July 2022 arXiv papers — page 70

Labh Singh, Monal Kashav, Surender Verma

In the framework of anomaly free $U(1)_{L_{\mu}-L_{\tau}}$ model, charged scalar fields give rise to massive gauge boson ($Z_{\mu\tau}$) through spontaneous symmetry breaking. $Z_{\mu\tau}$ leads to one loop contribution to the muon anomalous magnetic moment. These scalar fields may, also, appear in the structure of right-handed neutrino mass matrix, thus, c

Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt

Outlier explanation is the task of identifying a set of features that distinguish a sample from normal data, which is important for downstream (human) decision-making. Existing methods are based on beam search in the space of feature subsets. They quickly becomes computationally expensive, as they require to run an outlier detection algorithm from scratch fo

Antonio Lerario, Domenico Marinucci, Maurizia Rossi, Michele Stecconi

Spin (spherical) random fields are very important in many physical applications, in particular they play a key role in Cosmology, especially in connection with the analysis of the Cosmic Microwave Background radiation. These objects can be viewed as random sections of the s-th complex tensor power of the tangent bundle of the 2-sphere. In this paper, we disc

Mevan Ekanayake, Kamlesh Pawar, Mehrtash Harandi, Gary Egan

Global correlations are widely seen in human anatomical structures due to similarity across tissues and bones. These correlations are reflected in magnetic resonance imaging (MRI) scans as a result of close-range proton density and T1/T2 parameters. Furthermore, to achieve accelerated MRI, k-space data are undersampled which causes global aliasing artifacts.

Masanori Adachi, Yoshifumi Matsuda, Hiraku Nozawa

We study rigidity properties of actions of a torsion-free lattice of $\operatorname{PSU}(1,1)$ on the circle $S^1$. We follow the approaches of Frankel and Thurston proposed in preprints via foliated harmonic measures on the suspension bundles. Our main results are a curvature estimate and a Gauss--Bonnet formula for the $S^1$ connection obtained by taking t

Lior Ben-Moshe, Sagie Benaim, Lior Wolf

We introduce FewGAN, a generative model for generating novel, high-quality and diverse images whose patch distribution lies in the joint patch distribution of a small number of N>1 training samples. The method is, in essence, a hierarchical patch-GAN that applies quantization at the first coarse scale, in a similar fashion to VQ-GAN, followed by a pyramid of

Rohollah Parvinianzadeh

Let $B(H)$ be the algebra of all bounded linear operators on an infinite-dimensional complex Hilbert space $H$. For $T \in B(H)$ and $\lambda \in \mathbb{C}$, let $H_{T}(\{\lambda\})$ denotes the local spectral subspace of $T$ associated with $\{\lambda\}$. We prove that if $\varphi:B(H)\rightarrow B(H)$ be an additive map such that its range contains all op

Jihao Liu, Boxiao Liu, Hang Zhou, Hongsheng Li

CutMix is a popular augmentation technique commonly used for training modern convolutional and transformer vision networks. It was originally designed to encourage Convolution Neural Networks (CNNs) to focus more on an image's global context instead of local information, which greatly improves the performance of CNNs. However, we found it to have limited ben

Ping Yu, Wei Wang, Chunyuan Li, Ruiyi Zhang

Prompt tuning has been an extremely effective tool to adapt a pre-trained model to downstream tasks. However, standard prompt-based methods mainly consider the case of sufficient data of downstream tasks. It is still unclear whether the advantage can be transferred to the few-shot regime, where only limited data are available for each downstream task. Althou

Danilo Labranca, Hervè Atsè Corti, Leonardo Banchi, Alessandro Cidronali

Quantum sensing is a rapidly growing field of research which is already improving sensitivity in fundamental physics experiments. The ability to control quantum devices to measure physical quantities received a major boost from superconducting qubits and the improved capacity in engineering and fabricating this type of devices. The goal of the QUB-IT project

Rajibul Islam, Rahul Verma, Barun Ghosh, Zahir Muhammad

Quantum spin Hall (QSH) insulators exhibit spin-polarized conducting edge states that are topologically protected from backscattering and offer unique opportunities for addressing fundamental science questions and device applications. Finding viable materials that host such topological states, however, remains a challenge. Here by using in-depth first-princi

Minh Ha Quang

In this work, we present formulations for regularized Kullback-Leibler and R\'enyi divergences via the Alpha Log-Determinant (Log-Det) divergences between positive Hilbert-Schmidt operators on Hilbert spaces in two different settings, namely (i) covariance operators and Gaussian measures defined on reproducing kernel Hilbert spaces (RKHS); and (ii) Gaussian

Vibhakar Vemulapati, Deming Chen

Simultaneous Localization and Mapping (SLAM) is one of the main components of autonomous navigation systems. With the increase in popularity of drones, autonomous navigation on low-power systems is seeing widespread application. Most SLAM algorithms are computationally intensive and struggle to run in real-time on embedded devices with reasonable accuracy. O

Rodrigo S. Mitishita, Jordan A. MacKenzie, Gwynn J. Elfring, Ian A. Frigaard

Turbulent flows of viscoplastic fluids at high Reynolds numbers have been investigated recently with direct numerical simulations (DNS) but experimental results have been limited. For this reason, we carry out an experimental study of fully turbulent flows of a yield stress fluid in a rectangular aspect ratio channel with a high-resolution laser doppler velo

Juewen Peng, Jianming Zhang, Xianrui Luo, Hao Lu

Partial occlusion effects are a phenomenon that blurry objects near a camera are semi-transparent, resulting in partial appearance of occluded background. However, it is challenging for existing bokeh rendering methods to simulate realistic partial occlusion effects due to the missing information of the occluded area in an all-in-focus image. Inspired by the

Norio Iwase

To construct an $A_{\infty}$-form for a loop space in the category of diffeological spaces, we have two minor problems. Firstly, the concatenation of paths in the category of diffeological spaces needs a small technical trick (see P.~I-Zemmour \cite{MR3025051}), which apparently restricts the number of iterations of concatenations. Secondly, we do not know a

Xiang 'Anthony' Chen, Chien-Sheng Wu, Lidiya Murakhovs'ka, Philippe Laban

We explore the design of Marvista -- a human-AI collaborative tool that employs a suite of natural language processing models to provide end-to-end support for reading online news articles. Before reading an article, Marvista helps a user plan what to read by filtering text based on how much time one can spend and what questions one is interested to find out

Joakim Arnlind, Kwalombota Ilwale

We introduce $(\sigma,\tau)$-algebras as a framework for twisted differential calculi over noncommutative, as well as commutative, algebras with motivations from the theory of $\sigma$-derivations and quantum groups. A $(\sigma,\tau)$-algebra consists of an associative algebra together with a set of $(\sigma,\tau)$-derivations, and corresponding notions of $

Abdallah Ammar, Anthony Scemama, Emmanuel Giner

In this work we present an extension of the popular selected configuration interaction (SCI) algorithms to the Transcorrelated (TC) framework. Although we used in this work the recently introduced one-parameter correlation factor [E. Giner, J. Chem. Phys., 154, 084119 (2021)], the theory presented here is valid for any correlation factor. Thanks to the forma

Changyong Oh, Roberto Bondesan, Dana Kianfar, Rehan Ahmed

Macro placement is the problem of placing memory blocks on a chip canvas. It can be formulated as a combinatorial optimization problem over sequence pairs, a representation which describes the relative positions of macros. Solving this problem is particularly challenging since the objective function is expensive to evaluate. In this paper, we develop a novel

Alireza Aliahmadi, Hamed Nozari, Javid Ghahremani-Nahr, Agnieszka Szmelter-Jarosz

In recent years, the high complexity of the business environment, dynamism and environmental change, uncertainty and concepts such as globalization and increasing competition of organizations in the national and international arena have caused many changes in the equations governing the supply chain. In this case, supply chain organizations must always be pr

Kai Liao, Marek Biesiada, Zong-Hong Zhu

The past decades have witnessed a lot of progress in gravitational lensing with two main targets: stars and galaxies (with active galactic nuclei). The success is partially attributed to the continuous luminescence of these sources making the detection and monitoring relatively easy. With the running of ongoing and upcoming large facilities/surveys in variou

Shao-Wen Wei, Yu-Xiao Liu

A topological approach has been successfully used to study the properties of the light ring and the null circular orbit, in a generic black hole background. However, for the equatorial timelike circular orbit, quite different from the light ring case, its radius is closely dependent of the energy and angular momentum of a test particle. This fact seems to re

Kazuki Tokuda, Sarolta Zahorecz, Yuri Kunitoshi, Kosuke Higashino

Protostellar outflows are one of the most outstanding features of star formation. Observational studies over the last several decades have successfully demonstrated that outflows are ubiquitously associated with low- and high-mass protostars in the solar-metallicity Galactic conditions. However, the environmental dependence of protostellar outflow properties

Yu Zhang, Tianmeng Zhang, Danzengluobu, Zhitong Li

We present the optical photometric and spectroscopic observations of the nearby Type Ia supernova (SN) 2021hpr. The observations covered the phase of $-$14.37 to +63.68 days relative to its maximum luminosity in the $B$ band. The evolution of multiband light/color curves of SN 2021hpr is similar to that of normal Type Ia supernovae (SNe Ia) with the exceptio

Hiu Yung Wong, Yaniv Jacob Rosen, Kristin M. Beck, Prabjot Dhillon

Qubit readout is a critical part of any quantum computer including the superconducting-qubit-based one. The readout fidelity is affected by the readout pulse width, readout pulse energy, resonator design, qubit design, qubit-resonator coupling, and the noise generated along the readout path. It is thus important to model and predict the fidelity based on var

Batu Ozturkler, Arda Sahiner, Tolga Ergen, Arjun D Desai

Unrolled neural networks have recently achieved state-of-the-art accelerated MRI reconstruction. These networks unroll iterative optimization algorithms by alternating between physics-based consistency and neural-network based regularization. However, they require several iterations of a large neural network to handle high-dimensional imaging tasks such as 3

Ertem Nusret Tas, David Tse, Fangyu Gai, Sreeram Kannan

Bitcoin is the most secure blockchain in the world, supported by the immense hash power of its Proof-of-Work miners. Proof-of-Stake chains are energy-efficient, have fast finality but face several security issues: susceptibility to non-slashable long-range safety attacks, low liveness resilience and difficulty to bootstrap from low token valuation. We show t

Hiep Nguyen, Lam Phan, Harikrishna Warrier, Yogesh Gupta

Federated learning (FL) is an emerging technique used to collaboratively train a global machine learning model while keeping the data localized on the user devices. The main obstacle to FL's practical implementation is the Non-Independent and Identical (Non-IID) data distribution across users, which slows convergence and degrades performance. To tackle this

L. Huang, Z. X. Chang

We use the X-ray luminosity relation of radio-loud quasars (RLQs) to measure these luminosity distances as well as estimate cosmological parameters. We adopt four parametric models of X-ray luminosity to test luminosity correlation for RLQs and radio-intermediate quasars (RIQs) and give these cosmological distances. By Bayesian information criterion (BIC), t

Albert Lu, Jordan Marshall, Yifan Wang, Ming Xiao

In this paper, two methodologies are used to speed up the maximization of the breakdown volt-age (BV) of a vertical GaN diode that has a theoretical maximum BV of ~2100V. Firstly, we demonstrated a 5X faster accurate simulation method in Technology Computer-Aided-Design (TCAD). This allows us to find 50% more numbers of high BV (>1400V) designs at a given si

Amir H. Ashouri, Mostafa Elhoushi, Yuzhe Hua, Xiang Wang

For the past 25 years, we have witnessed an extensive application of Machine Learning to the Compiler space; the selection and the phase-ordering problem. However, limited works have been upstreamed into the state-of-the-art compilers, i.e., LLVM, to seamlessly integrate the former into the optimization pipeline of a compiler to be readily deployed by the us

Shivam Singh Dhama

In this article, we study the dynamics of a nonlinear system governed by an ordinary differential equation under the combined influence of fast periodic sampling with period $\delta$ and small jump noise of size $\varepsilon, 0< \varepsilon,\delta \ll 1.$ The noise is a combination of Brownian motion and Poisson random measure. The instantaneous rate of chan

Zan Gao, Hongwei Wei, Weili Guan, Jie Nie

Cloth-changing person reidentification (ReID) is a newly emerging research topic that aims to retrieve pedestrians whose clothes are changed. Since the human appearance with different clothes exhibits large variations, it is very difficult for existing approaches to extract discriminative and robust feature representations. Current works mainly focus on body

Thien-Nu Hoang, Daehee Kim

High-end vehicles have been furnished with a number of electronic control units (ECUs), which provide upgrading functions to enhance the driving experience. The controller area network (CAN) is a well-known protocol that connects these ECUs because of its modesty and efficiency. However, the CAN bus is vulnerable to various types of attacks. Although the int

Xuejing Liu, Liang Li, Shuhui Wang, Zheng-Jun Zha

Weakly supervised Referring Expression Grounding (REG) aims to ground a particular target in an image described by a language expression while lacking the correspondence between target and expression. Two main problems exist in weakly supervised REG. First, the lack of region-level annotations introduces ambiguities between proposals and queries. Second, mos

Xin-Yu Zhang, Hai-Jun Wu, Bing-Shi Yu, Carmelo Rosales-Guzmán

Optical interferometers are pillars of modern precision metrology, but their resolution is limited by the wavelength of the light source, which cannot be infinitely reduced. Magically, this limitation can be circumvented by using an entangled multiphoton source because interference produced by an N-photon amplitude features a reduced de Broglie wavelength {\

Mingming Qiu, Elie Najm, Remi Sharrock, Bruno Traverson

Designing smart home services is a complex task when multiple services with a large number of sensors and actuators are deployed simultaneously. It may rely on knowledge-based or data-driven approaches. The former can use rule-based methods to design services statically, and the latter can use learning methods to discover inhabitants' preferences dynamically

Soon-Yeong Chung, Jaeho Hwang

The purpose of this paper is to give a necessary and sufficient condition for the existence and non-existence of global solutions of the following semilinear parabolic equations \[ u_{t}=\Delta u+\psi(t)f(u),\,\,\mbox{ in }\Omega\times (0,t^{*}), \] under the Dirichlet boundary condition on a bounded domain. In fact, this has remained as an open problem for

Abdurro'uf, Yen-Ting Lin, Hiroyuki Hirashita, Takahiro Morishita

We study spatially resolved scaling relations among stars, dust, and gas in ten nearby spiral galaxies. In a preceding paper Abdurro'uf et al. (2022), we have derived spatially resolved properties of the stellar population and dust by panchromatic spectral energy distribution (SED) fitting using piXedfit. Now, we investigate resolved star formation ($\Sigma_

Soonbeom Seo, Yongkang Luo, S. M. Thomas, Z. Fisk

The proposed topological Kondo insulator SmB$_{6}$ hosts a bulk Kondo hybridization gap that stems from strong electronic correlations and a metallic surface state whose effective mass remains disputed. Thermopower and scanning tunneling spectroscopy measurements argue for heavy surface states that also stem from strong correlations, whereas quantum oscillat

Kalin Stefanov, Bhawna Paliwal, Abhinav Dhall

Realistic fake videos are a potential tool for spreading harmful misinformation given our increasing online presence and information intake. This paper presents a multimodal learning-based method for detection of real and fake videos. The method combines information from three modalities - audio, video, and physiology. We investigate two strategies for combi

Guoqing Liu, Mengzhang Cai, Li Zhao, Tao Qin

Deep reinforcement learning (DRL) has attracted much attention in automated game testing. Early attempts rely on game internal information for game space exploration, thus requiring deep integration with games, which is inconvenient for practical applications. In this work, we propose using only screenshots/pixels as input for automated game testing and buil

Yuki Kato

The Gersten conjecture is still an open problem of algebraic $K$-theory for mixed characteristic discrete valuation rings. In this paper, we establish non-unital algebraic $K$-theory which is modified to become an exact functor from the category of non-unital algebras to the stable $\infty$-category of spectra. We prove that for any almost unital algebra, th

Yi Yang, Sunil K. Sinha

We have developed a 3 dimensional Coherent Diffraction Imaging (CDI) algorithm to retrieve phases of diffraction patterns of samples in Grazing Incidence Small Angle X-ray Scattering (GISAXS) experiments. The algorithm interprets the diffraction patterns using the Distorted-Wave Born Approximation (DWBA) instead of the Born Approximation (BA), as in this cas

Xuelong Li, Ziheng Jiao, Hongyuan Zhang, Rui Zhang

Admittedly, Graph Convolution Network (GCN) has achieved excellent results on graph datasets such as social networks, citation networks, etc. However, softmax used as the decision layer in these frameworks is generally optimized with thousands of iterations via gradient descent. Furthermore, due to ignoring the inner distribution of the graph nodes, the deci

Cagri Arisoy, Anuradha Mandal, Nitesh Saxena

The spread of digital disinformation (aka "fake news") is arguably one of the most significant threats on the Internet which can cause individual and societal harm of large scales. The susceptibility to fake news attacks hinges on whether Internet users perceive a fake news article/snippet to be legitimate after reading it. In this paper, we attempt to garne

Rudeep Gaur, Matt Visser

Cosmology is most typically analyzed using standard co-moving coordinates, in which the galaxies are (on average, up to presumably small peculiar velocities) "at rest", while "space" is expanding. But this is merely a specific coordinate choice; and it is important to realise that for certain purposes other, (sometimes radically different) coordinate choices

Qiying Yu, Jieming Lou, Xianyuan Zhan, Qizhang Li

Contrastive learning (CL) has recently been applied to adversarial learning tasks. Such practice considers adversarial samples as additional positive views of an instance, and by maximizing their agreements with each other, yields better adversarial robustness. However, this mechanism can be potentially flawed, since adversarial perturbations may cause insta

Pratim Guha Niyogi, Ping-Shou Zhong, Xiaohong Joe Zhou

In this paper, we develop a multi-step estimation procedure to simultaneously estimate the varying-coefficient functions using a local-linear generalized method of moments (GMM) based on continuous moment conditions. To incorporate spatial dependence, the continuous moment conditions are first projected onto eigen-functions and then combined by weighted eige

Jin Sima, Jehoshua Bruck

One of the main challenges in developing racetrack memory systems is the limited precision in controlling the track shifts, that in turn affects the reliability of reading and writing the data. A current proposal for combating deletions in racetrack memories is to use redundant heads per-track resulting in multiple copies (potentially erroneous) and recoveri

Ling-Jie Zhou, Ruobing Mei, Yi-Fan Zhao, Ruoxi Zhang

In quantum anomalous Hall (QAH) insulators, the interior is insulating but electrons can travel with zero resistance along one-dimensional conducting paths known as chiral edge channels (CECs). These CECs have been predicted to be confined to the one-dimensional (1D) edges and exponentially decay in the two-dimensional (2D) bulk. In this work, we present the

Jeremy M. Myers, Daniel M. Dunlavy

There is growing interest to extend low-rank matrix decompositions to multi-way arrays, or tensors. One fundamental low-rank tensor decomposition is the canonical polyadic decomposition (CPD). The challenge of fitting a low-rank, nonnegative CPD model to Poisson-distributed count data is of particular interest. Several popular algorithms use local search met

Marija Ilic, Rupamathi Jaddivada

This paper points out some key drawbacks of today's modeling and control underlying hierarchical electric power system operations and planning as the hidden roadblocks on the way to decarbonization. We suggest that these can be overcome by enhancing today's information exchange and control. This can be done by revealing and utilising inherent structure-prese

Zhenlan Ji, Pingchuan Ma, Shuai Wang

Debugging performance anomalies in real-world databases is challenging. Causal inference techniques enable qualitative and quantitative root cause analysis of performance downgrade. Nevertheless, causality analysis is practically challenging, particularly due to limited observability. Recently, chaos engineering has been applied to test complex real-world so

Yun Xu, Shanli Ye, Zhihui Zhou

Let $\mu$ be a positive Borel measure on the interval $[0,1)$. The Hankel matrix $\mathcal{H}_{\mu}=(\mu_{n,k})_{n,k\geq 0}$ with entries $\mu_{n,k}=\mu_{n+k}$, where $\mu_{n}=\int_{[0,1)}t^nd\mu(t)$, induces formally the operator as $$\mathcal{DH}_\mu(f)(z)=\sum_{n=0}^\infty\left(\sum_{k=0}^\infty \mu_{n,k}a_k\right)(n+1)z^n , z\in \mathbb{D},$$ where $f(z)

Michelle Chen, Olga Ohrimenko

We consider the problem of ensuring confidentiality of dataset properties aggregated over many records of a dataset. Such properties can encode sensitive information, such as trade secrets or demographic data, while involving a notion of data protection different to the privacy of individual records typically discussed in the literature. In this work, we dem

Felipe Pereira-Alves, Diogo O. Soares-Pinto, Fernando F. Paiva

The diffusion motion of spin-bearing molecules is considerably affected in confined environments. In Nuclear Magnetic Resonance (NMR) experiments, under the presence of magnetic field gradients, this movement can be encoded in spin phase and the NMR signal attenuation due to diffusion can be evaluated. This paper considered this effect in both normal and ano

Nand Sharma, Joshua Millstein

Finding a globally optimal Bayesian Network using exhaustive search is a problem with super-exponential complexity, which severely restricts the number of variables that it can work for. We implement a dynamic programming based algorithm with built-in dimensionality reduction and parent set identification. This reduces the search space drastically and can be

Hanhaodi Zhang

This paper presents a simple method for speech videos generation based on audio: given a piece of audio, we can generate a video of the target face speaking this audio. We propose Generative Adversarial Networks (GAN) with cut speech audio input as condition and use Convolutional Gate Recurrent Unit (GRU) in generator and discriminator. Our model is trained

Devdas Karmakar, Sujoy Kumar Mandal, Sumana Paul, Saptarshi Pal

Pristine Antimony tungstate nanoparticles prepared via a simple hydrothermal process showcase interesting photocatalytic efficiency, degrading Methylene Blue (MB) completely in 180 min under visible light. In this study, the impact on crystalline quality and related optical properties as well as photocatalytic efficiency of antimony tungstate due to temperat

Xue Jiang, Xiulian Peng, Huaying Xue, Yuan Zhang

Neural audio/speech coding has recently demonstrated its capability to deliver high quality at much lower bitrates than traditional methods. However, existing neural audio/speech codecs employ either acoustic features or learned blind features with a convolutional neural network for encoding, by which there are still temporal redundancies within encoded feat

Chengyan Zhao, Kazunori Sakurama, Masaki Ogura

This letter deals with the optimization problems of stochastic switching buffer networks, where the switching law is governed by Markov process. The dynamical buffer network is introduced, and its application in modeling the car-sharing network is also presented. To address the nonconvexity for getting a solution as close-to-the-global-optimal as possible of

Luca Boccioli, Lorenzo Roberti, Marco Limongi, Grant J. Mathews

We present a simple criterion to predict the explodability of massive stars based on the density and entropy profiles before collapse. If a pronounced density jump is present near the Si/Si-O interface, the star will likely explode. We develop a quantitative criterion by using $\sim 1300$ 1D simulations where $\nu$-driven turbulence is included via time-depe

Wujie Shen, Jiajun Wang

In the present paper, we show that the minimal length of closed geodesics on finite-type hyperbolic surfaces with self-intersection number $k$ has order $2\log k$ as $k$ gets large.

Fanjun Meng

We give estimates on the Kodaira dimension for fibrations over abelian varieties, and give some applications. One of the results strengthens the subadditivity of Kodaira dimension of fibrations over abelian varieties.

Yu Deng, Zaher Hani

The main purpose of this expository note is to give a short account of the recent developments in mathematical wave kinetic theory. After reviewing the physical theory, we explain the importance of the notion of a scaling law, which dictates the relation between the asymptotic parameters as the kinetic limit is taken. This sets some natural limitations on th

Xiaohui Xu, Abhishek. B. Solanki, Demid Sychev, Xingyu Gao

Two-dimensional hexagonal boron nitride (hBN) has been known to host a variety of quantum emitters with properties suitable for a broad range of quantum photonic applications. Among them, the negatively charged boron vacancy (VB-) defect with optically addressable spin states has emerged recently due to its potential use in quantum sensing. Compared to spin

Han Zhu, Zhenzhong Chen, Shan Liu

Knowledge distillation (KD), which can efficiently transfer knowledge from a cumbersome network (teacher) to a compact network (student), has demonstrated its advantages in some computer vision applications. The representation of knowledge is vital for knowledge transferring and student learning, which is generally defined in hand-crafted manners or uses the

Feraz Azhar, David I. Kaiser

For decades, physicists have analyzed various versions of a ``cosmic no-hair" conjecture, to understand under what conditions a spacetime that is initially spatially anisotropic and/or inhomogeneous will flow into an isotropic and homogeneous state. Wald's theorem, in particular, established that homogeneous but anisotropic spacetimes, if filled with a posit

Chinmay Ghosh, Soumen Mondal

In this paper, we have defined bicomplex valued functions of bounded variations and rectifiable hyperbolic path. We have studied the integration of product-type bicomplex functions over rectifiable hyperbolic path. Also we have established bicomplex analogue of the Fundamental Theorem of Calculus for line integral.

Daichi Kagamihara, Ryui Kaneko, Shion Yamashika, Kota Sugiyama

We investigate the time-dependent R\'{e}nyi entanglement entropy after a quantum quench starting from the Mott-insulating and charge-density-wave states in a one-dimensional free boson system. The second R\'{e}nyi entanglement entropy is found to be the negative of the logarithm of the permanent of a matrix consisting of time-dependent single-particle correl

Uttaran Bhattacharya, Gang Wu, Stefano Petrangeli, Viswanathan Swaminathan

We propose a method to detect individualized highlights for users on given target videos based on their preferred highlight clips marked on previous videos they have watched. Our method explicitly leverages the contents of both the preferred clips and the target videos using pre-trained features for the objects and the human activities. We design a multi-hea

Canqian Yang, Meiguang Jin, Yi Xu, Rui Zhang

Image-adaptive lookup tables (LUTs) have achieved great success in real-time image enhancement tasks due to their high efficiency for modeling color transforms. However, they embed the complete transform, including the color component-independent and the component-correlated parts, into only a single type of LUTs, either 1D or 3D, in a coupled manner. This s

Liangzu Peng, Mahyar Fazlyab, René Vidal

The rotation search problem aims to find a 3D rotation that best aligns a given number of point pairs. To induce robustness against outliers for rotation search, prior work considers truncated least-squares (TLS), which is a non-convex optimization problem, and its semidefinite relaxation (SDR) as a tractable alternative. Whether this SDR is theoretically ti

Julie Jiang, Xiang Ren, Emilio Ferrara

Estimating the political leanings of social media users is a challenging and ever more pressing problem given the increase in social media consumption. We introduce Retweet-BERT, a simple and scalable model to estimate the political leanings of Twitter users. Retweet-BERT leverages the retweet network structure and the language used in users' profile descrip

Zechen Xiong, Liqi Chen, Wenxiong Hao, Yufeng Su

Inspired by the snap-through action of a steel hairclip, we propose a design method for in-plane prestressed mechanisms that exhibit biomimetic morphing and high locomotion performance. Compliant bistable flapping mechanisms are fabricated using this method and are mounted on our untethered soft robotic fish. Using this mechanism, we achieve life-like undula

Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Ruoqi Shen

We propose a new framework for differentially private optimization of convex functions which are Lipschitz in an arbitrary norm $\|\cdot\|$. Our algorithms are based on a regularized exponential mechanism which samples from the density $\propto \exp(-k(F+\mu r))$ where $F$ is the empirical loss and $r$ is a regularizer which is strongly convex with respect t

Shahram Ghandeharizadeh

This paper presents techniques to display 3D illuminations using Flying Light Specks, FLSs. Each FLS is a miniature (hundreds of micrometers) sized drone with one or more light sources to generate different colors and textures with adjustable brightness. It is network enabled with a processor and local storage. Synchronized swarms of cooperating FLSs render

Bingze Yan, Yucheng Qiao, Qiong Li, Haokun Mao

Precise quantum key distribution (QKD) secure bound analysis is essential for practical QKD systems. The effect of uniformity of random number seed for privacy amplification is not considered in existing secure bound analysis. In this paper, we propose and prove the quantum leftover hash lemma with non-uniform random number seeds based on the min-entropy, an

Jian-An Li, Li Wang, Wen-Jie Xie, Wei-Xing Zhou

The statistical properties including community structure of the international trade networks of all commodities as a whole have been studied extensively. However, the international trade networks of individual commodities often behave differently. Due to the importance of pesticides in agricultural production and food security, we investigate the evolving co

Nicholas E. Bousse, Stephen E. Kuenstner, James M. L. Miller, Hyun-Keun Kwon

Encapsulated bulk mode microresonators in the megahertz range are used in commercial timekeeping and sensing applications but their performance is limited by the current state of the art of readout methods. We demonstrate a readout using dispersive coupling between a high-Q encapsulated bulk mode micromechanical resonator and a lumped element microwave reson

Philip Amortila, Nan Jiang, Dhruv Madeka, Dean P. Foster

The current paper studies sample-efficient Reinforcement Learning (RL) in settings where only the optimal value function is assumed to be linearly-realizable. It has recently been understood that, even under this seemingly strong assumption and access to a generative model, worst-case sample complexities can be prohibitively (i.e., exponentially) large. We i

Gauthier Mukerjee, Juan A. Bonachela, Miguel A. Muñoz, Kay Joerg Wiese

Depinning of elastic systems advancing on disordered media can usually be described by the quenched Edwards-Wilkinson equation (qEW). However, additional ingredients such as anharmonicity and forces that can not be derived from a potential energy may generate a different scaling behavior at depinning. The most experimentally relevant is the Kardar-Parisi-Zha

Yi Zhou, Shan Hu, Zimo Sheng

The densest subgraph problem (DSG) aiming at finding an induced subgraph such that the average edge-weights of the subgraph is maximized, is a well-studied problem. However, when the input graph is a hypergraph, the existing notion of DSG fails to capture the fact that a hyperedge partially belonging to an induced sub-hypergraph is also a part of the sub-hyp

Paul Duncan, Benjamin Schweinhart

The $i$-dimensional plaquette random-cluster model on a finite cubical complex is the random complex of $i$-plaquettes with each configuration having probability proportional to $$p^{\text{# of plaquettes}}(1-p)^{\text{# of complementary plaquettes}}q^{\mathbf{ b}_{i-1}},$$ where $q\geq 1$ is a real parameter and $\mathbf{b}_{i-1}$ denotes the rank of the $(

Hoang Le, Liang Zhang, Amir Said, Guillaume Sautiere

Realizing the potential of neural video codecs on mobile devices is a big technological challenge due to the computational complexity of deep networks and the power-constrained mobile hardware. We demonstrate practical feasibility by leveraging Qualcomm's technology and innovation, bridging the gap from neural network-based codec simulations running on wall-

Xue-Jia Yu, Sheng Yang, Jinbo Xu, Limei Xu

In recent years, programmable Rydberg-atom arrays have been widely used to simulate new quantum phases and phase transitions, generating great interest among theorists and experimentalists. Based on the large-scale density matrix renormalization group method, the ground-state phase diagram of one-dimensional Rydberg chains is investigated with fidelity susce

Canyu Chen, Yueqing Liang, Xiongxiao Xu, Shangyu Xie

Machine learning models have demonstrated promising performance in many areas. However, the concerns that they can be biased against specific demographic groups hinder their adoption in high-stake applications. Thus, it is essential to ensure fairness in machine learning models. Most previous efforts require direct access to sensitive attributes for mitigati

Salil Vadhan, Wanrong Zhang

We study the concurrent composition properties of interactive differentially private mechanisms, whereby an adversary can arbitrarily interleave its queries to the different mechanisms. We prove that all composition theorems for non-interactive differentially private mechanisms extend to the concurrent composition of interactive differentially private mechan

R. Romero

It is shown that c-number elko spinors obey the massless Dirac equation and are unitarily equivalent to Weyl bispinors. Therefore, they do not constitute a new spinor type with mass dimension one.

Sangmyeong Woh, Jaemin Lee, Ho Joong Kim, Jinsuk Lee

As computer vision and NLP make progress, Vision-Language(VL) is becoming an important area of research. Despite the importance, evaluation metrics of the research domain is still at a preliminary stage of development. In this paper, we propose a quantitative metric "Equivariance Score" and evaluation dataset "Human Puzzle" to assess whether a VL model is un

Maopeng Ran, Shuai Feng, Juncheng Li, Lihua Xie

This paper is concerned with the quantized consensus problem for uncertain nonlinear multi-agent systems under data-rate constraints and Denial-of-Service (DoS) attacks. The agents are modeled in strict-feedback form with unknown nonlinear dynamics and external disturbance. Extended state observers (ESOs) are leveraged to estimate agents' total uncertainties

Sayan Banerjee, Amarjit Budhiraja

\noindent Consider an infinite collection of particles on the real line moving according to independent Brownian motions and such that the $i$-th particle from the left gets the drift $g_{i-1}$. The case where $g_0=1$ and $g_{i}=0$ for all $i \in \mathbb{N}$ corresponds to the well studied infinite Atlas model. Under conditions on the drift vector $\boldsymb

Hanxu Zhang, Wu Wang, Xu Wang

Nuclear excitation cross section of $^{229}$Th from the ground state to the low-lying isomeric state via inelastic electron scattering is calculated, on the level of Dirac distorted wave Born approximation. With electron energies below 100 eV, inelastic scattering is very efficient in the isomeric excitation, yielding excitation cross sections on the order o

Justin M. Kennedy, Jason J. Ford, Daniel E. Quevedo

For geographically separated cyber-physical systems, state estimation at a remote monitoring or control site is important to ensure stability and reliability of the system. Often for safety or commercial reasons it is necessary to ensure confidentiality of the process state and control information. A current topic of interest is the private transmission of c

Leonardo Dagdug, Alexei T. Skvortsov, Alexander M. Berezhkovskii, Sergey M. Bezrukov

Being motivated by recent progress in nanopore sensing, we develop a theory of the effect of large analytes, or blockers, trapped within the nanopore confines, on diffusion flow of small solutes. The focus is on the nanopore diffusion resistance which is the ratio of the solute concentration difference in the reservoirs connected by the nanopore to the solut

Rafael D. Benguria, Juan Manuel Gonzalez-Brantes, Trinidad Tubino

In this manuscript, using a technique introduced by P.~T.~Nam in 2012 and the {\it Coulomb Uncertainty Principle}, we prove new bounds on the excess charge for non relativistic atomic systems, independent of the particle statistics. These new bounds are the best bounds to date for bosonic systems for all values of the atomic number $Z$ and they are also the

Wenhua Li, Shengjun Huang, Tao Zhang, Rui Wang

Binary matrix optimization commonly arise in the real world, e.g., multi-microgrid network structure design problem (MGNSDP), which is to minimize the total length of the power supply line under certain constraints. Finding the global optimal solution for these problems faces a great challenge since such problems could be large-scale, sparse and multimodal.

Teal Pershing, Daniel Naim, Brian Lenardo, Jingke Xu

Liquid xenon-based direct detection dark matter experiments have recently expanded their searches to include high-energy nuclear recoil events as motivated by effective field theory dark matter and inelastic dark matter interaction models, but few xenon recoil calibrations above 100 keV are currently available. In this work, we measured the scintillation and