November 2022 arXiv papers — page 74

Wan-Ting Hou, Jing-Zhao Qi, Tao Han, Jing-Fei Zhang

With the measurement of the electromagnetic (EM) counterpart, a gravitational wave (GW) event could be treated as a standard siren. As a novel cosmological probe, GW standard sirens will bring significant implications for cosmology. In this paper, by considering the coincident detections of GW and associated $\gamma$ ray burst (GRB), we find that only about

Kaspar Beelen, Daniel van Strien

This paper discusses the benefits of including metadata when training language models on historical collections. Using 19th-century newspapers as a case study, we extend the time-masking approach proposed by Rosin et al., 2022 and compare different strategies for inserting temporal, political and geographical information into a Masked Language Model. After f

Mingyu Kang, Duxin Chen, Ning Meng, Gang Yan

Identifying vanilla Bayesian network to model spatial-temporal causality can be a critical yet challenging task. Different Markovian-equivalent directed acyclic graphs would be identified if the identifiability is not satisfied. To address this issue, Directed Cyclic Graph is proposed to drop the directed acyclic constraint. But it does not always hold, and

Danan Yang, Himani Garg, Martin Andersson

Liquid water within the cathode Gas Diffusion Layer (GDL) and Gas Channel (GC) of Proton Exchange Membrane Fuel Cells (PEMFCs) is strongly coupled to gas transport properties, thereby affecting the electrochemical conversion rates. In this study, the GDL and GC regions are utilized as the simulation domain, which differs from previous studies that only focus

Pingzhi Yuan

In this paper, we provide a local method to find compositional inverses of all PPs, some new PPs and their compositional inverses are given.

Audra McMillan, Omid Javidbakht, Kunal Talwar, Elliot Briggs

Privately learning statistics of events on devices can enable improved user experience. Differentially private algorithms for such problems can benefit significantly from interactivity. We argue that an aggregation protocol can enable an interactive private federated statistics system where user's devices maintain control of the privacy assurance. We describ

Eleonora Denich, Paolo Novati, Stefano Picotti

This paper deals with the solution of Maxwell's equations to model the electromagnetic fields in the case of a layered earth. The integrals involved in the solution are approximated by means of a novel approach based on the splitting of the reflection term. The inverse problem, consisting in the computation of the unknown underground conductivity distributio

Yue Hao, Silu Huang, Xiaowen Xu

For solving the discretized three-temperature energy linear systems, Xu et al. proposed a physical-variable based coarsening two-level iterative method (PCTL algorithm) in 2009 and verified its efficiency by numerical experiments in practical applications. In this paper, we study in detail the specific convergence property of the PCTL algorithm based on the

F. Romano, G. Herdrich, Y. -A. Chan, N. H. Crisp

Challenging space missions include those at very low altitudes, where the atmosphere is source of aerodynamic drag on the spacecraft that finally defines the missions lifetime unless way to compensate for it is provided. This environment is named Very Low Earth Orbit (VLEO) and is defined for $h<450~km$. In addition to the satellite's aerodynamic design, to

Shangyun Wang, Songbai Chen, Jiliang Jing

We investigate the classical-quantum correspondence in the inverted harmonic oscillator (IHO) system. It is shown that the out-of-time-order correlators (OTOCs) which the initial states are located at any position in the IHO system possess the same exponential growth rates (EGRs) as that at the saddle point, and their EGRs are twice the classical lyapunov ex

Yuta Watanabe

In this article, we first establish an $L^2$-type Dolbeault isomorphism for the sheaf of logarithmic differential forms twisted by the multiplier ideal sheaf. By using this isomorphism and $L^2$-estimates equipped with a singular Hermitian metric, we obtain logarithmic vanishing theorems involving multiplier ideal sheaves on compact K\"ahler manifolds with s

Anpeng Zhang, Xiutao Feng

This paper presents a new method to reduce the optimization of a pseudo-Boolean function to QUBO problem which can be solved by quantum annealer. The new method has two aspects, one is coefficient optimization and the other is variable optimization. The former is an improvement on the existing algorithm in a special case. The latter is realized by means of t

Rizhong Wang, Huiping Li, Bin Liang, Yang Shi

The unaffordable computation load of nonlinear model predictive control (NMPC) has prevented it for being used in robots with high sampling rates for decades. This paper is concerned with the policy learning problem for nonlinear MPC with system constraints, and its applications to unmanned surface vehicles (USVs), where the nonlinear MPC policy is learned o

Demessie Ergabus Birmechu, Hunduma Legesse Geleta

Some zero-free regions were known on the right half of the complex plane in the form of vertical strips for fractional hypergeometric zeta functions. In this paper, we describe and demonstrate zero free regions on the left half of the complex plane for fractional hypergeometric zeta functions. The fractional hypergeometric zeta function of order $a$ has no z

Meduri Venkata Shivaditya, Francesca Bugiotti, Frederic Magoules

In this paper, we explore point-cloud based deep learning models to analyze numerical simulations arising from finite element analysis. The objective is to classify automatically the results of the simulations without tedious human intervention. Two models are here presented: the Point-Net classification model and the Dynamic Graph Convolutional Neural Net m

Rishabh Thakkar, Prasad Hegde

Knowledge of the screening masses at finite chemical potential can provide insight into the nature of the QCD phase diagram. However, lattice studies at finite chemical potential suffer from the well-known issue of the sign problem, which has made the calculation of observables such as screening correlators and screening masses at finite chemical potential q

O. G. Styrt

An equivalent condition for the product of elements of an independent random sample on a compact algebraic group converging in distribution to some random variable as the sample size increases is obtained. Namely, a limit distribution exists and is uniform on the support of the parent distribution if a random variable with such a distribution does not belong

Bumjin Park, Jaesik Choi

As the number of fine tuning of pretrained models increased, understanding the bias of pretrained model is essential. However, there is little tool to analyse transformer architecture and the interpretation of the attention maps is still challenging. To tackle the interpretability, we propose Input-Attribution and Attention Score Vector (IAV) which measures

Zhuoning Li, Zhenli Xu, Zhiguo Yang

We present an efficient and accurate energy-conserving implicit particle-in-cell~(PIC) algorithm for the electrostatic Vlasov system, with particular emphasis on its high robustness for simulating complex plasma systems with multiple physical scales. This method consists of several indispensable elements: (\romannumeral1) the reformulation of the original Vl

Gavin Brown, Tom Coates, Alessio Corti, Tom Ducat

Fano varieties are 'atomic pieces' of algebraic varieties, the shapes that can be defined by polynomial equations. We describe the role of computation and database methods in the construction and classification of Fano varieties, with an emphasis on three-dimensional Fano varieties with mild singularities called Q-Fano threefolds. The classification of Q-Fan

MuSeong Kim, Mi-Ra Hwang, Eylee Jung, DaeKil Park

Scrambling is a concept introduced from information loss problem arising in black hole. In this paper we discuss the effect of scrambling from a perspective of pure quantum information theory. We introduce $7$-qubit quantum circuit for a quantum teleportation. It is shown that the teleportation can be perfect if a maximal scrambling unitary is used. From thi

Brahim Dridi, Rached Jaidane

In this article, we study the following problem $$\Delta(w(x)\Delta u) = \ f(x,u) \quad\mbox{ in }\quad B, \quad u=\frac{\partial u}{\partial n}=0 \quad\mbox{ on } \quad\partial B,$$ where $B$ is the unit ball of $\mathbb{R}^{4}$ and $ w(x)$ a singular weight of logarithm type. The reaction source $f(x,u)$ is a radial function with respect to $x$ and it is c

Clément Bonet, Laetitia Chapel, Lucas Drumetz, Nicolas Courty

It has been shown beneficial for many types of data which present an underlying hierarchical structure to be embedded in hyperbolic spaces. Consequently, many tools of machine learning were extended to such spaces, but only few discrepancies to compare probability distributions defined over those spaces exist. Among the possible candidates, optimal transport

Tiziano Granucci

In this paper we study the everywhere H\"older continuity of the minima of a class of vectorial integral functionals

Leon O. Guertler, Andri Ashfahani, Anh Tuan Luu

The long-standing challenge of building effective classification models for small and imbalanced datasets has seen little improvement since the creation of the Synthetic Minority Over-sampling Technique (SMOTE) over 20 years ago. Though GAN based models seem promising, there has been a lack of purpose built architectures for solving the aforementioned proble

Anoop Mutneja, Smarajit Karmakar

The growth of correlation lengths in equilibrium glass-forming liquids near the glass transition is considered a critical finding in the quest to understand the physics of glass formation. These understandings helped us understand various dynamical phenomena observed in supercooled liquids. It is known that at least two different length scales exist - one is

Chang Zhang, Guo-Yin Zhang, Jin-Zeng Li, Jing-Hua Yuan

Massive young stellar objects (MYSOs) play a crucial role in star formation. Given that MYSOs were previously identified based on the extended structure and the observational data for them is limited, screening the Wide-field Infrared Survey Explorer (WISE) objects showing green features (for the common coding of the 4.6 $\mu$m band as green channel in three

Moyuru Yamada

Object detection is a computer vision task of predicting a set of bounding boxes and category labels for each object of interest in a given image. The category is related to a linguistic symbol such as 'dog' or 'person' and there should be relationships among them. However the object detector only learns to classify the categories and does not treat them as

Martin Kodys, Zhi Lu, Kar Wai Fok, Vrizlynn L. L. Thing

Internet of Things (IoT) has become a popular paradigm to fulfil needs of the industry such as asset tracking, resource monitoring and automation. As security mechanisms are often neglected during the deployment of IoT devices, they are more easily attacked by complicated and large volume intrusion attacks using advanced techniques. Artificial Intelligence (

Ben Dai, Xiaotong Shen, Lin Yee Chen, Chunlin Li

In explainable artificial intelligence, discriminative feature localization is critical to reveal a blackbox model's decision-making process from raw data to prediction. In this article, we use two real datasets, the MNIST handwritten digits and MIT-BIH Electrocardiogram (ECG) signals, to motivate key characteristics of discriminative features, namely adapti

Wei Luo, Haiming Yao, Wenyong Yu

Visual anomaly detection plays a significant role in the development of industrial automatic product quality inspection. As a result of the utmost imbalance in the amount of normal and abnormal data, growing attention has been given to unsupervised methods for defect detection. Although existing reconstruction-based methods have been widely studied recently,

Osamu Seto, Tetsuo Shindou, Takanao Tsuyuki

We show that three open questions in particle physics and cosmology: the origin of neutrino mass, the identity of dark matter, and the origin of the baryon asymmetry of the universe can be explained simultaneously in the three-loop seesaw model proposed by Krauss, Nasri, and Trodden. We discuss the difficulty of successful leptogenesis with three right-hande

Linjie Song, Hichem Hajaiej

We give a new method to prove the existence, non-existence, multiplicity, orbital stability/instability of standing waves for NLS with partial confinement without the subcritical hypothesis, even in the reduction equation. Using this method, we give an affirmative answer for an open problem proposed by [7, Remark 1.10] where the authors conjectured the exist

Firoj Alam, Hamdy Mubarak, Wajdi Zaghouani, Giovanni Da San Martino

Propaganda is the expression of an opinion or an action by an individual or a group deliberately designed to influence the opinions or the actions of other individuals or groups with reference to predetermined ends, which is achieved by means of well-defined rhetorical and psychological devices. Propaganda techniques are commonly used in social media to mani

Zongshang Pang, Yuta Nakashima, Mayu Otani, Hajime Nagahara

Video summarization aims to select the most informative subset of frames in a video to facilitate efficient video browsing. Unsupervised methods usually rely on heuristic training objectives such as diversity and representativeness. However, such methods need to bootstrap the online-generated summaries to compute the objectives for importance score regressio

Ting Yan, Yuanzhang Li, Jinfeng Xu, Yaning Yang

Likelihood ratio tests and the Wilks theorems have been pivotal in statistics but have rarely been explored in network models with an increasing dimension. We are concerned here with likelihood ratio tests in the $\beta$-model for undirected graphs. For two growing dimensional null hypotheses including a specified null $H_0: \beta_i=\beta_i^0$ for $i=1,\ldot

Yufan Liao, Qi Wu, Zhaodi Wu, Xing Yan

Invariant learning methods, aimed at identifying a consistent predictor across multiple environments, are gaining prominence in out-of-distribution (OOD) generalization. Yet, when environments aren't inherent in the data, practitioners must define them manually. This environment partitioning--algorithmically segmenting the training dataset into environments-

Zhiling Wang, Zenghui Bao, Yan Li, Yukai Wu

A photonic transistor that can switch or amplify an optical signal with a single gate photon requires strong non-linear interaction at the single-photon level. Circuit quantum electrodynamics provides great flexibility to generate such an interaction, and thus could serve as an effective platform to realize a high-performance single-photon transistor. Here w

Chao Hu, Liqiang Zhu

Aiming at the problem that the current video anomaly detection cannot fully use the temporal information and ignore the diversity of normal behavior, an anomaly detection method is proposed to integrate the spatiotemporal information of pedestrians. Based on the convolutional autoencoder, the input frame is compressed and restored through the encoder and dec

Tatsuya Matsumoto, Tsvi Piran

The equipartition analysis yields estimates of the radius and energy of synchrotron self-absorbed radio sources. Here we generalize this method to relativistic off-axis viewed emitters. We find that the Lorentz factor $\Gamma$ and the viewing angle $\theta$ cannot be determined independently but become degenerate along a trajectory of minimal energy solution

Ruolan Jin, C. -Y. Ng, Mallory S. E. Roberts, Kwan-Lok Li

The Dragonfly Nebula (G75.2$+$0.1) powered by the young pulsar J2021$+$3651 is a rare pulsar wind nebula (PWN) that shows double tori and polar jets enclosed by a bow-shock structure in X-rays. We present new radio observations of this source taken with the Very Large Array (VLA) at 6 GHz. The radio PWN has an overall size about two times as large as the X-r

Sumio Watanabe

This article is a review of theoretical advances in the research field of algebraic geometry and Bayesian statistics in the last two decades. Many statistical models and learning machines which contain hierarchical structures or latent variables are called nonidentifiable, because the map from a parameter to a statistical model is not one-to-one. In nonident

Kar Wai Fok, Vrizlynn L. L. Thing

Malwares are the key means leveraged by threat actors in the cyber space for their attacks. There is a large array of commercial solutions in the market and significant scientific research to tackle the challenge of the detection and defense against malwares. At the same time, attackers also advance their capabilities in creating polymorphic and metamorphic

Srinivas Virinchi, Anoop Saladi, Abhirup Mondal

Related product recommendation (RPR) is pivotal to the success of any e-commerce service. In this paper, we deal with the problem of recommending related products i.e., given a query product, we would like to suggest top-k products that have high likelihood to be bought together with it. Our problem implicitly assumes asymmetry i.e., for a phone, we would li

Shiquan Ma, Rongyu Dong, Yi-Jian Du

It is well known that gravity amplitudes in four dimensions can be reconstructed by the inverse soft limit (ISL) method. According to ISL, a tree level $n$-graviton maximally-helicity-violating (MHV) amplitude is expressed in terms of deformed $(n-1)$-graviton amplitudes accompanied by soft graviton factors. On another hand, single- and double-trace tree-lev

Jason Gavriel, Daniel Herr, Alexis Shaw, Michael J. Bremner

Fault-tolerant, error-corrected quantum computation is commonly acknowledged to be crucial to the realisation of large-scale quantum algorithms that could lead to extremely impactful scientific or commercial results. Achieving a universal set of quantum gate operations in a fault-tolerant error-corrected framework suffers from a `conservation of unpleasantne

Peggy Pei-Ying Lu, Makoto Konishi, Shin Sano, Sho Hiruta

Recent advances in technology have allowed an automation system to recognize its errors and repair trust more actively than ever. While previous research has called for further studies of different human factors and design features, their effect on human-automation trust repair scenarios remains unknown, especially concerning emotions. This paper seeks to fi

William Q. Erickson, Daniel Herden, Jonathan Meddaugh, Mark R. Sepanski

For a graph $G$ and an abelian group $A$, a labeling of the vertices of $G$ induces a labeling of the edges via the sum of adjacent vertex labels. Hovey introduced the notion of an $A$-cordial vertex labeling when both the vertex and edge labels are as evenly distributed as possible. Much work has since been done with trees, hypertrees, paths, cycles, ladder

Emerald U. Henry, Onyeka Emebob, Conrad Asotie Omonhinmin

Transformer, a model comprising attention-based encoder-decoder architecture, have gained prevalence in the field of natural language processing (NLP) and recently influenced the computer vision (CV) space. The similarities between computer vision and medical imaging, reviewed the question among researchers if the impact of transformers on computer vision be

Hang-Hyun Jo

To characterize temporal correlations in temporal networks, we define an autocorrelation function (ACF) for temporal networks in terms of the similarity between two snapshot networks separated by a certain time interval. By employing a copula-based method recently developed for a single time series, we analyze the ACF for the temporal network in which activi

Wei-Ning Chen, Ayfer Özgür, Graham Cormode, Akash Bharadwaj

We consider the federated frequency estimation problem, where each user holds a private item $X_i$ from a size-$d$ domain and a server aims to estimate the empirical frequency (i.e., histogram) of $n$ items with $n \ll d$. Without any security and privacy considerations, each user can communicate its item to the server by using $\log d$ bits. A naive applica

Huawei Hou, Suzhi Bi, Lili Zheng, Xiaohui Lin

Accurate indoor crowd counting (ICC) is a key enabler to many smart home/office applications. In this paper, we propose a Domain-Agnostic and Sample-Efficient wireless indoor crowd Counting (DASECount) framework that suffices to attain robust cross-domain detection accuracy given very limited data samples in new domains. DASECount leverages the wisdom of few

Zeping Min, Qian Ge, Cheng Tai

Recently, pseudo label based semi-supervised learning has achieved great success in many fields. The core idea of the pseudo label based semi-supervised learning algorithm is to use the model trained on the labeled data to generate pseudo labels on the unlabeled data, and then train a model to fit the previously generated pseudo labels. We give a theory anal

Wahab Khawaja, Martins Ezuma, Vasilii Semkin, Fatih Erden

The use of unmanned aerial vehicles (UAVs) for different applications has increased many folds in recent years. The UAVs are expected to change the future air operations. However, there are instances where the UAVs can be used for malicious purposes. The detection, tracking, and classification of UAVs is challenging compared to manned aerial vehicles (MAVs)

Jonathan Gruber

We use minimal tilting complexes to construct an explicit bijection between the set of thick tensor ideals with the two-out-of-three property in the category of finite-dimensional modules over a quantum group at a root of unity and the set of thick tensor ideals in the subcategory of tilting modules. We also explain why the analogous construction for rationa

Amit Kumar Ror, Rahul Gupta, Martin Jelínek, Shashi Bhushan Pandey

We present a detailed prompt emission and early optical afterglow analysis of the two very high energy (VHE) detected bursts GRB 201015A and GRB 201216C, and their comparison with a subset of similar bursts. Time-resolved spectral analysis of multi-structured GRB 201216C using the Bayesian binning algorithm revealed that during the entire duration of the bur

Rebecca L. Larson, Taylor A. Hutchison, Micaela Bagley, Steven L. Finkelstein

The selection of high-redshift galaxies often involves spectral energy distribution (SED) fitting to photometric data, an expectation for contamination levels, and measurement of sample completeness -- all vetted through comparison to spectroscopic redshift measurements of a sub-sample. The first JWST data is now being taken over several extragalactic fields

Abeed Sarker

Substance use, substance use disorder, and overdoses related to substance use are major public health problems globally and in the United States. A key aspect of addressing these problems from a public health standpoint is improved surveillance. Traditional surveillance systems are laggy, and social media are potentially useful sources of timely data. Howeve

Saugata Basu, Ali Mohammad-Nezhad

Let $\mathrm{R}$ be a real closed field. Given a closed and bounded semi-algebraic set $A \subset \mathrm{R}^n$ and semi-algebraic continuous functions $f,g:A \rightarrow \mathrm{R}$, such that $f^{-1}(0) \subset g^{-1}(0)$, there exist $N$ and $c \in \mathrm{R}$, such that the inequality ({\L}ojasiewicz inequality) $|g(x)|^N \le c \cdot |f(x)|$ holds for al

Bibek Upadhayay, Vahid Behzadan

Machine learning models are known to be vulnerable to adversarial perturbations in the input domain, causing incorrect predictions. Inspired by this phenomenon, we explore the feasibility of manipulating EEG-based Motor Imagery (MI) Brain Computer Interfaces (BCIs) via perturbations in sensory stimuli. Similar to adversarial examples, these \emph{adversarial

Ying Jin, Dominik Rothenhäusler

This paper develops a new framework, called modular regression, to utilize auxiliary information -- such as variables other than the original features or additional data sets -- in the training process of linear models. At a high level, our method follows the routine: (i) decomposing the regression task into several sub-tasks, (ii) fitting the sub-task model

Kai Shi, Yu Tian, Xiaoning Wu, Hongbao Zhang

We perform a thorough analysis of the dynamic and thermodynamic stability for the charged perfect fluid star by applying the Wald formalism to the Lagrangian formulation of Einstein-Maxwell-charged fluid system. As a result, we find that neither the presence of the additional electromagnetic field nor the Lorentz force experienced by the charged fluid makes

Kunpeng Jia, Xinwei Yi, Xiaohan Wang, Yunfeng Liu

Microresonator-based optical frequency comb (microcomb) has the potential to revolutionize the accuracy of frequency synthesizer in radar and communication applications. However, fundamental limit exists for low noise microcomb generation, especially in low size, weight, power and cost (SWaP-C) package. Here we resolve this limit, by the demonstration of an

Qinggang Zhang, Junnan Dong, Keyu Duan, Xiao Huang

Knowledge Graph (KG) errors introduce non-negligible noise, severely affecting KG-related downstream tasks. Detecting errors in KGs is challenging since the patterns of errors are unknown and diverse, while ground-truth labels are rare or even unavailable. A traditional solution is to construct logical rules to verify triples, but it is not generalizable sin

Joshua J. Bon, Adam Bretherton, Katie Buchhorn, Susanna Cramb

Building on a strong foundation of philosophy, theory, methods and computation over the past three decades, Bayesian approaches are now an integral part of the toolkit for most statisticians and data scientists. Whether they are dedicated Bayesians or opportunistic users, applied professionals can now reap many of the benefits afforded by the Bayesian paradi

Tanvi S. Patel, Srinivasakranthikiran Kolachina, Daxesh P. Patel, Pranav S. Shrivastav

A database is a prime target for cyber-attacks as it contains confidential, sensitive, or protected information. With the increasing sophistication of the internet and dependencies on internet data transmission, it has become vital to be aware of various encryption technologies and trends. It can assist in safeguarding private information and sensitive data,

P. Srikanth, Adarsh Kumar

Quantum computing research might lead to "quantum leaps," and it could have unanticipated repercussions in the medical field. This technique has the potential to be used in a broad range of contexts, some of which include the development of novel drugs, the individualization of medical treatments, and the speeding of DNA sequencing. This work has assembled a

Salma Gonzalez-Sabbagh, Antonio Robles-Kelly, Shang Gao

Underwater images are usually covered with a blue-greenish colour cast, making them distorted, blurry or low in contrast. This phenomenon occurs due to the light attenuation given by the scattering and absorption in the water column. In this paper, we present an image enhancement approach for dewatering which employs a conditional generative adversarial netw

Ana Beatriz L. B. Fernandes, Zhichao Shao, Lukas T. N. Landau, Rodrigo C. de Lamare

Low-resolution analog-to-digital converters (ADCs) are promising for reducing energy consumption and costs of multiuser multiple-input multiple-output (MIMO) systems with many antennas. We propose low-resolution multiuser MIMO receivers where the signals are simultaneously processed by 1-bit ADCs and a comparator network, which can be interpreted as addition

Stephen Casper, Kaivalya Hariharan, Dylan Hadfield-Menell

This paper considers the problem of helping humans exercise scalable oversight over deep neural networks (DNNs). Adversarial examples can be useful by helping to reveal weaknesses in DNNs, but they can be difficult to interpret or draw actionable conclusions from. Some previous works have proposed using human-interpretable adversarial attacks including copy/

Ming-Yuan Yu, Ram Vasudevan, Matthew Johnson-Roberson

LiDARs have been widely adopted to modern self-driving vehicles, providing 3D information of the scene and surrounding objects. However, adverser weather conditions still pose significant challenges to LiDARs since point clouds captured during snowfall can easily be corrupted. The resulting noisy point clouds degrade downstream tasks such as mapping. Existin

Amir Abboud, Seri Khoury, Oree Leibowitz, Ron Safier

In this note we present an algorithm that lists all $4$-cycles in a graph in time $\tilde{O}(\min(n^2,m^{4/3})+t)$ where $t$ is their number. Notably, this separates $4$-cycle listing from triangle-listing, since the latter has a $(\min(n^3,m^{3/2})+t)^{1-o(1)}$ lower bound under the $3$-SUM Conjecture. Our upper bound is conditionally tight because (1) $O(n

Matteo Ferraresso, Albert Kong, Mehadi Hasan, Gwynn J. Elfring

Cytoskeletal gels are prototyped to reproduce the mechanical contraction of the cytoskeleton in-vitro. They are composed of a polymer network (backbone), swollen by the presence of a liquid solvent, and active molecules (molecular motors, MMs) that transduce chemical energy into the mechanical work of contraction. These motors attach to the polymer chains to

Liliaokeawawa Cothren, Gianluca Bianchin, Sarah Dean, Emiliano Dall'Anese

Motivated by perception-based control problems in autonomous systems, this paper addresses the problem of developing feedback controllers to regulate the inputs and the states of a dynamical system to optimal solutions of an optimization problem when one has no access to exact measurements of the system states. In particular, we consider the case where the s

Shihang Zhang, Yu He, Peihao Huang

Long coherence time and compatibility with semiconductor fabrication make spin qubits in silicon an attractive platform for quantum computing. In recent years, hole spin qubits are being developed as they have the advantages of weak coupling to nuclear spin noise and strong spin-orbit coupling (SOC), in constructing high-fidelity quantum gates. However, ther

Yew Ken Chia, Lidong Bing, Sharifah Mahani Aljunied, Luo Si

Relation extraction has the potential for large-scale knowledge graph construction, but current methods do not consider the qualifier attributes for each relation triplet, such as time, quantity or location. The qualifiers form hyper-relational facts which better capture the rich and complex knowledge graph structure. For example, the relation triplet (Leona

Young Jin Kim, Rawn Henry, Raffy Fahim, Hany Hassan Awadalla

Mixture of Experts (MoE) models with conditional execution of sparsely activated layers have enabled training models with a much larger number of parameters. As a result, these models have achieved significantly better quality on various natural language processing tasks including machine translation. However, it remains challenging to deploy such models in

Yuliang Xin, Xiaolei Guo

We report the extended GeV $\gamma$-ray emission that spatially associated with the high Galactic latitude supernova remnant (SNR) candidate - Calvera's SNR with the Pass 8 data recorded by the {\em Fermi} Large Area Telescope. The $\gamma$-ray spectrum of Calvera's SNR between 100 MeV and 1 TeV shows an evident ($\sim$ 3.4$\sigma$) spectral curvature at sev

Tonglin Zhang

The $k$-means is one of the most important unsupervised learning techniques in statistics and computer science. The goal is to partition a data set into many clusters, such that observations within clusters are the most homogeneous and observations between clusters are the most heterogeneous. Although it is well known, the investigation of the asymptotic pro

Roshan Ayyalasomayajula, Aditya Arun, Wei Sun, Dinesh Bharadia

WiFi-based indoor localization has now matured for over a decade. Most of the current localization algorithms rely on the WiFi access points (APs) in the enterprise network to localize the WiFi user accurately. Thus, the WiFi user's location information could be easily snooped by an attacker listening through a compromised WiFi AP. With indoor localization a

Hideitsu Hino, Shinto Eguchi

Active learning is a widely used methodology for various problems with high measurement costs. In active learning, the next object to be measured is selected by an acquisition function, and measurements are performed sequentially. The query by committee is a well-known acquisition function. In conventional methods, committee disagreement is quantified by the

Shehroz S. Khan, Ali Abedi

Physical activity is recognized as an essential component of overall health. One measure of physical activity, the step count, is well known as a predictor of long-term morbidity and mortality. Step Counting (SC) is the automated counting of the number of steps an individual takes over a specified period of time and space. Due to the ubiquity of smartphones

Guanqin Zhang, Jiankun Sun, Feng Xu, H. M. N. Dilum Bandara

Deep neural networks (DNNs), are widely used in many industries such as image recognition, supply chain, medical diagnosis, and autonomous driving. However, prior work has shown the high accuracy of a DNN model does not imply high robustness (i.e., consistent performances on new and future datasets) because the input data and external environment (e.g., soft

Alexander Partin, Thomas S. Brettin, Yitan Zhu, Oleksandr Narykov

Cancer claims millions of lives yearly worldwide. While many therapies have been made available in recent years, by in large cancer remains unsolved. Exploiting computational predictive models to study and treat cancer holds great promise in improving drug development and personalized design of treatment plans, ultimately suppressing tumors, alleviating suff

Sumin Seo, Heeseon Cheon, Hyunho Kim, Dongseok Hyun

This work presents six structural quality metrics that can measure the quality of knowledge graphs and analyzes five cross-domain knowledge graphs on the web (Wikidata, DBpedia, YAGO, Google Knowledge Graph, Freebase) as well as 'Raftel', Naver's integrated knowledge graph. The 'Good Knowledge Graph' should define detailed classes and properties in its ontol

Liting Xiao, Arianna I. Renzini, Alan J. Weinstein

A stochastic gravitational-wave (GW) background consists of a large number of weak, independent and uncorrelated events of astrophysical or cosmological origin. The GW power on the sky is assumed to contain anisotropies on top of an isotropic component, i.e., the angular monopole. Complementary to the LIGO--Virgo--KAGRA (LVK) searches, we develop an efficien

Theo Beldon, Mia DeStefano, Adam M. Lowrance, Wyatt Milgrim

The Turaev surface of a link diagram $D$ is a closed, oriented surface constructed from a cobordism between the all-$A$ and all-$B$ Kauffman states of $D$. The Turaev genus of a link $L$ is the minimum genus of the Turaev surface of any diagram $D$ of $L$. A link is alternating if and only if its Turaev genus is zero, and so one can view Turaev genus one lin

Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Bo Li

This paper studies the confounding effects from the unmeasured confounders and the imbalance of observed confounders in IV regression and aims at unbiased causal effect estimation. Recently, nonlinear IV estimators were proposed to allow for nonlinear model in both stages. However, the observed confounders may be imbalanced in stage 2, which could still lead

C. Zhang, Z. X. Ling, X. J. Sun, S. L. Sun

As a novel X-ray focusing technology, lobster eye micro-pore optics (MPO) feature both a wide observing field of view and true imaging capability, promising sky monitoring with significantly improved sensitivity and spatial resolution in soft X-rays. Since first proposed by Angel (1979), the optics have been extensively studied, developed and trialed over th

Xiang Ni, Simon Yves, Alex Krasnok, Andrea Alu

One of the most significant breakthroughs in physics of the last decade has been the discovery that materials with non-trivial topological properties for electronic, electromagnetic, acoustic and mechanical responses can be designed and manufactured at our will through engineered metamaterials (MMs). Here, we review the foundation and the state-of-the-art ad

Matti Jarvinen

Solving the properties of dense QCD matter is an extremely challenging problem because standard theoretical tools do not work at intermediate densities. The gauge/gravity duality may help to provide answers in this region. I give a brief review of recent progress in this field, focusing on the V-QCD model, which is one of the most sophisticated holographic m

Shuning Lin, Yong Chen

We put forth two physics-informed neural network (PINN) schemes based on Miura transformations and the novelty of this research is the incorporation of Miura transformation constraints into neural networks to solve nonlinear PDEs. The most noteworthy advantage of our method is that we can simply exploit the initial-boundary data of a solution of a certain no

Jiashi Chen, Wei Wang

Tidal disruption events (TDEs) may occur in supermassive black holes (SMBHs) surrounded by clouds. TDEs can generate ultrafast and large opening-angle outflow with a velocity of $\sim$ 0.01--0.2 c, which will collide with clouds with time lags depending on outflow velocity and cloud distances. Since the fraction of the outflow energy transferred into cloud's

Gwantae Kim, Youngsuk Ryu, Junyeop Lee, David K. Han

In this paper, a deep learning-based model for 3D human motion generation from the text is proposed via gesture action classification and an autoregressive model. The model focuses on generating special gestures that express human thinking, such as waving and nodding. To achieve the goal, the proposed method predicts expression from the sentences using a tex

Haoren Zhu, Hao Ge, Xiaodong Gu, Pengfei Zhao

Traditional recommender systems are typically passive in that they try to adapt their recommendations to the user's historical interests. However, it is highly desirable for commercial applications, such as e-commerce, advertisement placement, and news portals, to be able to expand the users' interests so that they would accept items that they were not origi

Erya Jiang, Bo Qin, Qin Wang, Qianhong Wu

Trading data through blockchain platforms is hard to achieve \textit{fair exchange}. Reasons come from two folds: Firstly, guaranteeing fairness between sellers and consumers is a challenging task as the deception of any participating parties is risk-free. This leads to the second issue where judging the behavior of data executors (such as cloud service prov

Onuralp Soylemez, Pablo Cordero

Despite being self-supervised, protein language models have shown remarkable performance in fundamental biological tasks such as predicting impact of genetic variation on protein structure and function. The effectiveness of these models on diverse set of tasks suggests that they learn meaningful representations of fitness landscape that can be useful for dow

Zhenyu Xiao, Kohei Kawabata, Xunlong Luo, Tomi Ohtsuki

We study quantum phase transitions of three-dimensional disordered systems in the chiral classes (AIII and BDI) with and without weak topological indices. We show that the systems with a nontrivial weak topological index universally exhibit an emergent thermodynamic phase where wave functions are delocalized along one spatial direction but exponentially loca

Xiaochun Rong

For $\rho, v>0$, we say that an $n$-manifold $M$ satisfies local $(\rho,v)$-bound Ricci covering geometry, if Ricci curvature $\text{Ric}_M\ge -(n-1)$, and for all $x\in M$, $\text{vol}(B_\rho(\tilde x))\ge v>0$, where $\tilde x$ is an inverse image of $x$ on the (local) Riemannian universal cover of the $\rho$-ball at $x$. In this paper, we extend the nilpo

Stefan Zellmann, Qi Wu, Alper Sahistan, Kwan-Liu Ma

Adaptive Mesh Refinement (AMR) is becoming a prevalent data representation for scientific visualization. Resulting from large fluid mechanics simulations, the data is usually cell centric, imposing a number of challenges for high quality reconstruction at sample positions. While recent work has concentrated on real-time volume and isosurface rendering on GPU