November 2022 arXiv papers — page 157

Carlos Rojas Castillo, Matteo Marra, Jim Bauwens, Elisa Gonzalez Boix

Context: Internet of Things (IoT) has become an important kind of distributed systems thanks to the wide-spread of cheap embedded devices equipped with different networking technologies. Although ubiquitous, developing IoT systems remains challenging. Inquiry: A recent field study with 194 IoT developers identifies debugging as one of the main challenges fac

Benjamin Chetioui, Jaakko Järvi, Magne Haveraaen

Context: Generic programming, as defined by Stepanov, is a methodology for writing efficient and reusable algorithms by considering only the required properties of their underlying data types and operations. Generic programming has proven to be an effective means of constructing libraries of reusable software components in languages that support it. Generics

Ben Greenman, Sam Saarinen, Tim Nelson, Shriram Krishnamurthi

Context: Linear Temporal Logic (LTL) has been used widely in verification. Its importance and popularity have only grown with the revival of temporal logic synthesis, and with new uses of LTL in robotics and planning activities. All these uses demand that the user have a clear understanding of what an LTL specification means. Inquiry: Despite the growing use

Wenran Yang, Yong Deng

Random permutation set (RPS), as a recently proposed theory, enables powerful information representation by traversing all possible permutations. However, the repetition of items is not allowed in RPS while it is quite common in real life. To address this issue, we propose repeatable random permutation set ($\rm R^2PS$) which takes the repetition of items in

G. M. Shahariar, Swapnil Biswas, Faiza Omar, Faisal Muhammad Shah

A robust and reliable system of detecting spam reviews is a crying need in todays world in order to purchase products without being cheated from online sites. In many online sites, there are options for posting reviews, and thus creating scopes for fake paid reviews or untruthful reviews. These concocted reviews can mislead the general public and put them in

Daniel Kapec, Alexandru Lupsasca, Andrew Strominger

The black hole photon ring is a prime target for upcoming space-based VLBI missions seeking to image the fine structure of astrophysical black holes. The classical Lyapunov exponents of the corresponding nearly bound null geodesics control the quasinormal ringing of a perturbed black hole as it settles back down to equilibrium, and they admit a holographic i

Andreas Athenodorou, Claudio Bonanno, Claudio Bonati, Giuseppe Clemente

The QCD topological observables are essential inputs to obtain theoretical predictions about axion phenomenology, which are of utmost importance for current and future experimental searches for this particle. Among them, we focus on the topological susceptibility, related to the axion mass. We present lattice results for the topological susceptibility in QCD

Jin Wang, Yongsong Zou, Se-Jung Lim

Recurrent Neural Networks (RNNs) have been widely applied to deal with temporal problems, such as flood forecasting and financial data processing. On the one hand, traditional RNNs models amplify the gradient issue due to the strict time serial dependency, making it difficult to realize a long-term memory function. On the other hand, RNNs cells are highly co

Youngwoo Koh, Yoonjung Lee, Ihyeok Seo

We revisit the local well-posedness theory of nonlinear Schr\"odinger and wave equations in Sobolev spaces $H^s$ and $\dot{H}^s$, $0< s\leq 1$. The theory has been well established over the past few decades under Sobolev initial data regular with respect to all spatial variables. But here, we reveal that the initial data do not need to have complete regulari

Xingxing Wei, Bangzheng Pu, Shiji Zhao, Jiefan Lu

Although Deep Neural Networks (DNNs) have been widely applied in various real-world scenarios, they remain vulnerable to adversarial examples. Adversarial attacks in computer vision can be categorized into digital attacks and physical attacks based on their different forms. Compared to digital attacks, which generate perturbations in digital pixels, physical

Ce Wang, Kun Shang, Haimiao Zhang, Shang Zhao

Computed tomography (CT) is a widely-used imaging technology that assists clinical decision-making with high-quality human body representations. To reduce the radiation dose posed by CT, sparse-view and limited-angle CT are developed with preserved image quality. However, these methods are still stuck with a fixed or uniform sampling strategy, which inhibits

Vrunda N. Sukhadia, A. Arunkumar, S. Umesh

This paper proposes a novel technique to obtain better downstream ASR performance from a joint encoder-decoder self-supervised model when trained with speech pooled from two different channels (narrow and wide band). The joint encoder-decoder self-supervised model extends the HuBERT model with a Transformer decoder. HuBERT performs clustering of features and

Ya-Dong Wu, Yan Zhu, Ge Bai, Yuexuan Wang

The task of testing whether two uncharacterized quantum devices behave in the same way is crucial for benchmarking near-term quantum computers and quantum simulators, but has so far remained open for continuous-variable quantum systems. In this Letter, we develop a machine learning algorithm for comparing unknown continuous variable states using limited and

Marco Genovese

Quantum non locality, as described by EPR paradox, represents one of the mysteries at the very foundations of quantum mechanics. Here we suggest to investigate if it can be understood by considering extra dimensions.

Shiksha Singhal, Veeraruna Kavitha, Sreenath Ramanath

We consider a system with a Base Station (BS) and multiple mobile/stationary users. BS uses millimeter waves (mmWaves) for data transmission and hence needs to align beams in the directions of the end-users. The idea is to avail regular user-position estimates, which help in accurate beam alignment towards multiple users, paving way for opportunistic mmWave

Robert Neagu

We will show that for a separable exact $C^*$-algebra with a faithful amenable trace, the property that all amenable traces are quasidiagonal is invariant under homotopy.

Kai-Min Chung, Mi-Ying Huang, Er-Cheng Tang, Jiapeng Zhang

Alon et al. (CRYPTO 2021) introduced a multiparty quantum computation protocol that is secure with identifiable abort (MPQC-SWIA). However, their protocol allows only inside MPQC parties to know the identity of malicious players. This becomes problematic when two groups of people disagree and need a third party, like a jury, to verify who the malicious party

Lipeng Gu, Xuefeng Yan, Peng Cui, Lina Gong

There is a trend to fuse multi-modal information for 3D object detection (3OD). However, the challenging problems of low lightweightness, poor flexibility of plug-and-play, and inaccurate alignment of features are still not well-solved, when designing multi-modal fusion newtorks. We propose PointSee, a lightweight, flexible and effective multi-modal fusion s

M. Iakovleva, T. Petersen, A. Alfonsov, Y. Skourski

We report a comprehensive study of the static susceptibility, high-field magnetization and high-frequency/high-magnetic field electron spin resonance (HF-ESR) spectroscopy of polycrystalline samples of the bismuth cobalt oxy-phosphate BiCoPO$_5$. This compound features a peculiar spin system that can be considered as antiferromagnetic (AFM) chains built of p

Shiva Raj Pokhrel, Jinho Choi, Anwar Walid

The bottleneck of distributed edge learning (DEL) over wireless has shifted from computing to communication, primarily the aggregation-averaging (Agg-Avg) process of DEL. The existing transmission control protocol (TCP)-based data networking schemes for DEL are application-agnostic and fail to deliver adjustments according to application layer requirements.

Giacomo Bracci-Testasecca, Andrea Pelissetto

We consider a variant of the charge-Q compact Abelian-Higgs model, in which an Nf-dimensional complex vector is coupled with an Abelian Z_q gauge field. For Nf=2 and Q=1 we observe several transition lines that belong to the O(4), O(3), and O(2) vector universality classes, depending on the symmetry breaking pattern at the transition. The universality class

Naoki Fujita, André Röhm, Takatomo Mihana, Ryoichi Horisaki

Fully pairing all elements of a set while attempting to maximize the total benefit is a combinatorically difficult problem. Such pairing problems naturally appear in various situations in science, technology, economics, and other fields. In our previous study, we proposed an efficient method to infer the underlying compatibilities among the entities, under t

Lubomíra Dvořáková

In this paper, we describe string attractors of all factors of episturmian sequences and show that their size is equal to the number of distinct letters contained in the factor.

Alexandros Papadopoulos, Antonios Lalas, Konstantinos Votis, Dimitrios Tyrovolas

Reconfigurable Intelligent Surfaces (RIS) constitute a promising technology that could fulfill the extreme performance and capacity needs of the upcoming 6G wireless networks, by offering software-defined control over wireless propagation phenomena. Despite the existence of many theoretical models describing various aspects of RIS from the signal processing

James Smith

Sharing a secret efficiently amongst a group of participants is not easy since there is always an adversary / eavesdropper trying to retrieve the secret. In secret sharing schemes, every participant is given a unique share. When the desired group of participants come together and provide their shares, the secret is obtained. For other combinations of shares,

Ali Akil, Mariano Cadoni, Leonardo Modesto, Mauro Oi

We derive the gravitational field and the spacetime metric generated by sources in quantum superposition of different locations. We start by working in a Newtonian approximation, in which the effective gravitational potential is computed as the expectation value of the gravitational potential operator in a Gaussian distribution of width $R$ for the position

Emily Jefferson, James Liley, Maeve Malone, Smarti Reel

TREs are widely, and increasingly used to support statistical analysis of sensitive data across a range of sectors (e.g., health, police, tax and education) as they enable secure and transparent research whilst protecting data confidentiality. There is an increasing desire from academia and industry to train AI models in TREs. The field of AI is developing q

Yixuan Xue, Jin-Wu Jiang, Harold S. Park

Fullerene-based sandwiches have emerged as new candidates for potential applications of two-dimensional nanomaterials in electronics or energy storage. Recently, experimentalists have observed the evolution of boundaries for fullerene clusters sandwiched by two graphene layers, while vacuum space with typical dimension of 30 {\AA} was found within the fuller

M. Wang, M. Zhang, X. Zhou, Y. H. Zhang

A novel technique for broadband high-precision mass measurements of short-lived exotic nuclides is reported. It is based on the isochronous mass spectrometry (IMS) and realizes simultaneous determinations of revolution time and velocity of short-lived stored ions at the cooler storage ring CSRe in Lanzhou. The new technique, named as the $B\rho$-defined IMS

Johannes Fiedler, Kristian Berland, Stefan Yoshi Buhmann

We study the impact of an environment on the electromagnetic responses of a molecule in the presence of a dielectric medium. By applying the dipole-dipole coupling between the molecule's and the environment's degrees of freedom, we can reduce the complex system into its components and predict excitation lifetimes of single and few molecules attached to a die

Shashank Shekhar Pandey, Arnab Sarkar, Amna Ali, A. S. Majumdar

We consider the propagation of gravitational waves in the late-time Universe in the presence of matter distribution inhomogeneities, and we also consider the cosmic fluid to be viscous. In this work, we investigate the cumulative effect of inhomogeneities and viscosity of the cosmic-fluid on the observables associated with the sources of the gravitational wa

Belur Ravindra, Partha Chowdhury, Pratap Chandra Ray, Kumaravel Pichamani

The Kodaikanal Observatory has made synoptic observations of the Sun in white light since 1904, and these images are sketched on the Stonyhurst grids called sun charts. These continuous hand-drawn data sets are used for long-term studies of the Sun. This article investigates temporal and periodic variations of the monthly hemispheric sunspot number and sunsp

Antonio M. García-García, Lucas Sá, Jacobus J. M. Verbaarschot

Spectral rigidity in Hermitian quantum chaotic systems signals the presence of dynamical universal features at timescales that can be much shorter than the Heisenberg time. We study the analog of this timescale in many-body non-Hermitian quantum chaos by a detailed analysis of long-range spectral correlators. For that purpose, we investigate the number varia

Satoshi Taguchi, Tetsuro Tsuji

The transverse force exerted on a rotating sphere immersed in an otherwise uniform flow of a rarefied gas is investigated based on the Bhatnagar-Gross-Krook (BGK) model of the Boltzmann equation assuming the Maxwell boundary condition on the sphere. In several existing studies, it has been shown that the transverse force acting on the sphere, also known as t

Stefano Piani, Luca Heltai, Wenyu Lei

We present a Scharfetter-Gummel (SG) stabilization scheme for high-order Hybrid Discontinuous Galerkin (HDG) approximations of convection-diffusion problems. The scheme is based on a careful choice of the stabilization parameters used to define the numerical flux in the HDG method. We show that, in one dimension, the SG-HDG scheme is equivalent to the Finite

Xuan-Bo Tong, Bo-Wen Xiao, Yuan-Yuan Zhang

Parton saturation is one of the most intriguing phenomena in the high energy nuclear physics research frontier, especially in the upcoming era of the Electron-Ion Collider (EIC). The lepton-jet correlation in deep inelastic scattering provides us with a new gateway to the parton saturation at the EIC. In particular, we demonstrate that azimuthal angle anisot

Zengrui Jin, Xurong Xie, Mengzhe Geng, Tianzi Wang

Automatic recognition of disordered speech remains a highly challenging task to date. The underlying neuro-motor conditions, often compounded with co-occurring physical disabilities, lead to the difficulty in collecting large quantities of impaired speech required for ASR system development. This paper presents novel variational auto-encoder generative adver

Du Nguyen Duy, David Gabauer, Ramin Nikzad-Langerodi

The ongoing transition from a linear (produce-use-dispose) to a circular economy poses significant challenges to current state-of-the-art information and communication technologies. In particular, the derivation of integrated, high-level views on material, process, and product streams from (real-time) data produced along value chains is challenging for sever

Kai Chen, Stephen James, Congying Sui, Yun-Hui Liu

Most existing methods for category-level pose estimation rely on object point clouds. However, when considering transparent objects, depth cameras are usually not able to capture meaningful data, resulting in point clouds with severe artifacts. Without a high-quality point cloud, existing methods are not applicable to challenging transparent objects. To tack

Kosuke Yamato

For downward skip-free continuous-time Markov chains on non-negative integers stopped at zero, existence of a quasi-stationary distribution is studied. The scale function for these processes is introduced and the boundary is classified by a certain integrability condition on the scale function, which gives an extension of Feller's classification of the bound

Haojie Zhang, Ge Li, Jia Li, Zhongjin Zhang

Large-scale pre-trained language models have achieved impressive results on a wide range of downstream tasks recently. However, fine-tuning an extremely large-scale pre-trained language model on limited target datasets is often plagued by overfitting and representation degradation. In this paper, we propose a Dynamic Parameter Selection (DPS) algorithm for t

Pramila Thapa, Veena Singh, Virendra Kumar, Sunil Bhatt

Objective: Survival rate of oral squamous cell carcinoma (OSCC) patients is very poor and can be improved using highly sensitive, specific and accurate techniques. Autofluorescence and fluorescence techniques are very sensitive and useful in cancer screening. Furthermore, fluorescence spectroscopy is directly linked with molecular levels of human tissue and

Peibin Chen, Yinghe Zhao, Junfeng Wang

NGC 1266 is a lenticular galaxy (S0) hosting an active galactic nucleus (AGN), and known to contain a large amount of shocked gas. We compare the luminosity ratio of mid-\emph{J} CO lines to IR continuum with star-forming galaxies (SFGs), and then model the CO spectral line energy distribution (SLED). We confirm that in the mid- and high-\emph{J} regions ($J

Zhengyu Wang, Wei Yang, Tiebin Mi, Robert Caiming Qiu

In this paper, we consider a reconfigurable intelligent surface (RIS)-assisted 3D direction-of-arrival (DoA) estimation system, in which a uniform planar array (UPA) RIS is deployed to provide virtual line-of-sight (LOS) links and reflect the uplink pilot signal to sensors. To overcome the mutually coupled problem between the beamforming design at the RIS an

Meiqin Liu, Shuo Jin, Chao Yao, Chunyu Lin

Video super-resolution (VSR) is a task that aims to reconstruct high-resolution (HR) frames from the low-resolution (LR) reference frame and multiple neighboring frames. The vital operation is to utilize the relative misaligned frames for the current frame reconstruction and preserve the consistency of the results. Existing methods generally explore informat

Zhicheng Wang, Tianyu Shi, Cong Liu

In constituency parsing, span-based decoding is an important direction. However, for Chinese sentences, because of their linguistic characteristics, it is necessary to utilize other models to perform word segmentation first, which introduces a series of uncertainties and generally leads to errors in the computation of the constituency tree afterward. This wo

Liangchen Liu, Qiuhong Ke, Chaojie Li, Feiping Nie

Spectral clustering is an effective methodology for unsupervised learning. Most traditional spectral clustering algorithms involve a separate two-step procedure and apply the transformed new representations for the final clustering results. Recently, much progress has been made to utilize the non-negative feature property in real-world data and to jointly le

Zaihui Gan, Yuchen Wang, Yue Wang, Jialing Yu

In this paper, we consider the Cauchy problem of the magnetic Zakharov system in two-dimensional space: \[ \begin{cases} & i E_{1t}+\Delta E_1-n E_1+\eta E_2 (E_1\overline{E_2}-\overline{E_1} E_2)=0, \\ & i E_{2t}+\Delta E_2-n E_2+\eta E_1(\overline{E_1} E_2-E_1\overline{E_2})=0, \\ & n_t+\nabla \cdot \textbf{v}=0, \\ & \textbf{v}_t+\nabla n+\nabla (|E_1|^2+

Akant Vats, Amit Pathak

The detection of benzonitrile (C6H5CN), 1- and 2-cyano-naphthalene (C10H7CN) in the cold, dark molecular cloud TMC-1 at centimetre (cm) wavelengths has opened up prospects for the detection of other N- and CN-containing polycyclic aromatic hydrocarbons (PAHs). In this light, the pure rotational spectra of N-pyrene (C15H9N), CN-pyrene (C15H9CN), N-coronene (C

Peiyuan Gong, Xuebo Liu, Heyan Huang, Min Zhang

Pretraining-based (PT-based) automatic evaluation metrics (e.g., BERTScore and BARTScore) have been widely used in several sentence generation tasks (e.g., machine translation and text summarization) due to their better correlation with human judgments over traditional overlap-based methods. Although PT-based methods have become the de facto standard for tra

Qiao Sun, Xin Huang, Brian C. Williams, Hang Zhao

Motion prediction is crucial in enabling safe motion planning for autonomous vehicles in interactive scenarios. It allows the planner to identify potential conflicts with other traffic agents and generate safe plans. Existing motion predictors often focus on reducing prediction errors, yet it remains an open question on how well they help identify the confli

Björn Koopmann, Stefan Puch, Günter Ehmen, Martin Fränzle

In this paper, we propose an approach how connected and highly automated vehicles can perform cooperative maneuvers such as lane changes and left-turns at urban intersections where they have to deal with human-operated vehicles and vulnerable road users such as cyclists and pedestrians in so-called mixed traffic. In order to support cooperative maneuvers the

M. Yoneda

Regarding the duality of the XY-plaquette model in the $2+1d$ system, We compared and discussed the equivalence and difference between the modified Villain formulation, recently introduced by Gorantla et al. to study duality in exotic field theories such as fracton theory, and the standard Villain formulation and dual Hamiltonian method we introduced in our

Xinzhe Luo, Xiahai Zhuang

This paper presents a generic probabilistic framework for estimating the statistical dependency and finding the anatomical correspondences among an arbitrary number of medical images. The method builds on a novel formulation of the $N$-dimensional joint intensity distribution by representing the common anatomy as latent variables and estimating the appearanc

Yin Shi, D. R. Blackman, R. J. Kingham, A. V. Arefiev

We present results of twisted plasma waves driven by twisted ponderomotive force. With beating of two, co-propagating, Laguerre-Gaussian (LG) orbital angular momentum (OAM) laser pulses with different frequencies and also different twist indices, we can get twisted ponderomotive force. Three-dimensional particle-in-cell simulations are used to demonstrate th

Omkar Ranadive, Jisu Kim, Serin Lee, Youngseo Cha

Wildfires are a disastrous phenomenon which cause damage to land, loss of property, air pollution, and even loss of human life. Due to the warmer and drier conditions created by climate change, more severe and uncontrollable wildfires are expected to occur in the coming years. This could lead to a global wildfire crisis and have dire consequences on our plan

Qiuchen Zhang, Jing Ma, Jian Lou, Li Xiong

Deep learning models trained on large-scale data have achieved encouraging performance in many real-world tasks. Meanwhile, publishing those models trained on sensitive datasets, such as medical records, could pose serious privacy concerns. To counter these issues, one of the current state-of-the-art approaches is the Private Aggregation of Teacher Ensembles

Sébastien Roux, Patrice Loisel, Samuel Buis

We address the question of sensitivity analysis for model outputs of any dimension using Regional Sensitivity Analysis (RSA). Classical RSA computes sensitivity indices related to the impact of model inputs variations on the occurrence of a target region of the model output space. In this work, we invert this perspective by proposing to find, for a given tar

Jianwei Deng, Xu Guo, Yue Mei, Stephane Avril

It is of great significance to identify the nonhomogeneous distribution of material properties in human tissues for different clinical and medical applications. This leads to the requirement of solving an inverse problem in elasticity. The virtual fields method (VFM) is a rather recent inverse method with remarkable computational efficiency compared with the

Xiuyu Wu, Yunfang Wu

Chinese Grammatical Error Correction (CGEC) aims to generate a correct sentence from an erroneous sequence, where different kinds of errors are mixed. This paper divides the CGEC task into two steps, namely spelling error correction and grammatical error correction. Specifically, we propose a novel zero-shot approach for spelling error correction, which is s

M. V. Jyothirmai, D. Roshini, B. Moses Abraham, Jayant K. Singh

Two-dimensional materials supported by single atom catalysis (SACs) are foreseen to replace platinum for large-scale industrial scalability of sustainable hydrogen generation. Here, a series of metal (Al, Sc, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn) and non-metal (B, C, N, O, F, Si, P, S, Cl) single atoms embedded on various active sites of g-C$_3$N$_4$ are screened b

M. R. Azimi, I. Akbarbaglu, M. Asadipour

A bounded linear operator $T$ on a Banach space $X$ is called a convex-cyclic operator if there exists a vector $x \in X$ such that the convex hull of $Orb(T, x)$ is dense in $X$. In this paper, for given an aperiodic element $g$ in a locally compact group $G$, we give some sufficient conditions for a weighted translation operator $T_{g,w}: f \mapsto w\cdot

Yin Shi, David R Blackman, Ping Zhu, Alexey Arefiev

A linearly polarized Laguerre-Gaussian (LP-LG) laser beam with a twist index $l = -1$ has field structure that fundamentally differs from the field structure of a conventional linearly polarized Gaussian beam. Close to the axis of the LP-LG beam, the longitudinal electric and magnetic fields dominate over the transverse components. This structure offers an a

Christian Heider Nielsen, Zheng-Hua Tan

In recent years, significant progress has been made in deep model-based automatic speech recognition (ASR), leading to its widespread deployment in the real world. At the same time, adversarial attacks against deep ASR systems are highly successful. Various methods have been proposed to defend ASR systems from these attacks. However, existing classification

Ahmad Salmanogli

This study significantly concentrates on cryogenic InP HEMT high-frequency circuit analysis using quantum theory to find how the transistor nonlinearity can affect the quantum correlation of the modes generated in the circuit. Firstly, the total Hamiltonian of the circuit is derived, and the dynamic equation of the motion contributed is examined using the He

P. D. Marinos, G. P. Rowell, T. A. Porter, G. Jóhannesson

Cosmic Rays (CRs) interact with the diffuse gas, radiation, and magnetic fields in the interstellar medium (ISM) to produce electromagnetic emissions that are a significant component of the all-sky flux across a broad wavelength range. The Fermi Large Area Telescope (LAT) has measured these emissions at GeV $\gamma$-ray energies with high statistics. Meanwhi

Sutanu Bera, Prabir Kumar Biswas

The resurgence of deep neural networks has created an alternative pathway for low-dose computed tomography denoising by learning a nonlinear transformation function between low-dose CT (LDCT) and normal-dose CT (NDCT) image pairs. However, those paired LDCT and NDCT images are rarely available in the clinical environment, making deep neural network deploymen

Ilya Golokolenov, Sumit Kumar, Baptiste Alperin, Bruno Fernandez

Within recent years, the field of nano-mechanics has diversified in a variety of applications, ranging from quantum information processing to biological molecules recognition. Among the diversity of devices produced these days, the simplest (but versatile) element remains the doubly-clamped beam: it can store very large tensile stresses (producing high reson

Zhi-zhong Xing

Current neutrino oscillation data indicate that the $3\times 3$ Pontecorvo-Maki-Nakagawa-Sakata matrix $U$ exhibits a $\mu$-$\tau$ flavor interchange symmetry $|U^{}_{\mu i}| = |U^{}_{\tau i}|$ (for $i = 1, 2, 3$) as a good approximation. In particular, the T2K measurement implies that the maximal neutrino mixing angle $\theta^{}_{23}$ and the CP-violating p

James Jing Yu Zhao

Recently, the higher order Tur\'{a}n inequalities for the Boros-Moll sequences $\{d_\ell(m)\}_{\ell=0}^m$ were obtained by Guo. In this paper, we show a different approach to this result. Our proof is based on a criterion derived by Hou and Li, which need only checking four simple inequalities related to sufficiently sharp bounds for $d_\ell(m)^2/(d_{\ell-1}

Hui Wen Koay

Stripping extraction of hydrogen molecular ions has gained interest in the cyclotron industry due to its high extraction efficiency. However, the magnetic field could result in undesired Lorentz dissociation of the hydrogen anion/molecular ions during acceleration. Studies of dissociation under electric fields comparable to that of a Lorentz-transformed magn

Griffin Mooers, Tom Beucler, Mike Pritchard, Stephan Mandt

Despite the importance of quantifying how the spatial patterns of extreme precipitation will change with warming, we lack tools to objectively analyze the storm-scale outputs of modern climate models. To address this gap, we develop an unsupervised machine learning framework to quantify how storm dynamics affect changes in precipitation extremes, without sac

Fatemeh Rajabi-Alni, Alireza Bagheri

Given two sets A={a_1,a_2,...,a_s} and {b_1,b_2,...,b_t}, a many-to-many matching with demands and capacities (MMDC) between A and B matches each element a_i in A to at least \alpha_i and at most \alpha'_i elements in B, and each element b_j in B to at least \beta_j and at most \beta'_j elements in A for all 1=<i<=s and 1=<j<=t. In this paper, we present an

Christian B. Jepsen

For every prime number $p$ it is possible to define a $p$-adic version of the Veneziano amplitude and its higher-point generalizations. Multiplying together the real amplitude with all its $p$-adic counterparts yields the adelic amplitude. At four points it has been argued that the adelic amplitude, after regulating the product that defines it, equals one. F

Bowen Li, Bin Shi, Ya-xiang Yuan

For first-order smooth optimization, the research on the acceleration phenomenon has a long-time history. Until recently, the mechanism leading to acceleration was not successfully uncovered by the gradient correction term and its equivalent implicit-velocity form. Furthermore, based on the high-resolution differential equation framework with the correspondi

Chuanwen Zhao, Xin Yi, Qiao Chen, Chengyu Yan

Van der Waals (vdW) Josephson junctions can possibly accelerate the development of advanced superconducting device that utilizes the unique properties of two-dimensional (2D) transition metal dichalcogenide (TMD) superconductors such as spin-orbit coupling, spin-valley locking. Here, we fabricate vertically stacked NbS$_{2}$/NbS$_{2}$ Josephson junctions usi

Arijit Manna, Sabyasachi Pal

The studies of the complex organic molecular lines towards the hot molecular cores at millimeter and submillimeter wavelengths provide instructive knowledge about the chemical complexity in the interstellar medium (ISM). We present the detection of the rotational emission lines of the complex nitrogen-bearing molecule ethyl cyanide (C$_{2}$H$_{5}$CN) towards

An Zeng, Chunbiao Wu, Meiping Huang, Jian Zhuang

Cardiovascular disease (CVD) accounts for about half of non-communicable diseases. Vessel stenosis in the coronary artery is considered to be the major risk of CVD. Computed tomography angiography (CTA) is one of the widely used noninvasive imaging modalities in coronary artery diagnosis due to its superior image resolution. Clinically, segmentation of coron

Ayan Ghosh, Souvik Chakraborty, Unmesh Ghorai, Arup Kumar Paul

Recently, magic-angle twisted bilayer graphene (MATBLG) has shown the emergence of various interaction-driven novel quantum phases at the commensurate fillings of the moir'e superlattice, while the charge neutrality point (CNP) remains mostly a vanilla insulator. Here, we show an emerging phase of nearly compensated semimetallicity at the CNP of twisted doub

Abdul Muneem, Junya Yoshida, Hiroyuki Ekawa, Masahiro Hino

Fluorescent nuclear track detectors (FNTDs) based on Al${_2}$O${_3}$:C,Mg crystals are luminescent detectors that can be used for dosimetry and detection of charged particles and neutrons. These detectors can be utilised for imaging applications where a reasonably high track density, approximately of the order of 1 $\times$ $10^4$ tracks in an area of 100 $\

Hyo Jung Park, Anna Lappala

Knots are entangled structures that cannot be untangled without a cut. Topological stability of knots is one of the many examples of their important properties that can be used in information storage and transfer. Knot dynamics is important for understanding general principles of entanglement as knots provide an isolated system where tangles are highly contr

Tian Qin, Alex Beatson, Deniz Oktay, Nick McGreivy

Partial differential equations (PDEs) are often computationally challenging to solve, and in many settings many related PDEs must be be solved either at every timestep or for a variety of candidate boundary conditions, parameters, or geometric domains. We present a meta-learning based method which learns to rapidly solve problems from a distribution of relat

Saish Jaiswal, Shreya Nema, Hema A Murthy, Manikandan Narayanan

Genomic signal processing has been used successfully in bioinformatics to analyze biomolecular sequences and gain varied insights into DNA structure, gene organization, protein binding, sequence evolution, etc. But challenges remain in finding the appropriate spectral representation of a biomolecular sequence, especially when multiple variable-length sequenc

Mesut Yang, Micah Carroll, Anca Dragan

AI agents designed to collaborate with people benefit from models that enable them to anticipate human behavior. However, realistic models tend to require vast amounts of human data, which is often hard to collect. A good prior or initialization could make for more data-efficient training, but what makes for a good prior on human behavior? Our work leverages

Jiangwei Hou, Qiaozhu Zhai, Yuzhou Zhou, Xiaohong Guan

The unit commitment problem (UC) is crucial for the operation and market mechanism of power systems. With the development of modern electricity, the scale of power systems is expanding, and solving the UC problem is also becoming more and more difficult. To this end, this paper proposes a new fast solution method based on Lagrangian relaxation and dynamic pr

Lily Goli, Daniel Rebain, Sara Sabour, Animesh Garg

We introduce a technique for pairwise registration of neural fields that extends classical optimization-based local registration (i.e. ICP) to operate on Neural Radiance Fields (NeRF) -- neural 3D scene representations trained from collections of calibrated images. NeRF does not decompose illumination and color, so to make registration invariant to illuminat

Jungwoo Heo, Hyun-seo Shin, Ju-ho Kim, Chan-yeong Lim

In music, short-term features such as pitch and tempo constitute long-term semantic features such as melody and narrative. A music genre classification (MGC) system should be able to analyze these features. In this research, we propose a novel framework that can extract and aggregate both short- and long-term features hierarchically. Our framework is based o

Gaurav Kumar Nayak, Ruchit Rawal, Inder Khatri, Anirban Chakraborty

The high cost of acquiring and annotating samples has made the `few-shot' learning problem of prime importance. Existing works mainly focus on improving performance on clean data and overlook robustness concerns on the data perturbed with adversarial noise. Recently, a few efforts have been made to combine the few-shot problem with the robustness objective u

Yuka Yamaguchi, Naoya Yamaguchi

We determine all possible values of the integer group determinant of ${\rm C}_{4}^{2}$, where ${\rm C}_{4}$ is the cyclic group of order $4$.

Karthik Natarajan, Arjun Kodagehalli Ramachandra, Colin Tan

A collection of $n$ random events is said to be $(n - 1)$-wise independent if any $n - 1$ events among them are mutually independent. We characterise all probability measures with respect to which $n$ random events are $(n - 1)$-wise independent. We provide sharp upper and lower bounds on the probability that at least $k$ out of $n$ events with given margina

Siddharth Chandak, Pratik Shah, Vivek S Borkar, Parth Dodhia

Motivated by the novel paradigm developed by Van Roy and coauthors for reinforcement learning in arbitrary non-Markovian environments, we propose a related formulation and explicitly pin down the error caused by non-Markovianity of observations when the Q-learning algorithm is applied on this formulation. Based on this observation, we propose that the criter

Kerun Shao, Chengbo Wang

Considering $1+n$ dimensional semilinear wave equations with energy supercritical powers $p> 1+4/(n-2)$, we obtain global solutions for any initial data with small norm in $H^{s_c}\times H^{s_c-1}$, under the technical smooth condition $p>s_c-\bar{s}_0$, with $\bar{s}_0= 1/2+(n-3)/(2\max(n-1-p,n-3))$ and $s_c=n/2-2/(p-1)$. In particular, combined with previo

Aishwaryadev Banerjee, Carlos H. Mastrangelo

Quantum tunneling sensors are typically ultra-sensitive devices which have been specifically designed to convert a stimulus into an electronic signal using the wondrous principles of quantum mechanical tunneling. In the early 1990s, William Kaiser developed one of the first micromachined quantum tunneling sensors as part of his work with the Nasa Jet Propuls

Sohom Dutta, Steven J. Miller

Building on the work of Iwaniec, Luo and Sarnak, we use the $n$-level density to bound the probability of vanishing to order at least $r$ at the central point for families of cuspidal newforms of prime level $N \to \infty$, split by sign. There are three methods to improve bounds on the order of vanishing: optimizing the test functions, increasing the suppor

Chong Chen, Ying Gao, Leyu Shi, Siquan Huang

Healthcare IoMT systems are becoming intelligent, miniaturized, and more integrated into daily life. As for the distributed devices in the IoMT, federated learning has become a topical area with cloud-based training procedures when meeting data security. However, the distribution of IoMT has the risk of protection from data poisoning attacks. Poisoned data c

Steven G. Xu, Shu Yang, Brian J. Reich

Standard causal inference characterizes treatment effect through averages, but the counterfactual distributions could be different in not only the central tendency but also spread and shape. To provide a comprehensive evaluation of treatment effects, we focus on estimating quantile treatment effects (QTEs). Existing methods that invert a nonsmooth estimator

Zhicheng Tong, Shuyuan Xiao, Yong Li

By introducing the modulus of continuity, we first establish the corresponding cross-ratio distortion estimates under $ C^2 $ smoothness, and further derive a Denjoy-type inequality, which is almost optimal for dealing with circle diffeomorphisms. The latter plays a prominent role in the study of $ C^1 $ conjugacy to irrational rotations. We also establish a

Wadnerson Boileau

Insurance has been around for more than centuries. This risk mitigation strategy has been utilized in maritime commerce as early thousand years ago, where Asian merchant seafarers were pooling together their wares in collective funds to pay for damages of individual capsized ship. In 2018, insurance industry made up 6 percent of global GDP while financial in

Yuan Hu, Zhibin Wang, Zhou Huang, Yu Liu

We present PolyBuilding, a fully end-to-end polygon Transformer for building extraction. PolyBuilding direct predicts vector representation of buildings from remote sensing images. It builds upon an encoder-decoder transformer architecture and simultaneously outputs building bounding boxes and polygons. Given a set of polygon queries, the model learns the re

Xiaoxiao Li, Zhao Song, Runzhou Tao, Guangyi Zhang

Federated learning enables a large amount of edge computing devices to learn a model without data sharing jointly. As a leading algorithm in this setting, Federated Average FedAvg, which runs Stochastic Gradient Descent (SGD) in parallel on local devices and averages the sequences only once in a while, have been widely used due to their simplicity and low co