July 2023 arXiv papers — page 46

Edward Fish, Umberto Michieli, Mete Ozay

Recent advancement in Automatic Speech Recognition (ASR) has produced large AI models, which become impractical for deployment in mobile devices. Model quantization is effective to produce compressed general-purpose models, however such models may only be deployed to a restricted sub-domain of interest. We show that ASR models can be personalized during quan

Matteo Carducci

The key point to prove the optimal $C^{1,\frac12}$ regularity of the thin obstacle problem is that the frequency at a point of the free boundary $x_0\in\Gamma(u)$, say $N^{x_0}(0^+,u)$, satisfies the lower bound $N^{x_0}(0^+,u)\ge\frac32$. In this paper we show an alternative method to prove this estimate, using an epiperimetric inequality for negative energ

Aleksey S. Gvozdarev

The presented research proposes the $\alpha$-modification of the Beaulieu-Xie shadowed fading channel for wireless communications. For the assumed model the closed-form analytical description of the basic statistical characteristics is carried out (i.e., probability density function, cumulative distribution function, and their asymptotics). The derived stati

Qing-Hua Zhang, Liang-Tian He, Yi-Lun Wang, Liang-Jian Deng

Inspired by the fact that the matrix formulated by nonlocal similar patches in a natural image is of low rank, the rank approximation issue have been extensively investigated over the past decades, among which weighted nuclear norm minimization (WNNM) and weighted Schatten $p$-norm minimization (WSNM) are two prevailing methods have shown great superiority i

Nathalie Aubrun, Nicolas Bitar

In this article we study domino snake problems on finitely generated groups. We provide general properties of these problems and introduce new tools for their study. The first is the use of symbolic dynamics to understand the set of all possible snakes. Using this approach we solve many variations of the infinite snake problem including the geodesic snake pr

Joshua Cudby, Sergii Strelchuk

Magic states, pivotal for universal quantum computation via classically simulable Clifford gates, often undergo decomposition into resourceless stabilizer states, facilitating simulation through classical means. This approach yields three operationally significant metrics: stabilizer rank, fidelity, and extent. We extend these simulation methods to encompass

Gauthier Philippe, Mathieu Moalic, Jarosław W. Kłos

We demonstrate that the spin wave Cherenkov effect can be used to design the unidirectional spin wave emitter with tunable frequency and switchable direction of emission. In our numerical studies, we propose to use a pair of traveling profiles of the magnetic field which generate the spin waves, for sufficiently large velocity of their motion. In the conside

Jianjun Liu, Duihui Xiang

Rational normal form is a powerful tool to deal with Hamiltonian partial differential equations without external parameters. In this paper, we build rational normal form with exact global control of small divisors. As an application to nonlinear Schr\"{o}dinger equations in Gevrey spaces, we prove sub-exponentially long time stability results for generic sma

Céline Lichtensteiger, Chia-Ping Su, Iaroslav Gaponenko, Marios Hadjimichael

We investigate nanoscale domain engineering via epitaxial coupling in a set of SrRuO$_3$/PbTiO$_3$/SrRuO$_3$ heterostructures epitaxially grown on (110)$_o$-oriented DyScO$_3$ substrates. The SrRuO$_3$ layer thickness is kept at 55 unit cells, whereas the PbTiO$_3$ layer is grown to thicknesses of 23, 45 and 90 unit cells. Through a combination of atomic for

Chengwei Xia, Junjie Zhang, Eric C. Kerrigan, Georgios Rigas

Active flow control for drag reduction with reinforcement learning (RL) is performed in the wake of a 2D square bluff body at laminar regimes with vortex shedding. Controllers parameterised by neural networks are trained to drive two blowing and suction jets that manipulate the unsteady flow. RL with full observability (sensors in the wake) successfully disc

S. Paischer, D. Eilmsteiner, I. Maznichenko, N. Buczek

Understanding the profound impact of correlation effects and crystal imperfections is essential for an accurate description of solids. Here we study the role of correlation, disorder, and multi-magnon processes in THz magnons. Our findings reveal that a significant part of the electron self-energy, which goes beyond the adiabatic local spin density approxima

Loïc Buckwell, Olivier Gilles, Daniel Gracia Pérez, Nikolai Kosmatov

RISC-V is a recently developed open instruction set architecture gaining a lot of attention. To achieve a lasting security on these systems and design efficient countermeasures, a better understanding of vulnerabilities to novel and potential future attacks is mandatory. This paper demonstrates that RISC-V is sensible to Jump-Oriented Programming, a class of

E. N. Popov, A. A. Gaidash, A. V. Kozubov, S. P. Voskoboynikov

We theoretically describe the phenomenon of non-adiabatic spin dynamics, which occurs in a gas cell filled by alkali vapor in presence of a strong alternating magnetic field and pump light. Steep increase of the spin polarization occurs if frequency of the magnetic field is equal to the certain value. Although, the observable effect relies on the periodic fi

Zeev Nutov, Dawod Kahba

In the $Activation$ $k$ $Disjoint$ $st$-$Paths$ ($Activation$ $k$-$DP$) problem we are given a graph $G=(V,E)$ with activation costs $\{c_{uv}^u,c_{uv}^v\}$ for every edge $uv \in E$, a source-sink pair $s,t \in V$, and an integer $k$. The goal is to compute an edge set $F \subseteq E$ of $k$ internally node disjoint $st$-paths of minimum activation cost $\d

Yilun Wang, Shilong Liao, Nicola Giacobbo, Aleksandra Olejak

For binary systems with an unseen primary and a luminous secondary, the astrometric wobble of the secondary could be used to study the primary. With Gaia, it is possible to measure the mass of the black hole or neutron star with a luminous companion (hereafter BH/NS-LC). Our aim is to provide a method for predicting Gaia's ability in measuring the mass of BH

Dae-Yeol Kim, Eunsu Goh, KwangKee Lee, JongEui Chae

rPPG (Remote photoplethysmography) is a technology that measures and analyzes BVP (Blood Volume Pulse) by using the light absorption characteristics of hemoglobin captured through a camera. Analyzing the measured BVP can derive various physiological signals such as heart rate, stress level, and blood pressure, which can be applied to various applications suc

Waqas Aman, Flavio Giorgi, Giulio Attenni, Saif Al-Kuwari

The colossal evolution of wireless communication technologies over the past few years has driven increased interest in its integration in a variety of less-explored environments, such as the underwater medium. In this magazine paper, we present a comprehensive discussion on a novel concept of routing protocol known as cross-media routing, incorporating the m

Jaeyoul Ko, Jaewoo Kim, Jimin Choi, Jaemyung Ahn

A conceptual design of a launch vehicle involves the optimization of trajectory and stages considering its launch operations. This process encompasses various disciplines, such as structural design, aerodynamics, propulsion systems, flight control, and stage sizing. Traditional approaches used for the conceptual design of a launch vehicle conduct the stage a

De-Chao Song, Jun Tian, Y. Li, M. D. Ding

The heating mechanisms of solar white-light flares remain unclear. We present an X1.0 white-light flare on 2022 October 2 (SOL2022-10-02T20:25) observed by the Chinese \ha\ Solar Explorer (CHASE) that provides two-dimensional spectra in the visible light for the full solar disk with a seeing-free condition. The flare shows a prominent enhancement of $\sim$40

Roberto Prado-Rivera, Daniela Radu, Vincent H. Crespi, Yuanxi Wang

Despite the rapid pace of computationally and experimentally discovering new two-dimensional layered materials, a general criteria for a given compound to prefer a layered structure over a non-layered one remains unclear. Articulating such criteria would allow one to identify materials at the verge of an inter-dimensional structural phase transition between

Shuzhi Gong, Richard O. Sinnott, Jianzhong Qi, Cecile Paris

The popularity of online social networks has enabled rapid dissemination of information. People now can share and consume information much more rapidly than ever before. However, low-quality and/or accidentally/deliberately fake information can also spread rapidly. This can lead to considerable and negative impacts on society. Identifying, labelling and debu

Luis A. Razo-López, Geoffroy J. Aubry, Felipe A. Pinheiro, Fabrice Mortessagne

We carry out dynamical microwave transport experiments in aperiodic Vogel spiral arrays of cylinders with high dielectric permittivity. We experimentally disclose the electromagnetic modal structure of these structures in real space showing that they simultaneously support long-lived modes with Gaussian, exponential, and power law spatial decay. This unique

Wenjing Chen, Zexi Wang

In this paper, we study the following fractional Choquard system \begin{align*} \begin{split} \left\{ \begin{array}{ll} (-\Delta)^{1/2}u=\lambda_1 u+(I_\mu*F(u,v))F_u (u,v), \quad\mbox{in}\ \ \mathbb{R}, (-\Delta)^{1/2}v=\lambda_2 v+(I_\mu*F(u,v)) F_v(u,v), \quad\mbox{in}\ \ \mathbb{R}, \displaystyle\int_{\mathbb{R}}|u|^2\mathrm{d}x=a^2,\quad \displaystyle\i

Inyong Koo, Inyoung Lee, Se-Ho Kim, Hee-Seon Kim

One of the main challenges in LiDAR-based 3D object detection is that the sensors often fail to capture the complete spatial information about the objects due to long distance and occlusion. Two-stage detectors with point cloud completion approaches tackle this problem by adding more points to the regions of interest (RoIs) with a pre-trained network. Howeve

Maurizio Titz, Sebastian Pütz, Dirk Witthaut

The transition to a sustainable energy supply challenges the operation of electric power systems in manifold ways. Transmission grid loads increase as wind and solar power are often installed far away from the consumers. In extreme cases, system operators must intervene via countertrading or redispatch to ensure grid stability. In this article, we provide a

Zhengyi Zhou

We show that a contact $(+1)$-surgery along a Legendrian sphere in a flexibly fillable contact manifold ($c_1=0$ if not subcritical) yields a contact manifold that is algebraically overtwisted if the Legendrian's homology class is not annihilated in the filling. Our construction can also be implemented in more general contact manifolds yielding algebraically

Qi Su, Na Wang, Jiawen Xie, Yinan Chen

The automatic lung lobe segmentation algorithm is of great significance for the diagnosis and treatment of lung diseases, however, which has great challenges due to the incompleteness of pulmonary fissures in lung CT images and the large variability of pathological features. Therefore, we propose a new automatic lung lobe segmentation framework, in which we

Pavel Shumyatsky, Matteo Vannacci

Let cp(R) be the probability that two random elements of a finite ring R commute and zp(R) the probability that the product of two random elements in R is zero. We show that if cp(R)=e, then there exists a Lie-ideal D in the Lie-ring (R,[.,.]) with e-bounded index and with [D,D] of e-bounded order. If zp(R)=e, then there exists an ideal D in R with e-bounded

F. Zaidi, M. Sajjad Athar, S. K. Singh

We have studied the tau-lepton polarization in the charged current $\nu_\tau/\bar\nu_\tau$ induced deep inelastic scattering (DIS) from the free nucleon as well as off the nuclear targets that are being used in ongoing and proposed experiments such as IceCube, DUNE, etc. For the free nucleon target, the differential scattering cross sections are obtained by

Xiaoshui Lin, Ming Gong

It has been widely believed that almost all states in one-dimensional (1d) disordered systems with short-range hopping and uncorrelated random potential are localized. Here, we consider the fate of these localized states by coupling between a disordered chain (with localized states) and a free chain (with extended states), showing that states in the overlapp

Tao Wang, Zhongzheng Huang, Jiawei Wu, Yuanzheng Cai

Medical image segmentation has made significant progress when a large amount of labeled data are available. However, annotating medical image segmentation datasets is expensive due to the requirement of professional skills. Additionally, classes are often unevenly distributed in medical images, which severely affects the classification performance on minorit

Zhan-Fang Chen, Chuan Yue, Wei Jiang, Ming-Yang Cui

The Dark Matter Particle Explorer (DAMPE) is a satellite-borne detector designed to measure high energy cosmic-rays and $\gamma$-rays. As a key sub-detector of DAMPE, the Bismuth Germanium Oxide (BGO) imaging calorimeter is utilized to measure the particle energy with a high resolution. The nonlinear fluorescence response of BGO for large ionization energy d

Frank Kleibergen, Lingwei Kong

We propose identification robust statistics for testing hypotheses on the risk premia in dynamic affine term structure models. We do so using the moment equation specification proposed for these models in Adrian et al. (2013). We extend the subset (factor) Anderson-Rubin test from Guggenberger et al. (2012) to models with multiple dynamic factors and time-va

Emma Leschiera, Gheed Al-Hity, Melanie S. Flint, Chandrasekhar Venkataraman

In recent in vitro experiments on co-culture between breast tumour spheroids and activated immune cells, it was observed that the introduction of the stress hormone cortisol resulted in a decreased immune cell infiltration into the spheroids. Moreover, the presence of cortisol deregulated the normal levels of the pro- and anti-inflammatory cytokines IFN-{\ga

Jingxuan Wei, Cheng Tan, Zhangyang Gao, Linzhuang Sun

Multimodal reasoning is a critical component in the pursuit of artificial intelligence systems that exhibit human-like intelligence, especially when tackling complex tasks. While the chain-of-thought (CoT) technique has gained considerable attention, the existing ScienceQA dataset, which focuses on multimodal scientific questions and explanations from elemen

Yonghe Zhao, Qiang Huang, Haolong Zeng, Yun Pen

Counterfactual inference for continuous rather than binary treatment variables is more common in real-world causal inference tasks. While there are already some sample reweighting methods based on Marginal Structural Model for eliminating the confounding bias, they generally focus on removing the treatment's linear dependence on confounders and rely on the a

Hidetoshi Omiya, Kimihiro Nomura, Jiro Soda

Pulsar timing arrays (PTAs) provide a way to detect gravitational waves (GWs) at nanohertz frequencies. To ensure the detection of GWs, observational data must exhibit the Hellings-Downs angular correlation. It is also known that PTAs can probe ultralight dark matter. In this paper, we consider possible contamination of the Hellings-Downs angular correlation

Hai-Ming Zhang, Yi-Yun Huang, Ruo-Yu Liu, Xiang-Yu Wang

Recently, LHAASO reported the detection of brightest-of-all-time GRB 221009A, revealing the early onset of a TeV afterglow. However, there is no evidence of afterglow emission at such early time at other wavelengths. Here we report the discovery of a hidden afterglow component during the prompt emission phase with Fermi Gamma-Ray Burst Monitor (GBM) observat

Chengming Hu, Yeqian Du, Rui Wang, Hao Chen

The Fourier transform, an explicit decomposition method for visual signals, has been employed to explain the out-of-distribution generalization behaviors of Deep Neural Networks (DNNs). Previous studies indicate that the amplitude spectrum is susceptible to the disturbance caused by distribution shifts, whereas the phase spectrum preserves highly-structured

Matthias Johann Steiner

Let $\mathbb{F}_q$ be a finite field of characteristic $p$. In this paper we prove that the $c$-Boomerang Uniformity, $c \neq 0$, for all permutation monomials $x^d$, where $d > 1$ and $p \nmid d$, is bounded by $d^2$. Further, we utilize this bound to estimate the $c$-boomerang uniformity of a large class of Generalized Triangular Dynamical Systems, a polyn

Pedro Cabalar, Martín Diéguez, François Laferrière, Torsten Schaub

Extensions of Answer Set Programming with language constructs from temporal logics, such as temporal equilibrium logic over finite traces (TELf), provide an expressive computational framework for modeling dynamic applications. In this paper, we study the so-called past-present syntactic subclass, which consists of a set of logic programming rules whose body

Josh Stein, Maxime Di Folco, Julia Schnabel

Short axis cardiac MRI segmentation is a well-researched topic, with excellent results achieved by state-of-the-art models in a supervised setting. However, annotating MRI volumes is time-consuming and expensive. Many different approaches (e.g. transfer learning, data augmentation, few-shot learning, etc.) have emerged in an effort to use fewer annotated dat

Maxime Di Folco, Cosmin Bercea, Julia A. Schnabel

Deep generative models have emerged as influential instruments for data generation and manipulation. Enhancing the controllability of these models by selectively modifying data attributes has been a recent focus. Variational Autoencoders (VAEs) have shown promise in capturing hidden attributes but often produce blurry reconstructions. Controlling these attri

Sören Becker, Michal Klein, Alexander Neitz, Giambattista Parascandolo

We develop a transformer-based sequence-to-sequence model that recovers scalar ordinary differential equations (ODEs) in symbolic form from irregularly sampled and noisy observations of a single solution trajectory. We demonstrate in extensive empirical evaluations that our model performs better or on par with existing methods in terms of accurate recovery a

Kaining Ying, Qing Zhong, Weian Mao, Zhenhua Wang

The discrimination of instance embeddings plays a vital role in associating instances across time for online video instance segmentation (VIS). Instance embedding learning is directly supervised by the contrastive loss computed upon the contrastive items (CIs), which are sets of anchor/positive/negative embeddings. Recent online VIS methods leverage CIs sour

Bastien Batardière, Joon Kwon

For finite-sum optimization, variance-reduced gradient methods (VR) compute at each iteration the gradient of a single function (or of a mini-batch), and yet achieve faster convergence than SGD thanks to a carefully crafted lower-variance stochastic gradient estimator that reuses past gradients. Another important line of research of the past decade in contin

Muhammad Taufiqur Rohman, Triyanta, Agus Suroso

We are investigating the localization of matter that interacts nonminimally with gravity within thick braneworld models generated by a scalar bulk. Our review focuses on two models of scalar thick branes. The natural mechanism is used to analyze the localization of the fields. Without losing the point of field localization, we examine matter field localizati

Huixin Zhong, Eamonn O'Neill, Janina A. Hoffmann

Article 5 of the European Union's Artificial Intelligence Act is intended to regulate AI use to prevent potentially harmful consequences. Nevertheless, applying this legislation practically is likely to be challenging because of ambiguously used terminologies and because it fails to specify which manipulation techniques may be invoked by AI, potentially lead

Sjoerd Dirksen, Johannes Maly

We consider covariance estimation of any subgaussian distribution from finitely many i.i.d. samples that are quantized to one bit of information per entry. Recent work has shown that a reliable estimator can be constructed if uniformly distributed dithers on $[-\lambda,\lambda]$ are used in the one-bit quantizer. This estimator enjoys near-minimax optimal, n

Dehua Zheng, Wenhui Dong, Hailin Hu, Xinghao Chen

DETR-like models have significantly boosted the performance of detectors and even outperformed classical convolutional models. However, all tokens are treated equally without discrimination brings a redundant computational burden in the traditional encoder structure. The recent sparsification strategies exploit a subset of informative tokens to reduce attent

Rodrigo López Pouso

We introduce a small change in the definition of the Fourier series so that we can guarantee the coincidence with the given function at the endpoints of the interval even if the function does not assume the same value at the endpoints. This definition of the Fourier series also wipes out the Gibbs phenomenom at the endpoints of the interval and proves useful

Samar Layek, Mads Fonager Hansen, Jean-Baptiste Vaney, Pierre Toulemonde

The lattice dynamics of the superconducting materials LaFeSiH and LaFeSiO as well as their intermetallic precursor LaFeSi are investigated by polarized Raman spectroscopy and first-principles calculations, together with X-ray and advanced electron diffraction techniques for their structural analysis. We find that the Fe-dominated Raman-active modes reflect t

Jordan Samhi, Tegawendé F. Bissyandé, Jacques Klein

Android app developers extensively employ code reuse, integrating many third-party libraries into their apps. While such integration is practical for developers, it can be challenging for static analyzers to achieve scalability and precision when libraries account for a large part of the code. As a direct consequence, it is common practice in the literature

Chiara Guidolin, Christopher Heim, Nathan B P Adams, Philipp Baaske

Introduced more than fifty years ago, dynamic light scattering is routinely used to determine the size distribution of colloidal suspensions, as well as of macromolecules in solution, such as proteins, nucleic acids, and their complexes. More recently, differential dynamic microscopy has been proposed as a way to perform dynamic light scattering experiments

Akanksha Dixit, Yashashwee Chakrabarty, Smruti R. Sarangi

High-frequency displays are gaining immense popularity because of their increasing use in video games and virtual reality applications. However, the issue is that the underlying GPUs cannot continuously generate frames at this high rate -- this results in a less smooth and responsive experience. Furthermore, if the frame rate is not synchronized with the ref

Shubham Singh, Ryan P. Russell, Patrick M. Wensing

Differential Dynamic Programming (DDP) is a popular technique used to generate motion for dynamic-legged robots in the recent past. However, in most cases, only the first-order partial derivatives of the underlying dynamics are used, resulting in the iLQR approach. Neglecting the second-order terms often slows down the convergence rate compared to full DDP.

Ioannis Caragiannis, Kristoffer Arnsfelt Hansen, Nidhi Rathi

We study the classic problem of dividing a collection of indivisible resources in a fair and efficient manner among a set of agents having varied preferences. Pareto optimality is a standard notion of economic efficiency, which states that it should be impossible to find an allocation that improves some agent's utility without reducing any other's. On the ot

Arup Chattopadhyay, Saikat Giri, Chandan Pradhan

In recent years, higher-order trace formulas of operator functions have attracted considerable attention to a large part of the perturbation theory community. In this direction, we prove estimates for traces of higher-order derivatives of multivariable operator functions with associated scalar functions arising from multivariable analytic function space and,

Clara Grazian

Antimicrobial resistance is becoming a major threat to public health throughout the world. Researchers are attempting to contrast it by developing both new antibiotics and patient-specific treatments. In the second case, whole-genome sequencing has had a huge impact in two ways: first, it is becoming cheaper and faster to perform whole-genome sequencing, and

Ildikó Schlotter

We consider the following problem that we call the Shortest Two Disjoint Paths problem: given an undirected graph $G=(V,E)$ with edge weights $w:E \rightarrow \mathbb{R}$, two terminals $s$ and $t$ in $G$, find two internally vertex-disjoint paths between $s$ and $t$ with minimum total weight. As shown recently by Schlotter and Seb\H{o} (2022), this problem

Patrik Hammersborg, Inga Strümke

Neural network models are widely used in a variety of domains, often as black-box solutions, since they are not directly interpretable for humans. The field of explainable artificial intelligence aims at developing explanation methods to address this challenge, and several approaches have been developed over the recent years, including methods for investigat

Kun Xu, Mei Huang

Two critical end points (CEPs) of the chiral phase transition and the nuclear liquid-gas phase transition show up at finite baryon chemical potential. The kurtosis $\kappa\sigma^2$ of baryon number fluctuation on the $T-\mu_B$ plane is positive on the first-order side and negative on the crossover side along the phase boundary. The freeze-out line extracted

M. Karthick Selvan, S. Balakrishnan

We discuss the characteristics of special perfect entanglers and construct single parameter two-qubit circuits which are locally equivalent to special perfect entanglers. We present the results obtained from the implementation of one of the circuits using cross-resonance interaction and discuss their applications. First, we show that the ability of two-qubit

Cai-Yun Zhao, Hui-Li Han, Ting-Yun Shi

We investigate the effects of $p$-wave interactions on Efimov trimers in systems comprising two identical heavy fermions and a light particle, with mass ratios larger than $13.6$. Our focus lies on the borromean regime where the ground-state trimer exists in the absence of dimers. Using pair-wise Lennard-Jones potentials and concentrating on the $L^{\pi} = 1

Javier Aguilar, Riccardo Gatto

This article analyzes and compares two general techniques of rare event simulation for generating paths of Markov processes over fixed time horizons: exponential tilting and stochastic bridge. These two methods allow to accurately compute the probability that a Markov process ends within a rare region, which is unlikely to be attained. Exponential tilting is

Yue Liu, Thanh Le-Cong, Ratnadira Widyasari, Chakkrit Tantithamthavorn

We systematically study the quality of 4,066 ChatGPT-generated code implemented in two popular programming languages, i.e., Java and Python, for 2,033 programming tasks. The goal of this work is three folds. First, we analyze the correctness of ChatGPT on code generation tasks and uncover the factors that influence its effectiveness, including task difficult

Pu Yuan, Hao Liu, Junjie Tan, Dajie Jiang

This paper investigates a novel underlaid sensing pilot signal design for integrated sensing and communications (ISAC) in an OFDM-based communication system. The proposed two-dimensional (2D) pilot signal is first generated on the delay-Doppler (DD) plane and then converted to the time-frequency (TF) plane for multiplexing with the OFDM data symbols. The sen

Guilong Peng, Senshan Sun, Zhenwei Xu, Juxin Du

Machine learning's application in solar-thermal desalination is limited by data shortage and inconsistent analysis. This study develops an optimized dataset collection and analysis process for the representative solar still. By ultra-hydrophilic treatment on the condensation cover, the dataset collection process reduces the collection time by 83.3%. Over 1,0

Lidija Stanovnik, Miha Moškon, Miha Mraz

Non-overlapping codes are block codes that have arisen in diverse contexts of computer science and biology. Applications typically require finding non-overlapping codes with large cardinalities, but the maximum size of non-overlapping codes has been determined only for cases where the codeword length divides the size of the alphabet, and for codes with codew

Hugo Brehier, Arnaud Breloy, Chengfang Ren, Guillaume Ginolhac

The detection of multiple targets in an enclosed scene, from its outside, is a challenging topic of research addressed by Through-the-Wall Radar Imaging (TWRI). Traditionally, TWRI methods operate in two steps: first the removal of wall clutter then followed by the recovery of targets positions. Recent approaches manage in parallel the processing of the wall

Yiqing Wang, Zihan Li, Jieru Mei, Zihao Wei

Recent advancements in large-scale Vision Transformers have made significant strides in improving pre-trained models for medical image segmentation. However, these methods face a notable challenge in acquiring a substantial amount of pre-training data, particularly within the medical field. To address this limitation, we present Masked Multi-view with Swin T

Christian Bayer, Simon Breneis, Terry Lyons

We present an adaptive algorithm for effectively solving rough differential equations (RDEs) using the log-ODE method. The algorithm is based on an error representation formula that accurately describes the contribution of local errors to the global error. By incorporating a cost model, our algorithm efficiently determines whether to refine the time grid or

Chamkor Singh, Abhishek Chaudhuri

We numerically study the effect of an active turbulent environment on a passive deformable droplet. The system is simulated using coupled hydrodynamic and nematodynamic equations for nematic liquid crystals with an active stress which is non-zero outside the droplet, and is zero inside. The droplet undergoes deformation fluctuations and its movement shows pe

Alireza Ahmadi, Michael Halstead, Chris McCool

Cultivation and weeding are two of the primary tasks performed by farmers today. A recent challenge for weeding is the desire to reduce herbicide and pesticide treatments while maintaining crop quality and quantity. In this paper, we introduce BonnBot-I a precise weed management platform which can also performs field monitoring. Driven by crop monitoring app

Danqing Wang, Ankun Yang

Miniaturized and rationally assembled nanostructures exhibit extraordinarily distinct physical properties beyond their individual units. This review will focus on structured small-scale optical cavities that show unique electromagnetic near fields and collective optical coupling. By harnessing different material systems and structural designs, various light-

Guoxiang Grayson Tong, Carlos A. Sing Long, Daniele E. Schiavazzi

Use of generative models and deep learning for physics-based systems is currently dominated by the task of emulation. However, the remarkable flexibility offered by data-driven architectures would suggest to extend this representation to other aspects of system synthesis including model inversion and identifiability. We introduce inVAErt (pronounced "invert"

Lorenzo Speri, Michael L. Katz, Alvin J. K. Chua, Scott A. Hughes

Extreme Mass Ratio Inspirals (EMRIs) are one of the key sources for future space-based gravitational wave interferometers. Measurements of EMRI gravitational waves are expected to determine the characteristics of their sources with sub-percent precision. However, their waveform generation is challenging due to the long duration of the signal and the high har

Katy L. Proctor, Claudia del P. Lagos, Aaron D. Ludlow, Aaron S. G. Robotham

We perform a structural decomposition of galaxies identified in three cosmological hydrodynamical simulations by applying Gaussian Mixture Models (GMMs) to the kinematics of their stellar particles. We study the resulting disc, bulge, and intra-halo light (IHL) components of galaxies whose host dark matter haloes have virial masses in the range $M_{200}=10^{

Hironobu Sakagawa

We consider the Gaussian interface model in the presence of random external fields, that is the finite volume (random) Gibbs measure on $\mathbb{R}^{\Lambda_N}$, $\Lambda_N=[-N, N]^d\cap \mathbb{Z}^d$ with Hamiltonian $H_N(\phi)= \frac{1}{4d}\sum\limits_{x\sim y}(\phi(x)-\phi(y))^2-\sum\limits_{x\in \Lambda_N}\eta(x)\phi(x)$ and $0$-boundary conditions. $\{\

Lin Chen, Jiayi Lian, Yuchen Mao, Guochuan Zhang

We investigate pseudopolynomial-time algorithms for Bounded Knapsack and Bounded Subset Sum. Recent years have seen a growing interest in settling their fine-grained complexity with respect to various parameters. For Bounded Knapsack, the number of items $n$ and the maximum item weight $w_{\max}$ are two of the most natural parameters that have been studied

Dmitriy Kunisky

Recently, Eldan, Koehler, and Zeitouni (2020) showed that Glauber dynamics mixes rapidly for general Ising models so long as the difference between the largest and smallest eigenvalues of the coupling matrix is at most $1 - \epsilon$ for any fixed $\epsilon > 0$. We give evidence that Glauber dynamics is in fact optimal for this "general-purpose sampling" ta

Yixin Chen, Yan Wang

Deep learning techniques for medical image analysis usually suffer from the domain shift between source and target data. Most existing works focus on unsupervised domain adaptation (UDA). However, in practical applications, privacy issues are much more severe. For example, the data of different hospitals have domain shifts due to equipment problems, and data

Tommaso Tedeschi, Vincenzo Eduardo Padulano, Daniele Spiga, Diego Ciangottini

The challenges expected for the next era of the Large Hadron Collider (LHC), both in terms of storage and computing resources, provide LHC experiments with a strong motivation for evaluating ways of rethinking their computing models at many levels. Great efforts have been put into optimizing the computing resource utilization for the data analysis, which lea

Harpreet Kaur, Thomas Franosch, Michele Caraglio

Developing behavioral policies designed to efficiently solve target-search problems is a crucial issue both in nature and in the nanotechnology of the 21st century. Here, we characterize the target-search strategies of simple microswimmers in a homogeneous environment containing sparse targets of unknown positions. The microswimmers are capable of controllin

Pujin Cheng, Li Lin, Junyan Lyu, Yijin Huang

Contrastive learning based vision-language joint pre-training has emerged as a successful representation learning strategy. In this paper, we present a prototype representation learning framework incorporating both global and local alignment between medical images and reports. In contrast to standard global multi-modality alignment methods, we employ a local

Junghyun Koo, Yunkee Chae, Chang-Bin Jeon, Kyogu Lee

Music source separation (MSS) faces challenges due to the limited availability of correctly-labeled individual instrument tracks. With the push to acquire larger datasets to improve MSS performance, the inevitability of encountering mislabeled individual instrument tracks becomes a significant challenge to address. This paper introduces an automated techniqu

Yi Sun, Hong Shen, Wei Xu, Nan Hu

In this paper, we investigate the design of statistically robust detectors for multi-input multi-output (MIMO) systems subject to imperfect channel state information (CSI). A robust maximum likelihood (ML) detection problem is formulated by taking into consideration the CSI uncertainties caused by both the channel estimation error and the channel variation.

Jinjing Zhu, Yunhao Luo, Xu Zheng, Hao Wang

In this paper, we strive to answer the question "how to collaboratively learn convolutional neural network (CNN)-based and vision transformer (ViT)-based models by selecting and exchanging the reliable knowledge between them for semantic segmentation?" Accordingly, we propose an online knowledge distillation (KD) framework that can simultaneously learn compa

Yuanzhi Liang, Linchao Zhu, Yi Yang

Recent advancements in natural language and Large Language Models (LLMs) have enabled AI agents to simulate human-like interactions within virtual worlds. However, these interactions still face limitations in complexity and flexibility, particularly in scenarios involving multiple characters and novel objects. Pre-defining all interactable objects in the age

Chiara Ricca, Elizabeth Skoropata, Marta D. Rossell, Rolf Erni

Recently a highly ordered Moir\'e dislocation lattice was identified at the interface between a \ce{SrTiO3} (STO) thin film and the (LaAlO$_3$)$_{0.3}$(Sr$_2$TaAlO$_6$)$_{0.7}$ (LSAT) substrate. A fundamental understanding of the local ionic and electronic structure around the dislocation cores is crucial to further engineer the properties of these complex m

Beiya Dai, Xing li, Qunyi Xie, Yulin Li

Document dewarping from a distorted camera-captured image is of great value for OCR and document understanding. The document boundary plays an important role which is more evident than the inner region in document dewarping. Current learning-based methods mainly focus on complete boundary cases, leading to poor document correction performance of documents wi

Jean-Lou Pierson

Motivated by the dynamics of microbubbles in dissolved gas flotation processes, we consider theoretically the approach between two shear-free spherical bubbles with time-dependent radii. We make use of the lubrication assumption to obtain the thin film flow between the bubbles. Our analysis underscores that for the shear-free condition and spherical shape as

Yunhee Shim, Shagun Jhaver

As popular demand for digital information increases, public libraries are increasingly turning to commercial digital content distribution services to save curation time and costs. These services let libraries subscribe to pre-configured digital content packages that become instantly available wholesale to their patrons. However, these packages often contain

Kamaljeet Singh, Jayanta Dey, Raghunath Sahoo

The effect of the temperature evolution of QGP on its thermal conductivity and elliptic flow is investigated here in the presence of a time-varying magnetic field. Thermal conductivity plays a vital role in the cooling rate of the medium or its temperature evolution. The magnetic field produced during the early stages of (non-central) heavy-ion collisions de

Tomoyuki Ehira, Daisuke Kotani, Hiroki Shirokura, Hirofumi Ichihara

Kubernetes is a container management system that has many automated functionalities. Those functionalities are managed by configuring objects and resources in the control plane. Since most objects change their state depending on other objects' states, a change propagates to other objects in a chain. As cluster availability is influenced by the time required

Vasileios Niaouris, Samuel H. D'Ambrosia, Christian Zimmermann, Xingyi Wang

Neutral shallow donors in zinc oxide (ZnO) are spin qubits with optical access via the donor-bound exciton. This spin-photon interface enables applications in quantum networking, memories and transduction. Essential optical parameters which impact the spin-photon interface include radiative lifetime, optical inhomogeneous and homogeneous linewidth and optica

Han Miao

In this talk, recent measurements of charmonium decays of BESIII are presented. Using 448 million $\psi(3686)$ events collected with the BESIII detector, the branching fractions of the decays $\chi_{cJ} \to \phi \phi (J=0,1,2)$ have been measured most precisely, and the polarization parameters of $\chi_{cJ} \to \phi \phi$ have been determined for the first t

Xiaohao Yang, He Zhao, Dinh Phung, Lan Du

Topic models have evolved from conventional Bayesian probabilistic models to recent Neural Topic Models (NTMs). Although NTMs have shown promising performance when trained and tested on a specific corpus, their generalisation ability across corpora has yet to be studied. In practice, we often expect that an NTM trained on a source corpus can still produce qu

Lev A. Smirnov, Arkady Pikovsky

We consider a population of globally coupled oscillators in which phase shifts in the coupling are random. We show that in the maximally disordered case, where the pairwise shifts are i.i.d. random variables, the dynamics of a large population reduces to one without randomness in the shifts but with an effective coupling function, which is a convolution of t

Dmitry Metelev, Aleksandr Beznosikov, Alexander Rogozin, Alexander Gasnikov

We consider a decentralized convex unconstrained optimization problem, where the cost function can be decomposed into a sum of strongly convex and smooth functions, associated with individual agents, interacting over a static or time-varying network. Our main concern is the convergence rate of first-order optimization algorithms as a function of the network'