March 2024 arXiv papers — page 39

Tom Wettlin, Youxi Lin, Nebojsa Stojanovic, Stefano Calabrò

We show a beyond 200Gb/s VCSEL transmission experiment. Results are based on 35GHz VCSEL and advanced DSP. We show an AIR of 245Gb/s PAM-6 back-to-back, and 200Gb/s PAM-4 over 60m OM4 fiber assuming KP4-FEC.

Takuro Abe, Tan Nhat Tran

Given an irreducible root system, the Worpitzky-compatible subsets are defined by a geometric property of the alcoves inside the fundamental parallelepiped of the root system. This concept is motivated and mainly understood through a lattice point counting formula concerning the characteristic and Ehrhart quasi-polynomials. In this paper, we show that the Wo

Ermal Rrapaj, Evan Rule

We develop a constructive approach to generate quantum neural networks capable of representing the exact thermal states of all many-body qubit Hamiltonians. The Trotter expansion of the imaginary-time propagator is implemented through an exact block encoding by means of a unitary, restricted Boltzmann machine architecture. Marginalization over the hidden-lay

Saeed Behzadi, Amir Bagheri, Abbas Rabiee

As natural disasters bring about power outage and financial losses, network resiliency is an important challenge for distribution network operators (DNOs). On the other side, power loss reduction during normal operating condition is a major concern of DNOs. In this paper, optimal scheduling of active distribution network (ADN) is addressed through simultaneo

Lior Shamir

The unprecedented imaging power of JWST provides new abilities to observe the shapes of objects in the early Universe in a way that has not been possible before. Recently, JWST acquired a deep field image inside the same field imaged in the past as the HST Ultra Deep Field. Computer-based quantitative analysis of spiral galaxies in that field shows that amon

Ryan Gupta, Hyonyoung Shin, Emily Norman, Keri K. Stephens

Despite the rise of mobile robot deployments in home and work settings, perceived safety of users and bystanders is understudied in the human-robot interaction (HRI) literature. To address this, we present a study designed to identify elements of a human-robot encounter that correlate with observed stress response. Stress is a key component of perceived safe

Zewei Xiong, Meng-Ru Wu, Manu George, Chun-Yu Lin

The quantum kinetic evolution of neutrinos in dense environments, such as the core-collapse supernovae or the neutron star mergers, can result in fast flavor conversion (FFC), presenting a significant challenge to achieving robust astrophysical modeling of these systems. Recent works that directly simulate the quantum kinetic transport of neutrinos in locali

Andrey Sokolov, Jaideep Katuri, Juan J. de Pablo, Alexey Snezhko

Active nematics are materials composed of mobile, elongated particles that can transform energy from the environment into a mechanical motion. Current experimental realizations of the active nematics are of biological origin and include cell layers, suspensions of elongated bacteria in liquid crystal, and combinations of bio-filaments with molecular motors.

Sergey Kuznetsov, Lev Titarchuk

The multi-wavelength outburst activity in the BL Lacertae source OJ 287 has sparked a lot of controversy about whether the source contains one or two black holes (BHs) and what characteristics of this black hole binary would be. In this article we present the results of analysis of the X-ray flaring activity of OJ 287 using the data of Swift/XRT observations

Xinrui Wang, Yan Jin

This study explores a learning-based tri-finger robotic arm manipulating task, which requires complex movements and coordination among the fingers. By employing reinforcement learning, we train an agent to acquire the necessary skills for proficient manipulation. To enhance the efficiency and effectiveness of the learning process, two knowledge transfer stra

Farshad Rostami Ghadi, Kai-Kit Wong, Kin-Fai Tong, Yangyang Zhang

This letter investigates the performance of content caching in a heterogeneous cellular network (HetNet) consisting of fluid antenna system (FAS)-equipped mobile users (MUs) and millimeter-wave (mm-wave) single-antenna small base stations (SBSs), distributed according to the independent homogeneous Poisson point processes (HPPP). In particular, it is assumed

Vanessa Figueiredo, Catherine Ann Cameron

Investigating child-computer interactions within their contexts is vital for designing technology that caters to children's needs. However, determining what aspects of context are relevant for designing child-centric technology remains a challenge. We introduce EXPLORA, a multimodal, multistage online methodology comprising three pivotal stages: (1) building

Augustus Brown, Francesco Galvagno, Congkao Wen

We study the four-point correlator $\langle \mathcal{O}_2 \mathcal{O}_2 \mathcal{D} \mathcal{D} \rangle$ in $\mathcal{N}=4$ super Yang-Mills theory (SYM) with $SU(N)$ gauge group, where $\mathcal{O}_2$ represents the superconformal primary operator with dimension two, while $\mathcal{D}$ denotes a determinant operator of dimension $N$, which is holographical

Chenzi Jin, Yanir A. Rubinstein

In 1988, Tian posed the stabilization problem for equivariant global log canonical thresholds. We solve it in the case of toric Fano manifolds. This is the first general result on Tian's problem. A key new estimate involves expressing complex singularity exponents associated to orbits of a group action in terms of support and gauge functions from convex geom

Manas Kale, Paul G. Kry

We present a technique designed for parallelizing large rigid body simulations, capable of exploiting multiple CPU cores within a computer and across a network. Our approach can be applied to simulate both unilateral and bilateral constraints, requiring straightforward modifications to the underlying physics engine. Starting from an approximate partitioning,

Marco Golla

We give restrictions on the weak combinatorics of line arrangements with singular points of odd multiplicity using topological arguments on locally-flat spheres in 4-manifolds. As a corollary, we show that there is no line arrangement comprising 13 lines and with only triple points.

Trung-Kien Nguyen, Yuan Fang

Link prediction is a fundamental task for graph analysis with important applications on the Web, such as social network analysis and recommendation systems, etc. Modern graph link prediction methods often employ a contrastive approach to learn robust node representations, where negative sampling is pivotal. Typical negative sampling methods aim to retrieve h

Andrea Dei, Emil J. Martinec

Worldsheet string theory is solvable for a variety of backgrounds involving Neveu-Schwarz fivebranes, in terms of gauged nonlinear sigma models on group manifolds. We compute the worldsheet torus partition function of these models, and propose gauging of null isometries as a unifying principle and conceptual framework for this large family of string backgrou

Anjana Wijayawardhana, Thomas Suesse, David Gunawan

Efficient estimation methods for simultaneous autoregressive (SAR) models with missing data in the response variable have been well-explored in the literature. A common practice is to introduce measurement error into SAR models to separate the noise component from the spatial process. However, prior research has not considered incorporating measurement error

Li Qiao, Mahdi Boloursaz Mashhadi, Zhen Gao, Chuan Heng Foh

Generative foundation AI models have recently shown great success in synthesizing natural signals with high perceptual quality using only textual prompts and conditioning signals to guide the generation process. This enables semantic communications at extremely low data rates in future wireless networks. In this paper, we develop a latency-aware semantic com

Souradeep Chakraborty, Dana Perez, Paul Friedman, Natallia Sheuka

We present a method for classifying the expertise of a pathologist based on how they allocated their attention during a cancer reading. We engage this decoding task by developing a novel method for predicting the attention of pathologists as they read whole-slide Images (WSIs) of prostate and make cancer grade classifications. Our ground truth measure of a p

Gaurav Negi, Rajdeep Sarkar, Omnia Zayed, Paul Buitelaar

Aspect-Based Sentiment Analysis (ABSA) aims to identify terms or multiword expressions (MWEs) on which sentiments are expressed and the sentiment polarities associated with them. The development of supervised models has been at the forefront of research in this area. However, training these models requires the availability of manually annotated datasets whic

Yanfeng Li, Manman Wang, Guoqi Huang, Li Liu

Laser light possesses perfect coherence, but cannot be attenuated to single photons via linear optics. An elegant route to convert laser light into single photons is based on photon blockade in a cavity with a single atom in the strong coupling regime. However, the single-photon purity achieved by this method remains relatively low. Here we propose an interf

Caleb McIrvin, Ankith Mohan, Jamie Sikora

The quantum state discrimination problem has Alice sending a quantum state to Bob who wins if he correctly identifies the state. The pretty good measurement, also known as the square root measurement, performs pretty well at this task. We study the version of this problem where Bob tries to lose with the greatest probability possible (which is harder than it

Joaquín Moraga

Let $(X,B)$ be a log Calabi-Yau pair of dimension $n$, index one, and birational complexity $c$. We show that $(X,B)$ has a crepant birational model that admits a tower of Mori fiber spaces of which at least $n-c$ are conic fibrations. Motivated by the proof of the previous statement, we introduce new measures of the complexity of a log Calabi-Yau pair; the

Elira Shaska, Tony Shaska

We use machine learning to study the moduli space of genus two curves, specifically focusing on detecting whether a genus two curve has $(n, n)$-split Jacobian. Based on such techniques, we observe that there are very few rational moduli points with small weighted moduli height and $(n, n)$-split Jacobian for $n=2, 3, 5$. We computational prove that there ar

Lei Yan, Theodoros Stouraitis, João Moura, Wenfu Xu

This paper investigates one of the most challenging tasks in dynamic manipulation -- catching large-momentum moving objects. Beyond the realm of quasi-static manipulation, dealing with highly dynamic objects can significantly improve the robot's capability of interacting with its surrounding environment. Yet, the inevitable motion mismatch between the fast m

Maria Cuellar, Susan Vanderplas, Amanda Luby, Michael Rosenblum

Reviews conducted by the National Academy of Sciences (2009) and the President's Council of Advisors on Science and Technology (2016) concluded that the field of forensic firearm comparisons has not been demonstrated to be scientifically valid. Scientific validity requires adequately designed studies of firearm examiner performance in terms of accuracy, repe

Nicolò Dal Fabbro, Arman Adibi, H. Vincent Poor, Sanjeev R. Kulkarni

We consider a setting in which $N$ agents aim to speedup a common Stochastic Approximation (SA) problem by acting in parallel and communicating with a central server. We assume that the up-link transmissions to the server are subject to asynchronous and potentially unbounded time-varying delays. To mitigate the effect of delays and stragglers while reaping t

David Bai, Ishika Singh, David Traum, Jesse Thomason

Classical planning formulations like the Planning Domain Definition Language (PDDL) admit action sequences guaranteed to achieve a goal state given an initial state if any are possible. However, reasoning problems defined in PDDL do not capture temporal aspects of action taking, such as concurrent actions between two agents when there are no conflicting cond

Yilun Zhu, Siyao Peng, Sameer Pradhan, Amir Zeldes

Singleton mentions, i.e.~entities mentioned only once in a text, are important to how humans understand discourse from a theoretical perspective. However previous attempts to incorporate their detection in end-to-end neural coreference resolution for English have been hampered by the lack of singleton mention spans in the OntoNotes benchmark. This paper addr

Juan Villegas-Febres

Starting from a plausible assumption about the Total Revenue concept, a system of economic agents, that simulates the exchange of goods, is studied. Following a methodology equivalent to that used in the statistical-mechanical determination of the distribution of energies in a physical system, it is shown that the price of the exchanged goods arises naturall

Shaun Bangay, Adam P. A. Cardilini, Sophie McKenzie, Maria Nicholas

Educators, developers, and other stakeholders face challenges when creating, adapting, and utilizing virtual and augmented reality (XR) experiences for teaching curriculum topics. User created reviews of these applications provide important information about their relevance and effectiveness in supporting achievement of educational outcomes. To make these re

José I. Latorre, Germán Sierra

We conjecture a relation between the local dimension $d$ of a local nearest-neighbor critical Hamiltonian in one spatial dimension and the maximum central charge, $c_{\text{max}}$, that it can yield. Specifically, we propose that $c_{\text{max}} \leq d-1$, establishing a link between the short-distance lattice realization of a model and its emerging long-dis

Lei Huang, Jiawang Nie

This paper studies the matrix Moment-SOS hierarchy for solving polynomial matrix optimization. Our first result is to show the finite convergence of this hierarchy, if the nondegeneracy condition, strict complementarity condition and second order sufficient condition hold at every minimizer, under the Archimedean property. A useful criterion for detecting th

Luca Malagutti, Andrius Buinovskij, Anej Svete, Clara Meister

For nearly three decades, language models derived from the $n$-gram assumption held the state of the art on the task. The key to their success lay in the application of various smoothing techniques that served to combat overfitting. However, when neural language models toppled $n$-gram models as the best performers, $n$-gram smoothing techniques became less

Yunqing Li, Xiaorui Liu, Binil Starly

In the current landscape, the predominant methods for identifying manufacturing capabilities from manufacturers rely heavily on keyword matching and semantic matching. However, these methods often fall short by either overlooking valuable hidden information or misinterpreting critical data. Consequently, such approaches result in an incomplete identification

Jonathan Salfity, Selma Wanna, Minkyu Choi, Mitch Pryor

Recent works in Task and Motion Planning (TAMP) show that training control policies on language-supervised robot trajectories with quality labeled data markedly improves agent task success rates. However, the scarcity of such data presents a significant hurdle to extending these methods to general use cases. To address this concern, we present an automated f

Jean Thierry-Mieg

Taken as a classification paradigm completing the standard model, a new compact form of the SU(2/1) supergroup explains many mysterious properties of the weak interactions: the maximal breaking of parity, the fractional charges of the quarks, the cancellation of the quantum field theory anomalies, and ties together the existence of the right neutrinos and of

Pantelis P. Analytis, Karthikeya Kaushik, Stefan Herzog, Bahador Bahrami

How do the ratings of critics and amateurs compare and how should they be combined? Previous research has produced mixed results about the first question, while the second remains unanswered. We have created a new, unique dataset, with wine ratings from critics and amateurs, and simulated a recommender system using the k-nearest-neighbor algorithm. We then f

Yuanze Lin, Ronald Clark, Philip Torr

We present DreamPolisher, a novel Gaussian Splatting based method with geometric guidance, tailored to learn cross-view consistency and intricate detail from textual descriptions. While recent progress on text-to-3D generation methods have been promising, prevailing methods often fail to ensure view-consistency and textural richness. This problem becomes par

Wei Luo, Bo Chen

Neural image compression has been shown to outperform traditional image codecs in terms of rate-distortion performance. However, quantization introduces errors in the compression process, which can degrade the quality of the compressed image. Existing approaches address the train-test mismatch problem incurred during quantization, the random impact of quanti

Qianhong Zhao, Gang Tao

This paper develops an adaptive state tracking control scheme for discrete-time systems, using the least-squares algorithm, as the new solution to the long-standing discrete-time adaptive state tracking control problem to which the Lyapunov method (well-developed for the continuous-time adaptive state tracking problem) is not applicable. The new adaptive sta

Xinlong Zheng, Xiaozhou Zhang, Donghao Xu

In this paper, we address a method that integrates reinforcement learning into the Monte Carlo tree search to boost online path planning under fully observable environments for automated parking tasks. Sampling-based planning methods under high-dimensional space can be computationally expensive and time-consuming. State evaluation methods are useful by lever

Kevin S. Miller, Adam J. Thorpe, Ufuk Topcu

We present an active learning algorithm for learning dynamics that leverages side information by explicitly incorporating prior domain knowledge into the sampling process. Our proposed algorithm guides the exploration toward regions that demonstrate high empirical discrepancy between the observed data and an imperfect prior model of the dynamics derived from

Nathaniel Hanson, Gary Lvov, Vedant Rautela, Samuel Hibbard

Near Infrared (NIR) spectroscopy is widely used in industrial quality control and automation to test the purity and grade of items. In this research, we propose a novel sensorized end effector and acquisition strategy to capture spectral signatures from objects and register them with a 3D point cloud. Our methodology first takes a 3D scan of an object genera

Saad Abdul Ghani, Zizhao Wang, Peter Stone, Xuesu Xiao

This paper introduces Dynamic Learning from Learned Hallucination (Dyna-LfLH), a self-supervised method for training motion planners to navigate environments with dense and dynamic obstacles. Classical planners struggle with dense, unpredictable obstacles due to limited computation, while learning-based planners face challenges in acquiring high-quality demo

Yingqi Liu

Let $G$ be a simple algebraic group of type $F_{4}$, $E_{6}$, $E_{7}$ or $E_{8}$, and let $\mathfrak{g}$ be its Lie algebra. The adjoint variety $X_{ad} \subseteq \mathbb{P} \mathfrak{g}$ is defined as the unique closed orbit of the adjoint action of $G$ on $\mathbb{P}\mathfrak{g}$. $X_{ad}$ is a Fano contact manifold covered by lines in $\mathbb{P} \mathfra

Hanwen Liu, Mihail Stoian, Alexander van Renen, Andreas Kipf

Column encoding schemes have witnessed a spark of interest with the rise of open storage formats (like Parquet) in data lakes in modern cloud deployments. This is not surprising -- as data volume increases, it becomes more and more important to reduce storage cost on block storage (such as S3) as well as reduce memory pressure in multi-tenant in-memory buffe

Gioacchino Ranucci

In the ongoing vibrant experimental quest to assess whether the numerous indications for a light sterile neutrino are only experimental fluctuations or the manifestations of a profound and real underlying effect, one aspect which has recently attracted a specific interest is the statistical treatment of the data. Especially in cases of supposed positive hint

Dmitry Melnikov

In these notes we review the calculation of Jones polynomials using a matrix representation of the braid group and Temperley-Lieb algebra. The pseudounitary representation that we consider allows constructing ``states'' from the group/algebra matrices and compute the knot invariants as matrix elements, rather than traces. In comparison with a more standard w

Zekun Li, Nadia Benabdallah, Daniel L. J. Thorek, Abhinav K. Jha

SPECT can enable the quantification of activity uptake in lesions and at-risk organs in {\alpha}-particle-emitting radiopharmaceutical therapies ({\alpha}-RPTs). But this quantification is challenged by the low photon counts, complicated isotope physics, and the image-degrading effects in {\alpha}-RPT SPECT. Thus, strategies to optimize the SPECT system and

Van Tran, Aarushi Mehrotra, Marshini Chetty, Nick Feamster

The widespread sharing of consumers personal information with third parties raises significant privacy concerns. The California Consumer Privacy Act (CCPA) mandates that online businesses offer consumers the option to opt out of the sale and sharing of personal information. Our study automatically tracks the presence of the opt-out link longitudinally across

Mihir Mulye, Matias Valdenegro-Toro

Explanation methods help understand the reasons for a model's prediction. These methods are increasingly involved in model debugging, performance optimization, and gaining insights into the workings of a model. With such critical applications of these methods, it is imperative to measure the uncertainty associated with the explanations generated by these met

Binay Kumar Singh, Niels Da Vitoria Lobo

In this paper, we propose a novel deep learning based approach for identifying co-occurring objects in conjunction with base objects in multilabel object categories. Nowadays, with the advancement in computer vision based techniques we need to know about co-occurring objects with respect to base object for various purposes. The pipeline of the proposed work

Nico Deshler, Sebastiaan Haffert, Amit Ashok

Discovering exoplanets in orbit around distant stars via direct imaging is fundamentally impeded by the combined effect of optical diffraction and photon shot noise under extreme star-planet contrast. Coronagraphs strive to increase the signal-to-noise ratio of exoplanet signatures by optically suppressing light from the host star while preserving light from

Philipp del Hougne

Physics-compliant models of RIS-parametrized channels assign a load-terminated port to each RIS element. For conventional diagonal RIS (D-RIS), each auxiliary port is terminated by its own independent and individually tunable load (i.e., independent of the other auxiliary ports). For beyond-diagonal RIS (BD-RIS), the auxiliary ports are terminated by a tunab

Kai Qi, Guanyu Hu, Wei Wu

In this paper, we develop a novel depth-based testing procedure on spatial point processes to examine the difference in made and missed field goal attempts for NBA players. Specifically, our testing procedure can statistically detect the differences between made and missed field goal attempts for NBA players. We first obtain the depths of two processes under

Lydia Nishimwe, Benoît Sagot, Rachel Bawden

NLP models have been known to perform poorly on user-generated content (UGC), mainly because it presents a lot of lexical variations and deviates from the standard texts on which most of these models were trained. In this work, we focus on the robustness of LASER, a sentence embedding model, to UGC data. We evaluate this robustness by LASER's ability to repr

Akshat Choube, Vedant Das Swain, Varun Mishra

Advances in mobile and wearable technologies have enabled the potential to passively monitor a person's mental, behavioral, and affective health. These approaches typically rely on longitudinal collection of self-reported outcomes, e.g., depression, stress, and anxiety, to train machine learning (ML) models. However, the need to continuously self-report adds

Benjamin Steenhoek, Md Mahbubur Rahman, Monoshi Kumar Roy, Mirza Sanjida Alam

In this paper, we present a challenging code reasoning task: vulnerability detection. Large Language Models (LLMs) have shown promising results in natural-language and math reasoning, but state-of-the-art (SOTA) models reported only 54.5% Balanced Accuracy in our vulnerability detection evaluation, even those models pre-trained on large amounts of source cod

Stella Bounareli, Christos Tzelepis, Vasileios Argyriou, Ioannis Patras

Video-driven neural face reenactment aims to synthesize realistic facial images that successfully preserve the identity and appearance of a source face, while transferring the target head pose and facial expressions. Existing GAN-based methods suffer from either distortions and visual artifacts or poor reconstruction quality, i.e., the background and several

Na Li, Thomas Bailleux, Zied Bouraoui, Steven Schockaert

We consider the problem of finding plausible knowledge that is missing from a given ontology, as a generalisation of the well-studied taxonomy expansion task. One line of work treats this task as a Natural Language Inference (NLI) problem, thus relying on the knowledge captured by language models to identify the missing knowledge. Another line of work uses c

James Boerkoel, Mehmet Ergezer

Despite an increasing number of successful interventions designed to broaden participation in computing research, there is still significant attrition among historically marginalized groups in the computing research pipeline. This experience report describes a first-of-its-kind Undergraduate Consortium (UC) that addresses this challenge by empowering student

Marcos Macedo, Yuan Tian, Filipe R. Cogo, Bram Adams

Code translation between programming languages (PLs) is a critical task in software engineering, facilitating the modernization of legacy systems, ensuring cross-platform compatibility, and enhancing software performance. Most existing studies instruct LLMs to perform code translation and evaluate their performance by either running the generated outputs thr

Dimitrios Gerogiannis, Foivos Paraperas Papantoniou, Rolandos Alexandros Potamias, Alexandros Lattas

The field of photorealistic 3D avatar reconstruction and generation has garnered significant attention in recent years; however, animating such avatars remains challenging. Recent advances in diffusion models have notably enhanced the capabilities of generative models in 2D animation. In this work, we directly utilize these models within the 3D domain to ach

Matias Valdenegro-Toro, Mihir Mulye

Explanations for machine learning models can be hard to interpret or be wrong. Combining an explanation method with an uncertainty estimation method produces explanation uncertainty. Evaluating explanation uncertainty is difficult. In this paper we propose sanity checks for uncertainty explanation methods, where a weight and data randomization tests are defi

Jürgen Angst, Ronan Herry, Dominique Malicet, Guillaume Poly

In this article, we revisit the question of fluctuations of linear statistics of beta ensembles in the single cut and non-critical regime for general potentials $V$ under mild regularity and growth assumptions. Our main objective is to establish sharp quantitative Central Limit Theorems (CLT) for strong distances, such as the total variation distance, which

Azmine Toushik Wasi, Taki Hasan Rafi, Raima Islam, Serbetar Karlo

Examining Drug-Drug Interactions (DDIs) is a pivotal element in the process of drug development. DDIs occur when one drug's properties are affected by the inclusion of other drugs. Detecting favorable DDIs has the potential to pave the way for creating and advancing innovative medications applicable in practical settings. However, existing DDI prediction mod

Yuchen Xia, Zhewen Xiao, Nasser Jazdi, Michael Weyrich

This research introduces a novel approach for achieving semantic interoperability in digital twins and assisting the creation of Asset Administration Shell (AAS) as digital twin model within the context of Industry 4.0. The foundational idea of our research is that the communication based on semantics and the generation of meaningful textual data are directl

Jnanajyoti Bhaumik, Naoki Masuda

The population structure often impacts evolutionary dynamics. In constant-selection evolutionary dynamics between two types, amplifiers of selection are networks that promote the fitter mutant to take over the entire population, and suppressors of selection do the opposite. It has been shown that most undirected and unweighted networks are amplifiers of sele

Stefano Falletta, Andrea Cepellotti, Anders Johansson, Chuin Wei Tan

Predicting response of materials to external stimuli is a primary objective of computational materials science. However, current methods are limited to small-scale simulations due to the unfavorable scaling of computational costs. Here, we implement an equivariant machine-learning framework where response properties stem from exact differential relationships

Mario Bossler, Ying Liang, Thorsten Schank

In 2015, Germany introduced a national minimum wage. While the literature agrees on at most limited negative effects on the overall employment level, we go into detail and analyze the impact on the working hours dimension and on the subset of minijobs. Using data from the German Structure of Earnings Survey in 2010, 2014, and 2018, we find empirical evidence

Pau Escofet, Anabel Ovide, Medina Bandic, Luise Prielinger

Quantum computing represents a paradigm shift in computation, offering the potential to solve complex problems intractable for classical computers. Although current quantum processors already consist of a few hundred of qubits, their scalability remains a significant challenge. Modular quantum computing architectures have emerged as a promising approach to s

I. A. Aleksandrov, A. Kudlis, A. I. Klochai

We investigate the phenomenon of electron-positron pair production from vacuum in the presence of a uniform time-dependent electric field of arbitrary polarization. Taking into account the interaction with the external classical background in a nonperturbative manner, we quantize the electron-positron field and derive a system of ten quantum kinetic equation

Gal Orenstein, Viktor Krapivin, Yijing Huang, Zhuquan Zhan

The nature of the "failed" ferroelectric transition in SrTiO3 has been a long-standing puzzle in condensed matter physics. A compelling explanation is the competition between ferroelectricity and an instability with a mesoscopic modulation of the polarization. These polarization density waves, which should become especially strong near the quantum critical p

Julian B. Voits, Ulrich S. Schwarz

Biological systems are remarkably susceptible to relatively small temperature changes. The most obvious example is fever, when a modest rise in body temperature of only few Kelvin has strong effects on our immune system and how it fights pathogens. Another very important example is climate change, when even smaller temperature changes lead to dramatic shifts

Shrohan Mohapatra, P. G. Kevrekidis, Stephane Lafortune

In the present work we revisit the Painlev\'e property for partial differential equations. We consider the PDE variant of the relevant algorithm on the basis of the fundamental work of Weiss, Tabor and Carnevale and explore a number of relevant examples. Subsequently, we present an implementation of the relevant algorithm in an open-source platform in Python

Jannatul Ferdous, Mingyuan Hong, Riley B. Dawkins, Fatemeh Mostafavi

The modification of the quantum properties of coherence of photons through their interaction with matter lies at the heart of the quantum theory of light. Indeed, the absorption and emission of photons by atoms can lead to different kinds of light with characteristic quantum statistical properties. As such, different types of light are typically associated w

Yu Wang, Fenglong You

Given a smooth projective variety $X$ and a smooth nef divisor $D$, we identify genus zero relative Gromov--Witten invariants of $(X,D)$ with $(n+1)$ relative markings with genus zero orbifold Gromov--Witten invariants of multi-root stacks over the $\mathbb P^1$-bundle $P:=\mathbb P(\mathcal O_X(-D)\oplus \mathcal O_X)$ with $n$ orbifold markings. This is a

Braja Gopal Patra, Lauren A. Lepow, Praneet Kasi Reddy Jagadeesh Kumar, Veer Vekaria

Background: Social support (SS) and social isolation (SI) are social determinants of health (SDOH) associated with psychiatric outcomes. In electronic health records (EHRs), individual-level SS/SI is typically documented as narrative clinical notes rather than structured coded data. Natural language processing (NLP) algorithms can automate the otherwise labo

Grant D. Phillips, M. S. Oey, Maria Cuevas, Norberto Castro

We use the kinematics of field OB stars to estimate the frequencies of runaway stars generated by the dynamical ejection scenario (DES), the binary supernova scenario (BSS), and the combined two-step mechanism. We update the proper motions for field OB and OBe stars in the Small Magellanic Cloud (SMC) using Gaia DR3. Our sample now contains 336 stars from th

João Paulo S. Melo, Mario J. Neves, Jefferson M. A. Paixão, José A. Helayël-Neto

The efforts in this contribution consist in reassessing a modified Dirac equation that incorporates a $\gamma^0 \gamma_5$-Lorentz-symmetry violating (LSV) term induced as a Loop Quantum Gravity (LQG) effect. Originally, this equation has been applied and considered as a good scenario for describing a number of investigations on the flight time of cosmic neut

Thomas R. Shultz, Jamie M. Wise, Ardavan Salehi Nobandegani

We examine whether a leading AI system GPT4 understands text as well as humans do, first using a well-established standardized test of discourse comprehension. On this test, GPT4 performs slightly, but not statistically significantly, better than humans given the very high level of human performance. Both GPT4 and humans make correct inferences about informa

Andrei Luferau, Maximilian Obst, Stephan Winnerl, Alexej Pashkin

We report THz-pump / mid-infrared probe near-field studies on Si-doped GaAs-InGaAs core-shell nanowires utilizing THz radiation from the free-electron laser FELBE. Upon THz excitation of free carriers, we observe a red shift of the plasma resonance in both amplitude and phase spectra, which we attribute to the heating up of electrons in the conduction band.

Susanne Wagner, Gerhard Kahl, Roman Melnyk, Andrij Baumketner

Among lattice configurations of densely packed hard ellipses, Monte Carlo simulations are used to identify the so-called parallel and diagonal lattices as the two favourable states. The free energies of these two states are computed for several system sizes employing the Einstein Crystal method. An accurate calculation of the free energy difference between t

Hani Abdelwahab, Amir Fernández Ouaridi, Ivan Kaygorodov

The degenerations of Poisson-type algebras are studied in the following varieties in dimension two: Leibniz--Poisson algebras, transposed Leibniz--Poisson algebras, Novikov--Poisson algebras, commutative pre-Lie algebras, anti-pre-Lie Poisson algebras and pre-Poisson algebras. For these varieties, the algebraic and geometric classifications are given. Also,

Fiona R. Kolbinger, Jiangpeng He, Jinge Ma, Fengqing Zhu

Accurate identification and localization of anatomical structures of varying size and appearance in laparoscopic imaging are necessary to leverage the potential of computer vision techniques for surgical decision support. Segmentation performance of such models is traditionally reported using metrics of overlap such as IoU. However, imbalanced and unrealisti

Shannon Wotherspoon, William Hartmann, Matthew Snover

This paper introduces a set of English translations for a 123-hour subset of the CallHome Mandarin Chinese data and the HKUST Mandarin Telephone Speech data for the task of speech translation. Paired source-language speech and target-language text is essential for training end-to-end speech translation systems and can provide substantial performance improvem

Ivan Kaygorodov, Yury Volkov

We give the full description of all degenerations of complex five dimensional noncommutative Heisenberg algebras. As a corollary, we have the full description of all degenerations of four dimensional anticommutative $3$-ary algebras.

Gian Carlo Maffettone, Mario di Bernardo, Maurizio Porfiri

This paper investigates the robustness of a novel high-dimensional continuification control method for complex multi-agent systems. We begin by formulating a partial differential equation describing the spatio-temporal density dynamics of swarming agents. A stable control action for the density is then derived and validated under nominal conditions. Subseque

Antonio Amariti, Pietro Glorioso, Davide Morgante, Andrea Zanetti

We consider the insertion of a Gukov-Witten surface defect in $\mathrm{SU}(N)$ $\mathcal{N}=4$ SYM corresponding to a probe D3-brane in the holographic dual setup. The defect gives rise to a $4d$-$2d$ coupled system encoding the entropy of the dual perturbed black hole, which can be extracted from the corresponding Superconformal Index. Elaborating on previo

Jun Ōiké, Robert Peters

Nonlinear spintronics, which combines nonlinear dynamics and spintronics, opens a new route for controlling spins and spin dynamics beyond conventional spintronics based on linear responses. Strongly correlated electron systems, which can have large nonlinear responses, are promising candidates for nonlinear spintronics. In this paper, we focus on the nonlin

Siyuan Cheng, Guanhong Tao, Yingqi Liu, Guangyu Shen

Backdoor attack poses a significant security threat to Deep Learning applications. Existing attacks are often not evasive to established backdoor detection techniques. This susceptibility primarily stems from the fact that these attacks typically leverage a universal trigger pattern or transformation function, such that the trigger can cause misclassificatio

W. Brent Lindquist, Svetlozar T. Rachev

We develop two alternate approaches to arbitrage-free, market-complete, option pricing. The first approach requires no riskless asset. We develop the general framework for this approach and illustrate it with two specific examples. The second approach does use a riskless asset. However, by ensuring equality between real-world and risk-neutral price-change pr

Stefano Schmidt, Sarah Caudill, Jolien D. E. Creighton, Ryan Magee

Precession in Binary Black Holes (BBH) is caused by the failure of the Black Hole spins to be aligned and its study can open up new perspectives in gravitational waves (GW) astronomy, providing, among other advancements, a precise measure of distance and an accurate characterization of the BBH spins. However, detecting precessing signals is a highly non-triv

V. A. S. V. Bittencourt, C. A. Potts, J. P. Davis, A. Metelmann

In cavity magnomechanical systems, magnetic excitations couple simultaneously with mechanical vibrations and microwaves, incorporating the tunability of magnetism and the long lifetimes of mechanical modes. Applications of such systems, such as thermometry and sensing, require precise measurement of the mechanical degree-of-freedom. In this paper, we propose

Yu Zhou, Andrey Polyakov, Gang Zheng

This paper investigates the robust asymptotic stabilization of a linear time-invariant (LTI) system by a static feedback with a static state quantization. It is shown that the controllable LTI system can be stabilized to zero in a finite time by means of a nonlinear feedback with a quantizer having a limited (finite) number of values (quantization seeds) eve

M. Zdunek, S. Shekhar, S. Mielcarek, A. Trzaskowska

The interaction between phonons and magnons is a widely developing topic, especially in the field of acoustic spintronics. To discuss this interaction, it is necessary to observe two different waves (acoustic and spin waves) with the same frequency and wavelength. In the Ni80Fe20/Au/Co/Au system deposited on a silicon substrate, we observe the interaction be

Craig S. Hamilton, Igor Jex

Boson sampling has emerged as an important tool to demonstrate the difference between quantum and classical computers and has attracted the interest of experimentalists and theoreticians. In this work we study Boson sampling from general, single-mode states using a scheme that can generate any such state by combining Gaussian states and photon number measure