July 2022 arXiv papers — page 40

Bang-Shien Chen, Jann-Long Chern

We present and compare two methods of generating quantum feature maps for quantum-enhanced support vector machine, a classifier based on kernel method, by which we can access high dimensional Hilbert space efficiently. The first method is a genetic algorithm with multi-objective fitness function using penalty method, which incorporates maximizing the accurac

Haris Moazam Sheikh, Sangjoon Lee, Jinge Wang, Philip S. Marcus

We present Design-by-Morphing (DbM), a novel design methodology applicable to creating a search space for topology optimization of 2D airfoils. Most design techniques impose geometric constraints and sometimes designers' bias on the design space itself, thus restricting the novelty of the designs created, and only allowing for small local changes. We show th

Xu Zhou, Xinyu Lei, Cong Yang, Yichun Shi

Federated learning (FL) supports distributed training of a global machine learning model across multiple devices with the help of a central server. However, data heterogeneity across different devices leads to the client model drift issue and results in model performance degradation and poor model fairness. To address the issue, we design Federated learning

Minh On Vu Ngoc, Yizi Chen, Nicolas Boutry, Jonathan Fabrizio

Capturing the global topology of an image is essential for proposing an accurate segmentation of its domain. However, most of existing segmentation methods do not preserve the initial topology of the given input, which is detrimental for numerous downstream object-based tasks. This is all the more true for deep learning models which most work at local scales

Ibrahem Yakzan Hasan, Rudra Narayan Padhan, Manjula Das

In this article, we define the capable pairs of Lie superalgebras. We classify all capable pairs of abelian and Heisenberg Lie superalgebras. After that we discuss on pairs of Lie superalgebras with derived subalgebra of dimension one and a non-abelian ideal. Finally, we determine the structure of the Schur multiplier of pairs of Heisenberg Lie superalgebras

Jie Yang, Yilin Li, Deddy Jobson

Promotions have been trending in the e-commerce marketplace to build up customer relationships and guide customers towards the desired actions. Since incentives are effective to engage customers and customers have different preferences for different types of incentives, the demand for personalized promotion decision making is increasing over time. However, r

M. Abughalwa, H. D. Tuan, D. N. Nguyen, H. V. Poor

This paper considers the downlink of an ultra-reliable low-latency communication (URLLC) system in which a base station (BS) serves multiple single-antenna users in the short (finite) blocklength (FBL) regime with the assistance of a reconfigurable intelligent surface (RIS). In the FBL regime, the users' achievable rates are complex functions of the beamform

Nupur Nandi, Rudra Narayan Padhan

The main object of study of this paper is the notion of 3-Lie superalgebras with superderivations. We consider a representation $(\Phi,\mathcal{P})$ of a $3$-Lie superalgebra $\mathcal{Q}$ on $\mathcal{P}$ and construct first-order cohomologies by using superderivations of $\mathcal{P},\mathcal{Q}$ which induces a Lie superalgebra $\mathcal{T}_{\Phi}$ and it

Xindi Luo, Zequn Sun, Wei Hu

This paper presents $\mu\text{KG}$, an open-source Python library for representation learning over knowledge graphs. $\mu\text{KG}$ supports joint representation learning over multi-source knowledge graphs (and also a single knowledge graph), multiple deep learning libraries (PyTorch and TensorFlow2), multiple embedding tasks (link prediction, entity alignme

Li Xu, Haoxuan Qu, Jason Kuen, Jiuxiang Gu

Video scene graph generation (VidSGG) aims to parse the video content into scene graphs, which involves modeling the spatio-temporal contextual information in the video. However, due to the long-tailed training data in datasets, the generalization performance of existing VidSGG models can be affected by the spatio-temporal conditional bias problem. In this w

A. Chilingarian, G. Hovsepyan, T. Karapetyan, L. Kozliner

In the present report, we describe the NaI particle detector network and present the first results of the experiment demonstrating that the particle fluxes from the atmospheric electron accelerators can cover large areas on the earth surface.

Guillermo Martín-Sánchez, Sander Bohté, Sebastian Otte

Backpropagation through time (BPTT) is the de facto standard for training recurrent neural networks (RNNs), but it is non-causal and non-local. Real-time recurrent learning is a causal alternative, but it is highly inefficient. Recently, e-prop was proposed as a causal, local, and efficient practical alternative to these algorithms, providing an approximatio

Lizhen Long, Chi-Man Pun

Arbitrary style transfer generates an artistic image which combines the structure of a content image and the artistic style of the artwork by using only one trained network. The image representation used in this method contains content structure representation and the style patterns representation, which is usually the features representation of high-level i

Chenghao Yang, Zhongda Wang, Yinshui Xia, Zhufei Chu

In the logic synthesis stage, structure transformations in the synthesis tool need to be combined into optimization sequences and act on the circuit to meet the specified circuit area and delay. However, logic synthesis optimization sequences are time-consuming to run, and predicting the quality of the results (QoR) against the synthesis optimization sequenc

Yuxin Wang, Yuanning Cui, Wenqiang Liu, Zequn Sun

Entity alignment is a basic and vital technique in knowledge graph (KG) integration. Over the years, research on entity alignment has resided on the assumption that KGs are static, which neglects the nature of growth of real-world KGs. As KGs grow, previous alignment results face the need to be revisited while new entity alignment waits to be discovered. In

Jessica Wang, Joseph Fehribach

A Kirchhoff graph is a vector graph with orthogonal cycles and vertex cuts. An algorithm has been developed that constructs all the Kirchhoff graphs up to a fixed edge multiplicity. This algorithm is used to explore the structure of prime Kirchhoff graph tilings. The existence of infinitely many prime Kirchhoff graphs given a set of fundamental Kirchhoff gra

Baolin Li, Rohan Basu Roy, Tirthak Patel, Vijay Gadepally

Deep learning model inference is a key service in many businesses and scientific discovery processes. This paper introduces RIBBON, a novel deep learning inference serving system that meets two competing objectives: quality-of-service (QoS) target and cost-effectiveness. The key idea behind RIBBON is to intelligently employ a diverse set of cloud computing i

Xinyi Wang, Zitao Wang, Weijian Sun, Wei Hu

Document-level relation extraction (RE) aims to identify the relations between entities throughout an entire document. It needs complex reasoning skills to synthesize various knowledge such as coreferences and commonsense. Large-scale knowledge graphs (KGs) contain a wealth of real-world facts, and can provide valuable knowledge to document-level RE. In this

Sebastian Rietsch, Shih-Yuan Huang, Georgios Kontes, Axel Plinge

Reinforcement learning (RL) has shown to reach super human-level performance across a wide range of tasks. However, unlike supervised machine learning, learning strategies that generalize well to a wide range of situations remains one of the most challenging problems for real-world RL. Autonomous driving (AD) provides a multi-faceted experimental field, as i

Ghanta Sai Krishna, Dyavat Sumith, Garika Akshay

A two-wheeled self-balancing robot is an example of an inverse pendulum and is an inherently non-linear, unstable system. The fundamental concept of the proposed framework "Epersist" is to overcome the challenge of counterbalancing an initially unstable system by delivering robust control mechanisms, Proportional Integral Derivative(PID), and Reinforcement L

Qiao Zhu, Zhihong Qian, Bruno Clerckx, Xue Wang

In this paper, the potential benefits of applying the Rate-Splitting Multiple Access (RSMA) in multi-cell dense networks are explored. Using tools of stochastic geometry, the sum-rate of RSMA-enhanced multi-cell dense networks is evaluated mathematically based on a Moment Generating Function (MGF) based framework to prove that RSMA is a general and powerful

Colin Benjamin, Naini Dudhe

The Internet is one of the most valuable technologies invented to date. Among them, Google is the most widely used search engine. The PageRank algorithm is the backbone of Google search, ranking web pages according to relevance and recency. We employ quantum stochastic walks (QSWs) to improve the classical PageRank (CPR) algorithm based on classical continuo

R. Balaji, Vinayak Gupta

We show that all off-diagonal entries in the Moore-Penrose inverse of the distance Laplacian matrix of a tree are non-positive.

Baolin Li, Tirthak Patel, Siddarth Samsi, Vijay Gadepally

GPU technology has been improving at an expedited pace in terms of size and performance, empowering HPC and AI/ML researchers to advance the scientific discovery process. However, this also leads to inefficient resource usage, as most GPU workloads, including complicated AI/ML models, are not able to utilize the GPU resources to their fullest extent -- encou

FASER Collaboration, Henso Abreu, Elham Amin Mansour, Claire Antel

FASER, the ForwArd Search ExpeRiment, is an experiment dedicated to searching for light, extremely weakly-interacting particles at CERN's Large Hadron Collider (LHC). Such particles may be produced in the very forward direction of the LHC's high-energy collisions and then decay to visible particles inside the FASER detector, which is placed 480 m downstream

Shehbaz Jaffer, Kaveh Mahdaviani, Bianca Schroeder

High density Solid State Drives, such as QLC drives, offer increased storage capacity, but a magnitude lower Program and Erase (P/E) cycles, limiting their endurance and hence usability. We present the design and implementation of non-binary, Voltage-Based Write-Once-Memory (WOM-v) Codes to improve the lifetime of QLC drives. First, we develop a FEMU based s

Huyuan Chen, Ying Wang, Feng Zhou

This paper is concerned with the elliptic equation $-\Delta u=\frac{\lambda }{(a-u)^p}$ in a connected, bounded $C^2$ domain $\Omega$ of $\mathbb{R}^N$ subject to zero Dirichlet boundary conditions, where $\lambda>0$, $N\geq 1$, $p>0$ and $a:\bar\Omega\to[0,1]$ vanishes at the boundary with the rate ${\rm dist}(x,\partial\Omega)^\gamma$ for $\gamma>0$. When

Sheng Zhang, Ashwin Pananjady, Justin Romberg

Motivated by decentralized sensing and policy evaluation problems, we consider a particular type of distributed stochastic optimization problem over a network, called the online stochastic distributed averaging problem. We design a dual-based method for this distributed consensus problem with Polyak--Ruppert averaging and analyze its behavior. We show that t

Ruowei Li

In this paper, let $G$ be a Cayley graph of a discrete group of polynomial growth with homogeneous dimension $N\geq3$. We study the Choquard type equation on $G$: \begin{equation} \Delta u+(R_{\alpha}\ast\mid u\mid^{p})\mid u\mid^{p-2}u=0, \end{equation} where $\alpha\in(0,N)$, $p>\frac{N+\alpha}{N-2}$ and $R_{\alpha}$ stands for the Green's function of the

Stefano Longhi

Discrete-time photonic quantum walks on a synthetic lattice, where both spatial and temporal evolution of light is discretized, have provided recently a fascinating platform for the observation of a wealth of non-Hermitian physical phenomena and for the control of light scattering in complex media. A rather open question is whether invisible potentials, anal

Tanner M. Melody, Krishna H. Patel, Peter K. Nguyen, Christopher L. Smallwood

We report on the construction and characterization of a low-cost Mach-Zehnder optical interferometer in which quadrature signal detection is achieved by means of polarization control. The device incorporates a generic green laser pointer, home-built photodetectors, 3D-printed optical mounts, a circular polarizer extracted from a pair of 3D movie glasses, and

Hao Wu, Junhao Hu, Chenggui Yuan

In this article, we prove the existence of weak solutions as well as the existence and uniqueness of strong solutions for McKean-Vlasov multivalued stochastic differential equations with oblique subgradients (MVMSDEswOS, for short) by means of the equations of Euler type and Skorohod's representation theorem. For this type of equation, compared with the meth

Koun Shirai

The third law of thermodynamics dictates that the entropy of materials becomes zero as temperature ($T$) approaches zero. Contrarily, glass and other similar materials exhibit nonzero entropy at $T=0$, which contradicts the third law. For over a century, it has been a common practice to evade this problem by regarding glass as nonequilibrium. However, this t

Satoru Hayami, Megumi Yatsushiro

We propose a new mechanism of nonlinear nonreciprocal transport in magnetic systems. By considering a noncoplanar magnetic ordering on a bilayer triangular lattice, we clarify that a local scalar chirality degree of freedom is a source of nonreciprocal transport, which does not require any relativistic spin-orbit coupling, net scalar chirality, and net magne

Vincent Béhani

In this paper, we study the so-called Bishop operators $T _ \alpha$ on $L ^ p ([0, 1])$, with $\alpha \in (0, 1)$ and $1 < p < + \infty$, from the point of view of linear dynamics. We show that they are never hypercyclic nor supercyclic, and investigate extensions of these results to the case of weighted translation operators. We then investigate the cyclici

Zhong Shen, Yufei Xue, Zebin Wu, Changsheng Song

We report CrISe monolayer as a room temperature ferromagnetic semiconductor with the Curie temperature ($T_C$), magnetic anisotropy energy (MAE) and band gap being 322 K, 113 $\mu$eV and 0.67 eV, respectively. The $T_C$ and MAE can be further enhanced up to 385 K and 313 $\mu$eV by tensile strain. More interestingly, the magnetic easy axis can be switched be

Björn Lütjens, Catherine H. Crawford, Campbell D Watson, Christopher Hill

Numerical simulations in climate, chemistry, or astrophysics are computationally too expensive for uncertainty quantification or parameter-exploration at high-resolution. Reduced-order or surrogate models are multiple orders of magnitude faster, but traditional surrogates are inflexible or inaccurate and pure machine learning (ML)-based surrogates too data-h

Julia V. Velikina, Ruiyang Zhao, Collin J. Buelo, Alexey A. Samsonov

Purpose: To improve repeatability and reproducibility across acquisition parameters and reduce bias in quantitative susceptibility mapping (QSM) of the liver, through development of an optimized regularized reconstruction algorithm for abdominal QSM. Theory and Methods: An optimized approach to estimation of magnetic susceptibility distribution is formulated

Yixian Zhu, Ketan Savla

We study the following repeated non-atomic routing game. In every round, nature chooses a state in an i.i.d. manner according to a publicly known distribution, which influences link latency functions. The system planner makes private route recommendations to participating agents, which constitute a fixed fraction, according to a publicly known signaling stra

Sebin Gracy, Philip E. Paré, Ji Liu, Henrik Sandberg

The paper deals with the setting where two viruses (say virus 1 and virus 2) coexist in a population, and they are not necessarily mutually exclusive, in the sense that infection due to one virus does not preclude the possibility of simultaneous infection due to the other. We develop a coupled bi-virus susceptible-infected-susceptible (SIS) model from a 4n-s

Daniel Posada, Jarred Jordan, Angelica Radulovic, Lillian Hong

Robotic and human lunar landings are a focus of future NASA missions. Precision landing capabilities are vital to guarantee the success of the mission, and the safety of the lander and crew. During the approach to the surface there are multiple challenges associated with Hazard Relative Navigation to ensure safe landings. This paper will focus on a passive a

Jarred Jordan, Daniel Posada, David Zuehlke, Angelica Radulovic

This work utilizes a MobileNetV2 Convolutional Neural Network (CNN) for fast, mobile detection of satellites, and rejection of stars, in cluttered unresolved space imagery. First, a custom database is created using imagery from a synthetic satellite image program and labeled with bounding boxes over satellites for "satellite-positive" images. The CNN is then

C. Ti, J. G. McDaniel, A. Liem, H. Gress

The oscillatory dynamics of nanoelectromechanical systems (NEMS) is at the heart of many emerging applications in nanotechnology. For common NEMS, such as beams and strings, the oscillatory dynamics is formulated using a dissipationless wave equation derived from elasticity. Under a harmonic ansatz, the wave equation gives an undamped free vibration equation

Mahnaz Rezaei, Jahanfar Abouie, Fariba Nazari

One of the most important tasks in the development of high-performance spintronic devices is the preparation of two dimensional (2D) magnetic layers with long-range exchange interactions. MN4 embedded graphene (MN4-G) layers, with M being transition metal elements, are experimentally accessible 2D layers, which exhibit interesting magnetic properties. In thi

Weihua Xu, Feifei Gao, Xiaoming Tao, Jianhua Zhang

Visual information, captured for example by cameras, can effectively reflect the sizes and locations of the environmental scattering objects, and thereby can be used to infer communications parameters like propagation directions, receiver powers, as well as the blockage status. In this paper, we propose a novel beam alignment framework that leverages images

Haitian Jiang, Dongliang Xiong, Xiaowen Jiang, Aiguo Yin

Deep neural networks have recently succeeded in digital halftoning using vanilla convolutional layers with high parallelism. However, existing deep methods fail to generate halftones with a satisfying blue-noise property and require complex training schemes. In this paper, we propose a halftoning method based on multi-agent deep reinforcement learning, calle

Po Hao Chen, Kurt Keville

The Big Memory solution is a new computing paradigm facilitated by commodity server platforms that are available today. It exposes a large RAM subsystem to the Operating System and therefore affords application programmers a number of previously unavailable options for data management. Additionally, certain vendor-specific solutions offer additional memory m

Wenqi Yang, Guanying Chen, Chaofeng Chen, Zhenfang Chen

Traditional multi-view photometric stereo (MVPS) methods are often composed of multiple disjoint stages, resulting in noticeable accumulated errors. In this paper, we present a neural inverse rendering method for MVPS based on implicit representation. Given multi-view images of a non-Lambertian object illuminated by multiple unknown directional lights, our m

Zhilei Wang, Robert V. Kohn

We develop a new approach to drifting games, a class of two-person games with many applications to boosting and online learning settings. Our approach involves (a) guessing an asymptotically optimal potential by solving an associated partial differential equation (PDE); then (b) justifying the guess, by proving upper and lower bounds on the final-time loss w

Tulin Kaman, Ryan Holley

Turbulent mixing due to hydrodynamic instabilities occurs in a wide range of science and engineering applications such as supernova explosions and inertial confinement fusion. The experimental, theoretical and numerical studies help us to understand the dynamics of hydrodynamically unstable interfaces between fluids in these important problems. In this paper

Nathaniel Tucker, Mahnoosh Alizadeh

We present a customizable online optimization framework for real-time EV smart charging to be readily implemented at real large-scale charging facilities. Notably, due to real-world constraints, we designed our framework around 3 main requirements. First, the smart charging strategy is readily deployable and customizable for a wide-array of facilities, infra

Fanrong Shi, Simon X. Yang, Xianguo Tuo, Lili Ran

One-way-broadcast based flooding time synchronization algorithms are commonly used in wireless sensor networks (WSNs). However, the packet delay and clock drift pose challenges to accuracy, as they entail serious by-hop error accumulation problems in the WSNs. To overcome it, a rapid flooding multi-broadcast time synchronization with real-time delay compensa

Qian Yang, Yunxin Li, Baotian Hu, Lin Ma

Visual Entailment with natural language explanations aims to infer the relationship between a text-image pair and generate a sentence to explain the decision-making process. Previous methods rely mainly on a pre-trained vision-language model to perform the relation inference and a language model to generate the corresponding explanation. However, the pre-tra

B. G. Palm, D. I. Alves, M. I. Pettersson, V. T. Vu

This paper presents five different statistical methods for ground scene prediction (GSP) in wavelength-resolution synthetic aperture radar (SAR) images. The GSP image can be used as a reference image in a change detection algorithm yielding a high probability of detection and low false alarm rate. The predictions are based on image stacks, which are composed

Hiroki Hoshina

To find out the possible scenarios for quantum gravity consistent with the observed universe, we numerically investigate the non-perturbative renormalization group equations of a general quadratic gravity theory recently derived by Sen, Wetterich and Yamada (\textit{JHEP} 03 (2022) 130). As boundary conditions, we impose consistency with the Hubble scale and

Masanori Fujiwara, Gaku Uchida, Izuru Ohki, Ming Liu

Silicon-vacancy (SiV) centers in diamond are a promising candidate for all-optical nanoscale high-sensitivity thermometry because they have sufficient sensitivity to reach the subkelvin precision required for application to biosystems. It is expected that nanodiamonds with SiV centers can be injected into cells to measure the nanoscale local temperatures of

B. G. Palm, F. M. Bayer, R. J. Cintra, M. I. Pettersson

This letter proposes a regression model for nonnegative signals. The proposed regression estimates the mean of Rayleigh distributed signals by a structure which includes a set of regressors and a link function. For the proposed model, we present: (i)~parameter estimation; (ii)~large data record results; and (iii)~a detection technique. In this letter, we pre

Xinxu Wei, Kaifu Yang, Danilo Bzdok, Yongjie Li

Most of the existing deep learning based methods for vessel segmentation neglect two important aspects of retinal vessels, one is the orientation information of vessels, and the other is the contextual information of the whole fundus region. In this paper, we propose a robust Orientation and Context Entangled Network (denoted as OCE-Net), which has the capab

Yonghong Li, Hao Miao

Due to the rapid development of quantum computing, the compact representation of quantum operations based on decision diagrams has been received more and more attraction. Since variable orders have a significant impact on the size of the decision diagram, identifying a good variable order is of paramount importance. In this paper, we integrate linear transfo

Miaomiao Wei, Longjun Xiang, Luyang Wang, Fuming Xu

The third-order nonlinear Hall effect induced by Berry-connection polarizability tensor has been observed in Weyl semimetals T$_d$-MoTe$_2$ as well as T$_d$-TaIrTe$_4$. The experiments were performed on bulk samples, and the results were interpreted with the semiclassical Boltzmann approach. Beyond the bulk limit, we develop a quantum nonlinear transport the

Xinxu Wei, Haohan Bai, Xianshi Zhang, Yongjie Li

Computer-aided X-ray pneumonia lesion recognition is important for accurate diagnosis of pneumonia. With the emergence of deep learning, the identification accuracy of pneumonia has been greatly improved, but there are still some challenges due to the fuzzy appearance of chest X-rays. In this paper, we propose a deep learning framework named Attention-Based

Yan Cui, Zhou Zhou

We consider the problem of joint simultaneous confidence band (JSCB) construction for regression coefficient functions of time series scalar-on-function linear regression when the regression model is estimated by roughness penalization approach with flexible choices of orthonormal basis functions. A simple and unified multiplier bootstrap methodology is prop

Wenrui Zhang, Wei Wang, Jinfu Zhang, Tan Zhang

Incorporating emerging ultrawide bandgap semiconductors with a metal-semiconductor-metal (MSM) architecture is highly desired for deep-ultraviolet (DUV) photodetection. However, synthesis-induced defects in semiconductors complicate the rational design of MSM DUV photodetectors due to their dual role as carrier donors and trap centers, leading to a commonly

Oriel A. Humes, Cristina A. Thomas, Joshua P. Emery, Will M. Grundy

The recently launched Lucy mission aims to understand the dynamical history of the Solar System by examining the Jupiter Trojans, a population of primitive asteroids co-orbital with Jupiter. Using the G280 grism on the Hubble Space Telescope's Wide Field Camera 3 we obtained near ultraviolet spectra of four of the five Lucy mission targets -- (617) Patroclus

Haiyang Sun, Zheng Lian, Bin Liu, Jianhua Tao

In this paper, we propose the solution to the Multi-Task Learning (MTL) Challenge of the 4th Affective Behavior Analysis in-the-wild (ABAW) competition. The task of ABAW is to predict frame-level emotion descriptors from videos: discrete emotional state; valence and arousal; and action units. Although researchers have proposed several approaches and achieved

Dong Yang, Fei Jiang, Wei Wu, Xuefei Fang

The Kalman filter has been adopted in acoustic echo cancellation due to its robustness to double-talk, fast convergence, and good steady-state performance. The performance of Kalman filter is closely related to the estimation accuracy of the state noise covariance and the observation noise covariance. The estimation error may lead to unacceptable results, es

Guido Roberts-Borsani, Takahiro Morishita, Tommaso Treu, Gabriel Brammer

We present the first search for $z\geqslant7$, continuum-confirmed sources with NIRISS/WFS spectroscopy over the Abell 2744 Frontier Fields cluster, as part of the GLASS-JWST ERS survey. With $\sim15$ hrs of pre-imaging and multi-angle grism exposures in the F115W, F150W, and F200W filters, we describe the general data handling (i.e., reduction, cleaning, mo

Victoria Manfredi, Alicia P. Wolfe, Xiaolan Zhang, Bing Wang

Designing effective routing strategies for mobile wireless networks is challenging due to the need to seamlessly adapt routing behavior to spatially diverse and temporally changing network conditions. In this work, we use deep reinforcement learning (DeepRL) to learn a scalable and generalizable single-copy routing strategy for such networks. We make the fol

Drago Plecko, Elias Bareinboim

Decision-making systems based on AI and machine learning have been used throughout a wide range of real-world scenarios, including healthcare, law enforcement, education, and finance. It is no longer far-fetched to envision a future where autonomous systems will be driving entire business decisions and, more broadly, supporting large-scale decision-making in

Xinyu Zhang, Jiangeng Huang, Yuanhao Huang, Kangyao Huang

Amphibious ground-aerial vehicles fuse flying and driving modes to enable more flexible air-land mobility and have received growing attention recently. By analyzing the existing amphibious vehicles, we highlight the autonomous fly-driving functionality for the effective uses of amphibious vehicles in complex three-dimensional urban transportation systems. We

Yalei Huang, Xinyu Yao, Fangyi Qi, Weihao Shen

Fe$_5$GeTe$_2$ (n = 3, 4, 5) have recently attracted increasing attention due to their two-dimensional van der Waals characteristic and high temperature ferromagnetism, which make promises for spintronic devices. The Fe(1) split site is one important structural characteristic of Fe$_5$GeTe$_2$ which makes it very different from other Fe$_5$GeTe$_2$ (n = 3, 4

Zepeng Huo, Xiaoning Qian, Shuai Huang, Zhangyang Wang

Medical events of interest, such as mortality, often happen at a low rate in electronic medical records, as most admitted patients survive. Training models with this imbalance rate (class density discrepancy) may lead to suboptimal prediction. Traditionally this problem is addressed through ad-hoc methods such as resampling or reweighting but performance in

Wen-Guei Hu, Guan-Yu Lai, Song-Sun Lin

Topological entropy or spatial entropy is a way to measure the complexity of shift spaces. This study investigates the relationships between the spatial entropy and the various periodic entropies which are computed by skew-coordinated systems $\gamma\in GL_2(\mathbb{Z})$ on two dimensional shifts of finite type.

Shintaro Kuroki, Grigory Solomadin

In this paper, we introduce the GKM theoretical counterpart of the equivariant complex vector bundles as the "leg bundle". We also provide a definition for the projectivization of a leg bundle and prove the Borel-Hirzebruch type formula for its graph equivariant cohomology, assuming that the projectivization is again a GKM graph. Furthermore, we study the re

P. Santini, A. Fontana, M. Castellano, N. Leethochawalit

We exploit James Webb Space Telescope (JWST) NIRCam observations from the GLASS-JWST-Early Release Science program to investigate galaxy stellar masses at z>7. We first show that JWST observations reduce the uncertainties on the stellar mass by a factor of at least 5-10, when compared with the highest quality data sets available to date. We then study the UV

Roy Ganz, Bahjat Kawar, Michael Elad

Adversarially robust classifiers possess a trait that non-robust models do not -- Perceptually Aligned Gradients (PAG). Their gradients with respect to the input align well with human perception. Several works have identified PAG as a byproduct of robust training, but none have considered it as a standalone phenomenon nor studied its own implications. In thi

Graeme Smecher, Tijmen de Haan, Matt Dobbs, Joshua Montgomery

We consider the stability and performance of a discrete-time control loop used as a dynamic nuller in the presence of a relatively large time delay in its feedback path. Controllers of this form occur in mm-wave telescopes using frequency-multiplexed Transition Edge Sensor (TES) bolometers. In this application, negative feedback is needed to linearize a Supe

Benjamin Hatanpää, Alexander Y. Choi, Peishi S. Cheng, Austin J. Minnich

The ab-initio theory of charge transport in semiconductors typically employs the lowest-order perturbation theory in which electrons interact with one phonon (1ph). This theory is accepted to be adequate to explain the low-field mobility of non-polar semiconductors but has not been tested extensively beyond the low-field regime. Here, we report first-princip

Graeme Smecher, Jean-Francois Cliche, Matt Dobbs, Joshua Montgomery

The next generation of space-based mm-wave telescopes, such as JAXA's LiteBIRD mission, require focal planes with thousands of detectors in order to achieve their science goals. Digital frequency-domain multiplexing (dfmux) techniques allow detector counts to scale without a linear growth in wire harnessing, sub-Kelvin refrigerator loads, and other scaling p

Graeme Smecher, Peter Cameron, Jean-Francois Cliche, Matt Dobbs

The next generation of space-based mm-wave telescopes, such as JAXA's LiteBIRD mission, require focal planes with thousands of detectors in order to achieve their science goals. Digital frequency-domain multiplexing (dfmux) techniques allow detector counts to scale without a linear growth in wire harnessing, sub-Kelvin refrigerator loads, and other scaling p

Marina Chugunova, Roman Taranets, Nataliya Vasylyeva

Compartmental models are widely used in mathematical epidemiology to describe dynamics of infection disease. A new SIS-PDE model, recently derived by Chalub and Souza, is based on a diffusion-drift approximation of probability density in a well-known discrete - time Markov chain SIS-DTMC model. This new SIS-PDE model is conservative due to degeneracy of the

Andre G. Hochuli, Alceu S. Britto, Paulo R. L. de Almeida, Williams B. S. Alves

When using vision-based approaches to classify individual parking spaces between occupied and empty, human experts often need to annotate the locations and label a training set containing images collected in the target parking lot to fine-tune the system. We propose investigating three annotation types (polygons, bounding boxes, and fixed-size squares), prov

Zhen-Qing Chen, Takashi Kumagai, Laurent Saloff-Coste, Jian Wang

We consider a natural class of long range random walks on torsion free nilpotent groups and develop limit theorems for these walks. Given the original discrete group $\Gamma$ and a random walk $(S_n)_ {n\ge1}$ driven by a certain type of symmetric probability measure $\mu$, we construct a homogeneous nilpotent Lie group $G_\bullet(\Gamma,\mu)$ which carries

Jose Luis Blázquez-Salcedo, Luis Manuel González-Romero, Fech Scen Khoo, Jutta Kunz

Scalar-tensor theories allow for a rich spectrum of quasinormal modes of neutron stars. The presence of the scalar field allows for polar monopole and dipole radiation, as well as for additional higher multipole modes led by the scalar field. Here we present these scalar-led $\phi$-modes for the lowest multipoles, $l=0$, 1 and 2 for a massless scalar-tensor

Rohini S Giles, Thomas K Greathouse, Patrick G J Irwin, Thérèse Encrenaz

High spectral resolution observations of Venus were obtained with the TEXES instrument at NASA's Infrared Telescope Facility. These observations focus on a CO$_2$ absorption feature at 791.4 cm$^{-1}$ as the shape of this absorption feature can be used to retrieve the vertical temperature profile in Venus' mesosphere. By scan-mapping the planet, we are able

Yunhao Ge, Harkirat Behl, Jiashu Xu, Suriya Gunasekar

Training computer vision models usually requires collecting and labeling vast amounts of imagery under a diverse set of scene configurations and properties. This process is incredibly time-consuming, and it is challenging to ensure that the captured data distribution maps well to the target domain of an application scenario. Recently, synthetic data has emer

Maik Reddiger, Bill Poirier

Even though the Madelung equations are central to many 'classical' approaches to the foundations of quantum mechanics such as Bohmian and stochastic mechanics, no coherent mathematical theory has been developed so far for this system of partial differential equations. Wallstrom prominently raised objections against the Madelung equations, aiming to show that

Danwen Yuan, Hanqi Pi, Yi Jiang, Yuefang Hu

Both the intrinsic anisotropic optical materials and fullerene-assembled 2D materials have attracted a lot of interests in fundamental science and potential applications. The synthesis of a monolayer (ML) fullerene makes the combination of these two features plausible. In this work, using first-principles calculations, we systematically study the electronic

Tushar Nagarajan, Santhosh Kumar Ramakrishnan, Ruta Desai, James Hillis

First-person video highlights a camera-wearer's activities in the context of their persistent environment. However, current video understanding approaches reason over visual features from short video clips that are detached from the underlying physical space and capture only what is immediately visible. To facilitate human-centric environment understanding,

M. A. Weber, C. Löschnauer, J. Wolf, M. F. Gely

We report the design, fabrication, and characterization of a cryogenic ion trap system for the implementation of quantum logic driven by near-field microwaves. The trap incorporates an on-chip microwave resonator with an electrode geometry designed to null the microwave field component that couples directly to the qubit, while giving a large field gradient f

Yen-Ting Lin, Alexandros Papangelis, Seokhwan Kim, Dilek Hakkani-Tur

While rich, open-domain textual data are generally available and may include interesting phenomena (humor, sarcasm, empathy, etc.) most are designed for language processing tasks, and are usually in a non-conversational format. In this work, we take a step towards automatically generating conversational data using Generative Conversational Networks, aiming t

Ramya Manjunath Anche, Ewan S. Douglas, Kian Milani, Jaren Ashcraft

The Roman coronagraph instrument will demonstrate high-contrast imaging technology, enabling the imaging of faint debris disks, the discovery of inner dust belts, and planets. Polarization studies of debris disks provide information on dust grains' size, shape, and distribution. The Roman coronagraph uses a polarization module comprising two Wollaston prism

Chenyao Li, Stylianos Kampakis, Philip Treleaven

In most sports, especially football, most coaches and analysts search for key performance indicators using notational analysis. This method utilizes a statistical summary of events based on video footage and numerical records of goal scores. Unfortunately, this approach is now obsolete owing to the continuous evolutionary increase in technology that simplifi

Alexander Fusco, Sahil Hassan, Joshua Mack, Ali Akoglu

Non-uniform performance and power consumption across the processing elements (PEs) of heterogeneous SoCs increase the computation complexity of the task scheduling problem compared to homogeneous architectures. Latency of a software-based scheduler with the increased heterogeneity level in terms of number and types of PEs creates the necessity of deploying a

Oscar Fuentealba, Marc Henneaux, Patricio Salgado-Rebolledo, Jakob Salzer

In this paper, three things are done. First, we study from an algebraic point of view the infinite-dimensional BMS-like extensions of the Carroll algebra relevant to the asymptotic structure of the electric and magnetic Carrollian limits of Einstein gravity. In the course of this study we exhibit by "Carroll-Galileo duality" a new infinite-dimensional BMS-li

Fred Greensite

We present a generalization of the notion of an algebra norm relevant to real finite-dimensional unital associative algebras. Among other things, this leads to a novel set of algebra isomorphism invariants, some of which are computationally straightforward in general, thereby augmenting the recognized accessible distinguishing features of algebra structure.

Molly Jane Nicholas, Eric Paulos

Both expert and novice animators have a need to engage in movement sketching -- low-cost, rapid iteration on a character's movement style -- especially early on in the ideation process. Yet animation tools currently focus on low-level character control mechanisms rather than encouraging engagement with and deep observation of movement. We identify Found Obje

Keith A. LeGrand, Silvia Ferrari

In object tracking and state estimation problems, ambiguous evidence such as imprecise measurements and the absence of detections can contain valuable information and thus be leveraged to further refine the probabilistic belief state. In particular, knowledge of a sensor's bounded field-of-view can be exploited to incorporate evidence of where an object was

Aaqib Peerzada, Miroslav Begovic, Wesam Rohouma, Robert S. Balog

The emergence of distributed energy resources has led to new challenges in the operation and planning of power networks. Of particular significance is the introduction of a new layer of complexity that manifests in the form of new uncertainties that could severely limit the resiliency and reliability of a modern power system. For example, the increasing adop

Hari Hara Suthan Chittoor, Osvaldo Simeone

Distributed quantum information processing protocols such as quantum entanglement distillation and quantum state discrimination rely on local operations and classical communications (LOCC). Existing LOCC-based protocols typically assume the availability of ideal, noiseless, communication channels. In this paper, we study the case in which classical communica