March 2024 arXiv papers — page 137

Andre Kornell

We prove that a unital completely positive map between finite-dimensional C*-algebras is a homomorphism if and only if it is completely entropy-nonincreasing, where the relevant notion of entropy is a variant of von Neumann entropy. This adjusted von Neumann entropy is the negative of the relative entropy with respect to the uniform state on the C*-algebra,

Aritra Kumar Lahiri, Emrul Hasan, Qinmin Vivian Hu, Cherie Ding

This paper describes Toronto Metropolitan University's participation in the TREC Clinical Trials Track for 2023. As part of the tasks, we utilize advanced natural language processing techniques and neural language models in our experiments to retrieve the most relevant clinical trials. We illustrate the overall methodology, experimental settings, and results

Jianxin Xie, Bing Yao, Zheyu Jiang

Soil moisture is a crucial hydrological state variable that has significant importance to the global environment and agriculture. Precise monitoring of soil moisture in crop fields is critical to reducing agricultural drought and improving crop yield. In-situ soil moisture sensors, which are buried at pre-determined depths and distributed across the field, a

Ziao Wang, Nadim Ghaddar, Banghua Zhu, Lele Wang

Let $\mathsf{TH}_k$ denote the $k$-out-of-$n$ threshold function: given $n$ input Boolean variables, the output is $1$ if and only if at least $k$ of the inputs are $1$. We consider the problem of computing the $\mathsf{TH}_k$ function using noisy readings of the Boolean variables, where each reading is incorrect with some fixed and known probability $p \in

Luigi Logrippo

Some theories on data flow security are based on order-theoretical concepts, most commonly on lattice concepts. This paper presents a correspondence between security concepts and partial order concepts, by which the former become an application of the latter. The formalization involves concepts of data flow, equivalence classes of entities that can access th

Weihan Wang, Chieh Chou, Ganesh Sevagamoorthy, Kevin Chen

We propose an accurate and robust initialization approach for stereo visual-inertial SLAM systems. Unlike the current state-of-the-art method, which heavily relies on the accuracy of a pure visual SLAM system to estimate inertial variables without updating camera poses, potentially compromising accuracy and robustness, our approach offers a different solutio

Fangyuan Yu, Dong Lai

In star clusters, close stellar encounters can strongly impact the architecture of a planetary system or even destroy it. We present a systematic study on the effects of stellar flybys on two-planet systems. When such a system experiences flybys, one or both planets can be ejected, forming free-floating planets (FFPs), captured planets (CPs) around the flyby

Qianqian Zou, Monika Sester

In this study, we address the challenge of constructing continuous three-dimensional (3D) models that accurately represent uncertain surfaces, derived from noisy and incomplete LiDAR scanning data. Building upon our prior work, which utilized the Gaussian Process (GP) and Gaussian Mixture Model (GMM) for structured building models, we introduce a more genera

Subhadeep Koley, Ayan Kumar Bhunia, Aneeshan Sain, Pinaki Nath Chowdhury

Two primary input modalities prevail in image retrieval: sketch and text. While text is widely used for inter-category retrieval tasks, sketches have been established as the sole preferred modality for fine-grained image retrieval due to their ability to capture intricate visual details. In this paper, we question the reliance on sketches alone for fine-grai

Chris Scott

We provide a first-principles approach to turbulence by employing the electrodynamics of continuous media at the viscous limit to recover the Navier-Stokes equations. We treat oscillators with two orthogonal angular momenta as a spin network with properties applicable to the Kolmogorov-Arnold-Moser (KAM) theorem. The microscopic viscous limit has an irreduci

Zhanpeng Zeng, Michael Davies, Pranav Pulijala, Karthikeyan Sankaralingam

While GPU clusters are the de facto choice for training large deep neural network (DNN) models today, several reasons including ease of workflow, security and cost have led to efforts investigating whether CPUs may be viable for inference in routine use in many sectors of the industry. But the imbalance between the compute capabilities of GPUs and CPUs is hu

Zhen Yang, Jianyong Zhang, Yanchuang Zhao

Remotely sensing the spatial distribution of exposed coal (EC) is significant for understanding the footprints of mining activities. However, widely applicable methods for the identification of EC surfaces remain inadequate because the choices of recent methods confront the diverse EC types and backgrounds. Therefore, this study proposed a new Automated Coal

Yike Zhang, Eduardo Davalos, Dingjie Su, Ange Lou

For those experiencing severe-to-profound sensorineural hearing loss, the cochlear implant (CI) is the preferred treatment. Augmented reality (AR) aided surgery can potentially improve CI procedures and hearing outcomes. Typically, AR solutions for image-guided surgery rely on optical tracking systems to register pre-operative planning information to the dis

Erik Buchholz, Alsharif Abuadbba, Shuo Wang, Surya Nepal

While location trajectories represent a valuable data source for analyses and location-based services, they can reveal sensitive information, such as political and religious preferences. Differentially private publication mechanisms have been proposed to allow for analyses under rigorous privacy guarantees. However, the traditional protection schemes suffer

Asma'a Almazaydeh, Mike Behrisch, Edith Vargas-García, Andreas Wachtel

We give a complete characterisation of the single and double arrow relations of the standard context $K(L_n)$ of the lattice $L_n$ of partitions of any positive integer $n$ under the dominance order, thereby addressing an open question of Ganter, 2022.

Mike Timmerman, Aryan Patel, Tim Reinhart

The paper presents a technique using reinforcement learning (RL) to adapt the control gains of a quadcopter controller. Specifically, we employed Proximal Policy Optimization (PPO) to train a policy which adapts the gains of a cascaded feedback controller in-flight. The primary goal of this controller is to minimize tracking error while following a specified

Sebastián Domínguez-Calderón, Harley D. Scammell

Superconducting transmon qubits with strong anharmonicity and insensitivity to offset charge are highly desirable for low-error implementation. In this work we propose a c-axis junction, comprising triplet superconductors, and set at a relative twist angle. Invoking spin-orbit coupling and spin polarization, which are known to occur in the material platform

Subhadeep Koley, Ayan Kumar Bhunia, Aneeshan Sain, Pinaki Nath Chowdhury

This paper, for the first time, explores text-to-image diffusion models for Zero-Shot Sketch-based Image Retrieval (ZS-SBIR). We highlight a pivotal discovery: the capacity of text-to-image diffusion models to seamlessly bridge the gap between sketches and photos. This proficiency is underpinned by their robust cross-modal capabilities and shape bias, findin

Sam G. Krupa

In this paper, we consider finite time blowup of the $BV$-norm for exact solutions to genuinely nonlinear hyperbolic systems in one space dimension, in particular the $p$-system. We consider solutions verifying shock admissibility criteria such as the Lax E-condition and the Liu E-condition. In particular, we present Riemann initial data which admits infinit

Valentin Allard, Nicolas Chamel

The interior of mature neutron stars is expected to contain superfluid neutrons and superconducting protons. The influence of temperature and currents on superfluid properties is studied within the self-consistent time-dependent nuclear energy-density functional theory. We find that this theory predicts the existence of a regime in which nucleons are superfl

Valentin Allard, Nicolas Chamel

The current interpretation of the observed late time cooling of transiently accreting neutron stars in low-mass X-ray binaries during quiescence requires the suppression of neutron superfluidity in their crust at variance with recent ab initio many-body calculations of dense matter. Focusing on the two emblematic sources KS~1731$-$260 and MXB~1659$-$29, we s

Margaret M. Bayer, Steffen Borgwardt, Teressa Chambers, Spencer Daugherty

For $\mathbf{b}=(b_1,\dots,b_n)\in \mathbb{Z}_{>0}^n$, a $\mathbf{b}$-parking function is defined to be a sequence $(β_1,\dots,β_n)$ of positive integers whose nondecreasing rearrangement $β'_1\leq β'_2\leq \cdots \leq β'_n$ satisfies $β'_i\leq b_1+\cdots + b_i$. The $\mathbf{b}$-parking-function polytope $\mathfrak{X}_n(\mathbf{b})$ is the c

John M. Campbell, M. Lawrence Glasser, Yajun Zhou

We introduce and prove evaluations for families of multiple elliptic integrals by solving special types of ordinary and partial differential equations. As an application, we obtain new expressions of Ramanujan-type series of level 4 and associated singular values for the complete elliptic integral $\mathbf K$ with integrals involving $\mathbf K$.

T. T. Hong, V. K. Le, L. T. T. Phuong, N . C. Hoi

Two decay channels $h\rightarrow γγ, Zγ$ of the Standard Model-like Higgs in a left-right symmetry model are investigated under recent experimental data. We will show there exist one-loop contributions that affect the $h\rightarrow Zγ$ amplitude, but not the $h\rightarrow γγ$ amplitude. From numerical investigations, we show that the signal strength $μ_{Z γ}

S. P. Hatkar, D. P. Tadas, S. D. Katore

We consider the Bianchi type-$VI_0$ space time with domain walls in the framework of the modified $f (R, T)$ theory of gravitation. To solve the field equations, we assume that the shear scalar $(σ)$ is proportional to the expansion scalar $(θ)$. We also consider the parametrization of the equation of the state parameter of barotropic fluid and discuss the e

Yu Xia, Fang Kong, Tong Yu, Liya Guo

Web-based applications such as chatbots, search engines and news recommendations continue to grow in scale and complexity with the recent surge in the adoption of LLMs. Online model selection has thus garnered increasing attention due to the need to choose the best model among a diverse set while balancing task reward and exploration cost. Organizations face

William M Feldman, Norbert Pozar

We give a new proof of a convex comparison principle for exterior Bernoulli free boundary problems with discontinuous anisotropy.

Thialita M. Nascimento

In this paper, we examine regularity estimates for solutions to fully nonlinear, degenerated elliptic equations, at interior vanishing source points. At these points, we obtain Schauder-type regularity estimates, which depend on the H\"older-like source-ellipticity vanishing rate.

Samantha Aziz, Dillon J Lohr, Lee Friedman, Oleg Komogortsev

We present an extensive, in-depth analysis of the eye tracking capabilities of the Meta Quest Pro virtual reality headset using a dataset of eye movement recordings collected from 78 participants. In addition to presenting classical signal quality metrics--spatial accuracy, spatial precision and linearity--in ideal settings, we also study the impact of backg

Lampros Gavalakis, Ioannis Kontoyiannis, Mokshay Madiman

Entropy comparison inequalities are obtained for the differential entropy $h(X+Y)$ of the sum of two independent random vectors $X,Y$, when one is replaced by a Gaussian. For identically distributed random vectors $X,Y$, these are closely related to bounds on the entropic doubling constant, which quantifies the entropy increase when adding an independent cop

Sandra Zarychta, Marek Balcerzak, Jerzy Wojewoda

The paper explains iterative and non-iterative approaches to control optimization with use of the Fourier series-based method. Both variants of the presented algorithm are used to numerically approximate optimal control of a discontinuous pendulum capsule drive. Firstly, the general algorithm and its two realizations (iterative and non-iterative) are present

Yinsong Wang, Yu Ding, Shahin Shahrampour

Dynamic density estimation is ubiquitous in many applications, including computer vision and signal processing. One popular method to tackle this problem is the "sliding window" kernel density estimator. There exist various implementations of this method that use heuristically defined weight sequences for the observed data. The weight sequence, however, is a

Todor D. Todorov

We consider a non-standard version of Egorov's algebra of generalized functions, with improved properties of the generalized scalars and embedding of the Schwartz distributions compared with the original standard Egorov's version. The embedding of distributions is similar to, but different from author's works in the past and independently done by Hans Vernae

Tongkeun Chang, Bum Ja Jin

In this paper, we study the decay rate of the Stokes flow in an exterior domain with a slowly decaying initial data ${\bf u}_0(x)=O(|x|^{-\al}), 0<\al\leq n$. %which is not $L^1$ integrable. As an application we find the unique strong solution of the Navier-Stokes equations corresponding to a slowly decaying initial data. We also derive the pointwise decay e

Sarah Gold, Elizabeth Milićević, Yuxuan Sun

Schubert polynomials represent a basis for the cohomology of the complete flag variety and thus play a central role in geometry and combinatorics. In this context, Schubert polynomials are generating functions over various combinatorial objects, such as rc-graphs or reduced pipe dreams. By restricting Bergeron and Billey's chute moves on rc-graphs, we define

Subhadeep Koley, Ayan Kumar Bhunia, Aneeshan Sain, Pinaki Nath Chowdhury

In this paper, we propose a novel abstraction-aware sketch-based image retrieval framework capable of handling sketch abstraction at varied levels. Prior works had mainly focused on tackling sub-factors such as drawing style and order, we instead attempt to model abstraction as a whole, and propose feature-level and retrieval granularity-level designs so tha

Eric Neyman

One aspect of the algorithmic lens in theoretical computer science is a view on other scientific disciplines that focuses on satisfactory solutions that adhere to real-world constraints, as opposed to solutions that would be optimal ignoring such constraints. The algorithmic lens has provided a unique and important perspective on many academic fields, includ

Grusha Prasad, Tal Linzen

Structural priming is a widely used psycholinguistic paradigm to study human sentence representations. In this work we introduce SPAWN, a cognitively motivated parser that can generate quantitative priming predictions from contemporary theories in syntax which assume a lexicalized grammar. By generating and testing priming predictions from competing theoreti

Brandon Silva, Miguel Contreras, Sabyasachi Bandyopadhyay, Yuanfang Ren

Assessing acute brain dysfunction (ABD), including delirium and coma in the intensive care unit (ICU), is a critical challenge due to its prevalence and severe implications for patient outcomes. Current diagnostic methods rely on infrequent clinical observations, which can only determine a patient's ABD status after onset. Our research attempts to solve thes

Håvard Bakke Bjerkevik, Magnus Bakke Botnan

Recently, $p$-presentation distances for $p\in [1,\infty]$ were introduced for merge trees and multiparameter persistence modules as more sensitive variations of the respective interleaving distances ($p=\infty)$. It is well-known that computing the interleaving distance is NP-hard in both cases. We extend this result by showing that computing the $p$-presen

Fabian C Weigend, Xiao Liu, Shubham Sonawani, Neelesh Kumar

This paper introduces iRoCo (intuitive Robot Control) - a framework for ubiquitous human-robot collaboration using a single smartwatch and smartphone. By integrating probabilistic differentiable filters, iRoCo optimizes a combination of precise robot control and unrestricted user movement from ubiquitous devices. We demonstrate and evaluate the effectiveness

Lan Wang, Vishnu Boddeti, Sernam Lim

We introduce a novel text-to-pose video editing method, ReimaginedAct. While existing video editing tasks are limited to changes in attributes, backgrounds, and styles, our method aims to predict open-ended human action changes in video. Moreover, our method can accept not only direct instructional text prompts but also `what if' questions to predict possibl

Jingyi Mei, Marcello Bonsangue, Alfons Laarman

Quantum circuit compilation comprises many computationally hard reasoning tasks that nonetheless lie inside #$\mathbf{P}$ and its decision counterpart in $\mathbf{PP}$. The classical simulation of general quantum circuits is a core example. We show for the first time that a strong simulation of universal quantum circuits can be efficiently tackled through we

Sasha Mintz, Brandon Coleman, Allison Kirkpatrick

Cold quasars are a rare population of luminous, unobscured quasars associated with host galaxies that have a high star formation rate. We aimed to study the host galaxies of sixty four of these cold quasars in order to probe how the supermassive black holes and host galaxies were coevolving. We compiled data from the XXL survey and crossmatched with the VHS,

Egor Shelukhin

We prove new cases of the Hilbert-Smith conjecture for actions by natural homeomorphisms in symplectic topology. Specifically, we prove that the group of $p$-adic integers $\mathbb Z_p$ does not admit non-trivial continuous actions by Hamiltonian homeomorphisms, the $C^0$ limits of Hamiltonian diffeomorphisms, on symplectically aspherical symplectic manifold

Antonio Ferrández, Rocío Lavigne-Cerván, Jesús Peral, Ignasi Navarro-Soria

In this article, we present CuentosIE (TalesEI: chatbot of tales with a message to develop Emotional Intelligence), an educational chatbot on emotions that also provides teachers and psychologists with a tool to monitor their students/patients through indicators and data compiled by CuentosIE. The use of "tales with a message" is justified by their simplicit

Benjamin A. Christie, Heramb Nemlekar, Dylan P. Losey

Robots often need to convey information to human users. For example, robots can leverage visual, auditory, and haptic interfaces to display their intent or express their internal state. In some scenarios there are socially agreed upon conventions for what these signals mean: e.g., a red light indicates an autonomous car is slowing down. But as robots develop

Yufeng Zhang, Liyu Chen, Boyi Liu, Yingxiang Yang

Recent advances in reinforcement learning (RL) algorithms aim to enhance the performance of language models at scale. Yet, there is a noticeable absence of a cost-effective and standardized testbed tailored to evaluating and comparing these algorithms. To bridge this gap, we present a generalized version of the 24-Puzzle: the $(N,K)$-Puzzle, which challenges

Purwoko Haryadi Santoso, Bayu Setiaji, Wahyudi, Johan Syahbrudin

The force concept inventory (FCI) is one of the research-based assessments (RBAs) established by the physics education research (PER) community to measure students' understanding of Newtonian mechanics. Former works have often recorded the notion of gendered mean FCI scores favoring male students notably in the North America (NA) based studies. Nevertheless,

Jean Barbier, Justin Ko, Anas A. Rahman

We consider a statistical model for symmetric matrix factorization with additive Gaussian noise in the high-dimensional regime, where the rank of the signal matrix to infer $M$ scales with its size $N$ as $M=\mathrm{o}(\sqrt{\ln N})$. Allowing for an $N$-dependent rank offers new challenges and requires new methods. Working in the Bayes-optimal setting, we s

Ayaka Usui, Abel Rojo-Francàs, James Schloss, Bruno Juliá-Díaz

Synthetic spin-orbit coupling in cold atoms couples the pseudo-spin and spatial degrees of freedom, and therefore the inherent spin symmetry of the system plays an important role. In systems of two pseudo-spin degrees, two particles contain symmetric states and anti-symmetric states, but the spin symmetry can be mixed for more particles. This mixed spin symm

Junhong Shen, Tanya Marwah, Ameet Talwalkar

We present Unified PDE Solvers (UPS), a data- and compute-efficient approach to developing unified neural operators for diverse families of spatiotemporal PDEs from various domains, dimensions, and resolutions. UPS embeds different PDEs into a shared representation space and processes them using a FNO-transformer architecture. Rather than training the networ

June-Young Kim, Ho-Yeon Won, Hyun-Chul Kim, Christian Weiss

We study the twist-3 spin-orbit correlations of quarks described by the nucleon matrix elements of the parity-odd rank-2 tensor QCD operator (the parity-odd partner of the QCD energy-momentum tensor). Our treatment is based on the effective dynamics emerging from the spontaneous breaking of chiral symmetry and the mean-field picture of the nucleon in the lar

Fangxin Wang, Yuqing Liu, Kay Liu, Yibo Wang

Graph Neural Networks (GNNs) have been extensively used in various real-world applications. However, the predictive uncertainty of GNNs stemming from diverse sources such as inherent randomness in data and model training errors can lead to unstable and erroneous predictions. Therefore, identifying, quantifying, and utilizing uncertainty are essential to enha

Hubertus Bromberger, David Pennicard, Rafael Ballabriga, Sebastian Trippel

The event-driven hybrid-pixel detector readout chip, Timepix3, has the ability to simultaneously measure the time of an event on the nanosecond timescale and the energy deposited in the sensor. However, the behaviour of the system when two events are recorded in quick succession of each other on the same pixel was not studied in detail previously. We present

Marvin Zammit, Antonios Liapis, Georgios N. Yannakakis

The recent advances in language-based generative models have paved the way for the orchestration of multiple generators of different artefact types (text, image, audio, etc.) into one system. Presently, many open-source pre-trained models combine text with other modalities, thus enabling shared vector embeddings to be compared across different generators. Wi

T. Kyle Petersen, Yan Zhuang

For any finite partially ordered set $P$, the $P$-Eulerian polynomial is the generating function for the descent number over the set of linear extensions of $P$, and is closely related to the order polynomial of $P$ arising in the theory of $P$-partitions. Here we study the $P$-Eulerian polynomial where $P$ is a naturally labeled zig-zag poset; we call these

Yuxiang Sun, Jingyi Li, Mengdie Lu, Zongying Guo

Big data revolutionizes accounting and auditing, offering deep insights but also introducing challenges like data privacy and security. With data from IoT, social media, and transactions, traditional practices are evolving. Professionals must adapt to these changes, utilizing AI and machine learning for efficient data analysis and anomaly detection. Key to o

Huaisheng Zhu, Teng Xiao, Vasant G Honavar

Generating molecular structures with desired properties is a critical task with broad applications in drug discovery and materials design. We propose 3M-Diffusion, a novel multi-modal molecular graph generation method, to generate diverse, ideally novel molecular structures with desired properties. 3M-Diffusion encodes molecular graphs into a graph latent sp

Daniel Grieser, Sina Held, Hannes Uecker, Boris Vertman

Using $\Gamma$-convergence, we study the Cahn-Hilliard problem with interface width parameter $\varepsilon > 0$ for phase transitions on manifolds with conical singularities. We prove that minimizers of the corresponding energy functional exist and converge, as $\varepsilon \to 0$, to a function that takes only two values with an interface along a hypersurfa

Inkoo Cho, Noah Williams

We develop a model of algorithmic pricing that shuts down every channel for explicit or implicit collusion while still generating collusive outcomes. We analyze the dynamics of a duopoly market where both firms use pricing algorithms consisting of a parameterized family of model specifications. The firms update both the parameters and the weights on models t

Shekhar Sharma, Myung-Chul Jung, Harrison LaBollita, Antia S. Botana

Motivated by the discovery of superconductivity in infinite-layer nickelates RNiO$_2$ (R= rare-earth), and the subsequent enhancement of their T$_c$ with pressure, we investigate the evolution of the electronic structure and magnetic properties of this family of materials via first-principles calculations employing hydrostatic and chemical pressure as tuning

Akshat Gupta, Sidharth Baskaran, Gopala Anumanchipalli

Recent work using Rank-One Model Editing (ROME), a popular model editing method, has shown that there are certain facts that the algorithm is unable to edit without breaking the model. Such edits have previously been called disabling edits. These disabling edits cause immediate model collapse and limits the use of ROME for sequential editing. In this paper,

Debabrata Deb, Manjari Bagchi, Sarmistha Banik

In this work, we explore the impact of higher dimensional spacetime on the stellar structure and thermodynamic properties of neutron stars. Utilizing the density-dependent relativistic hadron field theory, we introduce modifications to incorporate the influence of higher dimensionality, a novel approach not explored in existing literature to our best knowled

Zeinab Gharibi

In this work, we develop recent research on the fully mixed virtual element method (mixed-VEM) based on the Banach space for the stationary Boussinesq equation to suggest and analyze a new mixed-VEM for the stationary two-dimensional Boussinesq equation with temperature-dependent parameters in terms of the pseudostress, vorticity, velocity, pseudoheat vector

Kyle Akira Rocha, Vicky Kalogera, Zoheyr Doctor, Jeff J. Andrews

Be X-ray binaries (Be-XRBs) are one of the largest subclasses of high-mass X-ray binaries, comprised of a rapidly rotating Be star and neutron star companion in an eccentric orbit, intermittently accreting material from a decretion disk around the donor. Originating from binary stellar evolution, Be-XRBs are of significant interest to binary population synth

Ondřej Chwiedziuk, Matěj Doležálek, Emma Pěchoučková, Zdeněk Pezlar

We investigate generalized quadratic forms with values in the set of rational integers over quadratic fields. We characterize the real quadratic fields which admit a positive definite binary generalized form of this type representing every positive integer. We also show that there are only finitely many such fields where a ternary generalized form with these

Stefanos Kechagias, Vladas Pipiras, Pavlos Zoubouloglou

A new model for general cyclical long memory is introduced, by means of random modulation of certain bivariate long memory time series. This construction essentially decouples the two key features of cyclical long memory: quasi-periodicity and long-term persistence. It further allows for a general cyclical phase in cyclical long memory time series. Several c

P. G. de Oliveira, A. S. T. Pires

The copper fluoride $Cu_2F_5$ is a proposed stable compound that can be seen as a layered lattice of $S=1$ and $S=1/2$ sites, corresponding to copper ions. Intending to cast light on the transport properties of ferrimagnetic magnons, we use the linear spin wave approach to study the magnon band structure of the 2D lattice in a ferrimagnetic off-plane order,

Andrey Grekov, Nikita Nekrasov

We review the limit shape problem for the Plancherel measure and its generalizations found in supersymmetric gauge theory instanton count. We focus on the measure, interpolating between the Plancherel measure and uniform measure, a U(1) case of N=2* gauge theory. We give the formula for its limit shape in terms of elliptic functions, generalizing the trigono

Yunyue Elita Li, Feng Zhu, Jizhong Yang

Stacked cross-correlation functions have become ubiquitous in the ambient seismic imaging and monitoring community as approximations to the Green's function between two receivers. While theoretical understanding of this approximation to the ballistic arrivals is well established, the equivalent analysis for the non-ballistic arrivals is alarmingly inadequate

Doron Sayag, Avichai Snir, Daniel Levy

The finding of small price changes in many retail price datasets is often viewed as a puzzle. We show that a possible explanation for the presence of small price changes is related to sales volume, an observation that has been overlooked in the existing literature. Analyzing a large retail scanner price dataset that contains information on both prices and sa

Abhinava Chatterjee, Mourad Oudich, Yun Jing, Chao-Xing Liu

The most salient feature of electronic topological states of matter is the existence of exotic electronic modes localized at the surface or interface of a sample. In this work, in an electronic topological system, we demonstrate the existence of localized phonon modes at the domain wall between topologically trivial and non-trivial regions, in addition to th

P. Garbaczewski, M. Zaba

We analyze the relaxation dynamics of Feynman-Kac path integral kernel functions in terms of branching diffusion processes with killing. This sheds new light on the admissible path-wise description of the relaxation to equilibrium for conditioned Brownian motions, and diffusion processes with absorbing boundaries, where Feynman-Kac kernels appear as the buil

Jinu Jeong, Chenxing Liang, Narayana Aluru

Water isotope separation, specifically separating heavy from light water, is a socially significant issue due to the usage of heavy water in applications such as nuclear magnetic resonance, nuclear power, and spectroscopy. Separation of heavy water from light water is difficult due to very similar physical and chemical properties between the isotopes. We sho

Judith Michael, Istvan David, Dominik Bork

Smart ecosystems are the drivers of modern society. They control infrastructures of socio-techno-economic importance, ensuring their stable and sustainable operation. Smart ecosystems are governed by digital twins -- real-time virtual representations of physical infrastructure. To support the open-ended and reactive traits of smart ecosystems, digital twins

Sean Gryb, David Sloan

Classical cosmology exhibits a particular kind of scaling symmetry. The dynamics of the invariants of this symmetry forms a system that exhibits many of the features of open systems such as the non-conservation of mechanical energy and the focusing of measures along the dynamical flow. From these properties, we show that important dynamical features emerge t

Fritz Gesztesy, Markus Hunziker

We consider essential self-adjointness of strongly singular, homogeneous, polyharmonic operators of the form \[ T_m = \left((-\Delta)^m + c|x|^{-2m}\right)\big|_{C_0^{\infty}(\mathbb{R}^n \setminus \{0\})}, \quad m,n\in\mathbb{N},\ n\ge 2,\ c\in\mathbb{R}, \] in $L^2(\mathbb{R}^n; d^n x)$, with special emphasis on the biharmonic case $m=2$ and the case $m=3$

Elaine Cozzi, Zachary Radke

We consider the question of global existence of smooth solutions to a multi-species aggregation-diffusion equation for a class of singular interaction kernels. We establish a smallness condition on the initial data which yields global existence of smooth solutions. We also give conditions on the species interaction which ensure that pointwise inequalities co

Richard A. Davis, Leon Fernandes

A fundamental and often final step in time series modeling is to assess the quality of fit of a proposed model to the data. Since the underlying distribution of the innovations that generate a model is often not prescribed, goodness-of-fit tests typically take the form of testing the fitted residuals for serial independence. However, these fitted residuals a

Keegan Boyle, Nicholas Rouse

We prove that the SL(2, C) character variety of a hyperbolic, freely 2-periodic knot has two canonical components. We also prove that the hyperbolic torsion polynomial of such a knot satisfies a factorization condition which seems to be particularly effective at identifying freely 2-periodic knots.

Tianwei Xia, Kai Sun

In the modal analysis and control of nonlinear dynamical systems, the participation factors of state variables with respect to a critical or selected mode serve as a pivotal tool for simplifying stability studies by focusing on a subset of highly influential state variables. For linear systems, the participation factors of state variables regarding a mode ar

Cian Reeves, Vojtech Vlcek

Time-resolved photoemission spectroscopy is the key technique to probe the real-time non-equilibrium dynamics of electronic states. Theoretical predictions of the time dependent spectral function for realistic systems is however, a challenge. Employing the Kadanoff-Baym equations to find this quantity results in a cubic scaling in the total number of time st

Harry Parke, Robin Thomm, Alan C. Santos, André Cidrim

Interference underpins some of the most practical and impactful properties of both the classical and quantum worlds. In this work we experimentally investigate a new formalism to describe interference effects, based on collective states which have enhanced or suppressed coupling to a two-level system. We employ a single trapped ion, whose electronic state is

Leo Chen, Benjamin Boardley, Ping Hu, Yiru Wang

This article describes the 2023 IEEE Low-Power Computer Vision Challenge (LPCVC). Since 2015, LPCVC has been an international competition devoted to tackling the challenge of computer vision (CV) on edge devices. Most CV researchers focus on improving accuracy, at the expense of ever-growing sizes of machine models. LPCVC balances accuracy with resource requ

Yaron Azrieli, Christopher P. Chambers

We consider contests with a large set (continuum) of participants and axiomatize contest success functions that arise when performance is composed of both effort and a random element, and when winners are those whose performance exceeds a cutoff determined by a market clearing condition. A co-monotonicity property is essentially all that is needed for a repr

Behraj Khan, Tahir Syed, Zeshan Khan, Muhammad Rafi

New software and updates are downloaded by end users every day. Each dowloaded software has associated with it an End Users License Agreements (EULA), but this is rarely read. An EULA includes information to avoid legal repercussions. However,this proposes a host of potential problems such as spyware or producing an unwanted affect in the target system. End

Bishwamittra Ghosh, Debabrota Basu, Fu Huazhu, Wang Yuan

Federated Learning (FL) is a collaborative machine learning (ML) approach, where multiple clients participate in training an ML model without exposing their private data. Fair and accurate assessment of client contributions facilitates incentive allocation in FL and encourages diverse clients to participate in a unified model training. Existing methods for c

Nouran Soliman, Motahhare Eslami, Karrie Karahalios

Online social platforms allow users to filter out content they do not like. According to selective exposure theory, people tend to view content they agree with more to get more self-assurance. This causes people to live in ideological filter bubbles. We report on a user study that encourages users to break the political filter bubble of their Twitter feed by

Jim Zhao, Greg Leadman

Targeted Alpha Therapy (TAT) has emerged as a promising modality for the treatment of various malignancies, leveraging the high linear energy transfer (LET) and short range of alpha particles to selectively irradiate cancer cells while sparing healthy tissue. Monitoring and optimizing TAT delivery is crucial for its clinical success. Hyper-spectral Single Ph

Konstantinos Emmanouilidis, René Vidal, Nicolas Loizou

The Stochastic Extragradient (SEG) method is one of the most popular algorithms for solving finite-sum min-max optimization and variational inequality problems (VIPs) appearing in various machine learning tasks. However, existing convergence analyses of SEG focus on its with-replacement variants, while practical implementations of the method randomly reshuff

Akram Yazdani, Maureen Samms-Vaughan, Sepideh Saroukhani, Jan Bressler

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition with a wide range of behavioral and cognitive impairments. While genetic and environmental factors are known to contribute to its etiology, the underlying metabolic perturbations associated with ASD which can potentially connect genetic and environmental factors, remain poorly understoo

Manis Hazra, Debabrata Goswami

In the resource theory of coherence, the quantification of quantum-state coherence is an important task. In this regard, the key ingredients are the various coherence monotones (or measures). There are few coherence-monotone classes that solely depend on other coherence measures defined for all the pure states; in other words, they rely on the pure state coh

Xiu Liu, Yibai Zhong, Zexiao Wang, Tianyi Huang

Active metasurfaces have recently emerged as compact, lightweight, and efficient platforms for dynamic control of electromagnetic fields and optical responses. However, the complexities associated with their post-fabrication tunability significantly hinder their widespread applications, especially for the mid-infrared range due to material scarcity and desig

Chi-Yang Hsu, Kyle Cox, Jiawei Xu, Zhen Tan

We present the Thought Graph as a novel framework to support complex reasoning and use gene set analysis as an example to uncover semantic relationships between biological processes. Our framework stands out for its ability to provide a deeper understanding of gene sets, significantly surpassing GSEA by 40.28% and LLM baselines by 5.38% based on cosine simil

Shiliang Zuo

This work studies the online contract design problem. The principal's goal is to learn the optimal contract that maximizes her utility through repeated interactions, without prior knowledge of the agent's type (i.e., the agent's cost and production functions). We leverage the structure provided by continuous action spaces, which allows the application of fir

Ali Abbasi, Ashkan Shahbazi, Hamed Pirsiavash, Soheil Kolouri

The extensive amounts of data required for training deep neural networks pose significant challenges on storage and transmission fronts. Dataset distillation has emerged as a promising technique to condense the information of massive datasets into a much smaller yet representative set of synthetic samples. However, traditional dataset distillation approaches

P. Domenichini, J. Brock, J. Curiale, A. B. Kolton

The dynamical response of magnetic domain walls to external magnetic fields in ultra-thin multilayer magnetic films is determined not only by the composition and thickness of the layers but also by the growth conditions. Growth conditions can induce significant structural changes inside the layers and at the interfaces between them, affecting in particular t

Manus R. Visser, Zihan Yan

We study the first law for non-stationary perturbations of a stationary black hole whose event horizon is a Killing horizon, that relates the first-order change in the mass and angular momentum to the change in the entropy of an arbitrary horizon cross-section. Recently, Hollands, Wald and Zhang [1] have shown that the dynamical black hole entropy that satis

Aqsa Bashir, Wolfgang A. Schmid

Let $G$ be a finite abelian group with $\exp(G)$ the exponent of $G$. Then $\mathsf W(G)$ denotes the set of cross numbers of minimal zero-sum sequences over $G$ and $\mathsf w(G)$ denotes the set of all cross numbers of non-trivial zero-sum free sequences over $G$. It is clear that $\mathsf W(G)$ and $\mathsf w(G)$ are bounded subsets of $\frac{1}{\exp(G)}\