukino

Studying the early stages of transient events provides crucial information about the fundamental physical processes in cataclysmic variables (CVs). However, determining an appropriate observation mode immediately after the discovery of a new transient presents challenges due to significant uncertainties regarding its nature. We developed a framework designed

Kee Siong Ng, Samuel Yang-Zhao, Timothy Cadogan-Cowper

The AI safety literature is full of examples of powerful AI agents that, in blindly pursuing a specific and usually narrow objective, ends up with unacceptable and even catastrophic collateral damage to others. In this paper, we consider the problem of social harms that can result from actions taken by learning and utility-maximising agents in a multi-agent

Wuyue Yang, Liangrong Peng, Guojie Li, Liu Hong

Maximum entropy principle (MEP) offers an effective and unbiased approach to inferring unknown probability distributions when faced with incomplete information, while neural networks provide the flexibility to learn complex distributions from data. This paper proposes a novel neural network architecture, the MEP-Net, which combines the MEP with neural networ

Juncheng Dong, Zihao Wu, Hamid Jafarkhani, Ali Pezeshki

Many challenges in science and engineering, such as drug discovery and communication network design, involve optimizing complex and expensive black-box functions across vast search spaces. Thus, it is essential to leverage existing data to avoid costly active queries of these black-box functions. To this end, while Offline Black-Box Optimization (BBO) is eff

Yi Zheng, Jin-Shi Xu, Chuan-Feng Li, Guang-Can Guo

Klyshko's advanced-wave picture (AWP) is mainly interpreted by replacing the nonlinear crystal producing biphotons via spontaneous parametric down-conversion (SPDC) by a mirror in quantum imaging protocols with thin crystals, where the biphotons are perfectly correlated in position at the crystal. To better explain the biphoton spatial states produced by arb

Shuyi Wang, Kevin Li, Jiaoyang Huang

In this article, we study random graphs with a given degree sequence $d_1, d_2, \cdots, d_n$ from the configuration model. We show that under mild assumptions of the degree sequence, the spectral distribution of the normalized Laplacian matrix of such random graph converges in distribution to the semicircle distribution as the number of vertices $n\rightarro

Xin-Xin Yang, Kai-Ye Shi, F. Nur Ünal, Wei Zhang

A two-dimensional periodically driven (Floquet) system with zero winding number in the absence of time-reversal symmetry is usually considered topologically trivial. Here, we study the dynamics of a Gaussian wave packet placed at the boundary of a two-dimensional driven system with zero winding numbers but multiple valley-protected edge states that can be re

Ryosuke Takata, Yujin Tang, Yingtao Tian, Norihiro Maruyama

This study investigates collective behaviors that emerge from a group of homogeneous individuals optimized for a specific capability. We created a group of simple, identical neural network based agents modeled after chemotaxis-driven vehicles that follow pheromone trails and examined multi-agent simulations using clones of these evolved individuals. Our resu

Ashutosh Hathidara, Lalit Pandey

A Perceptron is a fundamental building block of a neural network. The flexibility and scalability of perceptron make it ubiquitous in building intelligent systems. Studies have shown the efficacy of a single neuron in making intelligent decisions. Here, we examined and compared two perceptrons with distinct mechanisms, and developed a quantum version of one

Matthew J. Green, Yoav Ziv, Hans-Walter Rix, Dan Maoz

Stellar-mass black holes descend from high-mass stars, most of which had stellar binary companions. However, the number of those binary systems that survive the binary evolution and black hole formation is uncertain by multiple orders of magnitude. The survival rate is particularly uncertain for massive stars with low-mass companions, which are thought to be

Shepard Xia, Brian Lu, Jason Eisner

A hallmark of intelligence is the ability to flesh out underspecified situations using "common sense." We propose to extract that common sense from large language models (LLMs), in a form that can feed into probabilistic inference. We focus our investigation on $\textit{guesstimation}$ questions such as "How much are Airbnb listings in Newark, NJ?" Formulati

Peng Gao

We establish lower bounds for the $2k$-th moment of central values of the family of primitive Dirichlet $L$-functions to a fixed prime modulus for all real $k<0$, assuming the non-vanishing of these $L$-values.

Fadi Hamad, Oliver Hinder

We present an adaptive trust-region method for unconstrained optimization that allows inexact solutions to the trust-region subproblems. Our method is a simple variant of the classical trust-region method of \citet{sorensen1982newton}. The method achieves the best possible convergence bound up to an additive log factor, for finding an $\epsilon$-approximate

Changqing Ji, Keisuke Kawasaki, Isao Hasegawa, Takayuki Okatani

In the application of brain-computer interface (BCI), while pursuing accurate decoding of brain signals, we also need consider the computational efficiency of BCI devices. ECoG signals are multi-channel temporal signals which is collected using a high-density electrode array at a high sampling frequency. The data between channels has a high similarity or red

Christian Carver, Jared Marchant, Benjamin Fisher, Nicholas Townsend

In this work, we perform on-chip quantum random number generation (QRNG) that uses a novel differential amplifier configuration for conjugate homodyne detection. Leveraging separate integrated photonics and integrated analog circuit platforms, we present an alternative method for QRNG. This approach exploits the observable $\hat{\text{Z}}$, derived from the

Bo Wen, Haochen Zhang, Dirk-Uwe G. Bartsch, William R. Freeman

Topological correctness is critical for segmentation of tubular structures, which pervade in biomedical images. Existing topological segmentation loss functions are primarily based on the persistent homology of the image. They match the persistent features from the segmentation with the persistent features from the ground truth and minimize the difference be

Liu Liu, Xinjie Wang, Jiaxiong Qiu, Tianwei Lin

3D scene reconstruction is a foundational problem in computer vision. Despite recent advancements in Neural Implicit Representations (NIR), existing methods often lack editability and compositional flexibility, limiting their use in scenarios requiring high interactivity and object-level manipulation. In this paper, we introduce the Gaussian Object Carver (G

Joonhyun Yeo, Haena Shim

An open quantum system interacting with a heat bath at given temperature is expected to reach the mean force Gibbs (MFG) state as a steady state. The MFG state is given by tracing out the bath degrees of freedom from the equilibrium Gibbs state of the total system plus bath. When the interaction between the system and the bath is not negligible, it is differ

Ismail Ismail Tijjani, Ahmad Abubakar Mustapha, Isma'il Tijjani Idris

The Naira is Nigeria's official currency in daily transactions. This study presents the deployment and evaluation of Deep Learning (DL) models to classify Currency Notes (Naira) by denomination. Using a diverse dataset of 1,808 images of Naira notes captured under different conditions, trained the models employing different architectures and got the highest

Zihui Xue, Joungbin An, Xitong Yang, Kristen Grauman

While image captioning provides isolated descriptions for individual images, and video captioning offers one single narrative for an entire video clip, our work explores an important middle ground: progress-aware video captioning at the frame level. This novel task aims to generate temporally fine-grained captions that not only accurately describe each frame

Liang Li, Shenghao Luo, Ruipeng Shen

Wave/Schr\"{o}dinger equations with potentials naturally originates from both the quantum physics and the study of nonlinear equations. The distractive Coulomb potential is a quantum mechanical description of distractive Coulomb force between two particles with the same charge. The spectrum of the operator $-\Delta +1/|x|$ is well known and there are also a

Marcelo Tala Pinto, Andrés Jordán, Lorena Acuña, Matías Jones

We report the discovery and characterization of three new transiting giant planets orbiting TOI-6628, TOI-3837 and TOI-5027, and one new warm sub-Saturn orbiting TOI-2328, whose transits events were detected in the lightcurves of the Transiting Exoplanet Survey Satellite \textbf{(TESS)} space mission. By combining TESS lightcurves with ground-based photometr

Shashi Chourasiya

Let $N(\sigma,T)$ denote the number of nontrivial zeros of the Riemann zeta function with real part greater than $\sigma$ and imaginary part lying between $0$ and $T$. In this article, we provide an explicit version of Carlson's zero density estimate, that is, $N(\sigma, T) \leq 0.78 T^{4 \sigma (1- \sigma)} (\log T)^{5-2 \sigma} $, with a slight improvement

Yik K. Lee, Jackson S. Smith, Hong Liu, Dimitrie Culcer

Two-dimensional hole gases (2DHGs) have strong intrinsic spin-orbit coupling and could be used to build spin filters by utilising transverse magnetic focusing (TMF). However, with an increase in the spin degree of freedom, holes demonstrate significantly different behaviour to electrons in TMF experiments, making it difficult to interpret the results of thes

Julian Junyan Wang, Victor Xiaoqi Wang

Unequal access to costly datasets essential for empirical research has long hindered researchers from disadvantaged institutions, limiting their ability to contribute to their fields and advance their careers. Recent breakthroughs in Large Language Models (LLMs) have the potential to democratize data access by automating data collection from unstructured sou

Igor Pak, Colleen Robichaux

Schubert coefficients are nonnegative integers $c^w_{u,v}$ that arise in Algebraic Geometry and play a central role in Algebraic Combinatorics. It is a major open problem whether they have a combinatorial interpretation, i.e, whether $c^w_{u,v} \in \#{\sf P}$. We study the closely related vanishing problem of Schubert coefficients: $\{c^w_{u,v}=^? 0\}$. Unti

B. Gimenez, G. Pelaitay, W. Zuluaga

This paper focuses on semilattices with adjunctions (SLatas), which are semilattices with a greatest element enriched with a pair of adjoint maps. We develop a spectral-style duality for SLatas, building on prior topological dualities for monotone semilattices. As an application of this duality, we characterize SLata congruences through an adaptation of lowe

Kazuya Echigo, Abhishek Cauligi, Saptarshi Bandyopadhyay, Dan Scharf

This paper presents the development and evaluation of an optimization-based autonomous trajectory planning algorithm for the asteroid reconnaissance phase of a deep-space exploration mission. The reconnaissance phase is a low-altitude flyby to collect detailed information around a potential landing site. Although such autonomous deep-space exploration missio

Qian Guo, Peiyuan Chen

With the intensification of global aging, health management of the elderly has become a focus of social attention. This study designs and implements a smart elderly care service model to address issues such as data diversity, health status complexity, long-term dependence and data loss, sudden changes in behavior, and data privacy in the prediction of health

Kristina Lerman

The friendship paradox in social networks states that your friends have more friends than you do, on average. Recently, a stronger variant of the paradox was shown to hold for most people within a network: `most of your friends have more friends than you do.' Unlike the original paradox, which arises trivially because a few very popular people appear in the

Shigeru Furuichi, Yuki Seo

Recently, the spectral geometric mean has been studied by some papers. In this paper, we firstly estimate the H\"{o}lder type inequality of the spectral geometric mean of positive invertible operators on the Hilbert space for all real order in terms of the generalized Kantorovich constant and show the relation between the weighted geometric mean and the spec

Ethan Crosby, Mario Mateo, Ivanna Escala, Helmut Jerjen

We report the spectroscopic analysis of ten satellite galaxy candidates in the sphere of influence of the Sombrero galaxy (M104, NGC4594), based on data obtained with IFUM (Integral Field Units for Magellan). Based on their newly-observed recessional velocities, we confirm that nine of these candidates are satellite galaxies of M104, with one being a backgro

Sherjeel Mahmood Baig, Hideki Abe

Flexible electronics are attracting attention due to the increasing demand for lightweight, bendable devices that can conform to various surfaces, including human skin. Although indium tin oxide (ITO) is widely used for electrical interconnection in flexible electronics, its brittleness limits its durability under repeated bending. In this study, we introduc

Ao Liu, Cuihong Wen, Jieci Wang

The integration of algorithms from quantum information with neural networks has enabled unprecedented advancements in various domains. Nonetheless, the application of quantum machine learning algorithms for image classification predominantly relies on traditional architectures such as variational quantum circuits. The performance of these models is closely t

Raisa Tasnim, Mehanaz Chowdhury, Md Ataur Rahman

Author profiling, the analysis of texts to uncover attributes such as gender and age of the author, has become essential with the widespread use of social media platforms. This paper focuses on author profiling in the Bangla language, aiming to extract valuable insights about anonymous authors based on their writing style on social media. The primary objecti

Anubha Mahajan, Shreya Hegde, Ethan Shay, Daniel Wu

In India, the majority of farmers are classified as small or marginal, making their livelihoods particularly vulnerable to economic losses due to market saturation and climate risks. Effective crop planning can significantly impact their expected income, yet existing decision support systems (DSS) often provide generic recommendations that fail to account fo

Surangika Ranathunga, Asanka Ranasinghea, Janaka Shamala, Ayodya Dandeniyaa

This paper presents a multi-way parallel English-Tamil-Sinhala corpus annotated with Named Entities (NEs), where Sinhala and Tamil are low-resource languages. Using pre-trained multilingual Language Models (mLMs), we establish new benchmark Named Entity Recognition (NER) results on this dataset for Sinhala and Tamil. We also carry out a detailed investigatio

X. L. Yan, Z. K. Xue, J. C. Wang, L. H. Yang

Solar filaments are spectacular objects in the solar atmosphere, consisting of accumulations of cool, dense, and partially ionized plasma suspended in the hot solar corona against gravity. The magnetic structures that support the filament material remain elusive, partly due to the lack of high resolution magnetic field measurements in the chromosphere and co

Lizhen Xu, Zehao Wu, Wenzhao Qiu, Shanmin Pang

Query-based models are extensively used in 3D object detection tasks, with a wide range of pre-trained checkpoints readily available online. However, despite their popularity, these models often require an excessive number of object queries, far surpassing the actual number of objects to detect. The redundant queries result in unnecessary computational and m

Kou Tian, Chentao Yue, Changyang She, Yonghui Li

This paper presents a novel auto-encoder based end-to-end channel encoding and decoding. It integrates deep reinforcement learning (DRL) and graph neural networks (GNN) in code design by modeling the generation of code parity-check matrices as a Markov Decision Process (MDP), to optimize key coding performance metrics such as error-rates and code algebraic p

Justin Folden, Atul Ingle, Sanjeev J. Koppal

Fast, efficient, and accurate depth-sensing is important for safety-critical applications such as autonomous vehicles. Direct time-of-flight LiDAR has the potential to fulfill these demands, thanks to its ability to provide high-precision depth measurements at long standoff distances. While conventional LiDAR relies on avalanche photodiodes (APDs), single-ph

Serena An, Katherine Tung, Yuchong Zhang

Postnikov--Stanley polynomials $D_u^w$ are a generalization of skew dual Schubert polynomials to the setting of arbitrary Weyl groups. We prove that Postnikov--Stanley polynomials are Lorentzian by showing that they are degree polynomials of Richardson varieties. Our result yields an interesting class of Lorentzian polynomials related to the geometry of Rich

Katherine E. Stange

These notes cover and expand upon the material for two summer schools: The first, which was held at CIRM, Marseille, France, July 10-14, 2023, as part of "Renormalization and Visualization for packing, billiard and surfaces", was titled "Number theory as a door to geometry, dynamics and illustration". The second was held at NSU IMS in Singapore, June 3-7, 20

Donald Silberger

Let $n,d$, and $k$ be positive integers where $n$ and $d$ are coprime. Our two main results are Theorem 1. There is a partition of the infinite interval $[kd,\infty)$ of positive integers into a family of finite sets $X$ for which the sum of the reciprocals of the elements in $X$ is $n/d$. Theorem 1. There is a partition of $[2kd,\infty)$ into an infinite fa

Gary A. McCully, John D. Hastings, Shengjie Xu

This study examines the impact of data snooping on neural networks used to detect vulnerabilities in lifted code, and builds on previous research that used word2vec and unidirectional and bidirectional transformer-based embeddings. The research specifically focuses on how model performance is affected when embedding models are trained with datasets, which in

Marco A. S. Netto, Wolfgang De Savador, Davide Vanzo

Azure Cloud offers a wide range of resources for running HPC workloads, requiring users to configure their deployment by selecting VM types, number of VMs, and processes per VM. Suboptimal decisions may lead to longer execution times or additional costs for the user. We are developing an open-source tool to assist users in making these decisions by consideri

Philipp Zimmermann

The main purpose of this article is to establish new uniqueness results for Calder\'on type inverse problems related to damped nonlocal wave equations. To achieve this goal we extend the theory of very weak solutions to our setting, which allows to deduce an optimal Runge approximation theorem. With this result at our disposal, we can prove simultaneous dete

Fernando Roldán, Cristian Vega

In this article, we study inertial algorithms for numerically solving monotone inclusions involving the sum of a maximally monotone and a cocoercive operator. In particular, we analyze the convergence of inertial and relaxed versions of the nonlinear forward-backward with momentum (NFBM). We propose an inertial version including a relaxation step, and a seco

Pan Zhang, Baochai Peng, Chaoran Lu, Quanjin Huang

Synthetic Aperture Radar (SAR) images have proven to be a valuable cue for multimodal Land Cover Classification (LCC) when combined with RGB images. Most existing studies on cross-modal fusion assume that consistent feature information is necessary between the two modalities, and as a result, they construct networks without adequately addressing the unique c

James Allan, Eunsol Choi, Daniel P. Lopresti, Hamed Zamani

In the fast-evolving field of information retrieval (IR), the integration of generative AI technologies such as large language models (LLMs) is transforming how users search for and interact with information. Recognizing this paradigm shift at the intersection of IR and generative AI (IR-GenAI), a visioning workshop supported by the Computing Community Conso

Vibujithan Vigneshwaran, Erik Ohara, Matthias Wilms, Nils Forkert

Although deep learning techniques show promising results for many neuroimaging tasks in research settings, they have not yet found widespread use in clinical scenarios. One of the reasons for this problem is that many machine learning models only identify correlations between the input images and the outputs of interest, which can lead to many practical prob

Mohammad Hossein Sarkhosh, Mohammad Hassan Dabirzadeh, Mohamad Ali Bijarchi, Hossein Nejat Pishkenari

Precise manipulation of liquid marbles has significant potential in various applications such as lab-on-a-chip systems, drug delivery, and biotechnology and has been a challenge for researchers. Ferrofluid marble (FM) is a marble with a ferrofluid core that can easily be manipulated by a magnetic field. Although FMs have great potential for accurate position

Kenneth Benício, Fazal-E-Asim, Bruno Sokal, André L. F. de Almeida

We study a monostatic multiple-input multiple-output sensing scenario assisted by a reconfigurable intelligent surface using tensor signal modeling. We propose a method that exploits the intrinsic multidimensional structure of the received echo signal, allowing us to recast the target sensing problem as a nested tensor-based decomposition problem to jointly

Kanav Singh Rana, Nitu Kumari

A Transformer-based Koopman autoencoder is proposed for linearizing Fisher&#39;s reaction-diffusion equation. The primary focus of this study is on using deep learning techniques to find complex spatiotemporal patterns in the reaction-diffusion system. The emphasis is on not just solving the equation but also transforming the system&#39;s dynamics into a mor

Abdullah Fajar, Setiadi Yazid, Indra Budi

Background: Explainability in phishing detection model can support a further solution of phishing attack mitigation by increasing trust and understanding how phishing can be detected. Objective: The aims of this study to determine and best recommendation to apply an approach which has several components with abilities to fulfil the critical needs Methods: A

Xiang Wang, Wenjie Yu, Yixin Xie, Yanfeng He

The fracturing-flooding technology is a new process for the development of low-permeability oil reservoirs, achieving a series of successful applications in oilfield production. However, existing numerical simulation methods for pressure drive struggle to efficiently and accurately simulate the dynamic changes in reservoir properties during the fracturing-fl

Ting-Ruen Wei, Haowei Liu, Huei-Chung Hu, Xuyang Wu

We introduce a novel framework for representation learning in head pose estimation (HPE). Previously such a scheme was difficult due to head pose data sparsity, making triplet sampling infeasible. Recent progress in 3D generative adversarial networks (3D-aware GAN) has opened the door for easily sampling triplets (anchor, positive, negative). We perform cont

Nasrin Farahani, Daria Popova-Gorelova

The Bethe-Salpeter equation (BSE) is a powerful theoretical approach that is capable to accurately treat electron-hole interactions in materials in an excited state. We developed an ab initio framework based on the BSE to describe a pump-probe experiment, in which an x-ray pulse probes solid-state valence excitons by means of x-ray absorption spectroscopy. O

Shimal Harichurn, András Némethi, Josef Svoboda

We study the minimal $q$-exponent $\Delta$ in the BPS $q$-series $\widehat{Z}$ of negative definite plumbed 3-manifolds equipped with a spin$^{\rm c}$-structure. We express $\Delta$ of Seifert manifolds in terms of an invariant commonly used in singularity theory. We provide several examples illustrating the interesting behaviour of $\Delta$ for non-Seifert

Soheila Sadeghi

In the dynamic landscape of project management, scope changes are an inevitable reality that can significantly impact project performance. These changes, whether initiated by stakeholders, external factors, or internal project dynamics, can lead to cost overruns and schedule delays. Accurately predicting the consequences of these changes is crucial for effec

Zechuan Yin, Justin J. Welter, Connor A. Hart, Paul V. Petruzzi

Quantum systems composed of solid-state electronic spins can be sensitive detectors of narrowband magnetic fields. A prominent example is the nitrogen-vacancy (NV) center in diamond, which has been employed for magnetic spectroscopy with high spatial and spectral resolution. However, NV-diamond spectroscopy protocols are typically based on dynamical decoupli

Aditya Dutt, Ishikaa Lunawat, Manpreet Kaur

Large Foundation Models like Dust3r can produce high quality outputs such as pointmaps, camera intrinsics, and depth estimation, given stereo-image pairs as input. However, the application of these outputs on tasks like Visual Localization requires a large amount of inference time and compute resources. To address these limitations, in this paper, we propose

Vijay Balasubramanian, Javier M. Magan, Poulami Nandi, Qingyue Wu

Recent proposals equate the size of Einstein-Rosen bridges in JT gravity to spread complexity of a dual, double-scaled SYK theory (DSSYK). We show that the auxiliary ``chord basis'' of these proposals is an extrapolation from a sub-exponential part of the finite-dimensional physical Krylov basis of a spreading thermofield double state. The physical tridiagon

Prasanna Salasiya, Bojan B. Guzina

We develop an effective computational tool for simulating the scattering of 1D waves by a composite layer architected in an otherwise homogeneous medium. The layer is designed as the union of segments cut from various mother periodic media, which allows us to describe the wavefield in each segment in terms of the ``left'' and ``right'' Bloch waves. For a giv

Sasha Salter, Richard Warren, Collin Schlager, Adrian Spurr

Hands are the primary means through which humans interact with the world. Reliable and always-available hand pose inference could yield new and intuitive control schemes for human-computer interactions, particularly in virtual and augmented reality. Computer vision is effective but requires one or multiple cameras and can struggle with occlusions, limited fi

Xiang Fang, Keyi Yin, Yuchen Zhu, Jixuan Ruan

Quantum Error Correction (QEC) is a cornerstone of fault-tolerant, large-scale quantum computing. However, qubit error drift significantly degrades QEC performance over time, necessitating periodic calibration. Traditional calibration methods disrupt quantum states, requiring system downtime and making in situ calibration infeasible. We present CaliScalpel,

Nadeen Fathallah, Steffen Staab, Alsayed Algergawy

Ontology learning in complex domains, such as life sciences, poses significant challenges for current Large Language Models (LLMs). Existing LLMs struggle to generate ontologies with multiple hierarchical levels, rich interconnections, and comprehensive class coverage due to constraints on the number of tokens they can generate and inadequate domain adaptati

Juan Pablo Gatica

We study observables in the scattering of classical, spinning objects using the KMOC formalism. In particular, we derive formulas to higher order in spin and one loop $\mathcal{O}(G^2)$ for the spin kick and momentum impulse. Our derivation method is agnostic to the choice of theory or special conditions, such as the spin supplementary condition (SSC); we on

William Sharpless, Zeyuan Feng, Somil Bansal, Sylvia Herbert

As the dimension of a system increases, traditional methods for control and differential games rapidly become intractable, making the design of safe autonomous agents challenging in complex or team settings. Deep-learning approaches avoid discretization and yield numerous successes in robotics and autonomy, but at a higher dimensional limit, accuracy falls a

Weilu Shen, Anqi Chen, Gurminder K. Paink, Nicole Black

Effective intracellular delivery is essential for successful gene editing of cells. Spatially selective delivery to cells that is simultaneously precise, consistent, and non-destructive remains challenging using conventional state-of-the-art techniques. Here, we introduce a carrier-free method for spatiotemporal delivery of fluorescently labeled cargo into b

Anthony Sofo, Jean-Christophe Pain, Victor Scharaschkin

In this paper we investigate a class of integrals that were encountered in the course of a work on statistical plasma physics, in the so-called Sommerfeld temperature-expansion of the electronic entropy. We show that such integrals, involving some parameters, can be fully described in closed form represented by special functions.

Dar-Yen Chen, Hmrishav Bandyopadhyay, Kai Zou, Yi-Zhe Song

We introduce NitroFusion, a fundamentally different approach to single-step diffusion that achieves high-quality generation through a dynamic adversarial framework. While one-step methods offer dramatic speed advantages, they typically suffer from quality degradation compared to their multi-step counterparts. Just as a panel of art critics provides comprehen

Ihab Tabbara, Hussein Sibai

Safety filters in control systems correct nominal controls that violate safety constraints. Designing such filters as functions of visual observations in uncertain and complex environments is challenging. Several deep learning-based approaches to tackle this challenge have been proposed recently. However, formally verifying that the learned filters satisfy c

Talant Talipov

We prove the existence of a constant $C > 0$ such that for any Riemannian metric $g$ on a 2-dimensional sphere $S^2$, there exist two distinct closed geodesics with lengths $L_{1}$ and $L_{2}$ satisfying $L_{1} L_{2} \leq C \cdot \operatorname{Area}(S^2, g)$.

Kimy Agudelo, Diego Restrepo, Andrés Rivera, David Suarez

Scenarios for secluded WIMP dark matter models have been extensively studied in simplified versions. This paper shows a complete UV realization of a secluded WIMP dark matter model with an extra Abelian gauge symmetry that includes two-component dark matter candidates, where the dark matter conversion process plays a significant role in determining the relic

Luke W. Yerbury, Ricardo J. G. B. Campello, G. C. Livingston, Mark Goldsworthy

The widespread adoption of smart meters for monitoring energy consumption has generated vast quantities of high-resolution time series data which remains underutilised. While clustering has emerged as a fundamental tool for mining smart meter time series (SMTS) data, selecting appropriate clustering methods remains challenging despite numerous comparative st

Xuewen Luo, Fan Ding, Yinsheng Song, Xiaofeng Zhang

There is growing interest in leveraging the capabilities of robust Multi-Modal Large Language Models (MLLMs) directly within autonomous driving contexts. However, the high costs and complexity of designing and training end-to-end autonomous driving models make them challenging for many enterprises and research entities. To address this, our study explores a

Luis M. San-José-Revuelta, Pablo Casaseca-de-la-Higuera

This work proposes a modified version of an emerging nature-inspired technique, named Flower Pollination Algorithm (FPA), for equalizing digital multiuser channels. This equalization involves two different tasks: 1) estimation of the channel impulse response, and 2) estimation of the users' transmitted symbols. The new algorithm is developed and applied in a

Kareem A. Wahid, Clifton D. Fuller, David Fuentes

In this manuscript, we draw on the insights from Kahneman, Sibony, and Sunsteins influential nonfiction book Noise: A Flaw in Human Judgment to explore the concept of unwanted variability in judgment (i.e., noise). We introduce key terms and connect these insights to the field of radiation oncology by illustrating how noise contributes to errors in clinicall

Xiaolei Zhang, Wei Qi

In this note, we give several characterizations of left pure-semisimple in terms of the (pre)envelope, (pre)cover, direct limits, direct sums, inverse limits and direct products properties of pure-projective modules or pure-injective modules.

Bharath Antarvedi Goda, Zhenwei Ma, Stefano Fregonese, Mattia Bacca

Cutting mechanics of soft solids is gaining rapid attention thanks to its promising benefits in material characterization and other applications. However, a full understanding of the physical phenomena is still missing, and several questions remain outstanding. E.g.: How can we directly and reliably measure toughness from cutting experiments? What is the rol

Tom Needham, Ethan Semrad

Graphs are fundamental tools for modeling pairwise interactions in complex systems. However, many real-world systems involve multi-way interactions that cannot be fully captured by standard graphs. Hypergraphs, which generalize graphs by allowing edges to connect any number of vertices, offer a more expressive framework. In this paper, we introduce a new met

Toni Mäkelä

Proton-proton collisions at the LHC generate high-intensity collimated beams of forward neutrinos up to TeV energies. Their recent observations and the initiation of a novel LHC neutrino program motivate investigations of this previously unexploited beam. The kinematic region for neutrino deep-inelastic scattering measurements at the LHC overlaps with that o

Mayer M. Feldman, Gordian Fuchs, Tiffany Liu, Luke A. D'Imperio

We report on low-frequency measurements of few electrons floating on superfluid helium using a bespoke cryogenic cascode amplifier circuit built with off-the-shelf GaAs High-Electron-Mobility Transistors (HEMTs). We integrate this circuit with a Charge-Coupled Device (CCD) to transport the electrons on helium and characterize its performance. We show that th

Jeremy Levy, Chandralekha Singh

Traditional approaches to undergraduate-level quantum mechanics require extensive mathematical preparation, preventing most students from enrolling in a quantum mechanics course until the third year of a physics major. Here we describe an approach to teaching quantum formalism and postulates that can be used with first-year undergraduate students and even hi

Ryan Yu, Mateusz Nowak, Qintong Xie, Michelle Yilin Feng

Current approximate Coarse Correlated Equilibria (CCE) algorithms struggle with equilibrium approximation for games in large stochastic environments but are theoretically guaranteed to converge to a strong solution concept. In contrast, modern Reinforcement Learning (RL) algorithms provide faster training yet yield weaker solutions. We introduce Exp3-IXrl -

Jordan Ellenberg, Adam Logan, Padmavathi Srinivasan

The Ceresa cycle is a canonical algebraic $1$-cycle on the Jacobian of an algebraic curve. We construct an algorithm which, given a curve over a number field, often provides a certificate that the Ceresa cycle is non-torsion, without relying on the presence of any additional symmetries of the curve. Under the hypothesis that the Sato--Tate group is the whole

Felipe de Bolle, Egemen Kolemen

With the increasing urgency of climate change's impacts and limited success in reducing emissions, "geoengineering," or the artificial manipulation of the climate to reduce warming rates, has been proposed as an alternative short-term solution. Options range from taking carbon out of the atmosphere through carbon sinks and brightening clouds to increasing th

Ying Jin, Andrew Leroux

Dynamic prediction, which typically refers to the prediction of future outcomes using historical records, is often of interest in biomedical research. For datasets with large sample sizes, high measurement density, and complex correlation structures, traditional methods are often infeasible because of the computational burden associated with both data scale

Stefano Fregonese, Mattia Bacca

The mechanics of puncture and soft solid penetration is commonly explored with the assumption of frictionless contact between the needle (penetrator) and the specimen. This leads to the hypothesis of a constant penetration force. Experimental observations, however, report a linear increment of penetration force with needle tip depth. This force increment is

Wenbo Zhang, Junyu Chen, Christopher Kanan

Due to their large sizes, volumetric scans and whole-slide pathology images (WSIs) are often processed by extracting embeddings from local regions and then an aggregator makes predictions from this set. However, current methods require post-hoc visualization techniques (e.g., Grad-CAM) and often fail to localize small yet clinically crucial details. To addre

F. Motte, Y. Pouteau, T. Nony, P. Dell'Ova

ALMA-IMF imaged 15 massive protoclusters down to a resolution of of 2 kau scales, identifying about 1000 star-forming cores. The mass and luminosity of these cores, which are fundamental physical characteristics, are difficult to determine, a problem greatly exacerbated at the distances >2 kpc of ALMA-IMF protoclusters. We combined new datasets and radiative

Tianxiong Han, R. D. McKenzie, Joanna Blawat, Tyler J. Slade

TbV$_6$Sn$_6$ is a topological metal where ferromagnetic Tb ions with strong uniaxial magnetic anisotropy interact with V kagome layers. Inelastic neutron scattering (INS) measurements show that the Tb ions adopt an Ising doublet ground state. Here, we consider whether a transverse magnetic field can drive TbV$_6$Sn$_6$ toward a quantum critical point, provi

Vincent A. Cicirello

Evolutionary algorithms rely very heavily on randomized behavior. Execution speed, therefore, depends strongly on how we implement randomness, such as our choice of pseudorandom number generator, or the algorithms used to map pseudorandom values to specific intervals or distributions. In this paper, we observe that the standard bit-flip mutation of a genetic

James Aspnes

A population protocol stably computes a relation R(x,y) if its output always stabilizes and R(x,y) holds if and only if y is a possible output for input x. Alternatively, a population protocol computes a predicate R(<x,y>) on pairs <x,y> if its output stabilizes on the truth value of the predicate when given <x,y> as input. We consider how stably computing R

Yuta Watanabe

Let $X$ be a weakly pseudoconvex manifold and $L\longrightarrow X$ be a holomorphic line bundle with a singular positive Hermitian metric $h$. In this article, we provide a points separation theorem and an embedding for the adjoint linear subsystem including the multiplier ideal sheaf $\mathscr{I}(h^m)$, with respect to an appropriate set excluding a singula

David Gimeno-Gómez, Catarina Botelho, Anna Pompili, Alberto Abad

Recent works in pathological speech analysis have increasingly relied on powerful self-supervised speech representations, leading to promising results. However, the complex, black-box nature of these embeddings and the limited research on their interpretability significantly restrict their adoption for clinical diagnosis. To address this gap, we propose a no

Shuhao Wu, Xinzhu Li, Ian Gallagher, Lexington Mandachi

We report the development of an experimental approach that can characterize the energy level structure of an individual silicon vacancy (SiV) center in a magnetic field and extract the key parameters for the energy level structure. This approach builds upon a theoretical model that includes effects of the static strain, dynamic Jahn-Teller coupling, and magn