February 2024 arXiv papers — page 129

Nicolai Jork, John Sebastian H. Simon

This paper investigates solution stability properties of unregularized tracking-type optimal control problems constrained by the Boussinesq system. In our model, the controls may appear linearly and distributed in both of the equations that constitute the Boussiniesq system and in the objective functional. We establish, not only the existence of weak solutio

Heewoo Kim, Hansol Jeong, Han Seb Moon

Photonic quantum states generated from atomic ensembles will play important roles in future quantum networks and long-distance quantum communication because their advantages, such as universal identity and narrow spectral bandwidth, are essential for quantum nodes and quantum repeaters based on atomic ensembles. In this study of the biphoton temporal wavefor

Yuxin Ren, Qiya Yang, Yichun Wu, Wei Xu

Contemporary recommendation systems are designed to meet users' needs by delivering tailored lists of items that align with their specific demands or interests. In a multi-stage recommendation system, reranking plays a crucial role by modeling the intra-list correlations among items. The key challenge of reranking lies in the exploration of optimal sequences

Trystan S. Lambert, R. J. Assef, C. Mazzucchelli, E. Bañados

High-redshift quasars are thought to live in the densest regions of space which should be made evident by an overdensity of galaxies around them. However, campaigns to identify these overdensities through the search of Lyman Break Galaxies (LBGs) and Lyman $\alpha$ emitters (LAEs) have had mixed results. These may be explained by either the small field of vi

Sundar Krishnan, William Bradley Glisson

These days, there are many ways to watch streaming videos on television. When compared to a standalone smart television, streaming devices such as Roku and Amazon Fire Stick have a plethora of app selections. While these devices are platform agnostic and compatible with smartphones, they can still leave behind crumbs of sensitive data that can cause privacy,

Amol Aggarwal, Alexei Borodin

In this paper we assign a family of $n$ coupled line ensembles to any $U_q (\widehat{\mathfrak{sl}}_{n+1})$ colored stochastic fused vertex model, which satisfies two properties. First, the joint law of their top curves coincides with that of the colored height functions for the vertex model. Second, the $n$ line ensembles satisfy an explicit Gibbs property

Gustavo Gutierrez-Cano, Gustavo Niz

We explore black hole solutions and some of its physical properties in Einstein's theory in 4D, modified by a cubic gravity term and in the presence of non-linear electrodynamics. In the context of Effective Field Theories (EFT) and under certain assumptions, these curvature and non-linear electromagnetic terms represent the first corrections to the Einstein

J. E. Horvath, Lucas M. de Sá, Lívia S. Rocha, Gustavo Y. Chinen

We address in this work the nature and evolution of the long-period compact star sources, which has recently added several unexpected members. The central hypothesis is that particle winds drive their evolution, being an important factor for these relatively old sources. We show the consistency of this picture and remark some unsolved problems and caveats wi

Qiyun Yi, Ting Han, Jinyi Jiang, Xiangjun Xing

In recent years, magnetic skyrmion-based spin-torque nano-oscillators (STNOs) attract considerable interest for their prospect in future-generation communication and spintronic technologies. However, some critical issues, which hamper their practical applications, e.g., the long start-up time and variable skyrmion gyration orbit, remain to be resolved. Here,

Rohan Sharma, Shijie Zhou, Kaiyi Ji, Changyou Chen

We introduce a novel machine unlearning framework founded upon the established principles of the min-max optimization paradigm. We capitalize on the capabilities of strong Membership Inference Attacks (MIA) to facilitate the unlearning of specific samples from a trained model. We consider the scenario of two networks, the attacker $\mathbf{A}$ and the traine

Yihong Ji, Danni Chen, Hanzhe Wu, Gan Xiang

Stimulated Emission Depletion Microscopy (STED) can achieve a spatial resolution as high as several nanometers. As a point scanning imaging method, it requires 3D scanning to complete the imaging of 3D samples. The time-consuming 3D scanning can be compressed into a 2D one in the non-diffracting Bessel-Bessel STED (BB-STED) where samples are effectively exci

Tomohiro Fukaya, Takumi Matsuka

In this paper, we compute (co)homologies of ideal boundaries of free products of geodesic coarsely convex spaces in terms of those of each of the components. The (co)homology theories we consider are, $K$-theory, Alexander-Spanier cohomology, $K$-homology, and Steenrod homology. These computations led to the computation of $K$-theory of the Roe algebra of fr

Yansong Ning, Hao Liu

Urban knowledge graph has recently worked as an emerging building block to distill critical knowledge from multi-sourced urban data for diverse urban application scenarios. Despite its promising benefits, urban knowledge graph construction (UrbanKGC) still heavily relies on manual effort, hindering its potential advancement. This paper presents UrbanKGent, a

Vishakha Ramani, Jiachen Chen, Roy D. Yates

In the realm of shared memory systems, the challenge of reader-writer synchronization is closely coupled with the potential for readers to access outdated updates. Read-Copy-Update (RCU) is a synchronization primitive that allows for concurrent and non-blocking read access to fresh data. This is achieved through the creation of updated data copies, with each

Fedor Borisyuk, Mingzhou Zhou, Qingquan Song, Siyu Zhu

We present LiRank, a large-scale ranking framework at LinkedIn that brings to production state-of-the-art modeling architectures and optimization methods. We unveil several modeling improvements, including Residual DCN, which adds attention and residual connections to the famous DCNv2 architecture. We share insights into combining and tuning SOTA architectur

Qing-Feng Xue, Xu-Cai Zhuang, De-Yang Duan, Ying-Jie Zhang

Entropy production is a fundamental concept that plays a crucial role in the second law of thermodynamics and the measure of irreversibility. It imposes rigorous constraints on the kinds of transformations allowed in thermodynamic processes. Using an optical setup, here we experimentally demonstrate the division of entropy production of an open quantum syste

Andrés Arrarás, Francisco J. Gaspar, Laura Portero, Carmen Rodrigo

In this work, an efficient blackbox-type multigrid method is proposed for solving multipoint flux approximations of the Darcy problem on logically rectangular grids. The approach is based on a cell-centered multigrid algorithm, which combines a piecewise constant interpolation and the restriction operator by Wesseling/Khalil with a line-wise relaxation proce

Yuzhou Gu, Aaradhya Pandey

We study the weak recovery problem on the $r$-uniform hypergraph stochastic block model ($r$-HSBM) with two balanced communities. In this model, $n$ vertices are randomly divided into two communities, and size-$r$ hyperedges are added randomly depending on whether all vertices in the hyperedge are in the same community. The goal of weak recovery is to recove

Muthu Chidambaram, Rong Ge

Data augmentation has been pivotal in successfully training deep learning models on classification tasks over the past decade. An important subclass of data augmentation techniques - which includes both label smoothing and Mixup - involves modifying not only the input data but also the input label during model training. In this work, we analyze the role play

Simin Luan, Cong Yang, Zeyd Boukhers, Xue Qin

Image research has shown substantial attention in deblurring networks in recent years. Yet, their practical usage in real-world deblurring, especially motion blur, remains limited due to the lack of pixel-aligned training triplets (background, blurred image, and blur heat map) and restricted information inherent in blurred images. This paper presents a simpl

Zichong Wang, Zhibo Chu, Thang Viet Doan, Shiwen Ni

Language models serve as a cornerstone in natural language processing (NLP), utilizing mathematical methods to generalize language laws and knowledge for prediction and generation. Over extensive research spanning decades, language modeling has progressed from initial statistical language models (SLMs) to the contemporary landscape of large language models (

Lachlan Thorpe, Lewis Bawden, Karanjot Vendal, John Bronskill

We present a transformer decoder based sports simulation engine, SportsNGEN, trained on sports player and ball tracking sequences, that is capable of generating sustained gameplay and accurately mimicking the decision making of real players. By training on a large database of professional tennis tracking data, we demonstrate that simulations produced by Spor

Di Zhang, Wei Liu, Qian Tan, Jingdan Chen

Large language models (LLMs) have made impressive progress in chemistry applications. However, the community lacks an LLM specifically designed for chemistry. The main challenges are two-fold: firstly, most chemical data and scientific knowledge are stored in structured databases, which limits the model's ability to sustain coherent dialogue when used direct

X. Oriols, D. K. Ferry

A proper knowledge of the reality of a physical theory is important to get an understanding of empirical phenomena. Despite its extraordinary predictive successes, the orthodox (also known as the Copenhagen) theory provides an indigestible definition of quantum reality: objects (such as electrons) become part of a nebulous many-particle wave function with no

Sylvia K. Lewin, Corey E. Frank, Sheng Ran, Johnpierre Paglione

Uranium ditelluride (UTe$_2$) is recognized as a host material to unconventional spin-triplet superconductivity, but it also exhibits a wealth of additional unusual behavior at high magnetic fields. One of the most prominent signatures of the unconventional superconductivity is a large and anisotropic upper critical field that exceeds the paramagnetic limit.

Ashok Khanna, Olivier Francon, Risto Miikkulainen

Diabetes, a chronic condition that impairs how the body turns food into energy, i.e. blood glucose, affects 38 million people in the US alone. The standard treatment is to supplement carbohydrate intake with an artificial pancreas, i.e. a continuous insulin pump (basal shots), as well as occasional insulin injections (bolus shots). The goal of the treatment

Yuya Koda, Kazuto Takao

We give two criteria for diagrams of Heegaard splittings of 3-manifolds. Weaker one of them guarantees that the splitting is strongly irreducible, and the stronger one guarantees in addition that the Goeritz group is finite. They are generalizations of the criteria introduced by Casson-Gordon and Lustig-Moriah. Their original ones require as input the diagra

Nadia Blackshaw, Nick Huggett, James Ladyman

This paper investigates the formation and propagation of wavefunction `branches' through the process of entanglement with the environment. While this process is a consequence of unitary dynamics, and hence significant to many if not all approaches to quantum theory, it plays a central role in many recent articulations of the Everett or `many worlds' interpre

Christoph Nölle

The numerical treatment of quantum mechanics in the semi-classical regime is known to be computationally demanding, due to the highly oscillatory behaviour of the wave function and its large spatial extension. A recently proposed representation of quantum mechanics as a residual theory on top of classical Hamiltonian mechanics transforms a semi-classical wav

Azuka Chiejina, Brian Kim, Kaushik Chowhdury, Vijay K. Shah

While the open architecture, open interfaces, and integration of intelligence within Open Radio Access Network technology hold the promise of transforming 5G and 6G networks, they also introduce cybersecurity vulnerabilities that hinder its widespread adoption. In this paper, we conduct a thorough system-level investigation of cyber threats, with a specific

Tsuyoshi Miezaki, Manabu Oura, Tadashi Sakuma, Hidehiro Shinohara

In the paper [Proceedings of the Japan Academy, Ser. A Mathematical Sciences, 95(10) 111-113], the authors introduce the concept of the Tutte polynomials of genus $g$ and announce that each matroid $M$ can be reconstructed from its Tutte polynomial of genus $|\mathcal{B}(M)|$, where $\mathcal{B}(M)$ denotes the family of bases of $M$. In that paper, we also

Jens Saak, Steffen W. R. Werner

Continuous-time algebraic Riccati equations can be found in many disciplines in different forms. In the case of small-scale dense coefficient matrices, stabilizing solutions can be computed to all possible formulations of the Riccati equation. This is not the case when it comes to large-scale sparse coefficient matrices. In this paper, we provide a reformula

Matthew Jankousky, Helen Chen, Andrew Novick, Vladan Stevanović

Rocksalt is the most common crystal structure among binary compounds. Moreover, no long-lived, metastable polymorphs are observed in compounds with the rocksalt ground state. We investigate the absence of polymorphism and the dominance of the rocksalt structure via first-principles random structure sampling and transformation kinetics modeling of three rocks

Rafael Holanda, Cleto B. Miranda-Neto

The main purpose of this note is to extend and establish a new approach to the concept of (relative) Cohen-Macaulayness, by investigating the cohomological dimension as well as the depth of a pair of modules over a commutative Noetherian ring. The notion also largely extends the cohomologically complete intersection property of Hellus and Schenzel. As crucia

Shaojie Tang, Penpen Miao, Xingyu Gao, Yu Zhong

A method was proposed for the point cloud-based registration and image fusion between cardiac single photon emission computed tomography (SPECT) myocardial perfusion images (MPI) and cardiac computed tomography angiograms (CTA). Firstly, the left ventricle (LV) epicardial regions (LVERs) in SPECT and CTA images were segmented by using different U-Net neural

Duy-Minh Dang, Hao Zhou

Option contracts on two underlying assets within uncertain volatility models have their worst-case and best-case prices determined by a two-dimensional (2D) Hamilton-Jacobi-Bellman (HJB) partial differential equation (PDE) with cross-derivative terms. This paper introduces a novel ``decompose and integrate, then optimize'' approach to tackle this HJB PDE. Wi

Roni Ben-Maimon, Yakov Solomons, Nir Davidson, Ofer Firstenberg

We consider quantum light-matter interfaces comprised of multiple layers of two-dimensional atomic arrays, whose lattice spacings exceed the wavelength of light. While the coupling of light to a single layer of such a ``superwavelength" lattice is considerably reduced due to scattering losses to high diffraction orders, we show that the addition of layers ca

Haitong Wang, Aaron Hao Tan, Goldie Nejat

In unknown cluttered and dynamic environments such as disaster scenes, mobile robots need to perform target-driven navigation in order to find people or objects of interest, while being solely guided by images of the targets. In this paper, we introduce NavFormer, a novel end-to-end transformer architecture developed for robot target-driven navigation in unk

Robin J. Deeley, Rufus Willett

We prove the rational HK-conjecture for a large class of transformation groupoids in the case when the relevant action has torsion-free stabilizers. A revised version of the rational HK-conjecture in the case of (possibly) torsion stabilizers is introduced and proved for a large class of transformation groupoids. In particular, this revised version holds for

Aaron D. Johnson, Katerina Chatziioannou, Will M. Farr

Upgrades beyond the current second generation of ground-based gravitational wave detectors will allow them to observe tens of thousands neutron star and black hole binaries. Given the typical minute-to-hour duration of neutron star signals in the detector frequency band, a number of them will overlap in the time-frequency plane resulting in a nonzero cross-c

Lionel Garcia, Daniel Foreman-Mackey, Catriona A. Murray, Suzanne Aigrain

The detection of planetary transits in the light curves of active stars, featuring correlated noise in the form of stellar variability, remains a challenge. Depending on the noise characteristics, we show that the traditional technique that consists of detrending a light curve before searching for transits alters their signal-to-noise ratio, and hinders our

Michel Ades, David Guillemette, Serge B. Provost

In this article, we explore the notion of infinity by studying Cantor's contribution to this field. A brief history of set theory is given. As an example of infinity, we consider Hilbert's famous hotel. A graphical construction is used to demonstrate the countability of rationals. Cantor's diagonal procedure is explored, demonstrating that the infinity of re

Hossein Faridian

We prove that if $f:R \rightarrow S$ is a local homomorphism of noetherian local rings of finite flat dimension and $M$ is a non-zero finitely generated $S$-module whose Gorenstein flat dimension over $R$ is bounded by the difference of the embedding dimensions of $R$ and $S$, then $M$ is a totally reflexive $S$-module and $f$ is an exceptional complete inte

Gabriel Picioroaga, Olivia Roberts

We apply geometric group theory to study and interpret known concepts from Western music. We show that chords, the circle of fifths, scales and certain aspects of the first species of counterpoint are encoded in the Cayley graph of the group $\mathbb{Z}_{12}$, generated by $3$ and $4$. Using $\mathbb{Z}_{12}$ as a model, we extend the above music concepts to

Noah Lebowitz-Lockard, J. C. Saunders

In 2023, the first author and Vandehey proved that the largest $k$ for which the string of equalities $\lambda(n+1)=\lambda(n+2)=\cdots=\lambda(n+k)$ holds for some $n\leq x$, where $\lambda$ is the Carmichael $\lambda$ function, is bounded above by $O\left((\log x\log\log x)^2\right)$. Their method involved bounding the value of $\lambda(n + i)$ from below

Tom Cunningham, Sana Pandey, Leif Sigerson, Jonathan Stray

Many online platforms predominantly rank items by predicted user engagement. We believe that there is much unrealized potential in including non-engagement signals, which can improve outcomes both for platforms and for society as a whole. Based on a daylong workshop with experts from industry and academia, we formulate a series of propositions and document e

Takumi Omori, Takashi Iida, Azusa Gando, Keishi Hosokawa

Uncovering neutrinoless double beta decay (0$\nu$2$\beta$) is crucial for confirming neutrinos' Majorana characteristics. The decay rate of 0$\nu\beta\beta$ is theoretically uncertain, influenced by nuclear matrix elements that vary across nuclides. To reduce this uncertainty, precise measurement of the half-life of neutrino-emitting double beta decay (2$\nu

Robert A. Egelmeers, Lars A. L. Janssen, Rob H. B. Fey, Jasper Gerritsen

Many complex mechatronic systems consist of multiple interconnected dynamical subsystems, which are designed, developed, analyzed, and manufactured by multiple independent teams. To support such a design approach, a modular model framework is needed to reduce computational complexity and, at the same time, enable multiple teams to develop and analyze the sub

Kunlun Qi, Li Wang, Alexander B. Watson

We use the Wigner transformation and asymptotic analysis to systematically derive the semi-classical model for the Schr\"{o}dinger equation in arbitrary spatial dimensions, with any periodic structure. Our particular emphasis lies in addressing the \textit{diabatic} effect, i.e., the impact of Bloch band crossings. We consider both deterministic and random s

Enyi Jiang, Gagandeep Singh

Most existing works focus on improving robustness against adversarial attacks bounded by a single $l_p$ norm using adversarial training (AT). However, these AT models' multiple-norm robustness (union accuracy) is still low, which is crucial since in the real-world an adversary is not necessarily bounded by a single norm. The tradeoffs among robustness agains

Shihao Shen, Louis Kerofsky, Varun Ravi Kumar, Senthil Yogamani

Dense 3D reconstruction has many applications in automated driving including automated annotation validation, multimodal data augmentation, providing ground truth annotations for systems lacking LiDAR, as well as enhancing auto-labeling accuracy. LiDAR provides highly accurate but sparse depth, whereas camera images enable estimation of dense depth but noisy

I-Chen Sang, William R. Norris

Ensuring the robustness of lane detection systems is essential for the reliability of autonomous vehicles, particularly in the face of diverse weather conditions. While numerous algorithms have been proposed, addressing challenges posed by varying weather remains an ongoing issue. Geometric-based lane detection methods, rooted in the inherent properties of r

Johannes E. Fröch, Praneeth K. Chakravarthula, Jipeng Sun, Ethan Tseng

Flat optics have been proposed as an attractive approach for the implementation of new imaging and sensing modalities to replace and augment refractive optics. However, chromatic aberrations impose fundamental limitations on diffractive flat optics. As such, true broadband high-quality imaging has thus far been out of reach for low f-number, large aperture,

Amirsadegh Mirgalooyebayat, Farzad Didehvar

In this article, we try to find the best routes during the pandemic so that the probability of contracting the disease is the lowest. According to the results of this article, we can design software to find the best route.

Kristina Asimi, Libor Barto, Victor Dalmau

We introduce the framework of the left-hand side restricted promise constraint satisfaction problem, which includes problems like approximating clique number of a graph. We study the parameterized complexity of problems in this class and provide some initial results. The main technical contribution is a sufficient condition for W[1]-hardness which, in partic

Tiago Mendes-Neves, Luís Meireles, João Mendes-Moreira

This paper introduces an approach to predicting the next event in a soccer match, a challenge bearing remarkable similarities to the problem faced by Large Language Models (LLMs). Unlike other methods that severely limit event dynamics in soccer, often abstracting from many variables or relying on a mix of sequential models, our research proposes a novel tec

Simone Parisi, Montaser Mohammedalamen, Alireza Kazemipour, Matthew E. Taylor

In reinforcement learning (RL), an agent learns to perform a task by interacting with an environment and receiving feedback (a numerical reward) for its actions. However, the assumption that rewards are always observable is often not applicable in real-world problems. For example, the agent may need to ask a human to supervise its actions or activate a monit

João Mendes-Moreira, Tiago Mendes-Neves

Ensemble learning has been a focal point of machine learning research due to its potential to improve predictive performance. This study revisits the foundational work on ensemble error decomposition, historically confined to bias-variance-covariance analysis for regression problems since the 1990s. Recent advancements introduced a "unified theory of diversi

Riccardo Catena, Nicola Spaldin

We combine the non-relativistic effective theory of dark matter (DM) - electron interactions with linear response theory to obtain a formalism that fully accounts for screening and collective excitations in DM-induced electronic transition rate calculations for general DM-electron interactions. In the same way that the response of a dielectric material to an

A. Ayuela, E. Ogando, N. Zabala

Abnormally large stability of Pb nanostructures grown on metallic or semiconductor substrates has been observed even for heights of about 30 monolayers. Using both density-functional theory calculations and analytical models, we demonstrate that the stability at even higher coverages (N>30 ML) is supported by an extra second quantum beat pattern in the energ

Rick Battle, Teja Gollapudi

Large Language Models (LLMs) have demonstrated remarkable problem-solving and basic mathematics abilities. However, their efficacy is highly contingent on the formulation of the prompt. This study endeavors to quantify the influence of incorporating "positive thinking" into the system message of the prompt, then compare that to systematic prompt optimization

Tiago Mendes-Neves, Luís Meireles, João Mendes-Moreira

This paper introduces an innovative application of Large Event Models (LEMs), akin to Large Language Models, to the domain of soccer analytics. By learning the language of soccer - predicting variables for subsequent events rather than words - LEMs facilitate the simulation of matches and offer various applications, including player performance prediction ac

Hessam Mahdavifar

We introduce fair-density parity-check (FDPC) codes targeting high-rate applications. In particular, we start with a base parity-check matrix $H_b$ of dimension $2 \sqrt{n} \times n$, where $n$ is the code block length, and the number of ones in each row and column of $H_b$ is equal to $\sqrt{n}$ and $2$, respectively. We propose a deterministic combinatoria

Kenneth DeMason

Quantitative stability for crystalline anisotropic perimeters, with control on the oscillation of the boundary with respect to the corresponding Wulff shape, is proven for $n\geq 3$. This extends a result of [Neu16] in $n=2$.

Jiacheng Liu, Lisa Kirkland, Jaideep Srivastava

Unlike in a clinical trial, where researchers get to determine the least number of positive and negative samples required, or in a machine learning study where the size and the class distribution of the validation set is static and known, in a real-world scenario, there is little control over the size and distribution of incoming patients. As a result, when

Andrew Smart, Ding Wang, Ellis Monk, Mark Díaz

Data annotation remains the sine qua non of machine learning and AI. Recent empirical work on data annotation has begun to highlight the importance of rater diversity for fairness, model performance, and new lines of research have begun to examine the working conditions for data annotation workers, the impacts and role of annotator subjectivity on labels, an

Vignesh Gokul, Chris Francis, Shlomo Dubnov

Co-creativity in music refers to two or more musicians or musical agents interacting with one another by composing or improvising music. However, this is a very subjective process and each musician has their own preference as to which improvisation is better for some context. In this paper, we aim to create a measure based on total information flow to quanti

Sachin Chhabra, Hemanth Venkateswara, Baoxin Li

In the absence of labeled target data, unsupervised domain adaptation approaches seek to align the marginal distributions of the source and target domains in order to train a classifier for the target. Unsupervised domain alignment procedures are category-agnostic and end up misaligning the categories. We address this problem by deploying a pretrained networ

Jiacheng Liu, Jaideep Srivastava

Missingness and measurement frequency are two sides of the same coin. How frequent should we measure clinical variables and conduct laboratory tests? It depends on many factors such as the stability of patient conditions, diagnostic process, treatment plan and measurement costs. The utility of measurements varies disease by disease, patient by patient. In th

Thomas Borsoni, Bertrand Lods

We provide the first quantitative result of convergence to equilibrium in the context of the spatially homogeneous Boltzmann-Fermi-Dirac equation associated to hard potentials interactions under angular cut-off assumption, providing an explicit - algebraic - rate of convergence to Fermi-Dirac steady solutions. This result complements the quantitative converg

Yuchen Wang, Zhengyu Fang, Wei Du, Shuai Xu

The opioid epidemic, referring to the growing hospitalizations and deaths because of overdose of opioid usage and addiction, has become a severe health problem in the United States. Many strategies have been developed by the federal and local governments and health communities to combat this crisis. Among them, improving our understanding of the epidemic thr

Yuntao Du, Ninghui Li

Data synthesis has been advocated as an important approach for utilizing data while protecting data privacy. In recent years, a plethora of tabular data synthesis algorithms (i.e., synthesizers) have been proposed. Some synthesizers satisfy Differential Privacy, while others aim to provide privacy in a heuristic fashion. A comprehensive understanding of the

Darryl Hannan, Ragib Arnab, Gavin Parpart, Garrett T. Kenyon

Collecting overhead imagery using an event camera is desirable due to the energy efficiency of the image sensor compared to standard cameras. However, event cameras complicate downstream image processing, especially for complex tasks such as object detection. In this paper, we investigate the viability of event streams for overhead object detection. We demon

J. Nijaid Arredondo, Antoine Klein, Nicolás Yunes

Future gravitational-wave detectors, especially the Laser Interferometer Space Antenna (LISA), will be sensitive to black hole binaries formed in astrophysical environments that promote large eccentricities and spin-induced orbital precession. Approximate models of gravitational waves that include both effects have only recently begun to be developed. The Ef

Syed Mujtaba Hassan, Shahid Hussain

In this paper, we introduce a class of graphs which we call average hereditary graphs. Many graphs that occur in the usual graph theory applications belong to this class of graphs. Many popular types of graphs fall under this class, such as regular graphs, trees and other popular classes of graphs. The paper aims to explore some interesting properties regard

Lucas H. P. Cunha, Aldo Spatafora-Salazar, Dana M. Lobmeyer, Kedar Joshi

Superparamagnetic colloids present interesting assembly dynamics and propulsion in time-varying magnetic fields due to their magnetic relaxation. However, little is known about the mechanisms governing this magnetic relaxation, which is commonly attributed to the interactions and polydispersity of the ferromagnetic nanoparticles distributed within the colloi

Dorin Shapira, Matt Franchi, Wendy Ju

Scaffolds, also called sidewalk sheds, are intended to be temporary structures to protect pedestrians from construction and repair hazards. However, some sidewalk sheds are left up for years. Long-term scaffolding becomes eyesores, creates accessibility issues on sidewalks, and gives cover to illicit activity. Today, there are over 8,000 active permits for s

Eren Gultepe, Sen Wang, Byron Blomquist, Harindra J. S. Fernando

This study presents the application of generative deep learning techniques to evaluate marine fog visibility nowcasting using the FATIMA (Fog and turbulence interactions in the marine atmosphere) campaign observations collected during July 2022 in the North Atlantic in the Grand Banks area and vicinity of Sable Island (SI), northeast of Canada. The measureme

Therese A. Kucera, James A. Klimchuk, Manuel Luna

We present the results of models of impulsively heated coronal loops using the 1-D hydrodynamic Adaptively Refined Godunov Solver (ARGOS) code. The impulsive heating events (which we refer to as "nanoflares") are modeled by discrete pulses of energy along the loop. We explore the occurrence of cold condensations due to the effective equivalent of thermal non

Shiyu Jin, Jinxuan Xu, Yutian Lei, Liangjun Zhang

Despite significant progress in robotic systems for operation within human-centric environments, existing models still heavily rely on explicit human commands to identify and manipulate specific objects. This limits their effectiveness in environments where understanding and acting on implicit human intentions are crucial. In this study, we introduce a novel

Anna N. Morozovska, Eugene A. Eliseev, Olha A. Kovalenko, Dean R. Evans

Using Landau-Ginzburg-Devonshire (LGD) approach we proposed the analytical description of the chemical strains influence on the spontaneous polarization and electrocaloric response in ferroelectric core-shell nanorods. We postulate that the nanorod core presents a defect-free single-crystalline ferroelectric material, and the elastic defects are accumulated

V. Sazgari, Tianping Ying, J. N. Graham, C. Mielke

Vacancies play a crucial role in solid-state physics, but their impact on materials with strong electron-electron correlations has been underexplored. A recent study on the Ir-Sb binary system, Ir$_{16}$Sb$_{18}$ revealed a novel extended buckled-honeycomb vacancy (BHV) order. Superconductivity is induced by suppressing the BHV ordering through high-pressure

Arthur Ballato, John Ballato

The blackbody spectrum "half-power points" are used to assign effective Q "quality factor" values that are found to be less than unity whether frequency or wavelength scaling is used. A comparison with values for coherent oscillators is made. This exercise blends two of Kirchhoff's interests, and is instructive in its own right, as it bridges the often mutua

Hochul Hwang, Sunjae Kwon, Yekyung Kim, Donghyun Kim

Safely navigating street intersections is a complex challenge for blind and low-vision individuals, as it requires a nuanced understanding of the surrounding context - a task heavily reliant on visual cues. Traditional methods for assisting in this decision-making process often fall short, lacking the ability to provide a comprehensive scene analysis and saf

Alexey Fedyushkin

The paper is devoted to the study of natural convection and the formation of delamination in an incompressible liquid due to convective laminar flows in a closed region heated from the side. Weak, medium and intensive modes of stationary laminar thermal, concentration and hemoconcentration (thermohaline) convection are considered, in which nonlinear flow fea

Lin Zhang, Yi Wang, Shu-Yu Zheng, Li Lu

We conduct an experimental study of high-mobility two-dimensional electron gas (2DEG) in GaAs/AlGaAs quantum wells modulated by strong magnetism at an in-plane magnetic field ($B$). The modulated $B$-fields are performed via the single stripe and gratings which are made of the heavy rare earth metal Terbium (Tb) thin films on the sample surface. The robust f

Niel de Beaudrap, Christopher Ramsey

This paper studies the diameter of the numerical range of bounded operators on Hilbert space and the induced seminorm, called the numerical diameter, on bounded linear maps between operator systems which is sensible in the case of unital maps and their scalar multiples. It is shown that the completely bounded numerical diameter is a norm that is comparable b

Hochul Hwang, Hee-Tae Jung, Nicholas A Giudice, Joydeep Biswas

Dog guides are favored by blind and low-vision (BLV) individuals for their ability to enhance independence and confidence by reducing safety concerns and increasing navigation efficiency compared to traditional mobility aids. However, only a relatively small proportion of BLV individuals work with dog guides due to their limited availability and associated m

T. Macwan, K. Barada, J. F. Parisi, R. Groebner

Enhanced $D_{\alpha}$ H-mode (EDA H-mode), an ELM-free H-mode regime, is explored in neutral beam heated, lower single null plasmas with near zero torque injection. This regime exhibits a good energy confinement ($\mathrm{H}_{\mathrm{98y2}}$ $\sim 1$) with $\beta_N \sim 2$, high density, regime access at low input power, and no ELMs. This paper further prese

Sangyun Lee, Andrew J. Woods, Minseong Lee, Shengzhi Zhang

A quantum spin liquid (QSL) is a state of matter characterized by fractionalized quasiparticle excitations, quantum entanglement, and a lack of long-range magnetic order. However, QSLs have evaded definitive experimental observation. Several Yb$^{3+}$-based triangular lattice antiferromagnets with effective $S$ = $\frac{1}{2}$ have been suggested to stabiliz

Liangyu Zhao, Saeed Maleki, Yuanhong Wang, Zezhou Wang

As modern DNN models grow ever larger, collective communications between the accelerators (allreduce, etc.) emerge as a significant performance bottleneck. Designing efficient communication schedules is challenging, given today's heterogeneous and diverse network fabrics. We present ForestColl, a tool that generates throughput-optimal schedules for any netwo

Patrick Folge, Michael Stefszky, Benjamin Brecht, Christine Silberhorn

Linear optical quantum networks, consisting of a quantum input state and a multi-port interferometer, are an important building block for many quantum technological concepts, e.g., Gaussian boson sampling. Here, we propose the implementation of such networks based on frequency conversion by utilising a so called multi-output quantum pulse gate (mQPG). This a

Farhad Kamarei, Aditya Kumar, Oscar Lopez-Pamies

In a recent study, Kumar and Lopez-Pamies (J. Mech. Phys. Solids 150: 104359, 2021) have provided a complete quantitative explanation of the famed poker-chip experiments of Gent and Lindley (Proc. R. Soc. Lond. Ser. A 249: 195--205, 1959) on natural rubber. In a nutshell, making use of the fracture theory of Kumar, Francfort, and Lopez-Pamies (J. Mech. Phys.

Matteo Paiano, Stefano Martina, Carlotta Giannelli, Filippo Caruso

The availability of data is limited in some fields, especially for object detection tasks, where it is necessary to have correctly labeled bounding boxes around each object. A notable example of such data scarcity is found in the domain of marine biology, where it is useful to develop methods to automatically detect submarine species for environmental monito

Feiyang Wu, Xavier Nal, Jaehwi Jang, Wei Zhu

Humanoid robots promise transformative capabilities for industrial and service applications. While recent advances in Reinforcement Learning (RL) yield impressive results in locomotion, manipulation, and navigation, the proposed methods typically require enormous simulation samples to account for real-world variability. This work proposes a novel one-stage t

Akbir Khan, John Hughes, Dan Valentine, Laura Ruis

Common methods for aligning large language models (LLMs) with desired behaviour heavily rely on human-labelled data. However, as models grow increasingly sophisticated, they will surpass human expertise, and the role of human evaluation will evolve into non-experts overseeing experts. In anticipation of this, we ask: can weaker models assess the correctness

Jake Mac Uilliam, Sarp Akcay, Jonathan E. Thompson

Angular momentum and spin precession are expected to be generic features of a significant fraction of binary black hole systems. As such, it is essential to have waveform models that faithfully incorporate the effects of precession. Here, we assess how well the current state of the art models achieve this for waveform strains constructed only from the $\ell=

Omar Nemoul, Hichem Guergouri, Jamal Mimouni

This paper provides an analytical examination of non-radial geodesics within the context of the spatially flat Friedmann Lema\^itre Robertson Walker (FLRW) spacetime. Using the symmetry properties of the system, two constants of motion related to this dynamical system are derived. This treatment enables us to explicitly compute the radial and angular peculia

Jimmy Calvo-Monge, Jorge Arroyo-Esquivel, Alyssa Gehman, Fabio Sanchez

This study presents a comprehensive analysis of a two-patch, two-life stage SI model without recovery from infection, focusing on the dynamics of disease spread and host population viability in natural populations. The model, inspired by real-world ecological crises like the decline of amphibian populations due to chytridiomycosis and sea star populations du

Ola Shorinwa, Mac Schwager

We present a distributed quasi-Newton (DQN) method, which enables a group of agents to compute an optimal solution of a separable multi-agent optimization problem locally using an approximation of the curvature of the aggregate objective function. Each agent computes a descent direction from its local estimate of the aggregate Hessian, obtained from quasi-Ne