October 2023 arXiv papers — page 86

Jing Jia, Kenta Saito, Hiroaki Nishi

Smart cities, which can monitor the real world and provide smart services in a variety of fields, have improved people's living standards as urbanization has accelerated. However, there are security and privacy concerns because smart city applications collect large amounts of privacy-sensitive information from people and their social circles. Anonymization,

Genglong Lin

Let $(X,\omega)$ be a compact K\"ahler manifold of dimension $n$ and fix an integer $m$ such that $1\leq m\leq n$. We reformulate most relative pluripotential results of Darvas-DiNezza-Lu's survey \cite{DNL23} to the Hessian setting. As an application, we use a slightly different method and give an characterization of finite energy range of the Hessian opera

Rui Yuan, Hossein Ranjbar, S. Ali Pourmousavi, Wen L. Soong

Many smart grid applications involve data mining, clustering, classification, identification, and anomaly detection, among others. These applications primarily depend on the measurement of similarity, which is the distance between different time series or subsequences of a time series. The commonly used time series distance measures, namely Euclidean Distanc

Zhuo Yu, Qi Wu, Dian-Yong Chen

In the present work, we investigate $X_0(2900)$ and its spin partners productions in the $B^+$ decay processes, where $X_0(2900)$ is regarded as a $\bar{D}^\ast K^\ast$ molecular state. We infer that the initial $B^+$ meson and the final $D^+ X_0(2900)$ are connected through $D_{s1}^+(2460) \bar{D}^{\ast 0} $ mesons by exchanging a $K^{\ast 0}$ meson. The co

Kaya Stechly, Matthew Marquez, Subbarao Kambhampati

There has been considerable divergence of opinion on the reasoning abilities of Large Language Models (LLMs). While the initial optimism that reasoning might emerge automatically with scale has been tempered thanks to a slew of counterexamples, a wide spread belief in their iterative self-critique capabilities persists. In this paper, we set out to systemati

Yota Maeda, Hideaki Kawaguchi, Hiroyuki Tezuka

Recently, the importance of analysing data and collecting valuable insight efficiently has been increasing in various fields. Estimating mutual information (MI) plays a critical role to investigate the relationship among multiple random variables with a nonlinear correlation. Particularly, the task to determine whether they are independent or not is called t

Christopher Scarvelis, Haitz Sáez de Ocáriz Borde, Justin Solomon

Score-based generative models (SGMs) sample from a target distribution by iteratively transforming noise using the score function of the perturbed target. For any finite training set, this score function can be evaluated in closed form, but the resulting SGM memorizes its training data and does not generate novel samples. In practice, one approximates the sc

Stephen Arndt, Josh Ascher, Kirk Pruhs

Motivated by demand-responsive parking pricing systems, we consider posted-price algorithms for the online metric matching problem. We give an $O(\log n)$-competitive posted-price randomized algorithm in the case that the metric space is a line. In particular, in this setting we show how to implement the ubiquitous guess-and-double technique using prices.

Chenhao Xu, Chang-Tsun Li, Yongjian Hu, Chee Peng Lim

Video instance segmentation, also known as multi-object tracking and segmentation, is an emerging computer vision research area introduced in 2019, aiming at detecting, segmenting, and tracking instances in videos simultaneously. By tackling the video instance segmentation tasks through effective analysis and utilization of visual information in videos, a ra

Julian Y. Günther, Jordy de Vries, Herbi K. Dreiner, Zeren Simon Wang

At the Deep Underground Neutrino Experiment (DUNE), a proton beam hits a fixed target leading to large production rates of mesons. These mesons can decay and potentially provide a source of long-lived neutral fermions. Examples of such long-lived fermions are heavy neutral leptons which can mix with the standard-model active neutrinos, and the bino-like ligh

Marianne Menictas, Chris J. Oates, Matt P. Wand

We develop and describe online algorithms for performing online semiparametric regression analyses. Earlier work on this topic is in Luts, Broderick & Wand (J. Comput. Graph. Statist., 2014) where online mean field variational Bayes was employed. In this article we instead develop sequential Monte Carlo approaches to circumvent well-known inaccuracies inhere

Xingchu Zhang, Weilong She

It is well known that, for an incident light of not so high intensity and in a certain range of frequency, the stopping voltage of photoelectric effect is independent of the intensity but dependent on the frequency of the light, which is described by the equation $V = h\nu /e - {W_0}/e$, where $V$ is the stopping voltage, $h$ is the Planck constant, $\nu$ is

Yuhong Huang, Wenxin Li, Chengkang Pan, Shuai Hou

Massive multiple-input multiple-output (MIMO) has gained widespread popularity in recent years due to its ability to increase data rates, improve signal quality, and provide better coverage in challenging environments. In this paper, we investigate the MIMO beam selection (MBS) problem, which is proven to be NP-hard and computationally intractable. To deal w

Rogelio Niño Hernández

We prove that every orientable infinite type surface without boundary and finite genus has a Riemann surface structure such that its modular group of quasiconformal homeomorphisms is countable.

Roberto Tellez-Dominguez

The classical Chern correspondence states that a choice of Hermitian metric on a holomorphic vector bundle determines uniquely a unitary 'Chern connection'. This basic principle in Hermitian geometry, later generalized to the theory of holomorphic principal bundles, provides one of the most fundamental ingredients in modern gauge theory, via its appl

Chen Wang, Victoria Huang, Gang Chen, Hui Ma

The optimal placement of sensors for environmental monitoring and disaster management is a challenging problem due to its NP-hard nature. Traditional methods for sensor placement involve exact, approximation, or heuristic approaches, with the latter being the most widely used. However, heuristic methods are limited by expert intuition and experience. Deep le

Bernhard Hengst, Maurice Pagnucco, David Rajaratnam, Claude Sammut

Complex robot behaviour typically requires the integration of multiple robotic and Artificial Intelligence (AI) techniques and components. Integrating such disparate components into a coherent system, while also ensuring global properties and behaviours, is a significant challenge for cognitive robotics. Using a formal framework to model the interactions bet

Eduardo Fernández, Hyunki Min

We determine the homotopy type of the spaces of several Legendrian knots and links with the maximal Thurston--Bennequin invariant. In particular, we give a recursive formula of the homotopy type of the space of Legendrian embeddings of sufficiently positive cables, and determine the homotopy type of the space of Legendrian embeddings of Seifert fibered links

Sophie Crisp, Alexander Ody, Joel England, Pietro Musumeci

The development of long, tunable structures is critical to increasing energy gain in laser-driven dielectric accelerators (DLAs). Here we combine pulse-front-tilt illumination with slab-geometry structures assembled by precisely aligning off-the-shelf 4~mm long transmission gratings to achieve up to 200 keV energy modulation for 6 MeV injected electrons. The

Sihan Chen, Tomer Markovich, Fred C. MacKintosh

Strain-controlled criticality governs the elasticity of jamming and fiber networks. While the upper critical dimension of jamming is believed to be $d_u$=2, non mean-field exponents are observed in numerical studies of 2D and 3D fiber networks. The origins of this remains unclear. In this study we propose a minimal mean-field model for strain-controlled crit

James Q. Quach, Giulio Cerullo, Tersilla Virgili

According to the International Energy Agency, each human uses more than 80 GJ of energy per year; this is equivalent to leaving a washing machine continuously running for one year for every person on Earth. This consumption is expected to increase by 28% by 2040 (from 2015 levels). The majority (86%) of this energy comes from fossil fuels. This dependence on

Ashley Gerard Davies, Jason Perry, David A. Williams, David M. Nelson

The distribution of Io's volcanic activity likely reflects the position and magnitude of internal tidal heating. We use new observations of Io's polar regions by the Juno spacecraft Jovian Infrared Auroral Mapper (JIRAM) to complete near-infrared global coverage, revealing the global distribution and magnitude of thermal emission from Io's currently erupting

Wei Yao, Yuhong Liu, Fadi P. Deek, Guiling Wang

The rapid development of intelligent transportation systems and connected vehicles has highlighted the need for secure and efficient key management systems (KMS). In this paper, we introduce VDKMS (Vehicular Decentralized Key Management System), a novel Decentralized Key Management System designed specifically as an infrastructure for Cellular Vehicular-to-E

Thomas Tarrants, Elvis Mendes

Much of the exoplanet discovery efforts over the next several years are largely tasked with finding candidates for the upcoming Ariel mission. This is a role that TESS is well-suited for. Radial velocity follow-up is needed to confirm the planetary nature of these systems, as many of its planet candidates turn out to be eclipsing binary systems with small st

Nitesh Kumar, Steven Schockaert

Modelling how concepts are related is a central topic in Lexical Semantics. A common strategy is to rely on knowledge graphs (KGs) such as ConceptNet, and to model the relation between two concepts as a set of paths. However, KGs are limited to a fixed set of relation types, and they are incomplete and often noisy. Another strategy is to distill relation emb

Tae Jin Park, He Huang, Ante Jukic, Kunal Dhawan

We present the NVIDIA NeMo team's multi-channel speech recognition system for the 7th CHiME Challenge Distant Automatic Speech Recognition (DASR) Task, focusing on the development of a multi-channel, multi-speaker speech recognition system tailored to transcribe speech from distributed microphones and microphone arrays. The system predominantly comprises of

Marc Vila, Aron W. Cummings, Stephan Roche

We report on exceptionally long spin transport and giant spin lifetime anisotropy in the gapped surface states of three-dimensional (3D) magnetic topological insulators (MTIs). We examine the properties of these states using the Fu-Kane-Mele Hamiltonian in presence of a magnetic exchange field. The corresponding spin textures of surface states, which are wel

Heejoo Choi, Young-Sik Kim, Hyukmo Kang, Solvay Blomquist

The size of the optics used in observatories is often limited by fabrication, metrology, and handling technology, but having a large primary mirror provides significant benefits for scientific research. The evolution of rocket launch options enables heavy payload carrying on orbit and outstretching the telescope's form-factor choices. Moreover, cost per laun

Iritan Ferreira dos Santos, Alexey M. Kuz'min

An explicit base with multiplication table is obtained for the free weakly Novikov metabelian algebra of infinite rank over an arbitrary field of characteristic $\neq 2$.

Erich Schmitz, Yunhui Guo, Jing Wang

Glioblastoma Multiforme (GBM) is an aggressive form of malignant brain tumor with a generally poor prognosis. Treatment usually includes a mix of surgical resection, radiation therapy, and akylating chemotherapy but, even with these intensive treatments, the 2-year survival rate is still very low. O6-methylguanine-DNA methyltransferase (MGMT) promoter methyl

Georgiana Fasolă, Marius Tărnăuceanu

Given a construction $f$ on groups, we say that a group $G$ is \textit{$f$-realisable} if there is a group $H$ such that $G\cong f(H)$, and \textit{completely $f$-realisable} if there is a group $H$ such that $G\cong f(H)$ and every subgroup of $G$ is isomorphic to $f(H_1)$ for some subgroup $H_1$ of $H$ and vice versa. Denote by $L(G)$ the absolute center o

Gongxiaohui Chen, Tyler H. Chang, John Power, Chungunag Jing

The overarching goal of beamline design is to achieve a high brightness electron beam from the beamline. Traditional beamline design studies involved separate optimizations of radio-frequency cavities, magnets, and beam dynamics using different codes and pursuing various intermediate objectives. In this work, we present a novel unified global optimization fr

Tae Jin Park, He Huang, Coleman Hooper, Nithin Koluguri

We introduce a sophisticated multi-speaker speech data simulator, specifically engineered to generate multi-speaker speech recordings. A notable feature of this simulator is its capacity to modulate the distribution of silence and overlap via the adjustment of statistical parameters. This capability offers a tailored training environment for developing neura

Martino Bernasconi, Matteo Castiglioni, Andrea Celli, Federico Fusco

Bilateral trade models the problem of intermediating between two rational agents -- a seller and a buyer -- both characterized by a private valuation for an item they want to trade. We study the online learning version of the problem, in which at each time step a new seller and buyer arrive and the learner has to set prices for them without any knowledge abo

Hyung Wook Choi, Mat Kelly

The semantics used for particular terms in an academic field organically evolve over time. Tracking this evolution through inspection of published literature has either been from the perspective of Linguistic scholars or has concentrated the focus of term evolution within a single domain of study. In this paper, we performed a case study to identify semantic

Yangjiang Wei, Yi Ming Zou

We showed that isomorphism classes of idempotent evolution algebras are in bijection with the orbits of the semidirect product group of the symmetric group and the torus, considered the combinatoric problem of enumeration of isomorphism classes for these algebras over arbitrary finite fields, derived a general counting formula, and obtained explicit formulas

Vishwa Dewage, Mishko Mitkovski

We use results and techniques from Werner's ``quantum harmonic analysis'' to show that $G$-invariant Toeplitz operators are norm dense in $G$-invariant Toeplitz algebras for all subgroups $G$ of the affine unitary group $U_n\ltimes \mathbb{C}^n$. Additionally, we prove that the quasi-radial Toeplitz operators are dense in the quasi-radial Toeplitz algebra ov

Santiago Rojas-Rojas, Camila Muñoz, Edgar Barriga, Pablo Solano

We present analytic solutions to the evolution in generalized tight-binding models, which consider complex first-neighbor couplings with equal amplitude and arbitrary phases. Our findings provide a powerful tool for efficiently calculating expectation values and correlations within the system, which are otherwise difficult to compute numerically. We apply ou

Abhijit Chowdhary, Mason Haberle, William Ofori-atta, Qiliang Wu

Roll solutions at the zigzag boundary, typically selected by patterns and defects in numerical simulations, are shown to be nonlinearly stable. This result also serves as an example that linear decay weaker than the classical diffusive decay, together with quadratic nonlinearity, still gives nonlinear stability of spatially periodic patterns. Linear analysis

Tyler Chen, Robert Chen, Kevin Li, Skai Nzeuton

We develop randomized matrix-free algorithms for estimating partial traces, a generalization of the trace arising in quantum physics and chemistry. Our algorithm improves on the typicality-based approach used in [T. Chen and Y-C. Cheng, \emph{Numerical computation of the equilibrium-reduced density matrix for strongly coupled open quantum systems}, J. Chem.

Ruisi Zhang, Shehzeen Samarah Hussain, Paarth Neekhara, Farinaz Koushanfar

We present REMARK-LLM, a novel efficient, and robust watermarking framework designed for texts generated by large language models (LLMs). Synthesizing human-like content using LLMs necessitates vast computational resources and extensive datasets, encapsulating critical intellectual property (IP). However, the generated content is prone to malicious exploitat

Connor Lennox, Sumanta Kashyapi, Laura Dietz

Query-specific article generation is the task of, given a search query, generate a single article that gives an overview of the topic. We envision such articles as an alternative to presenting a ranking of search results. While generative Large Language Models (LLMs) like chatGPT also address this task, they are known to hallucinate new information, their mo

Muhammad Asif Ali, Yan Hu, Jianbin Qin, Di Wang

Automated construction of bilingual dictionaries using monolingual embedding spaces is a core challenge in machine translation. The end performance of these dictionaries relies upon the geometric similarity of individual spaces, i.e., their degree of isomorphism. Existing attempts aimed at controlling the relative isomorphism of different spaces fail to inco

Yuhang Zhang, Marcos Quinones-Grueiro, Zhiyao Zhang, Yanbing Wang

Variable Speed Limit (VSL) control acts as a promising highway traffic management strategy with worldwide deployment, which can enhance traffic safety by dynamically adjusting speed limits according to real-time traffic conditions. Most of the deployed VSL control algorithms so far are rule-based, lacking generalizability under varying and complex traffic sc

Luis González-De La Fuente, Alicia Nieto-Reyes, Pedro Terán

Statistical depth functions are a standard tool in nonparametric statistics to extend order-based univariate methods to the multivariate setting. Since there is no universally accepted total order for fuzzy data (even in the univariate case) and there is a lack of parametric models, a fuzzy extension of depth-based methods is very interesting. In this paper,

Han Ji, Arman Oganisian

Observational studies are often conducted to estimate causal effects of treatments or exposures on event-time outcomes. Since treatments are not randomized in observational studies, techniques from causal inference are required to adjust for confounding. Bayesian approaches to causal estimates are desirable because they provide 1) prior smoothing provides us

Chongzhou Fang, Ning Miao, Shaurya Srivastav, Jialin Liu

Large language models (LLMs) have demonstrated significant potential in the realm of natural language understanding and programming code processing tasks. Their capacity to comprehend and generate human-like code has spurred research into harnessing LLMs for code analysis purposes. However, the existing body of literature falls short in delivering a systemat

H. Horner, L. M. Rachbauer, S. Rotter, U. Leonhardt

The Casimir force between dielectric bodies is well-understood, but not the Casimir force inside a dielectric, in particular its renormalization. We develop and analyse a simple model for the Casimir forces inside a medium that is completely free of renormalization and show then how renormalization emerges. We consider a one-dimensional chain of point partic

Giulio Iacobelli, Guilherme Ost, Daniel Y. Takahashi

We study random walks on Erd\"os-R\'enyi random graphs in which, every time the random walk returns to the starting point, first an edge probability is independently sampled according to a priori measure $\mu$, and then an Erd\"os-R\'enyi random graph is sampled according to that edge probability. When the edge probability $p$ does not depend on the size of

Syed Islam, Monika Filipovska

Traffic state forecasting is crucial for traffic management and control strategies, as well as user- and system-level decision making in the transportation network. While traffic forecasting has been approached with a variety of techniques over the last couple of decades, most approaches simply rely on endogenous traffic variables for state prediction, despi

Hiroyuki Deguchi, Hayate Hirano, Tomoki Hoshino, Yuto Nishida

k-nearest-neighbor machine translation (kNN-MT) boosts the translation quality of a pre-trained neural machine translation (NMT) model by utilizing translation examples during decoding. Translation examples are stored in a vector database, called a datastore, which contains one entry for each target token from the parallel data it is made from. Due to its si

Konstantinos Gkouliaras, Vasileios Theos, Phil Evans, Stylianos Chatzidakis

An experimental Quantum Key Distribution (QKD) implementation requires advanced costly hardware, unavailable in most research environments, making protocol testing and performance evaluation complicated. Historically, this has been a major motivation for the development of QKD simulation frameworks, to allow researchers to obtain insight before proceeding in

Nan Cui, Xiuling Wang, Wendy Hui Wang, Violet Chen

Graph Neural Networks (GNNs) have been widely used for various types of graph data processing and analytical tasks in different domains. Training GNNs over centralized graph data can be infeasible due to privacy concerns and regulatory restrictions. Thus, federated learning (FL) becomes a trending solution to address this challenge in a distributed learning

Zhenyu Gao, John-Paul Clarke, Javid Mardanov, Karen Marais

Unmanned Aerial Systems (UAS), an integral part of the Advanced Air Mobility (AAM) vision, are capable of performing a wide spectrum of tasks in urban environments. The societal integration of UAS is a pivotal challenge, as these systems must operate harmoniously within the constraints imposed by regulations and societal concerns. In complex urban environmen

S. G. Meintanis, B. Milošević, M. D. Jiménez-Gamero

We propose tests of fit for classes of distributions that include the Weibull, the Pareto and the Fr\'echet, distributions. The new tests employ the novel tool of the min--characteristic function and are based on an L2--type weighted distance between this function and its empirical counterpart applied on suitably standardized data. If data--standardization i

Matthew Hull, Vivian Pednekar, Hannah Murray, Nimisha Roy

Manually grading D3 data visualizations is a challenging endeavor, and is especially difficult for large classes with hundreds of students. Grading an interactive visualization requires a combination of interactive, quantitative, and qualitative evaluation that are conventionally done manually and are difficult to scale up as the visualization complexity, da

Samuel W Kerber, Nicholas A Duncan, Guillaume F LHer, Morgan Bazilian

Urban environments are intricate systems where the breakdown of critical infrastructure can impact both the economic and social well-being of communities. Electricity systems hold particular significance, as they are essential for other infrastructure, and disruptions can trigger widespread consequences. Typically, assessing electricity availability requires

Gustavo A. Vargas Hakim, David Osowiechi, Mehrdad Noori, Milad Cheraghalikhani

Deep Learning models have shown remarkable performance in a broad range of vision tasks. However, they are often vulnerable against domain shifts at test-time. Test-time training (TTT) methods have been developed in an attempt to mitigate these vulnerabilities, where a secondary task is solved at training time simultaneously with the main task, to be later u

Cheng-Fu Yang, Yen-Chun Chen, Jianwei Yang, Xiyang Dai

End-to-end Transformers have demonstrated an impressive success rate for Embodied Instruction Following when the environment has been seen in training. However, they tend to struggle when deployed in an unseen environment. This lack of generalizability is due to the agent's insensitivity to subtle changes in natural language instructions. To mitigate this is

Ouya Wang, Shenglong Zhou, Geoffrey Ye Li

Few-shot learning (FSL) enables adaptation to new tasks with only limited training data. In wireless communications, channel environments can vary drastically; therefore, FSL techniques can quickly adjust transceiver accordingly. In this paper, we develop two FSL frameworks that fit in wireless transceiver design. Both frameworks are base on optimization pro

Yongqi Tong, Yifan Wang, Dawei Li, Sizhe Wang

Chain-of-Thought(CoT) prompting and its variants explore equipping large language models (LLMs) with high-level reasoning abilities by emulating human-like linear cognition and logic. However, the human mind is complicated and mixed with both linear and nonlinear thinking. In this work, we propose \textbf{I}nferential \textbf{E}xclusion \textbf{P}rompting (I

Debashrita Mohapatra, Debi Prasad Mohapatra, Ram Sewak Dubey

This paper studies the widespread price dispersion of homogeneous products across different online platforms, even when consumers can easily access price information from comparison websites. We collect data for the 200 most popular hotels in London (UK) and document that prices vary widely across booking sites while making reservations for a hotel room. Add

Daniel J. Eisenstein, Benjamin D. Johnson, Brant Robertson, Sandro Tacchella

We summarize the properties and initial data release of the JADES Origins Field (JOF), the longest single pointing yet imaged with the James Webb Space Telescope (JWST). This field falls within the GOODS-S region about 8' south-west of the Hubble Ultra Deep Field (HUDF), where it was formed initially in Cycle 1 as a parallel field of HUDF spectroscopic obser

Silviu Balanescu, Mircea Cimpoeas

Let $K$ be a infinite field, $S=K[x_1,\ldots,x_n]$ and $0\subset I\subsetneq J\subset S$ two squarefree monomial ideals. In a previous paper we proved a new formula for the Hilbert depth of $J/I$. In this paper, we illustrate how one can use the Stanley-Reisner correspondence between (relative) simplicial complexes and (quotients of) squarefree monomial idea

Tadeja Veršič, Sabine Thater, Glenn van de Ven, Laura L. Watkins

The goal of this work is to probe the total mass distribution of early-type galaxies with globular clusters (GCs) as kinematic tracers, by constraining the parameters of the profile with a flexible modelling approach. To that end, we leverage the extended spatial distribution of GCs from the SLUGGS survey ($\langle R_{\rm GC,\ max} \rangle \sim 8R_{\rm e}$)

Regine Büter, Roger D. Soberanis-Mukul, Paola Ruiz Puentes, Ahmed Ghazi

Purpose: Metrics derived from eye-gaze-tracking and pupillometry show promise for cognitive load assessment, potentially enhancing training and patient safety through user-specific feedback in tele-robotic surgery. However, current eye-tracking solutions' effectiveness in tele-robotic surgery is uncertain compared to everyday situations due to close-range in

Luke Geeson, Lee Smith

Finding bugs is key to the correctness of compilers in wide use today. If the behaviour of a compiled program, as allowed by its architecture memory model, is not a behaviour of the source program under its source model, then there is a bug. This holds for all programs, but we focus on concurrency bugs that occur only with two or more threads of execution. W

Kate Y. L. Su, Grant M. Kennedy, George H. Rieke, A. Meredith Hughes

RZ Piscium (RZ Psc) is well-known in the variable star field because of its numerous, irregular optical dips in the past five decades, but the nature of the system is heavily debated in the literature. We present multiyear infrared monitoring data from Spitzer and WISE to track the activities of the inner debris production, revealing stochastic infrared vari

Micha Berkooz, Yiyang Jia, Navot Silberstein

Parisi's hypercube model describes a charged particle hopping on a $d$-dimensional hypercube with disordered background fluxes in the large $d$ limit. It was noted previously [Jia and Verbaarschot, J. High Energy Phys. 11 (2020) 154] that the hypercube model at leading order in $1/d$ has the same spectral density as the double-scaled Sachdev-Ye-Kitaev (DS-SY

Francisco Rowe, Carmen Cabrera-Arnau, Miguel González-Leonardo, Andrea Nasuto

The COVID-19 pandemic has impacted the national systems of population movement around the world. Existing work has focused on countries of the Global North and restricted to the immediate effects of COVID-19 data during 2020. Data have represented a major limitation to monitor change in mobility patterns in countries in the Global South. Drawing on aggregate

Weiyi Wu, Chongyang Gao, Joseph DiPalma, Soroush Vosoughi

Recent advances in whole-slide image (WSI) scanners and computational capabilities have significantly propelled the application of artificial intelligence in histopathology slide analysis. While these strides are promising, current supervised learning approaches for WSI analysis come with the challenge of exhaustively labeling high-resolution slides - a proc

Jungjun Park, Andrew L. Nguyen

In this paper, we study the Black-Litterman (BL) asset allocation model (Black and Litterman, 1990) under the hidden truncation skew-normal distribution (Arnold and Beaver, 2000). In particular, when returns are assumed to follow this skew normal distribution, we show that the posterior returns, after incorporating views, are also skew normal. By using Simaa

Haotian Cheng, Naijun Jin, Zhaowei Dai, Chao Xiang

The unique benefits of Fabry-P\'erot resonators as frequency-stable reference cavities and as an efficient interface between atoms and photons make them an indispensable resource for emerging photonic technologies. To bring these performance benefits to next-generation communications, computation, and timekeeping systems, it will be necessary to develop stra

Luis Mendonça

We show that if a countably generated Lie algebra $H$ does not contain isomorphic copies of certain finite-dimensional nilpotent Lie algebras $A$ and $B$ (satisfying some mild conditions), then $H$ embeds into a quotient of $A \ast B$ that is at the same time hopfian and cohopfian. This is a Lie algebraic version of an embedding theorem proved by C. Miller a

Jianwei Lyu, Stacey Alberts, George H. Rieke, Irene Shivaei

Understanding the co-evolution of supermassive black holes (SMBHs) and their host systems requires a comprehensive census of active galactic nuclei (AGN) behavior across a wide range of redshift, luminosity, obscuration level and galaxy properties. We report significant progress with JWST towards this goal from the Systematic Mid-infrared Instrument Legacy E

Yuvraj Singh, Glen M. Hocky

Small mechanical forces play important functional roles in many crucial cellular processes, including in the dynamical behavior of the cytoskeleton and in the regulation of osmotic pressure through membrane-bound proteins. Molecular simulations offer the promise of being able to design the behavior of proteins that sense and respond to these forces. However,

Mehdi Houshmand Sarkhoosh, Sayed Mohammad Majidi Dorcheh, Sushant Gautam, Cise Midoglu

In the era of digitalization, social media has become an integral part of our lives, serving as a significant hub for individuals and businesses to share information, communicate, and engage. This is also the case for professional sports, where leagues, clubs and players are using social media to reach out to their fans. In this respect, a huge amount of tim

Ilya Musabirov, Angela Zavaleta-Bernuy, Pan Chen, Michael Liut

Randomized A/B comparisons of alternative pedagogical strategies or other course improvements could provide useful empirical evidence for instructor decision-making. However, traditional experiments do not provide a straightforward pathway to rapidly utilize data, increasing the chances that students in an experiment experience the best conditions. Drawing i

Hanchen Wang, Qiang Guo, Tariq Alkhalifah

In micro-seismic event measurements, pinpointing the passive source's exact spatial and temporal location is paramount. This research advocates for the combined use of both P- and S-wave data, captured by geophone monitoring systems, to improve source inversion accuracy. Drawing inspiration from the secondary source concept in Elastic Reflection Full Wavefor

Luis F. Alday, Shai M. Chester, Daniele Dorigoni, Michael B. Green

Integrated correlation functions in $\mathcal{N}=4$ supersymmetric Yang--Mills theory with gauge group $SU(N)$ can be expressed in terms of the localised $S^4$ partition function, $Z_N$, deformed by a mass $m$. Two such cases are $\mathcal{C}_N=(\text{Im} \tau)^2 \partial_\tau\partial_{\bar\tau} \partial_m^2\log Z_N\vert_{m=0}$ and $\mathcal{H}_N=\partial_m^

Daniel McGann, Kyle Lassak, Michael Kaess

In this paper we present a fully distributed, asynchronous, and general purpose optimization algorithm for Consensus Simultaneous Localization and Mapping (CSLAM). Multi-robot teams require that agents have timely and accurate solutions to their state as well as the states of the other robots in the team. To optimize this solution we develop a CSLAM back-end

Pranav Narayanan Venkit, Mukund Srinath, Sanjana Gautam, Saranya Venkatraman

We conduct an inquiry into the sociotechnical aspects of sentiment analysis (SA) by critically examining 189 peer-reviewed papers on their applications, models, and datasets. Our investigation stems from the recognition that SA has become an integral component of diverse sociotechnical systems, exerting influence on both social and technical users. By delvin

Ovidiu Costin, Gerald V. Dunne, Angus Gruen, Sergei Gukov

Using resurgent analysis we offer a novel mathematical perspective on a curious bijection (duality) that has many potential applications ranging from the theory of vertex algebras to the physics of SCFTs in various dimensions, to q-series invariants in low-dimensional topology that arise, e.g. in Vafa-Witten theory and in non-perturbative completion of compl

Ian Fleschler, Xavier Tolsa, Michele Villa

In this paper we prove a higher dimensional analogue of Carleson's $\varepsilon^2$ conjecture. Given two arbitrary disjoint open sets $\Omega^+,\Omega^-\subset \mathbb{R}^{n+1}$, and $x\in\mathbb{R}^{n+1}$, $r>0$, we denote $$\varepsilon_n(x,r) := \frac{1}{r^n}\, \inf_{H^+} \mathcal{H}^n \left( ((\partial B(x,r)\cap H^+) \setminus \Omega^+) \cup ((\partial B

Fangcheng He, Ismail Zahed

The gravitational form factors of light nuclei are evaluated up to momenta of the order of the nucleon mass, using the impulse approximation. The nucleon gravitational form factors are reduced non-relativistically, and used to derive the gravitational form factors of light nuclei. The deuteron gravitational form factors are analysed using the Reid soft core

Marco Caporaletti, Andreas Deuchert

We consider a homogeneous Bose gas in the Gross--Pitaevskii limit at temperatures that are comparable to the critical temperature for Bose--Einstein condensation. Recently, an upper bound for the grand canonical free energy was proved in arXiv:2305.19173 [math-ph] capturing two novel contributions. First, the free energy of the interacting condensate is give

Peter R. Young

New reference wavelengths for atomic transitions of Mg VII and Si VII in the 272-281 A wavelength range are derived using measurements from the Extreme ultraviolet Imaging Spectrometer (EIS) on board the Hinode spacecraft. Mg VII and Si VII are important ions for measuring plasma properties in the solar transition region at around 0.6 MK. The six Si VII wave

Roberto S. Costas-Santos

This contribution aims to obtain several connection formulae for the polynomial sequence, which is orthogonal with respect to the discrete Sobolev inner product \[ \langle f, g\rangle_n=\langle {\bf u}, fg\rangle+ \sum_{j=1}^M \mu_{j} f^{(\nu_j)}(c_j) g^{(\nu_j)}(c_j), \] where ${\bf u}$ is a classical linear functional, $c_j\in \mathbb R$, $\nu_j\in \mathbb

Sk Sahadat Hossain, Biswajit Paul, Indrani Chattopadhyay, Debasis Sarkar

Identifying the nonlocality of a multiparty quantum state is an important task in quantum mechanics. Seevinck and Svetlichny [Phys. Rev. Lett. 89, 060401 (2002)], and independently, Collins and co-workers [Phys. Rev. Lett. 88, 170405 (2002)] have generalized the tripartite notion of Svetlichny nonlocality to n-parties. Here we have developed a tight upper bo

Tobias Heibges, Jonatan Posligua, Hannah Wistrand, Claire Guépin

During the Extreme Universe Space Observatory on a Super Pressure Balloon 2 (EUSO-SPB2) mission, we planned Target of Opportunity (ToO) operations to follow up on possible sources of $\gtrsim 10 \, {\rm PeV}$ neutrinos. The original plan before flight was to point the onboard Cherenkov Telescope (CT) to catch the source's path on the sky just below Earth's h

Zlatina Mileva, Antonis Bikakis, Fabio Aurelio D'Asaro, Mark Law

Argumentation is a very active research field of Artificial Intelligence concerned with the representation and evaluation of arguments used in dialogues between humans and/or artificial agents. Acceptability semantics of formal argumentation systems define the criteria for the acceptance or rejection of arguments. Several software systems, known as argumenta

Daniel Bennett, Daniel T. Larson, Louis Sharma, Stephen Carr

An accurate description of the low-energy electronic bands in twisted bilayer graphene (tBLG) is of great interest due to their relation to correlated electron phases, such as superconductivity and Mott-insulator behavior at half-filling. The paradigmatic model of Bistritzer and MacDonald [PNAS 108, 12233 (2011)], based on the moir\'e pattern formed by tBLG,

Claudio Gorodski, Andreas Kollross, Burkhard Wilking

We provide detailed calculations for the classification of representations of compact simple Lie groups with non-empty boundary in the orbit space, first announced in a previous paper [arXiv:2112.00513] by the same authors.

Kai Li, Shixuan Guan, Darren Lee

This paper presents the first comprehensive analysis of an emerging cryptocurrency scam named "arbitrage bot" disseminated on online social networks. The scam revolves around Decentralized Exchanges (DEX) arbitrage and aims to lure victims into executing a so-called "bot contract" to steal funds from them. To collect the scam at a large scale, we developed a

Eason Chen, Justa Liang, Ray Huang, Pierce Hung

Randomness plays a pivotal role in modern online gaming, but disputes have arisen over the accuracy of stated winning chances, resulting in legal issues and financial setbacks for gaming companies. Fortunately, blockchain-based games offer a solution to the transparency and fairness issue regarding randomness. Furthermore, emerging blockchain technology like

Ryan Park, Ryan Theisen, Navriti Sahni, Marcel Patek

Molecular language modeling is an effective approach to generating novel chemical structures. However, these models do not \emph{a priori} encode certain preferences a chemist may desire. We investigate the use of fine-tuning using Direct Preference Optimization to better align generated molecules with chemist preferences. Our findings suggest that this appr

Frithjof Petrick, Christian Herold, Pavel Petrushkov, Shahram Khadivi

Despite the known limitations, most machine translation systems today still operate on the sentence-level. One reason for this is, that most parallel training data is only sentence-level aligned, without document-level meta information available. In this work, we set out to build context-aware translation systems utilizing document-level monolingual data ins

Maximilian Schumacher, Gernot Alber

Sufficient and necessary conditions are presented for the existence of $(N,M)$-positive operator valued measures ($(N,M)$-POVMs) valid for arbitrary-dimensional quantum systems. A sufficient condition for the existence of $(N,M)$-POVMs is presented. It yields a simple relation determining an upper bound on the continuous parameter of an arbitrary $(N,M)$-POV

ATLAS Collaboration

A search for nonresonant Higgs boson pair production in the $b\bar{b}\gamma\gamma$ final state is performed using 140 fb$^{-1}$ of proton-proton collisions at a centre-of-mass energy of 13 TeV recorded by the ATLAS detector at the CERN Large Hadron Collider. This analysis supersedes and expands upon the previous nonresonant ATLAS results in this final state

Sheng Lu, Shan Chen, Yingya Li, Danielle Bitterman

In-context learning (ICL) is a new learning paradigm that has gained popularity along with the development of large language models. In this work, we adapt a recently proposed hardness metric, pointwise $\mathcal{V}$-usable information (PVI), to an in-context version (in-context PVI). Compared to the original PVI, in-context PVI is more efficient in that it