May 2023 arXiv papers — page 21

Antonio Brajdić

Resonant converters are often being used for high power and high voltage applications to achieve high efficiency, high power density and low EMI. In this paper, we will use a resonant converter for a completely different application. We will take advantage of the Zero Voltage Switching (ZVS) and operating in the vicinity of the series resonance to design a l

Luca Giuliani, Eleonora Misino, Michele Lombardi

We make two contributions in the field of AI fairness over continuous protected attributes. First, we show that the Hirschfeld-Gebelein-Renyi (HGR) indicator (the only one currently available for such a case) is valuable but subject to a few crucial limitations regarding semantics, interpretability, and robustness. Second, we introduce a family of indicators

Tamir Hemo, Timo Richarz, Jakob Scholbach

We present a uniform theory of constructible sheaves on arbitrary schemes with coefficients in topological or even condensed rings. This is accomplished by defining lisse sheaves to be the dualizable objects in the derived infinity-category of pro\'etale sheaves, while constructible sheaves are those that are lisse on a stratification. We show that construct

Yangyi Chen, Hongcheng Gao, Ganqu Cui, Lifan Yuan

Textual adversarial attacks can discover models' weaknesses by adding semantic-preserved but misleading perturbations to the inputs. The long-lasting adversarial attack-and-defense arms race in Natural Language Processing (NLP) is algorithm-centric, providing valuable techniques for automatic robustness evaluation. However, the existing practice of robustnes

Yanni Zhai, Xiying Yuan

For a set of graphs $\mathcal{F}$, a graph is said to be $\mathcal{F}$-free if it does not contain any graph in $\mathcal{F}$ as a subgraph. Let Ex$_{sp}(n,\mathcal{F})$ denote the graphs with the maximum spectral radius among all $\mathcal{F}$-free graphs of order $n$. A linear forest is a graph whose connected component is a path. Denote by $\mathcal{L}_s$

Alireza Ahmadi

We discuss how stability is related to the D-topology of mapping spaces, equipped with the functional diffeology. Indeed, we show that stable classes of mapping spaces are D-open. After a reformulation of the classical stability theorem of manifolds with respect to the D-topology, we prove a version of the stability theorem in the class of diffeological \'et

Pedro M. Q. Cruz, Bruno Murta

The controlled-SWAP and controlled-controlled-NOT gates are at the heart of the original proposal of reversible classical computation by Fredkin and Toffoli. Their widespread use in quantum computation, both in the implementation of classical logic subroutines of quantum algorithms and in quantum schemes with no direct classical counterparts, has made it imp

Harsh Varshney, Rohit Mukherjee, Arijit Kundu, Amit Agarwal

We present a systematic study of the nonlinear thermal Hall responses in bosonic systems using the quantum kinetic theory framework. We demonstrate the existence of an intrinsic nonlinear boson thermal current, arising from the quantum metric which is a wavefunction dependent band geometric quantity. In contrast to the nonlinear Drude and nonlinear anomalous

James Martin Speight, Thomas Winyard

It has become clear in recent years that the configuration space of the nuclear Skyrme model has, in each topological class, many almost degenerate local energy minima and that the number of such minima grows with the degree (or baryon number) $B$. Rigid body quantization, in which one quantizes motion on the spin-isospin orbit of just one minimum, is thus a

Shengchao Liu, Jiongxiao Wang, Yijin Yang, Chengpeng Wang

Recent advancements in conversational large language models (LLMs), such as ChatGPT, have demonstrated remarkable promise in various domains, including drug discovery. However, existing works mainly focus on investigating the capabilities of conversational LLMs on chemical reaction and retrosynthesis. While drug editing, a critical task in the drug discovery

Andrew Katz, Umair Shakir, Ben Chambers

The use of natural language processing (NLP) techniques in engineering education can provide valuable insights into the underlying processes involved in generating text. While accessing these insights can be labor-intensive if done manually, recent advances in NLP and large language models have made it a realistic option for individuals. This study explores

Luca Arnaboldi, Florent Krzakala, Bruno Loureiro, Ludovic Stephan

This study explores the sample complexity for two-layer neural networks to learn a generalized linear target function under Stochastic Gradient Descent (SGD), focusing on the challenging regime where many flat directions are present at initialization. It is well-established that in this scenario $n=O(d \log d)$ samples are typically needed. However, we provi

D. V. Dmitriev, V. Ya. Krivnov

We study the delta-chain with spin-$1$ on basal sites and spin-$\frac{1}{2}$ on apical sites. The Heisenberg interaction between neighbor basal spins is antiferromagnetic (AF) and the interaction between basal and apical spins is ferromagnetic (F). We show that the magnetization curve of this model is the same as that of the spin-$\frac{1}{2}$ kagome-like ch

Deepak, Arpita Chatterjee

We compare the lower and higher order non-classicality of a class of the photon-added Bell-type entangled coherent states (PBECS) got from Bell-type entangled coherent states using creation operators. We obtained lower and higher order criteria namely Mandel's $Q_m^l$, antibunching $d_h^{l-1}$, Subpoissioning photon statistics $D_h(l-1)$ and Squeezing $S(l)$

Yunhao Tang, Tadashi Kozuno, Mark Rowland, Anna Harutyunyan

Multi-step learning applies lookahead over multiple time steps and has proved valuable in policy evaluation settings. However, in the optimal control case, the impact of multi-step learning has been relatively limited despite a number of prior efforts. Fundamentally, this might be because multi-step policy improvements require operations that cannot be appro

Hyun-Sik Jeong, Keun-Young Kim, Ya-Wen Sun

We investigate the entanglement between the eternal black hole and Hawking radiation. For this purpose, we utilize the doubly holographic theories and study the entanglement entropy of the radiation to find the Page curve consistent with the unitarity principle. Doubly holographic theories introduce two types of boundaries in the AdS bulk, namely the usual A

Sihan Chen, Handong Li, Qunbo Wang, Zijia Zhao

Vision and text have been fully explored in contemporary video-text foundational models, while other modalities such as audio and subtitles in videos have not received sufficient attention. In this paper, we resort to establish connections between multi-modality video tracks, including Vision, Audio, and Subtitle, and Text by exploring an automatically gener

P. A. Almeida, M. A. Manya, M. S. Figueira, S. E. Ulloa

We study a Kondo state that is strongly influenced by its proximity to an w^-1/2 singularity in the metallic host density of states. This singularity occurs at the bottom of the band of a 1D chain, for example. We first analyze the non-interacting system: A resonant state e_d, located close to the band singularity, suffers a strong `renormalization', such th

Reza Dadfar, Sanaz Sabzevari, Mårten Björkman, Danica Kragic

Language-based fashion image editing allows users to try out variations of desired garments through provided text prompts. Inspired by research on manipulating latent representations in StyleCLIP and HairCLIP, we focus on these latent spaces for editing fashion items of full-body human datasets. Currently, there is a gap in handling fashion image editing due

Yibo Guo, Mingxin Li, Jingting Zong, Mingliang Xu

Unmanned warehouses are an important part of logistics, and improving their operational efficiency can effectively enhance service efficiency. However, due to the complexity of unmanned warehouse systems and their susceptibility to errors, incidents may occur during their operation, most often in inbound and outbound operations, which can decrease operationa

Christian Beck

This work aims to shed some light on the meaning of the positive energy assumption in relativistic quantum theory and its relation to questions of localization of quantum systems. It is shown that the positive energy property of solutions of relativistic wave equations (such as the Dirac equation) is very fragile with respect to state transformations beyond

Jialong Wu, Haoyu Ma, Chaoyi Deng, Mingsheng Long

Unsupervised pre-training methods utilizing large and diverse datasets have achieved tremendous success across a range of domains. Recent work has investigated such unsupervised pre-training methods for model-based reinforcement learning (MBRL) but is limited to domain-specific or simulated data. In this paper, we study the problem of pre-training world mode

Claude Bourrely, Franco Buccella, Wen-Chen Chang, Jen-Chieh Peng

We present an analysis to extract kaon parton distribution functions (PDFs) for the first time using meson-induced Drell-Yan and quarkonium production data. Starting from the statistical model first developed for determining the partonic structure of spin-1/2 nucleon and later applied to the spin-0 pion, we have extended this approach to perform a global fit

Michel Gondran, Alexandre Gondran

We present a new interpretation of quantum mechanics, called the double-scale theory, which expends on the de Broglie-Bohm (dBB) theory. It is based, for any quantum system, on the simultaneous existence of two wave functions in the laboratory reference frame : an external wavefunction and an internal one. The external wave function corresponds to a field th

Samuel J. Harris

We show that quantum graph parameters for finite, simple, undirected graphs encode winning strategies for all possible synchronous non-local games. Given a synchronous game $\mathcal{G}=(I,O,\lambda)$ with $|I|=n$ and $|O|=k$, we demonstrate what we call a weak $*$-equivalence between $\mathcal{G}$ and a $3$-coloring game on a graph with at most $3+n+9n(k-2)

Samuele Giraudo

Clones are specializations of operads forming powerful instruments to describe varieties of algebras wherein repeating variables are allowed in their equations. They allow us in this way to realize and study a large range of algebraic structures. A functorial construction from the category of monoids to the category of clones is introduced. The obtained clon

Bruno Ferman, Otávio Tecchio

In many situations, researchers are interested in identifying dynamic effects of an irreversible treatment with a time-invariant binary instrumental variable (IV). For example, in evaluations of dynamic effects of training programs with a single lottery determining eligibility. A common approach in these situations is to report per-period IV estimates. Under

Deepak, Arpita Chatterjee

In quantum mechanics, bosonic operators are mathematical objects that are used to represent the creation ($a^\dagger$) and annihilation ($a$) of bosonic particles. The natural power of a linear combination of bosonic operators represents an operator $(a^\dagger x+ay)^n$ with $n$ as the exponent and $x,\,y$ are the variables free from bosonic operators. The n

Na-Na Ma, Tao-Feng Wang, Rong Wang

The relation between the nuclear EMC effect and the nucleon-nucleon short-range correlation is a hot topic in high-energy nuclear physics, ever since a peculiar linear correlation between these two phenomena discovered. In this paper, the contribution to the nuclear EMC effect arising from the short-range correlated nucleons is examined in a nucleon-swelling

Ruhee D'Cunha, Matthew Otten, Matthew R. Hermes, Laura Gagliardi

State preparation for quantum algorithms is crucial for achieving high accuracy in quantum chemistry and competing with classical algorithms. The localized active space unitary coupled cluster (LAS-UCC) algorithm iteratively loads a fragment-based multireference wave function onto a quantum computer. In this study, we compare two state preparation methods, q

Kaishuai Xu, Wenjun Hou, Yi Cheng, Jian Wang

Medical dialogue systems (MDS) aim to provide patients with medical services, such as diagnosis and prescription. Since most patients cannot precisely describe their symptoms, dialogue understanding is challenging for MDS. Previous studies mainly addressed this by extracting the mentioned medical entities as critical dialogue history information. In this wor

Xuankai Chang, Brian Yan, Yuya Fujita, Takashi Maekaku

Self-supervised learning (SSL) of speech has shown impressive results in speech-related tasks, particularly in automatic speech recognition (ASR). While most methods employ the output of intermediate layers of the SSL model as real-valued features for downstream tasks, there is potential in exploring alternative approaches that use discretized token sequence

Ruofan Zhang, Jinjin Gu, Haoyu Chen, Chao Dong

Super-resolution (SR) techniques designed for real-world applications commonly encounter two primary challenges: generalization performance and restoration accuracy. We demonstrate that when methods are trained using complex, large-range degradations to enhance generalization, a decline in accuracy is inevitable. However, since the degradation in a certain r

P. G. Morrison

This paper covers some new results from the theory of time optimal quantum control, with particular application to relativistic particles including Majorana fermions. We give a brief review of the state of affairs regarding experimental results, and a concise overview of the methodology of time optimal control and unitary transformation. This technique is th

CMS Collaboration

A search for the lepton-flavor violating decay of the Higgs boson and potential additional Higgs bosons with a mass in the range 110-160 GeV to an e$^{\pm}\mu^{\mp}$ pair is presented. The search is performed with a proton-proton collision dataset at a center-of-mass energy of 13 TeV collected by the CMS experiment at the LHC, corresponding to an integrated

Vikram Giri, Razvan-Octavian Radu

For any $\gamma<1/3$, we construct a nontrivial weak solution $u$ to the two-dimensional, incompressible Euler equations, which has compact support in time and satisfies $u\in C^\gamma(\mathbb R_t \times \mathbb T^2_x)$. In particular, the constructed solution does not conserve energy and, thus, settles the flexible part of the Onsager conjecture in two dime

Di Huang, Ziyuan Nan, Xing Hu, Pengwei Jin

Though LLMs are capable of generating plausible programs, it's challenging to interact with the LLMs further to revise the program, especially if the user's specific requirements are different from the initial proposal. In this paper, we introduce ANPL, an interactive programming system that ensures users can always refine the generated code towards their sp

S. Kosulnikov, F. S. Cuesta, X. Wang, S. A. Tretyakov

Active development is taking place in reconfigurable and static metasurfaces that control and optimize reflections. However, existing designs typically only optimize reflections from the metasurface panels, neglecting interference with reflections originating from supporting walls and nearby objects in realistic scenarios. Moreover, when the area illuminated

Lian-Bao Jia

For loops with UV divergences, assuming that the physical contributions of loops from UV regions are insignificant, a method of UV-free scheme described by an equation is introduced to derive loop results without UV divergences in calculations, i.e., a route of the analytic continuation $\mathcal{T}_\mathrm{F} \to \mathcal{T}_\mathrm{P}$ besides the traditio

Steven A. Kivelson, Shivaji Sondhi

In 1973, Philip Anderson published a paper introducing the resonating valence bond state, which can be recognized in retrospect as a topologically ordered phase of matter - one that cannot be classified in the conventional way according to its patterns of spontaneously broken symmetry. Steven Kivelson and Shivaji Sondhi reflect on the impact of this paper ov

Ping Ai, Luca Moreschini, Ryo Mori, Drew W. Latzke

Molecular crystals are a flexible platform to induce novel electronic phases. Due to the weak forces between molecules, intermolecular distances can be varied over relatively larger ranges than interatomic distances in atomic crystals. On the other hand, the hopping terms are generally small, which results in narrow bands, strong correlations and heavy elect

Sophie Huczynska, Siaw-Lynn Ng

Strong external difference families (SEDFs) are much-studied combinatorial objects motivated by an information security application. A well-known conjecture states that only one abelian SEDF with more than 2 sets exists. We show that if the disjointness condition is replaced by non-disjointness, then abelian SEDFs can be constructed with more than 2 sets (in

Dongyang Fan, Celestine Mendler-Dünner, Martin Jaggi

We consider a collaborative learning setting where the goal of each agent is to improve their own model by leveraging the expertise of collaborators, in addition to their own training data. To facilitate the exchange of expertise among agents, we propose a distillation-based method leveraging shared unlabeled auxiliary data, which is pseudo-labeled by the co

Alessandro Granelli, Koichi Hamaguchi, Natsumi Nagata, Maura E. Ramirez-Quezada

We discuss the thermal leptogenesis mechanism within the minimal gauged U(1)$_{L_\mu-L_\tau}$ model to explain the observed baryon asymmetry of the Universe (BAU). In such framework, the phases of the Pontecorvo-Maki-Nakagawa-Sakata neutrino mixing matrix and the sum of the Standard Model neutrino masses are predictable because of a restricted neutrino mass

Stefano De Paoli

The goal of this paper is establishing if we can satisfactorily perform a Thematic Analysis (TA) of semi-structured interviews using a Large Language Model (more precisely GPT3.5-Turbo). Building on previous work by the author, which established an embryonal process for conducting a TA with the model, this paper will perform a further analysis and then cover

Wen Yang, Chong Li, Jiajun Zhang, Chengqing Zong

Large language models (LLMs) demonstrate promising translation performance among various natural languages. However, many LLMs especially the open-sourced ones, such as BLOOM and LLaMA, are English-dominant and support only dozens of natural languages, making the potential of LLMs on language translation less explored. In this work, we present BigTranslate w

Rongen Dong, Zhongyi Xie, Feng Shu, Mengxing Huang

As a new technology to reconfigure wireless communication environment by signal reflection controlled by software, intelligent reflecting surface (IRS) has attracted lots of attention in recent years. Compared with conventional relay system, the relay system aided by IRS can effectively save the cost and energy consumption, and significantly enhance the syst

Pratik Patil, Jin-Hong Du

We establish precise structural and risk equivalences between subsampling and ridge regularization for ensemble ridge estimators. Specifically, we prove that linear and quadratic functionals of subsample ridge estimators, when fitted with different ridge regularization levels $\lambda$ and subsample aspect ratios $\psi$, are asymptotically equivalent along s

Guan-Wei Wu, Guan-Ting Lin, Shang-Wen Li, Hung-yi Lee

Spoken Language Understanding (SLU) is a task that aims to extract semantic information from spoken utterances. Previous research has made progress in end-to-end SLU by using paired speech-text data, such as pre-trained Automatic Speech Recognition (ASR) models or paired text as intermediate targets. However, acquiring paired transcripts is expensive and imp

Giuliano Basso

We propose a slight variant of Ambrosio and Kirchheim's definition of a metric current. We show that with this new definition it is possible to obtain certain volume functionals from Finsler geometry as mass measures of currents. As an application, we obtain a whole family of extendibly convex $n$-volume densities. This family includes the mass* and the circ

Francisco Marques-Moros, Carla Boix-Constant, Samuel Mañas-Valero, Josep Canet-Ferrer

The Van der Waals semiconductor metamagnet CrSBr offers an ideal platform for studying the interplay between optical and magnetic properties in the two-dimensional limit. Here, we carried out an exhaustive optical characterization of this material by means of temperature and magnetic field dependent photoluminescence (PL) on flakes of different thicknesses d

Jianxin Huang, Youichi Yamakawa, Rina Tazai, Takahiro Morimoto

Kagome metals present a fascinating platform of quantum phases thanks to the interplay between the geometric frustration and strong electron correlation. Here, we propose the emergence of the electric odd-parity bond order (BO) that originates from the intra-unit-cell odd-parity configuration in recently discovered kagome metal CsTi$_3$Bi$_5$. The predicted

Philippe Drolet, Raphaël Dawant, Victor Yon, Pierre-Antoine Mouny

Passive resistive random access memory (ReRAM) crossbar arrays, a promising emerging technology used for analog matrix-vector multiplications, are far superior to their active (1T1R) counterparts in terms of the integration density. However, current transfers of neural network weights into the conductance state of the memory devices in the crossbar architect

Zhiying Jiang, Risheng Liu, Shuzhou Yang, Zengxi Zhang

Rain streaks significantly decrease the visibility of captured images and are also a stumbling block that restricts the performance of subsequent computer vision applications. The existing deep learning-based image deraining methods employ manually crafted networks and learn a straightforward projection from rainy images to clear images. In pursuit of better

Thong Nguyen, Sean MacAvaney, Andrew Yates

Learned sparse retrieval (LSR) is a family of neural retrieval methods that transform queries and documents into sparse weight vectors aligned with a vocabulary. While LSR approaches like Splade work well for short passages, it is unclear how well they handle longer documents. We investigate existing aggregation approaches for adapting LSR to longer document

Filip Lemic, Gerard Calvo Bartra, Arnau Brosa López, Jorge Torres Gómez

Nanodevices with Terahertz (THz)-based wireless communication capabilities are providing a primer for flow-guided localization within the human bloodstreams. Such localization is allowing for assigning the locations of sensed events with the events themselves, providing benefits along the lines of early and precise diagnostics, and reduced costs and invasive

Michael A. Hobley, Victor A. Prisacariu

We present a novel approach, in which we learn to cluster data directly from side information, in the form of a small set of pairwise examples. Unlike previous methods, with or without side information, we do not need to know the number of clusters, their centers or any kind of distance metric for similarity. Our method is able to divide the same data points

Jianxin Huang, Rina Tazai, Youichi Yamakawa, Seiichiro Onari

To understand the multistage phase transitions in V-based kagome metals inside the charge-density-wave (CDW) phase, we focus on the impact of the "mix-type" Fermi surface because it is intact in the CDW state on the "pure-type" Fermi surface. On the mixed-type Fermi surface, moderate spin correlations develop, and we reveal that uniform (q=0) bond order is c

Taouali W, Alimi K, Nangraj A. S., Casida M. E

As emphasized in a recent review article [Chem. Rev. 122, 14180 (2022)], organic solar cell (OSC) photoconversion efficiency has been rapidly evolving with results increasingly comparable to those of traditional inorganic solar cells. Historically, OSC performance improvement focused first on the morphology of P3HT:PC61BM solar cells then went through differ

Pengxiang Jin, Shenglin Zhang, Minghua Ma, Haozhe Li

Cloud systems have become increasingly popular in recent years due to their flexibility and scalability. Each time cloud computing applications and services hosted on the cloud are affected by a cloud outage, users can experience slow response times, connection issues or total service disruption, resulting in a significant negative business impact. Outages a

Yunhao Tang, Rémi Munos

TD-learning is a foundation reinforcement learning (RL) algorithm for value prediction. Critical to the accuracy of value predictions is the quality of state representations. In this work, we consider the question: how does end-to-end TD-learning impact the representation over time? Complementary to prior work, we provide a set of analysis that sheds further

George Kastrinakis

Within a strongly interacting Fermi liquid framework, we calculate the effects of the Zeeman energy $\omega_H$ for a finite magnetic field, in a metallic system with a van Hove peak in the density of states, located close to and below the Fermi surface. We find that the chemical potential increases with the square of $\omega_H$. We obtain a characteristic qu

Vassilis Papataxiarhis, Thomais Vassilopoulou, Sofia Kostakonti, Stathes Hadjiefthymiades

Correlating events in complex and dynamic IoT environments is a challenging task not only because of the amount of available data that needs to be processed but also due to the call for time efficient data processing. In this paper, we discuss the major steps that should be performed in real- or near real-time event management focusing on event detection and

D. C. W. Foo, Z. Zhan, Mohammed M. Al Ezzi, L. Peng

Theoretical and experimental studies have verified the existence of ``magic angles'' in twisted bilayer graphene, where the twist between layers gives rise to flat bands and consequently highly correlated phases. Narrow bands can also exist in multilayers with alternating twist angles, and recent theoretical work suggests that they can also be found in trila

Adrian Azzarelli, Nantheera Anantrasirichai, David R Bull

Neural Radiance Field (NeRF) research has attracted significant attention recently, with 3D modelling, virtual/augmented reality, and visual effects driving its application. While current NeRF implementations can produce high quality visual results, there is a conspicuous lack of reliable methods for evaluating them. Conventional image quality assessment met

Lawrence Wang, Stephen J. Roberts

Modern neural networks are undeniably successful. Numerous studies have investigated how the curvature of loss landscapes can affect the quality of solutions. In this work we consider the Hessian matrix during network training. We reiterate the connection between the number of "well-determined" or "effective" parameters and the generalisation performance of

Yarden Tzach, Yuval Meir, Ofek Tevet, Ronit D. Gross

Deep architectures consist of tens or hundreds of convolutional layers (CLs) that terminate with a few fully connected (FC) layers and an output layer representing the possible labels of a complex classification task. According to the existing deep learning (DL) rationale, the first CL reveals localized features from the raw data, whereas the subsequent laye

Federico Talamucci

The main theme of the article is the study of discrete systems of material points subjected to constraints not only of a geometric type (holonomic constraints) but also of a kinematic type (nonholonomic constraints). The setting up of the equations of motion follows a simple principle which generalizes the holonomic case. Furthermore, attention is paid to th

S. Candini, M. Brienza, A. Bonafede, K. Rajpurohit

Radio galaxies are a subclass of active galactic nuclei in which accretion onto the supermassive black hole releases energy via relativistic jets. The jets are not constantly active throughout the life of the host galaxy and alternate between active and quiescent phases. Remnant radio galaxies are detected during a quiescent phase and define a class of uniqu

Tao Feng, Jie Zhang, Huashan Liu, Zhijie Wang

Deep hashing retrieval has gained widespread use in big data retrieval due to its robust feature extraction and efficient hashing process. However, training advanced deep hashing models has become more expensive due to complex optimizations and large datasets. Coreset selection and Dataset Condensation lower overall training costs by reducing the volume of t

Vladimir Lotoreichik

We prove that the $(k+d)$-th Neumann eigenvalue of the biharmonic operator on a bounded connected $d$-dimensional $(d\ge2)$ Lipschitz domain is not larger than its $k$-th Dirichlet eigenvalue for all $k\in\mathbb{N}$. For a special class of domains with symmetries we obtain a stronger inequality. Namely, for this class of domains, we prove that the $(k+d+1)$

Luca Serafini, Samuele Cornell, Giovanni Morrone, Enrico Zovato

We performed an experimental review of current diarization systems for the conversational telephone speech (CTS) domain. In detail, we considered a total of eight different algorithms belonging to clustering-based, end-to-end neural diarization (EEND), and speech separation guided diarization (SSGD) paradigms. We studied the inference-time computational requ

Mislav Bui, Marko Jurčević

Phasor Measurement Units (PMUs) are being used extensively for electrical grid monitoring and control. However, their cost prohibits further adoption on the distribution grid and easy access for educational purposes. This paper proposes that simple and fundamental functions of a PMU can be achieved using an energy metering IC and integrated into smart electr

Feipeng Ma, Yizhou Zhou, Fengyun Rao, Yueyi Zhang

Image captioning requires numerous annotated image-text pairs, resulting in substantial annotation costs. Recently, large models (e.g. diffusion models and large language models) have excelled in producing high-quality images and text. This potential can be harnessed to create synthetic image-text pairs for training captioning models. Synthetic data can impr

Robert Loftin, Mustafa Mert Çelikok, Frans A. Oliehoek

Multiagent systems deployed in the real world need to cooperate with other agents (including humans) nearly as effectively as these agents cooperate with one another. To design such AI, and provide guarantees of its effectiveness, we need to clearly specify what types of agents our AI must be able to cooperate with. In this work we propose a generic model of

Mart Keizer, Zeno Geradts, Meike Kombrink

This research evaluates a convolutional neural network (CNN) based approach to forensic video steganalysis. A video steganography dataset is created to train a CNN to conduct forensic steganalysis in the spatial domain. We use a noise residual convolutional neural network to detect embedded secrets since a steganographic embedding process will always result

Mattia Giovanni Campana, Marco Colussi, Franca Delmastro, Sergio Mascetti

In recent months, the monkeypox (mpox) virus -- previously endemic in a limited area of the world -- has started spreading in multiple countries until being declared a ``public health emergency of international concern'' by the World Health Organization. The alert was renewed in February 2023 due to a persisting sustained incidence of the virus in several co

Georgios Kontogeorgiou, Alexandros Leivaditis, Kostas I. Psaromiligkos, Giannos Stamoulis

A graph parameter is self-dual in some class of graphs embeddable in some surface if its value does not change in the dual graph by more than a constant factor. We prove that the branchwidth of connected hypergraphs without bridges and loops that are embeddable in some surface of Euler genus at most g is an (1,g)-self-dual parameter. This is the first proof

Hedyeh Beyhaghi, Modibo K. Camara, Jason Hartline, Aleck Johnsen

Motivated by school admissions, this paper studies screening in a population with both advantaged and disadvantaged agents. A school is interested in admitting the most skilled students, but relies on imperfect test scores that reflect both skill and effort. Students are limited by a budget on effort, with disadvantaged students having tighter budgets. This

Benzheng Chen, Jieru Ren, Zhigang Deng, Wei Qi

Thoroughly understanding the transport and energy loss of intense ion beams in dense matter is essential for high-energy-density physics and inertial confinement fusion. Here, we report a stopping power experiment with a high-intensity laser-driven proton beam in cold, dense matter. The measured energy loss is one order of magnitude higher than the expectati

S. -A. Biehs, P. Rodriguez-Lopez, M. Antezza, G. S. Agarwal

We study the heat transfer between N coupled quantum resonators with applied synthetic electric and magnetic fields realized by changing the resonators parameters by external drivings. To this end we develop two general methods, based on the quantum optical master equation and on the Langevin equation for $N$ coupled oscillators where all quantum oscillators

Ahire Swapnil Ashok, Manu K.

This paper numerically investigates the instability characteristics of decelerating flows. The flow dynamics and temporal evolution of coherent structures in a diverging section with mild spatial pressure gradient are analyzed using numerical experiments with Incompact3d code. The unsteady nature of flow and adverse pressure gradient is the reason for inflec

D. S. Rosa, T. Frederico, G. Krein, M. T. Yamashita

We studied the single-particle momentum distribution of mass-imbalanced Efimov states embedded in noninteger dimensions. The contact parameters, which can be related to the thermodynamic properties of the gas, were calculated from the high momentum tail of the single particle densities. We studied the dependence of the contact parameters with the progressive

Tao Yang, Yuwang Wang, Cuiling Lan, Yan Lu

Recognizing elementary underlying concepts from observations (disentanglement) and generating novel combinations of these concepts (compositional generalization) are fundamental abilities for humans to support rapid knowledge learning and generalize to new tasks, with which the deep learning models struggle. Towards human-like intelligence, various works on

Sebastian Hönel

Real-world software applications must constantly evolve to remain relevant. This evolution occurs when developing new applications or adapting existing ones to meet new requirements, make corrections, or incorporate future functionality. Traditional methods of software quality control involve software quality models and continuous code inspection tools. Thes

Haojun Yu, Youcheng Li, QuanLin Wu, Ziwei Zhao

During ultrasonic scanning processes, real-time lesion detection can assist radiologists in accurate cancer diagnosis. However, this essential task remains challenging and underexplored. General-purpose real-time object detection models can mistakenly report obvious false positives (FPs) when applied to ultrasound videos, potentially misleading junior radiol

Zhe Wang, Zhiwei Fang, Zhaoxiang Liu, Youting Liang

We design an on-chip 8-channel TFLN AWG and fabricate the device using photolithography assisted chemo-mechanical etching (PLACE) technique. We experimentally measure the transmission of the fabricated TFLN AWG near the central wavelength of 1550 nm. We obtain an on-chip loss as low as 3.32 dB, a single-channel bandwidth of 1.6 nm and a total-channel bandwid

Anton Fonarev

We propose a conjecture on the structure of the bounded derived category of coherent sheaves of the moduli space rank $2$ parabolic bundles on $\mathbb{P}^1$.

Weicheng Xue, Hongyu Wang, Christopher J. Roy

This work deals with the CPU-GPU heterogeneous code acceleration of a finite-volume CFD solver utilizing multiple CPUs and GPUs at the same time. First, a high-level description of the CFD solver called SENSEI, the discretization of SENSEI, and the CPU-GPU heterogeneous computing workflow in SENSEI leveraging MPI and OpenACC are given. Then, a performance mo

Ilsang Ohn, Lizhen Lin, Yongdai Kim

In this paper, we propose a new Bayesian inference method for a high-dimensional sparse factor model that allows both the factor dimensionality and the sparse structure of the loading matrix to be inferred. The novelty is to introduce a certain dependence between the sparsity level and the factor dimensionality, which leads to adaptive posterior concentratio

Thomas M. Mercier, Tasmiat Rahman, Amin Sabet

This paper proposes an anticipative transformer-based model for short-term solar irradiance forecasting. Given a sequence of sky images, our proposed vision transformer encodes features of consecutive images, feeding into a transformer decoder to predict irradiance values associated with future unseen sky images. We show that our model effectively learns to

Jarah Evslin, Tomasz Romańczukiewicz, Andrzej Wereszczyński

Hertzberg has constructed a quantum oscillon that decays into pairs of relativistic mesons with a power much greater than the radiation from classical oscillon decay. This result is often construed as a proof that quantum oscillons decay quickly, and so are inconsequential. We apply a construction similar to Hertzberg's to the quantum kink. Again it leads to

Paul Fallon, Derck P Smits, Tapasi Ghosh, Christopher J. Salter

C-Band Mueller matrices for the Green Bank Telescope are presented here which enable on-sky Stokes parameters for point sources at the beam center to be determined. Standard calibrators, 3C138 and 3C286, were observed using the Spider program to steer the telescope across a broad range of Right Ascensions on both sides of the zenith transit. For this analysi

Md Tahmid Rahman Laskar, M Saiful Bari, Mizanur Rahman, Md Amran Hossen Bhuiyan

The development of large language models (LLMs) such as ChatGPT has brought a lot of attention recently. However, their evaluation in the benchmark academic datasets remains under-explored due to the difficulty of evaluating the generative outputs produced by this model against the ground truth. In this paper, we aim to present a thorough evaluation of ChatG

Aiwei Liu, Wei Liu, Xuming Hu, Shuang Li

In the context-dependent Text-to-SQL task, the generated SQL statements are refined iteratively based on the user input utterance from each interaction. The input text from each interaction can be viewed as component modifications to the previous SQL statements, which could be further extracted as the modification patterns. Since these modification patterns

Qian Guo, Jie He, Lei Li

In this paper, we present a numerical approach to solve the McKean-Vlasov equations, which are distribution-dependent stochastic differential equations, under some non-globally Lipschitz conditions for both the drift and diffusion coefficients. We establish a propagation of chaos result, based on which the McKean-Vlasov equation is approximated by an interac

José Gaitan, Allan Greenleaf, Eyvindur Ari Palsson, Georgios Psaromiligkos

We introduce a class of Falconer distance problems, which we call of restricted type, lying between the classical version and its pinned variant. Prototypical restricted distance sets are the diagonal distance sets, $k$-point configuration sets given by $$\Delta^{diag}(E)= \{ \,|(x,x,\dots,x)-(y_1,y_2,\dots,y_{k-1})| : x, y_1, \dots,y_{k-1} \in E\, \}$$ for

Yong-Kun Zhang, Di Li, Yi Feng, Pei Wang

The origin of fast radio bursts (FRBs), the brightest cosmic explosion in radio bands, remains unknown. We introduce here a novel method for a comprehensive analysis of active FRBs' behaviors in the time-energy domain. Using ``Pincus Index'' and ``Maximum Lyapunov Exponent'', we were able to quantify the randomness and chaoticity, respectively, of the bursti

Yongxing Zhu

We derive rigorously the reduced dynamical laws for quantized vortex dynamics of the nonlinear wave equation on the torus when the core size of vortex $\varepsilon\to 0$. It is proved that the reduced dynamical laws are second-order nonlinear ordinary differential equations which are driven by the renormalized energy on the torus, and the initial data of the

Mohamad Shalaby, Timon Thomas, Christoph Pfrommer, Rouven Lemmerz

We study the underlying physics of cosmic-ray (CR) driven instabilities that play a crucial role for CR transport across a wide range of scales, from interstellar to galaxy cluster environments. By examining the linear dispersion relation of CR-driven instabilities in a magnetised electron-ion background plasma, we establish that both, the intermediate and g