May 2022 arXiv papers — page 98

Humphrey Munn, Marcus Gallagher

Modularity has been widely studied as a mechanism to improve the capabilities of neural networks through various techniques such as hand-crafted modular architectures and automatic approaches. While these methods have sometimes shown improvements towards generalisation ability, robustness, and efficiency, the mechanisms that enable modularity to give perform

Tianshu Zheng, Cong Sun, Weihao Zheng, Wen Shi

Diffusion magnetic resonance imaging (dMRI) is an important tool in characterizing tissue microstructure based on biophysical models, which are complex and highly non-linear. Resolving microstructures with optimization techniques is prone to estimation errors and requires dense sampling in the q-space. Deep learning based approaches have been proposed to ove

Gongao Qi, Bin Yang, Wei Li

Fuzzy rough set (FRS) has a great effect on data mining processes and the fuzzy logical operators play a key role in the development of FRS theory. In order to further generalize the FRS theory to more complicated data environments, we firstly propose four types of fuzzy neighborhood operators based on fuzzy covering by overlap functions and their implicator

Thariq Shanavas, Michael Grayson, Bo Xu, Mo Zohrabi

We report the first observation of cascaded forward stimulated Brillouin scattering in a microresonator platform. We have demonstrated 25 orders of intramodal Stokes beams separated by a Brillouin shift of 34.5 MHz at a sub-milliwatt threshold at 1550 nm. An As$_2$S$_3$ microsphere of diameter 125 $\mu m$ with quality factor $1\times 10^6$ was used for this

Jinlong Peng, Zekun Luo, Liang Liu, Boshen Zhang

Image harmonization aims to generate a more realistic appearance of foreground and background for a composite image. Existing methods perform the same harmonization process for the whole foreground. However, the implanted foreground always contains different appearance patterns. All the existing solutions ignore the difference of each color block and losing

Xiaoqi Huang, Junyong Zhang

Let $(X,g)$ be a product cone with the metric $g=dr^2+r^2h$, where $X=C(Y)=(0,\infty)_r\times Y$ and the cross section $Y$ is a $(n-1)$-dimensional closed Riemannian manifold $(Y,h)$. We study the upper boundedness of heat kernel associated with the operator $L_V=-\Delta_g+V_0 r^{-2}$, where $-\Delta_g$ is the positive Friedrichs extension Laplacian on $X$ a

James Garner, Matthew Egbert

Living systems process sensory data to facilitate adaptive behaviour. A given sensor can be stimulated as the result of internally driven activity, or by purely external (environmental) sources. It is clear that these inputs are processed differently - have you ever tried tickling yourself? The canonical explanation of this difference is that when the brain

Zengrui Jin, Mengzhe Geng, Jiajun Deng, Tianzi Wang

Despite the rapid progress of automatic speech recognition (ASR) technologies targeting normal speech, accurate recognition of dysarthric and elderly speech remains highly challenging tasks to date. It is difficult to collect large quantities of such data for ASR system development due to the mobility issues often found among these users. To this end, data a

Daixuan Li, Benjamin Reidys, Jinghan Sun, Thomas Shull

Byte-addressable, non-volatile memory (NVM) is emerging as a promising technology. To facilitate its wide adoption, employing NVM in managed runtimes like JVM has proven to be an effective approach (i.e., managed NVM). However, such an approach is runtime specific, which lacks a generic abstraction across different managed languages. Similar to the well-know

A. Derzsi, P. Hartmann, M. Vass, B. Horváth

Phase Resolved Optical Emission Spectroscopy (PROES) measurements combined with 1d3v Particle-in-Cell/Monte Carlo Collisions (PIC/MCC) simulations are used to study the electron power absorption and excitation/ionization dynamics in capacitively coupled plasmas (CCPs) in mixtures of neon and oxygen gases. The study is performed for a geometrically symmetric

Emil A. Yuzbashyan, Boris L. Altshuler

We formulate the Migdal-Eliashberg theory of electron-phonon interactions in terms of classical spins by mapping the free energy to a Heisenberg spin chain in a Zeeman magnetic field. Spin components are energy-integrated normal and anomalous Green's functions and sites of the chain are fermionic Matsubara frequencies. The Zeeman field grows linearly with th

Subhajit Sarkar, Yonatan Dubi

Periodically-driven open quantum systems that never thermalize exhibit a discrete time-crystal behavior, a non-equilibrium quantum phenomenon that has shown promise in quantum information processing applications. Measurements of time-crystallinity are currently limited to (magneto-) optical experiments in atom-cavity systems and spin-systems making it an ind

Weiming Liu, Xiaolin Zheng, Mengling Hu, Chaochao Chen

Cross-Domain Recommendation (CDR) has been popularly studied to utilize different domain knowledge to solve the cold-start problem in recommender systems. Most of the existing CDR models assume that both the source and target domains share the same overlapped user set for knowledge transfer. However, only few proportion of users simultaneously activate on bo

Jen-tse Huang, Jianping Zhang, Wenxuan Wang, Pinjia He

Due to the labor-intensive nature of manual test oracle construction, various automated testing techniques have been proposed to enhance the reliability of Natural Language Processing (NLP) software. In theory, these techniques mutate an existing test case (e.g., a sentence with its label) and assume the generated one preserves an equivalent or similar seman

Fawei Zheng

Magnetic skyrmions are topologically protected spin swirling vertices, which are promising in device applications due to their particle-like nature and excellent controlability. Magnetic skyrmions have been extensively studied in a variety of materials and were proposed to exist in the extreme two-dimensional limit, i.e., in twisted bilayer CrI$_3$ (TBCI). U

Woo-Seok Choi, Brandon Reagen, Gu-Yeon Wei, David Brooks

This paper proposes Impala, a new cryptographic protocol for private inference in the client-cloud setting. Impala builds upon recent solutions that combine the complementary strengths of homomorphic encryption (HE) and secure multi-party computation (MPC). A series of protocol optimizations are developed to reduce both communication and performance bottlene

Xiangyu Xi, Chenxu Lv, Yuncheng Hua, Wei Ye

Though widely used in industry, traditional task-oriented dialogue systems suffer from three bottlenecks: (i) difficult ontology construction (e.g., intents and slots); (ii) poor controllability and interpretability; (iii) annotation-hungry. In this paper, we propose to represent utterance with a simpler concept named Dialogue Action, upon which we construct

Zihan Zhao, Lu Chen, Ruisheng Cao, Hongshen Xu

Recently, the structural reading comprehension (SRC) task on web pages has attracted increasing research interests. Although previous SRC work has leveraged extra information such as HTML tags or XPaths, the informative topology of web pages is not effectively exploited. In this work, we propose a Topological Information Enhanced model (TIE), which transform

Tian Chen, Ruyi Liu, Zhen Wu

In this paper, we consider a continuous-time mean-variance portfolio selection with regime-switching and random horizon. Unlike previous works, the dynamic of assets are described by non-Markovian regime-switching models in the sense that all the market parameters are predictable with respect to the filtration generated jointly by Markov chain and Brownian m

Tianshui Ma, Jie Li, Haiyan Yang, Shuanhong Wang

Let $H$ be a bialgebra. Let $\sigma: H\otimes H\to A$ be a linear map, where $A$ is a left $H$-comodule coalgebra, and an algebra with a left $H$-weak action $\triangleright$. Let $\tau: H\otimes H\to B$ be a linear map, where $B$ is a right $H$-comodule coalgebra, and an algebra with a right $H$-weak action $\triangleleft$. In this paper, we improve the nec

Yingkai Ouyang, Marco Tomamichel

We consider the problem of learning $N$ identical copies of an unknown $n$-qubit quantum graph state with product measurements. These graph states have corresponding graphs where every vertex has exactly $d$ neighboring vertices. Here, we detail an explicit algorithm that uses product measurements on multiple identical copies of such graph states to learn th

Martin John White

In this proceeding, I present the results of a recent global fit of an effective field theory of dark matter, performed using the Global and Modular Beyond-the-Standard Model Inference Tool (GAMBIT). A Dirac fermion dark matter candidate is assumed to interact only with Standard Model quarks and gluons, through a general set of operators up to mass dimension

Bing Liu, Rui-zhi Yang, Zhiwei Chen

Young massive clusters have been established as a new population of gamma-ray sources and potential cosmic ray (CR) accelerators. In this paper, we report the detection of gamma-ray emissions near the young star cluster NGC 6618, which is one of the youngest star clusters in our Galaxy. The detected gamma-ray emissions can be divided into two components. One

Qiao-Long Huang, Ke Ye, Xiao-Shan Gao

Based on the observation that $\mathbb{Q}^{(p-1) \times (p-1)}$ is isomorphic to a quotient skew polynomial ring, we propose a new method for $(p-1)\times (p-1)$ matrix multiplication over $\mathbb{Q}$, where $p$ is a prime number. The main feature of our method is the acceleration for matrix multiplication if the product is skew-sparse. Based on the new met

Koutaro Nakajima, Kouichi Okunishi

We study the angular-time evolution that is a parameter-time evolution defined by the entanglement Hamiltonian for the bipartitioned ground state of the Affleck-Kennedy-Lieb-Tasaki (AKLT) chain with the open boundary. In particular, we analytically calculate angular-time spin correlation functions $\langle S_n^\alpha(\tau)S_n^\alpha(0)\rangle$ with $\alpha =

Xingchen Zhao, Chang Liu, Anthony Sicilia, Seong Jae Hwang

The topic of generalizing machine learning models learned on a collection of source domains to unknown target domains is challenging. While many domain generalization (DG) methods have achieved promising results, they primarily rely on the source domains at train-time without manipulating the target domains at test-time. Thus, it is still possible that those

Weizhe Chen, Roni Khardon, Lantao Liu

Robotic Information Gathering (RIG) relies on the uncertainty of a probabilistic model to identify critical areas for efficient data collection. Gaussian processes (GPs) with stationary kernels have been widely adopted for spatial modeling. However, real-world spatial data typically does not satisfy the assumption of stationarity, where different locations a

Jiyoung Han

In his 1960 paper, Schmidt studied a quantitative type of Khintchine-Groshev theorem for general (higher) dimensions. Recently, a new proof of the theorem was found, which made it possible to relax the dimensional constraint and more generally, to add on the congruence condition by M. Alam, A. Ghosh, and S. Yu. In this paper, we generalize this new approach

Junpeng Hu, Shi Jin, Jinglai Li, Lei Zhang

In this paper, we evaluate the performance of the multilevel Monte Carlo method (MLMC) for deterministic and uncertain hyperbolic systems, where randomness is introduced either in the modeling parameters or in the approximation algorithms. MLMC is a well known variance reduction method widely used to accelerate Monte Carlo (MC) sampling. However, we demonstr

Logan Chariker, Anna De Masi, Joel L. Lebowitz, Errico Presutti

We derive macroscopic equations for a generalized contact process that is inspired by a neuronal integrate and fire model on the lattice $\mathbb{Z}^d$. The states at each lattice site can take values in $0,\ldots,k$. These can be interpreted as neuronal membrane potential, with the state $k$ corresponding to a firing threshold. In the terminology of the con

Jingmei Chang, Naihuan Jing

The CANDECOMP/PARAFAC (CP) decomposition is a generalization of the spectral decomposition of matrices to higher-order tensors. In this paper we use the CP decomposition to study unitary equivalence of higher order tensors and construct several invariants of local unitary equivalence for general higher order tensors. Based on this new method, we study the co

Hyoung-Kyu Song, Sang Hoon Woo, Junhyeok Lee, Seungmin Yang

In this work, we propose a joint system combining a talking face generation system with a text-to-speech system that can generate multilingual talking face videos from only the text input. Our system can synthesize natural multilingual speeches while maintaining the vocal identity of the speaker, as well as lip movements synchronized to the synthesized speec

Zihao Shen, Xiangdong Zhu, Rahim. R. Ullah, Peter Klavins

We report bulk magnetization measurements and spatially resolved measurements of magnetic domains in Co3Sn2S2 single crystals. The results indicate that a previously reported magnetic anomaly around 130 K is due to an anomalous domain wall depinning upon cooling. Our measurements also reveal a hysteresis between field-cooled-cooling (FCC) and field-cooled-wa

Daniel J. Slonim

We characterize ballistic behavior for general i.i.d. random walks in random environments on $\mathbb{Z}$ with bounded jumps. The two characterizations we provide do not use uniform ellipticity conditions. They are natural in the sense that they both relate to formulas for the limiting speed in the nearest-neighbor case. Note: This paper duplicates results f

He Zhang, Hechun Zhang, Ruibin Zhang

This paper is devoted to the representation theory of quantum coordinate algebra $\mathbb{C}_q[G]$, for a semisimple Lie group $G$ and a generic parameter $q$. By inspecting the actions of normal elements on tensor modules, we generalize a result of Levendorski and Soibelman in [22] for highest weight modules. For a double Bruhat cell $G^{w_1,w_2}$, we descr

Dewi Amaliah, Dianne Cook, Emi Tanaka, Kate Hyde

Textbook data is essential for teaching statistics and data science methods because they are clean, allowing the instructor to focus on methodology. Ideally textbook data sets are refreshed regularly, especially when they are subsets taken from an on-going data collection. It is also important to use contemporary data for teaching, to imbue the sense that th

Sanchit Hira, Digvijay Singh, Tae Soo Kim, Shobhit Gupta

Purpose: The objective of this investigation is to provide a comprehensive analysis of state-of-the-art methods for video-based assessment of surgical skill in the operating room. Methods: Using a data set of 99 videos of capsulorhexis, a critical step in cataract surgery, we evaluate feature based methods previously developed for surgical skill assessment m

Sandeep Kumar, Abhisek Panda, Smruti R. Sarangi

Trusted execution environments (TEEs) such as \intelsgx facilitate the secure execution of an application on untrusted machines. Sadly, such environments suffer from serious limitations and performance overheads in terms of writing back data to the main memory, their interaction with the OS, and the ability to issue I/O instructions. There is thus a plethora

Jianming Zhou, Xiaoli Hu, Naihuan Jing

The quantum discord of bipartite systems is one of the best-known measures of non-classical correlations and an important quantum resource. In the recent work appeared in [Phys. Rev. Lett 2020, 124:110401], the quantum discord has been generalized to multipartite systems. In this paper, we give analytic solutions of the quantum discord for tripartite states

Jie Fang, Zi-Hao Chen, Yao Wang, Rui-Xue Xu

Correlated driving-and-dissipation equation (CODDE) is an optimized complete second-order quantum dissipation approach, which is originally concerned with the reduced system dynamics only. However, one can actually extract the hybridized bath dynamics from CODDE with the aid of dissipaton-equation-of-motion theory, a statistical quasi-particle quantum dissip

Yue Qi, Mojtaba Vaezi

The Gaussian multiple-input multiple-output (MIMO) multi-receiver wiretap channel is studied in this paper. The base station broadcasts confidential messages to K intended users while keeping the messages secret from an eavesdropper. The capacity of this channel has already been characterized by applying dirty-paper coding and stochastic encoding. However, K

Koichi Hattori, Kazunori Itakura

We investigate the axial Ward identity (AWI) for massive fermions in strong magnetic fields. The divergence of the axial-vector current is computed at finite temperature and/or density with the help of a relation between the polarization and anomaly diagrams in the effective (1+1) dimensions realized in the lowest Landau level (LLL). We discuss delicate inte

Zhongyao Ma, Keyu Wu, Zhong Liu

The study of the multi-ship air defense model is of great significance in the simulation and evaluation of the actual combat process, the demonstration of air defense tactics, and the improvement of the security of important targets. The traditional multi-ship air defense model does not consider the coordination between ships, and the model assumptions are o

Tian-Yu Ye, Hong-Kun Li, Jia-Li Hu

In this paper, a novel semi-quantum key distribution (SQKD) protocol is designed based on single photons in both polarization and spatial-mode degrees of freedom, which allows to establish a raw key between one quantum communicant and one classical communicant. The proposed SQKD protocol only adopts one kind of quantum state as the initial quantum resource.

Daniel Matteo, Sergei Tochitsky, Chan Joshi

Supercontinuum generation is performed in the bulk semiconductor tellurium (Te) with a high-power picosecond CO$_2$ laser at peak intensities up to 20 GW/cm$^2$. The spectrum spans from the second harmonic of the pump at 5.3 $\mu$m to 32 $\mu$m. Stimulated Raman scattering along with self-phase modulation and four wave mixing are found to be the main nonline

Matt Wright

Natural language processing (NLP) is the field that attempts to make human language accessible to computers, and it relies on applying a mathematical model to express the meaning of symbolic language. One such model, DisCoCat, defines how to express both the meaning of individual words as well as their compositional nature. This model can be naturally implem

Tian-Yu Ye, Chong-Qiang Ye

In this paper, we successfully design the semi-quantum private comparison (SQPC) protocol with the measure-resend characteristic by using two-particle product states as the initial prepared quantum resource which allows two classical users to compare the equality of their private secrets under the help of a quantum third party (TP). The quantum TP is semi-ho

Minghua Wang, Danfeng Hong, Zhu Han, Jiaxin Li

Owing to the rapid development of sensor technology, hyperspectral (HS) remote sensing (RS) imaging has provided a significant amount of spatial and spectral information for the observation and analysis of the Earth's surface at a distance of data acquisition devices, such as aircraft, spacecraft, and satellite. The recent advancement and even revolution of

Robert Lizée

Neural networks promote a distributed representation with no clear place for symbols. Despite this, we propose that symbols are manufactured simply by training a sparse random noise as a self-sustaining attractor in a feedback spiking neural network. This way, we can generate many of what we shall call prime attractors, and the networks that support them are

Chong-Qiang Ye, Tian-Yu Ye

In this paper, by using d-level single-particle states, two novel multi-party quantum private comparison protocols for size relation comparison with two semi-honest third parties and one semi-honest third party are constructed, respectively. Here, each protocol can compare the size relation of secret integers from n parties rather than just the equality with

Serik Sagitov, Anders Ståhlberg

Detection of extremely rare variant alleles, such as tumour DNA, within a complex mixture of DNA molecules is experimentally challenging due to sequencing errors. Barcoding of target DNA molecules in library construction for next-generation sequencing provides a way to identify and bioinformatically remove polymerase induced errors. During the barcoding proc

Phuoc Nguyen, Truyen Tran, Ky Le, Sunil Gupta

We introduce a conditional compression problem and propose a fast framework for tackling it. The problem is how to quickly compress a pretrained large neural network into optimal smaller networks given target contexts, e.g. a context involving only a subset of classes or a context where only limited compute resource is available. To solve this, we propose an

Mohammadali Mohammadi, Tung T. Vu, Behnaz Naderi Beni, Hien Quoc Ngo

We consider a cell-free massive multiple-input multiple-output (MIMO) network utilizing a virtually full-duplex (vFD) mode, where access points (APs) with a downlink (DL) mode and those with an uplink (UL) mode simultaneously serve DL and UL users (UEs). In order to maximize the sum spectral efficiency (SE) of the DL and UL transmissions, we formulate a mixe

Joseph V. Pusztay, Matthew G. Knepley, Mark F. Adams

Particle-in-Cell (PIC) methods employ particle representations of unknown fields, but also employ continuum fields for other parts of the problem. Thus projection between particle and continuum bases is required. Moreover, we often need to enforce conservation constraints on this projection. We derive a mechanism for enforcement based on weak equality, and i

Hongbin Liu, Jinyuan Jia, Neil Zhenqiang Gong

Contrastive learning pre-trains an image encoder using a large amount of unlabeled data such that the image encoder can be used as a general-purpose feature extractor for various downstream tasks. In this work, we propose PoisonedEncoder, a data poisoning attack to contrastive learning. In particular, an attacker injects carefully crafted poisoning inputs in

SNO+ Collaboration, :, A. Allega, M. R. Anderson

This paper reports results from a search for single and multi-nucleon disappearance from the $^{16}$O nucleus in water within the \snoplus{} detector using all of the available data. These so-called "invisible" decays do not directly deposit energy within the detector but are instead detected through their subsequent nuclear de-excitation and gamma-ray emiss

Hiroshi Imamura, Hiroko Arai, Rie Matsumoto, Toshiki Yamaji

Recent advances in experimental techniques have made it possible to manipulate and measure the magnetization dynamics on the femtosecond time scale which is the same order as the correlation time of the bath degrees of freedom. In the equations of motion of magnetization, the correlation of the bath is represented by the non-Markovian damping. For developmen

Steffen Enders, Eva-Maria C. Behner, Niklas Bergmann, Mariia Rybalka

Analyzing third-party software such as malware or firmware is a crucial task for security analysts. Although various approaches for automatic analysis exist and are the subject of ongoing research, analysts often have to resort to manual static analysis to get a deep understanding of a given binary sample. Since the source code of encountered samples is rare

Pritam Dey, Zhengwu Zhang, David B. Dunson

It has become routine in neuroscience studies to measure brain networks for different individuals using neuroimaging. These networks are typically expressed as adjacency matrices, with each cell containing a summary of connectivity between a pair of brain regions. There is an emerging statistical literature describing methods for the analysis of such multi-n

Srivatsa Kundurthy

The Spotted Lanternfly (SLF) is an invasive planthopper that threatens the local biodiversity and agricultural economy of regions such as the Northeastern United States and Japan. As researchers scramble to study the insect, there is a great potential for computer vision tasks such as detection, pose estimation, and accurate identification to have important

Zhongze Zhang, Tao Jiang, Wei Yu

Reconfigurable intelligent surface (RIS) is capable of intelligently manipulating the phases of the incident electromagnetic wave to improve the wireless propagation environment between the base-station (BS) and the users. This paper addresses the joint user scheduling, RIS configuration, and BS beamforming problem in an RIS-assisted downlink network with li

Eric Sihite, Xintao Hu, Bozhen Li, Adarsh Salagame

Bats' dynamic morphing wings are known to be extremely high-dimensional, and they employ the combination of inertial dynamics and aerodynamics manipulations to showcase extremely agile maneuvers. Bats heavily rely on their highly flexible wings and are capable of dynamically morphing their wings to adjust aerodynamic and inertial forces applied to their wing

Mei-Ming Zhang, Naihuan Jing, Hui Zhao

We study the monogamy and polygamy inequalities of unified entanglement in multipartite quantum systems. We first derive the monogamy inequality of unified-$(q, s)$ entanglement for multi-qubit states under arbitrary bipartition, and then obtain the monogamy inequalities of the $\alpha$th ($0\leq\alpha\leq\frac{r}{2}, r\geq\sqrt{2}$) power of entanglement of

Gowtham R. Kurri, Monica Welfert, Tyler Sypherd, Lalitha Sankar

We prove a two-way correspondence between the min-max optimization of general CPE loss function GANs and the minimization of associated $f$-divergences. We then focus on $\alpha$-GAN, defined via the $\alpha$-loss, which interpolates several GANs (Hellinger, vanilla, Total Variation) and corresponds to the minimization of the Arimoto divergence. We show that

Eric Sihite, Benjamin Mottis, Paul Ghanem, Alireza Ramezani

There have been several successful implementations of bio-inspired legged robots that can trot, walk, and hop robustly even in the presence of significant unplanned disturbances. Despite all of these accomplishments, practical control and high-level decision-making algorithms in multi-modal legged systems are overlooked. In nature, animals such as birds impr

John Rushby

Modal logics allow reasoning about various modes of truth: for example, what it means for something to be possibly true, or to know that something is true as opposed to merely believing it. This report describes embeddings of propositional and quantified modal logic in the PVS verification system. The resources of PVS allow this to be done in an attractive w

Lionel Nganyewou Tidjon, Foutse Khomh

Artificial Intelligence (AI) is transforming our daily life with several applications in healthcare, space exploration, banking and finance. These rapid progresses in AI have brought increasing attention to the potential impacts of AI technologies on society, with ethically questionable consequences. In recent years, several ethical principles have been rele

Mina Udono, Koudai Sugimoto, Tatsuya Kaneko, Yukinori Ohta

To study excitonic effects on high-harmonic generation (HHG) in Mott insulators, we investigate pumped nonequilibrium dynamics in the one-dimensional extended Hubbard model. By employing time-dependent calculations based on the exact diagonalization and infinite time-evolving block decimation methods, we find the strong enhancement of the HHG intensity aroun

Markus Rambach, Akram Youssry, Marco Tomamichel, Jacquiline Romero

Quantum state tomography, which aims to find the best description of a quantum state -- the density matrix, is an essential building block in quantum computation and communication. Standard techniques for state tomography are incapable of tracking changing states and often perform poorly in the presence of environmental noise. Although there are different ap

Viqar Husain, Irfan Javed, Suprit Singh

Motivated by quantum gravity, semi-classical theory, and quantum theory on curved spacetimes, we study the system of an oscillator coupled to two spin-1/2 particles. This model provides a prototype for comparing three types of dynamics: the full quantum theory, the classical oscillator with spin backreaction, and spins propagating on a fixed oscillator backg

Li Li, Zhimeng Ouyang

We consider an inverse problem for the nonlinear Boltzmann equation near the equilibrium. Our goal is to determine the collision kernel in the Boltzmann equation from the knowledge of the Albedo operator. Our approach relies on a linearization technique as well as the injectivity of the Gauss-Weierstrass transform.

S. E. Woosley, Nathan Smith

We explore a variety of models in which SN~1961V, one of the most enigmatic supernovae (SNe) ever observed, was a pulsational pair-instability supernova (PPISN). Successful models reproduce the bolometric light curve of the principal outburst and, in some cases, the emission one year before and several years afterward. All models have helium-rich ejecta, bul

Sayle Sigarreta, Hugo Cruz-Suarez, Sergio Torralbas Fitz

In this paper, we examine a specific type of random chains and propose an unified approach to studying the degree-based topological indices, including their extreme values. We derive explicit analytical expressions for the expected values and variances of these indices and we establish the asymptotic behavior of the indices. Specifically, we analyze the firs

Andrea Flamini, Riccardo Longo, Alessio Meneghetti

In this paper we explore a context of application of Cob, a recently introduced Byzantine Fault Tolerant consensus protocol. Cob proves to be a leaderless consensus protocol which carries out the consensus process in parallel on each component of a list of events to be observed and recorded. We show how Cob can be used to define a consensus layer for scalabl

Owen Garnier

In his seminal paper on complex reflection arrangements, Bessis introduces a Garside structure for the braid group of a well-generated irreducible complex reflection group. Using this Garside structure, he establishes a strong connection between regular elements in the reflection group, and roots of the "full twist" element of the pure braid group. He then s

Benjamin K. Malia, Yunfan Wu, Julián Martínez-Rincón, Mark A. Kasevich

Quantum sensors are used for precision timekeeping, field sensing, and quantum communication. Comparisons among a distributed network of these sensors are capable of, for example, synchronizing clocks at different locations. The performance of a sensor network is limited by technical challenges as well as the inherent noise associated with the quantum states

Peter Sun, Dae-Kyoo Kim

Dependency injection (DI) is generally known to improve maintainability by keeping application classes separate from the library. Particularly within the Java environment, there are many applications using the principles of DI with the aim to improve maintainability. There exists some work that provides an inference on the impact of DI on maintainability, bu

James Greenberg, Rubab Amin, Brendan M. Heffernan, Antoine Rolland

Optical generation of millimeter-waves (mm-wave) is made possible by an optical heterodyne of two diode lasers on a uni-traveling-carrier photodiode (UTC-PD). We utilized this technique to produce a mm-wave oscillator with desirable phase-noise characteristics, which were inherited from a pair of narrow-linewidth diode lasers. We present the long-term stabil

John Golden, Daniel O'Malley, Hari Viswanathan

Modeling hydrological fracture networks is a hallmark challenge in computational earth sciences. Accurately predicting critical features of fracture systems, e.g. percolation, can require solving large linear systems far beyond current or future high performance capabilities. Quantum computers can theoretically bypass the memory and speed constraints faced b

Joshua Isaacson, William I. Jay, Alessandro Lovato, Pedro A. N. Machado

We present a novel lepton-nucleus event generator: ACHILLES, A CHIcagoLand Lepton Event Simulator. The generator factorizes the primary interaction from the propagation of hadrons in the nucleus, which allows for a great deal of modularity, facilitating further improvements and interfaces with existing codes. We validate our generator against high quality el

V. I. Kukulin, V. N. Pomerantsev, O. A. Rubtsova, M. N. Platonova

The dibaryon concept for the nuclear force is presented, assuming that the main attraction between the nucleons at medium distances is determined by the $s$-channel exchange of an intermediate six-quark (dibaryon) state. To construct the respective $NN$ interaction model, a microscopic six-quark description of the $NN$ system is used, in which symmetry aspec

Marlena S. Bannick, Fei Gao, Elizabeth R. Brown, Holly E. Janes

COVID-19 vaccines are highly efficacious at preventing symptomatic infection, severe disease, and death. Most of the evidence that COVID-19 vaccines also reduce transmission of SARS-CoV-2 is based on retrospective, observational studies. Specifically, an increasing number of studies are evaluating vaccine efficacy against the secondary attack rate of SARS-Co

Heinrich van Deventer, Pieter Janse van Rensburg, Anna Bosman

Neural networks have been criticised for their inability to perform continual learning due to catastrophic forgetting and rapid unlearning of a past concept when a new concept is introduced. Catastrophic forgetting can be alleviated by specifically designed models and training techniques. This paper outlines a novel Spline Additive Model (SAM). SAM exhibits

Viviane Pons

We give a description of the well known Zeta map on Dyck paths which sends the dinv,area statistics to the area,bounce statistics. Our description uses Dyck paths area sequences and can be implemented easily.

Michelle A. Hunter, Baris Demir, Charlotte F. Petersen, Debra J. Searles

Widely applicable, modified Green-Kubo expressions for the local diffusion coefficient ($D_l$) are obtained using linear response theory. In contrast to past definitions in use, these expressions are statistical mechanical results. Molecular simulations of systems with anisotropic diffusion and an inhomogeneous density profile confirm the validity of the res

Gabriel R. Barrenechea, Erik Burman, Ernesto Cáceres, Johnny Guzmán

In this paper we propose, analyze, and test numerically a pressure-robust stabilized finite element for a linearized problem in incompressible fluid mechanics, namely, the steady Oseen equation with low viscosity. Stabilization terms are defined by jumps of different combinations of derivatives for the convective term over the element faces of the triangulat

Belle II Collaboration

We present measurements of the first to fourth moments of the lepton mass squared $q^2$ of \mbox{$B \to X_c \, \ell\, \bar \nu_{\ell}$} decays for $\ell = e, \mu$ and with $X_c$ a hadronic system containing a charm quark. These results use a sample of electron-positron collisions at the $\Upsilon(4S)$ resonance corresponding to $62.8 \, \mathrm{fb}^{-1}$ of

Mingyu Fan, Gary A. Williams, Karla Galdamez, Charlie McDowell

Vortex fluctuations above and below the critical Kosterlitz-Thouless (KT) transition temperature are characterized using simulations of the 2D XY model. The net winding number of vortices at a given temperature in a circle of radius $R$ is computed as a function of $R$. The average squared winding number is found to vary linearly with the perimeter of the ci

Tuviere Onookome-Okome, Jonah Gorondensky, Eric Rose, Jeffery Sauer

The murder of George Floyd centered Minneapolis, Minnesota, in conversations on racial injustice in the US. We leverage open data from the Minneapolis Police Department to analyze individual, geographic, and temporal patterns in more than 170,000 police stops since 2016. We evaluate person and vehicle searches at the individual level by race using generalize

Matthew Jagielski, Stanley Wu, Alina Oprea, Jonathan Ullman

A large body of research has shown that machine learning models are vulnerable to membership inference (MI) attacks that violate the privacy of the participants in the training data. Most MI research focuses on the case of a single standalone model, while production machine-learning platforms often update models over time, on data that often shifts in distri

Jessica S. Purcell, Anastasiia Tsvietkova

Since the 1980s, it has been known that essential surfaces in alternating link complements can be isotoped to be transverse to the link diagram almost everywhere, with the exception of some well-understood intersections, and described combinatorially as a result. This was called standard position for surfaces and has had numerous applications. However, the o

Bernardo Luiz R. Ribeiro, Jennifer A. Franck

A machine learning model is developed to establish wake patterns behind oscillating foils whose kinematics are within the energy harvesting regime. The role of wake structure is particularly important for array deployments of oscillating foils, since the unsteady wake highly influences performance of downstream foils. This work explores 46 oscillating foil k

Kouki Nakata, Yuichi Ohnuma, Se Kwon Kim

The celebrated Wiedemann-Franz (WF) law which governs the relation between charge and heat transport traces back to the experimental discovery in 1853 by Wiedemann and Franz. Despite the fundamental difference of the quantum-statistical properties between fermions and bosons, the linear-in-$T$ behavior of the WF law at low temperatures has recently been foun

Evgeny I. Zelenov

The paper proposes a construction of a quantum differentiation operator defined on the spaces of complex-valued functions of $p$-adic argument, and taking values in the algebra of bounded operators on a Hilbert space. The properties of this operator are investigated. In particular, it is proved that the differentiation operator maps $p$-adic Besov spaces int

Raymond J. Spiteri, Siqi Wei

Fractional-step methods are a popular and powerful divide-and-conquer approach for the numerical solution of differential equations. When the integrators of the fractional steps are Runge--Kutta methods, such methods can be written as generalized additive Runge--Kutta (GARK) methods, and thus the representation and analysis of such methods can be done throug

Tae Yoon Lee, Paul Gustafson, Mohsen Sadatsafavi

In Value of Information (VoI) analysis, the unit normal loss integral (UNLI) frequently emerges as a solution for the computation of various VoI metrics. However, one limitation of the UNLI has been that its closed-form solution is available for only one dimension, and thus can be used for comparisons involving only two strategies (where it is applied to the

Rina Friedberg, Karthik Rajkumar, Jialiang Mao, Qian Yao

Information retrieval systems, such as online marketplaces, news feeds, and search engines, are ubiquitous in today's digital society. They facilitate information discovery by ranking retrieved items on predicted relevance, i.e. likelihood of interaction (click, share) between users and items. Typically modeled using past interactions, such rankings have a m

J. Amarel, D. Belitz, T. R. Kirkpatrick

We discuss contributions to the thermopower in an electron fluid. A simple argument based on Newton's second law with the pressure gradient as the force suggests that the thermopower is given by a thermodynamic derivative, viz., the entropy per particle, rather than being an independent transport coefficient. The resolution is the existence of an entropic fo

Yuqi Xue, Luyi Kang, Weiwei Jia, Xiaohao Wang

In-storage computing with modern solid-state drives (SSDs) enables developers to offload programs from the host to the SSD. It has been proven to be an effective approach to alleviating the I/O bottleneck. To facilitate in-storage computing, many frameworks have been proposed. However, few of them consider security as the priority for in-storage computing. S

William Schultz, Ian Dardik, Stavros Tripakis

We present a new technique for automatically inferring inductive invariants of parameterized distributed protocols specified in TLA+. Ours is the first such invariant inference technique to work directly on TLA+, an expressive, high level specification language. To achieve this, we present a new algorithm for invariant inference that is based around a core p