July 2022 arXiv papers — page 95

Xiao-Qiang Shao

We propose a dissipative method for preparation of a maximally entangled steady state of two trapped ions in the Lamb-Dicke limit. By addressing the trapped-ion system with a monochromatic standing wave laser pulse of frequency resonant with the ionic transition and a microwave field coupled to the ground-state transitions, we obtain an effective coupling be

Samy Jelassi, Yuanzhi Li

Stochastic gradient descent (SGD) with momentum is widely used for training modern deep learning architectures. While it is well-understood that using momentum can lead to faster convergence rate in various settings, it has also been observed that momentum yields higher generalization. Prior work argue that momentum stabilizes the SGD noise during training a

Michael Levet

In this paper, we show that Graph Isomorphism (GI) is not $\textsf{AC}^{0}$-reducible to several problems, including the Latin Square Isotopy problem, isomorphism testing of several families of Steiner designs, and isomorphism testing of conference graphs. As a corollary, we obtain that GI is not $\textsf{AC}^{0}$-reducible to isomorphism testing of Latin sq

Xiaoyi Qin, Na Li, Chao Weng, Dan Su

Automatic speaker verification has achieved remarkable progress in recent years. However, there is little research on cross-age speaker verification (CASV) due to insufficient relevant data. In this paper, we mine cross-age test sets based on the VoxCeleb dataset and propose our age-invariant speaker representation(AISR) learning method. Since the VoxCeleb i

Wenbiao Li, Rui Sun, Yunfang Wu

Most of the Chinese pre-trained models adopt characters as basic units for downstream tasks. However, these models ignore the information carried by words and thus lead to the loss of some important semantics. In this paper, we propose a new method to exploit word structure and integrate lexical semantics into character representations of pre-trained models.

Zidu Lin, Andrew W. Steiner, Jerome Margueron

We perform an extensive study of the correlations between the neutrino-nucleon inverse mean free paths (IMFPs) and the underlying equation of states (EoSs). Strong interaction uncertainties in the neutrino mean free path are investigated in different density regimes. The nucleon effective mass, the nucleon chemical potentials, and the residual interactions i

Y. Yao, X. Q. Shao

We study the problem of charging a dissipative one-dimensional $XXX$ spin-chain quantum battery using local magnetic fields in the presence of spin decay. The introduction of quantum feedback control based on homodyne measurement contributes to improve various performance of the quantum battery, such as energy storage, ergotropy, and effective space utilizat

Ke Yu, Y. Li, Jie Hong, De-Chao Song

We investigate various dynamic processes including magnetic reconnection, chromospheric evaporation, and coronal rain draining in two limb solar flares through imaging and spectroscopic observations from the Interface Region Imaging Spectrograph (IRIS) and the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory. In the early phase of t

Kazuho Kayama, Takaaki Tanaka, Hiroyuki Uchida, Takeshi Go Tsuru

The X-ray binary SS 433, embedded in the W50 nebula (or supernova remnant W50), shows bipolar jets that are ejected with mildly relativistic velocities, and extend toward the east and west out to scales of tens of parsecs. Previous X-ray observations revealed twin lobes along the jet precession axis that contain compact bright knots dominated by synchrotron

Jaehan Bae, Richard Teague, Sean M. Andrews, Myriam Benisty

We report the discovery of a circumplanetary disk (CPD) candidate embedded in the circumstellar disk of the T Tauri star AS 209 at a radial distance of about 200 au (on-sky separation of 1."4 from the star at a position angle of $161^\circ$), isolated via $^{13}$CO $J=2-1$ emission. This is the first instance of CPD detection via gaseous emission capable of

Yuji Ito, Kenji Fujimoto

This paper presents a new paradigm to stabilize uncertain stochastic linear systems. Herein, second moment polytopic (SMP) systems are proposed that generalize systems with both uncertainty and randomness. The SMP systems are characterized by second moments of the stochastic system matrices and the uncertain parameters. Further, a fundamental theory for guar

Huajun Zhou, Bo Qiao, Lingxiao Yang, Jianhuang Lai

Deep Learning-based Unsupervised Salient Object Detection (USOD) mainly relies on the noisy saliency pseudo labels that have been generated from traditional handcraft methods or pre-trained networks. To cope with the noisy labels problem, a class of methods focus on only easy samples with reliable labels but ignore valuable knowledge in hard samples. In this

Jiayuan Dong, Jiankan Liao, Xun Huan, Daniel Cooper

Bayesian inference allows the transparent communication of uncertainty in material flow analyses (MFAs), and a systematic update of uncertainty as new data become available. However, the method is undermined by the difficultly of defining proper priors for the MFA parameters and quantifying the noise in the collected data. We start to address these issues by

Weiqing Wang, Qingjian Lin, Ming Li

This paper proposes an online target speaker voice activity detection system for speaker diarization tasks, which does not require a priori knowledge from the clustering-based diarization system to obtain the target speaker embeddings. First, we employ a ResNet-based front-end model to extract the frame-level speaker embeddings for each coming block of a sig

Krishna Pothugunta, Xiao Liu, Anjana Susarla, Rema Padman

Studies suggest that one in three US adults use the Internet to diagnose or learn about a health concern. However, such access to health information online could exacerbate the disparities in health information availability and use. Health information seeking behavior (HISB) refers to the ways in which individuals seek information about their health, risks,

Hideya Watanabe

It has been known since their birth in Bao and Wang's work that the $\imath$canonical bases of $\imath$quantum groups are not stable in general. In the author's previous work, the stability of $\imath$canonical bases of certain quasi-split types turned out to be closely related to the theory of $\imath$crystals. In this paper, we prove the stability of $\ima

Shouqiang Du, Jingjing Sun, Shengqun Niu, Liping Zhang

We propose a new kind of stochastic absolute value equations involving absolute values of variables. By utilizing an equivalence relation to stochastic bilinear program, we investigate the expected value formulation for the proposed stochastic absolute value equations. We also consider the expected residual minimization formulation for the proposed stochasti

Jack M. Saville, Edward M. Hinton, Herbert E. Huppert

We present a shallow, isothermal, Newtonian model for the transient interaction of lava flows with topography. Numerical integrations and simple mathematical approximations are deployed to quantify how topography controls lava thicknesses and flow speeds. Considering idealised topographic features, we show that modest depressions thicken and accelerate the f

Wenyuan Wang, Rong Wang, Victor Zapatero, Li Qian

Passive implementations of quantum key distribution (QKD) sources are highly desirable as they eliminate side-channels that active modulators might introduce. Up till now, passive decoy-state and passive encoding BB84 schemes have both been proposed. Nonetheless, passive decoy-state generation and passive encoding have never been simultaneously implemented w

Mert Hidayetoglu, Michael Oelze, Erhan Kudeki, Weng Cho Chew

Inverse scattering involving microwave and ultrasound waves require numerical solution of nonlinear optimization problem. To alleviate the computational burden of a full three-dimensional (3-D) inverse problem, it is a common practice to approximate the object as two-dimensional (2-D) and treat the transmitter and receiver sensors as 3-D, through a Fourier i

Yuanwei Wu, Bo Zhang, Jingjing Li, Xing-Wu Zheng

A 22 GHz water maser survey was conducted towards 178 O-rich AGB stars with the aim of identifying maser emission associated with the Sagittarius stellar stream. In this survey, maser emissions were detected in 21 targets, of which 20 were new detections. We studied the Galactic distributions of H2O and SiO maser-traced AGBs towards the Sgr orbital plane, an

Yi-Chiao Wu, Patrick Lumban Tobing, Kazuki Yasuhara, Noriyuki Matsunaga

Neural-based text-to-speech (TTS) systems achieve very high-fidelity speech generation because of the rapid neural network developments. However, the huge labeled corpus and high computation cost requirements limit the possibility of developing a high-fidelity TTS system by small companies or individuals. On the other hand, a neural vocoder, which has been w

Jiahao Chen, Zitao Liu, Weiqi Luo

In this paper, we investigate the opportunities of automating the judgment process in online one-on-one math classes. We build a Wide & Deep framework to learn fine-grained predictive representations from a limited amount of noisy classroom conversation data that perform better student judgments. We conducted experiments on the task of predicting students' l

Xinrui Li, Yakui Huang

Nonmonotone gradient methods generally perform better than their monotone counterparts especially on unconstrained quadratic optimization. However, the known convergence rate of the monotone method is often much better than its nonmonotone variant. With the aim of shrinking the gap between theory and practice of nonmonotone gradient methods, we introduce a p

Yassine El Maazouz, Enis Kaya

We present a method for sampling points from an algebraic manifold, either affine or projective, defined over a local field, with a prescribed probability distribution. Inspired by the work of Breiding and Marigliano on sampling real algebraic manifolds, our approach leverages slicing the given variety with random linear spaces of complementary dimension. We

Fumi Egusa, Yulong Gao, Kana Morokuma-Matsui, Guilin Liu

We report high resolution 2" ~ 200 pc mappings of the central region of the nearby barred spiral galaxy NGC 1365 in the CO(1--0) and CO(2--1) emission lines. The 2--1/1--0 ratio of integrated intensities shows a large scatter (0.15) with a median value of 0.67. We also calculate the ratio of velocity dispersions and peak temperatures and find that in most ca

Tao Chen, Tianshu Liu

In this paper, we introduce a new physical concept referred to as the wall-normal Lamb dilatation flux (WNLDF), which is defined as the wall-normal derivative of the Lamb dilatation (namely, the divergence of the Lamb vector) multiplied by the dynamic viscosity for incompressible viscous flows. It is proved that the boundary Lamb dilatation flux (BLDF, namel

HongSheng Qi

The macroscopic fundamental diagram (MFD) is a powerful and popular tool that describes a network scale traffic operational state and serve as the plant model of perimeter control. As both the supply and the demand suffer from random disturbances, the traffic flow dynamics cannot be said to be deterministic. A stochastic MFD model can generate a stochastic e

S. R. Wu, B. Q. Wang, Z. W. Long

In this work, we investigate a static and spherically symmetric Bardeen-Kiselev black hole with cosmological constant which is a solution of the Einstein-non-linear Maxwell field equations along with a quintessential field. We compute the quasinormal frequencies for Bardeen-Kiselev black hole(BH) with cosmological constant due to electromagnetic and gravitat

Jun Lu, Danny Ding

Over the decades, the Markowitz framework has been used extensively in portfolio analysis though it puts too much emphasis on the analysis of the market uncertainty rather than on the trend prediction. While generative adversarial network (GAN), conditional GAN (CGAN), and autoencoding CGAN (ACGAN) have been explored to generate financial time series and ext

Junjun Pan, Siyuan Wang, Junxuan Bai, Ju Dai

Existing keyframe-based motion synthesis mainly focuses on the generation of cyclic actions or short-term motion, such as walking, running, and transitions between close postures. However, these methods will significantly degrade the naturalness and diversity of the synthesized motion when dealing with complex and impromptu movements, e.g., dance performance

Edward M. Hinton, Apoorv Jyoti

We consider the axisymmetric displacement of an ambient fluid by a second input fluid of lower density and lower viscosity in a horizontal porous layer. If the two fluids have been vertically segregated by buoyancy, the flow becomes self-similar with the input fluid preferentially flowing near the upper boundary. We show that this axisymmetric self-similar f

Geoffrey Exoo

Mixed graphs have both directed and undirected edges. A mixed cage is a regular mixed graph of given girth with minimum possible order. In this paper mixed cages are studied. Upper bounds are obtained by general construction methods and computer searches.

Edward E Allen, Sarah K Mason

We provide a combinatorial formula for the expansion of immaculate noncommutative symmetric functions into complete homogeneous noncommutative symmetric functions. To do this, we introduce generalizations of Ferrers diagrams which we call GBPR diagrams. We define tunnel hooks, which play a role similar to that of the special rim hooks appearing in the E\u{g}

Satoshi Munakata, Caterina Urban, Haruki Yokoyama, Koji Yamamoto

It is known that deep neural networks (DNNs) classify an input image by paying particular attention to certain specific pixels; a graphical representation of the magnitude of attention to each pixel is called a saliency-map. Saliency-maps are used to check the validity of the classification decision basis, e.g., it is not a valid basis for classification if

Joanna Zou, Eliz-Mari Lourens, Alice Cicirello

Virtual sensing techniques have gained traction in applications to the structural health monitoring of monopile-based offshore wind turbines, as the strain response below the mudline, which is a primary indicator of fatigue damage accumulation, is impractical to measure directly with physical instrumentation. The Gaussian process latent force model (GPFLM) i

M. Poisson, F. Grings, C. H. Mandrini, M. López-Fuentes

Context. Active regions (ARs) appear in the solar atmosphere as a consequence of the emergence of magnetic flux tubes. The presence of elongated magnetic polarities in line-of-sight (LOS) magnetograms indicates the existence of twist in the flux tubes forming them. These polarity elongations, called magnetic tongues, bias the measurement of AR characteristic

Mukul Gagrani, Corrado Rainone, Yang Yang, Harris Teague

Recent works on machine learning for combinatorial optimization have shown that learning based approaches can outperform heuristic methods in terms of speed and performance. In this paper, we consider the problem of finding an optimal topological order on a directed acyclic graph with focus on the memory minimization problem which arises in compilers. We pro

Thomas Chen, Shivam Nadimpalli, Henry Yuen

We consider the problem of testing and learning quantum $k$-juntas: $n$-qubit unitary matrices which act non-trivially on just $k$ of the $n$ qubits and as the identity on the rest. As our main algorithmic results, we give (a) a $\widetilde{O}(\sqrt{k})$-query quantum algorithm that can distinguish quantum $k$-juntas from unitary matrices that are "far" from

Yasin Findik, Farhad Pourkamali-Anaraki

Continual learning -- accumulating knowledge from a sequence of learning experiences -- is an important yet challenging problem. In this paradigm, the model's performance for previously encountered instances may substantially drop as additional data are seen. When dealing with class-imbalanced data, forgetting is further exacerbated. Prior work has proposed

Tony Zheng, Monimoy Bujarbaruah, Yvonne R. Stürz, Francesco Borrelli

We study a human-robot collaborative transportation task in presence of obstacles. The task for each agent is to carry a rigid object to a common target position, while safely avoiding obstacles and satisfying the compliance and actuation constraints of the other agent. Human and robot do not share the local view of the environment. The human policy either a

Tim B. Miller, Pieter van Dokkum, Lamiya Mowla

Recent studies have indicated that the ratio between half-mass and half-light radii, $r_{\rm mass} / r_{\rm light}$, varies significantly as a function of stellar mass and redshift, complicating the interpretation of the ubiquitous $r_{\rm light}- M_*$ relation. To investigate, in this study we construct the light and color profiles of $\sim 3000$ galaxies a

Jiahao Li, Bin Li, Yan Lu

For neural video codec, it is critical, yet challenging, to design an efficient entropy model which can accurately predict the probability distribution of the quantized latent representation. However, most existing video codecs directly use the ready-made entropy model from image codec to encode the residual or motion, and do not fully leverage the spatial-t

Sarthak Choudhury, Joachim Brand

A vortex molecule is a topological excitation in two coherently coupled superfluids consisting of a vortex in each superfluid connected by a domain wall of the relative phase, also known as a Josephson vortex. We investigate the dynamics of this excitation in a quasi-two-dimensional geometry with slab or channel boundary conditions using an extended point vo

Aderonke S. Folorunso, François Mauger, Kyle A. Hamer, Denawakage D Jayasinghe

Charge migration (CM) is a coherent attosecond process that involves the movement of localized holes across a molecule. To determine the relationship between a molecule's structure and the CM dynamics it exhibits, we perform systematic studies of para-functionalized bromobenzene molecules (X-C$_6$H$_4$-R) using real-time time-dependent density functional the

Mohamed-Amine Lahmeri, Walid Ghanem, Christina Knill, Robert Schober

In this paper, we study the trajectory and resource optimization for lightweight rotary-wing unmanned aerial vehicles (UAVs) equipped with a synthetic aperture radar (SAR) system. The UAV's mission is to perform SAR imaging of a given area of interest (AoI). In this setup, real-time communication with a base station (BS) is required to facilitate live missio

Zhihui Lin, Prosanta Gope, Jianting Ning, Biplab Sikdar

The transition from paper-based information to Electronic-Health-Records (EHRs) has driven various advancements in the modern healthcare-industry. In many cases, patients need to share their EHR with healthcare professionals. Given the sensitive and security-critical nature of EHRs, it is essential to consider the security and privacy issues of storing and s

Matthew McCurdy, Nicholas J. Moore, Xiaoming Wang

A ubiquitous arrangement in nature is a free-flowing fluid coupled to a porous medium, for example a river or lake lying above a porous bed. Depending on the environmental conditions, thermal convection can occur and may be confined to the clear fluid region, forming shallow convection cells, or it can penetrate into the porous medium, forming deep cells. He

Lin Bai, Yiming Zhao, Xinming Huang

Point cloud semantic segmentation has attracted attentions due to its robustness to light condition. This makes it an ideal semantic solution for autonomous driving. However, considering the large computation burden and bandwidth demanding of neural networks, putting all the computing into vehicle Electronic Control Unit (ECU) is not efficient or practical.

Sowon Jeong, Claire Donnat

By recursively summing node features over entire neighborhoods, spatial graph convolution operators have been heralded as key to the success of Graph Neural Networks (GNNs). Yet, despite the multiplication of GNN methods across tasks and applications, the impact of this aggregation operation on their performance still has yet to be extensively analysed. In f

Hossein Haeri, Reza Ahmadzadeh, Kshitij Jerath

In this work, we integrate `social' interactions into the MARL setup through a user-defined relational network and examine the effects of agent-agent relations on the rise of emergent behaviors. Leveraging insights from sociology and neuroscience, our proposed framework models agent relationships using the notion of Reward-Sharing Relational Networks (RSRN),

Rui Meireles, Junrui Liu, Peter Steenkiste

Modern web pages have complex structures comprised of up to hundreds of different resources, such as scripts and images. Server push is an HTTP/2 feature enabling servers to preemptively send resources to clients before they realize they need them to render a page. The objective is to reduce the amount of time the browser has to wait for data to be transferr

Leithold L. Aurazo-Alvarez

In this work we prove a global well-posedness result for a tridimensional rescaled Boussinesq system, with positive full viscosity and diffusivity parameters in the framework of critical Fourier-Besov spaces. This rescaled approach permits to know the behaviour of the system according to relations between both the parameters and the initial velocity and temp

Daniel Carney, Kyle G. Leach, David C. Moore

The development of quantum optomechanics now allows mechanical sensors with femtogram masses to be controlled and measured in the quantum regime. If the mechanical element contains isotopes that undergo nuclear decay, measuring the recoil of the sensor following the decay allows reconstruction of the total momentum of all emitted particles, including any neu

Brendon K. Colbert, Joslyn L. Mangal, Aleksandr Talitckii, Abhinav P. Acharya

The immune response is a dynamic process by which the body determines whether an antigen is self or nonself. The state of this dynamic process is defined by the relative balance and population of inflammatory and regulatory actors which comprise this decision making process. The goal of immunotherapy as applied to, e.g. Rheumatoid Arthritis (RA), then, is to

Adam M Tahir

This paper proposes an algorithm which can be used in hybrid Coulomb spacecraft formations to minimize propellant by maximizing the amount of force that is generated by Coulomb forces. This problem is difficult due to the nonlinearities inherent in Coulomb's law. The problem is posed as a series of matrix rank minimization problems which can be solved effici

Ogun Yurdakul, Erik Ela, Sahin Albayrak

This article puts forward a methodology for procuring flexible ramping products (FRPs) in the day-ahead market (DAM). The proposed methodology comprises two market passes, the first of which employs a stochastic unit commitment (SUC) model that explicitly evaluates the uncertainty and the intra-hourly and inter-hourly variability of net load so as to minimiz

Yingnan Song, Ammar Hoori, Hao Wu, Mani Vembar

Our long-range goal is to improve current whole-heart CT calcium score by extracting quantitative features from individual calcifications. We performed deconvolution to improve small calcifications assessment which challenge conventional CT calcium score scanning resolution. We analyzed features of individual calcifications on repeated standard (2.5-mm) and

Omar Malik, Melinda Varga, Alaa Moussawi, David Hunt

To better understand the temporal characteristics and the lifetime of fluctuations in stochastic processes in networks, we investigated diffusive persistence in various graphs. Global diffusive persistence is defined as the fraction of nodes for which the diffusive field at a site (or node) has not changed sign up to time $t$ (or in general, that the node re

R. Kammers, R. K. Saito, E. Botan, D. Minniti

The discovery of new clear windows in the Galactic plane using the VVV near-IR extinction maps allows the study of the structure of the Milky Way (MW) disk. The ultimate goal of this work is to map the spiral arms in the far side of the MW, which is a relatively unexplored region of our Galaxy, using red clump (RC) giants as distance indicators. We search fo

Alper Güngör, Salman UH Dar, Şaban Öztürk, Yilmaz Korkmaz

Deep MRI reconstruction is commonly performed with conditional models that de-alias undersampled acquisitions to recover images consistent with fully-sampled data. Since conditional models are trained with knowledge of the imaging operator, they can show poor generalization across variable operators. Unconditional models instead learn generative image priors

Yanbo J. Wang, Yuming Li, Hui Qin, Yuhang Guan

As a rising star in the field of natural language processing, question answering systems (Q&A Systems) are widely used in all walks of life. Compared with other scenarios, the applicationin financial scenario has strong requirements in the traceability and interpretability of the Q&A systems. In addition, since the demand for artificial intelligence technolo

John Southworth, L. Mancini, M. Dominik, U. G. Jørgensen

TRAPPIST-1 is an ultra-cool dwarf that hosts seven known transiting planets. We present photometry of the system obtained using three telescopes at ESO La Silla (the Danish 1.54-m telescope and the 2.2-m MPI telescope) and Paranal (Unit Telescope 1 of the Very Large Telescope). We obtained 18 light curves from the Danish telescope, eight from the 2.2-m and f

John Southworth, A. J. Barker, T. C. Hinse, Y. Jongen

HATS-18b is a transiting planet with a large mass and a short orbital period, and is one of the best candidates for the detection of orbital decay induced by tidal effects. We present extensive photometry of HATS-18 from which we measure 27 times of mid-transit. Two further transit times were measured from data from the Transiting Exoplanet Survey Satellite

Dmytro Filatov, Ghulam Nabi Ahmad Hassan Yar

Global environment monitoring is a task that requires additional attention in the contemporary rapid climate change environment. This includes monitoring the rate of deforestation and areas affected by flooding. Satellite imaging has greatly helped monitor the earth, and deep learning techniques have helped to automate this monitoring process. This paper pro

Philipp Bitzenbauer, Sebastian Höfler, Joaquin M. Veith, Bianca Winkler

Physics education research on explanatory videos has experienced a boost in recent years. Due to the vast number of explanatory videos available online, e.g. on YouTube, finding videos of high explaining quality is a challenging task for learners, teachers, and lecturers alike. Prior research on the explaining quality of explanatory videos on classical mecha

Quentin Dubroff

For $f$ chosen from the $\{-1,1\}$-valued functions on the edges of a hypergraph $\mathcal{H} = (V,E)$ with $\sum_{e \in E} f(e) = 0$, how large can one make $\min_{v \in V} |\sum_{e \ni v} f(e)|$? This question may be viewed as a reverse version of the hypergraph discrepancy problem or as a relaxation of the zero-sum Ramsey problem for stars. We prove exact

Hayden Joy, Marios Mattheakis, Pavlos Protopapas

Reservoir computers (RCs) are among the fastest to train of all neural networks, especially when they are compared to other recurrent neural networks. RC has this advantage while still handling sequential data exceptionally well. However, RC adoption has lagged other neural network models because of the model's sensitivity to its hyper-parameters (HPs). A mo

Parikshit Hegde, Robert Streit, Yanni Georghiades, Chaya Ganesh

In current blockchain systems, full nodes that perform all of the available functionalities need to store the entire blockchain. In addition to the blockchain, full nodes also store a blockchain-summary, called the \emph{state}, which is used to efficiently verify transactions. With the size of popular blockchains and their states growing rapidly, full nodes

Hanna Furmańczyk, Tytus Pikies, Inka Sokołowska, Krzysztof Turowski

The problem of scheduling jobs on parallel machines (identical, uniform, or unrelated), under incompatibility relation modeled as a block graph, under the makespan optimality criterion, is considered in this paper. No two jobs that are in the relation (equivalently in the same block) may be scheduled on the same machine in this model. The presented model ste

Zongze Li, Wenbin Mao

Hemodynamics in the aorta from computational fluid dynamics (CFD) simulations can provide a comprehensive analysis of relevant cardiovascular diseases. Coupling the three-element Windkessel model with the patient-specific CFD simulation to form a multi-scale model is a trending approach to capture more realistic flow fields. However, a set of parameters (e.g

A. Madanayake, R. J. Cintra, N. Akram, V. Ariyarathna

The discrete Fourier transform (DFT) is widely employed for multi-beam digital beamforming. The DFT can be efficiently implemented through the use of fast Fourier transform (FFT) algorithms, thus reducing chip area, power consumption, processing time, and consumption of other hardware resources. This paper proposes three new hybrid DFT 1024-point DFT approxi

Jonas Jäger, Roman V. Krems

Machine learning is considered to be one of the most promising applications of quantum computing. Therefore, the search for quantum advantage of the quantum analogues of machine learning models is a key research goal. Here, we show that variational quantum classifiers and support vector machines with quantum kernels can solve a classification problem based o

K. E. Castoria, S. A. Lyon

We have measured two-dimensional electron systems bound to a thin helium film supported by a metallic substrate. We report on our measurement of electron density obtained via a Kelvin probe technique. The underlying metallic substrate is an amorphous metallic alloy (TaWSi), which can support large uniform densities due to its low surface roughness and homoge

L. M. S. Alves, F. S. Oliveira, E. C. Romão, M. S. da Luz

COMSOL Multiphysics software is used to describe the behavior of the electrical resistivity of several samples with rectangular shape typically used in the Montgomery method. The simulation data obtained using four isotropic conductors allowed us to understand in detail the behavior of the electric potential and electric field of the samples. The results pro

Jean-Paul Doignon, Kota Saito

The Multiple Choice Polytope (MCP) is the prediction range of a random utility model due to Block and Marschak (1960). Fishburn (1998) offers a nice survey of the findings on random utility models at the time. A complete characterization of the MCP is a remarkable achievement of Falmagne (1978). Apart for a recognition of the facets by Suck (2002), the geome

Satoru Hayami

The stability of a magnetic skyrmion crystal in a centrosymmetric orthorhombic lattice system is numerically investigated. By performing the simulated annealing for an effective spin model with the momentum-resolved interaction on a uniaxially distorted triangular lattice, we find that the skyrmion crystal is robustly realized when dominant interaction chann

Xiao Liang, Omkant Pandey, Takashi Yamakawa

We provide the first $\mathit{constant}$-$\mathit{round}$ construction of post-quantum non-malleable commitments under the minimal assumption that $\mathit{post}$-$\mathit{quantum}$ $\mathit{one}$-$\mathit{way}$ $\mathit{functions}$ exist. We achieve the standard notion of non-malleability with respect to commitments. Prior constructions required $\Omega(\lo

Steven V Sam, Andrew Snowden

Let $M$ be a finitely generated module over a free twisted commutative algebra $A$ that is finitely generated in degree one. We show that the projective dimension of $M({\bf C}^n)$ as an $A({\bf C}^n)$-module is eventually linear as a function of $n$. This confirms a conjecture of Le, Nagel, Nguyen, and R\"omer for a special class of modules.

Shuo Li

In a recent paper, Jason P. Bell and Jeffrey Shallit introduced the notion of {\em Lie complexity} and proved that the Lie complexity function of an automatic sequence is automatic. In this note, we give more facts concerning Lie complexity and define the extended Lie complexity and the prefix Lie complexity. Further, we prove that some proprieties of Lie co

Siddarth Ajith, Kent Yagi, Nicolás Yunes

Ho\v{r}ava-Lifshitz gravity is an alternative theory to general relativity which breaks Lorentz invariance in order to achieve an ultraviolet complete and power-counting renormalizable theory of gravity. In the low energy limit, Ho\v{r}ava-Lifshitz gravity coincides with a vector-tensor theory known as khronometric gravity. The deviation of khronometric grav

Satoru Hayami, Megumi Yatsushiro

We theoretically propose a realization of a nonlinear nonreciprocal transport in antiferromagnets without relying on the relativistic spin-orbit coupling. Through the symmetry and microscopic model analyses, we show that a local spin scalar chirality to induce an asymmetric band modulation becomes a source of a Drude-type nonlinear transport, while an electr

Colton Stearns, Davis Rempe, Jie Li, Rares Ambrus

3D multi-object tracking aims to uniquely and consistently identify all mobile entities through time. Despite the rich spatiotemporal information available in this setting, current 3D tracking methods primarily rely on abstracted information and limited history, e.g. single-frame object bounding boxes. In this work, we develop a holistic representation of tr

Ka Ho Brian Chor, Kit T. Rodolfa, Rayid Ghani

Human services systems make key decisions that impact individuals in the society. The U.S. child welfare system makes such decisions, from screening-in hotline reports of suspected abuse or neglect for child protective investigations, placing children in foster care, to returning children to permanent home settings. These complex and impactful decisions on c

Yuvaraj Selvaraj, Jonas Krook, Wolfgang Ahrendt, Martin Fabian

Cyber-physical systems are often safety-critical and their correctness is crucial, as in the case of automated driving. Using formal mathematical methods is one way to guarantee correctness. Though these methods have shown their usefulness, care must be taken as modeling errors might result in proving a faulty controller safe, which is potentially catastroph

Luca Crosato, Hubert P. H. Shum, Edmond S. L. Ho, Chongfeng Wei

Motion control algorithms in the presence of pedestrians are critical for the development of safe and reliable Autonomous Vehicles (AVs). Traditional motion control algorithms rely on manually designed decision-making policies which neglect the mutual interactions between AVs and pedestrians. On the other hand, recent advances in Deep Reinforcement Learning

Andrea Tirinzoni, Aymen Al-Marjani, Emilie Kaufmann

Optimistic algorithms have been extensively studied for regret minimization in episodic tabular MDPs, both from a minimax and an instance-dependent view. However, for the PAC RL problem, where the goal is to identify a near-optimal policy with high probability, little is known about their instance-dependent sample complexity. A negative result of Wagenmaker

Brendan T. Gould, Philip N. Brown

The emerging technology of Vehicle-to-Vehicle (V2V) communication over vehicular ad hoc networks promises to improve road safety by allowing vehicles to autonomously warn each other of road hazards. However, research on other transportation information systems has shown that informing only a subset of drivers of road conditions may have a perverse effect of

Felix Hieber, Michael Denkowski, Tobias Domhan, Barbara Darques Barros

Sockeye 3 is the latest version of the Sockeye toolkit for Neural Machine Translation (NMT). Now based on PyTorch, Sockeye 3 provides faster model implementations and more advanced features with a further streamlined codebase. This enables broader experimentation with faster iteration, efficient training of stronger and faster models, and the flexibility to

Victor D. Dorobantu, Kamyar Azizzadenesheli, Yisong Yue

We study policy optimization problems for deterministic Markov decision processes (MDPs) with metric state and action spaces, which we refer to as Metric Policy Optimization Problems (MPOPs). Our goal is to establish theoretical results on the well-posedness of MPOPs that can characterize practically relevant continuous control systems. To do so, we define a

Yinglun Zhu, Paul Mineiro

Designing efficient general-purpose contextual bandit algorithms that work with large -- or even continuous -- action spaces would facilitate application to important scenarios such as information retrieval, recommendation systems, and continuous control. While obtaining standard regret guarantees can be hopeless, alternative regret notions have been propose

Hanqing Guo, Chenning Li, Lingkun Li, Zhichao Cao

In this paper, we propose NEC (Neural Enhanced Cancellation), a defense mechanism, which prevents unauthorized microphones from capturing a target speaker's voice. Compared with the existing scrambling-based audio cancellation approaches, NEC can selectively remove a target speaker's voice from a mixed speech without causing interference to others. Specifica

Mahbubur Rahman, M. Ramish Ashraf, Rongxiao Zhang, Xu Cao

Objective: In this study, a fast imaging technique was developed for the first in vivo Cherenkov emission imaging from an ultra-high dose rate (UHDR) electron beam source at single pulse (360 Hz) submillimeter resolution. Approach: A CMOS camera, gated to the UHDR LINAC, imaged the Cherenkov emission profiles pulse by pulse passively during the irradiation o

Brendan T. Gould, Philip N. Brown

The emerging technology of Vehicle-to-Vehicle (V2V) communication over vehicular ad hoc networks promises to improve road safety by allowing vehicles to autonomously warn each other of road hazards. However, research on other transportation information systems has shown that informing only a subset of drivers of road conditions may have a perverse effect of

Nathan Louis, Tylan N. Templin, Travis D. Eliason, Daniel P. Nicolella

Analyzing sports performance or preventing injuries requires capturing ground reaction forces (GRFs) exerted by the human body during certain movements. Standard practice uses physical markers paired with force plates in a controlled environment, but this is marred by high costs, lengthy implementation time, and variance in repeat experiments; hence, we prop

Haoning Kan, Jiale Yu, Jiajin Huang, Zihe Liu

The progress of EEG-based emotion recognition has received widespread attention from the fields of human-machine interactions and cognitive science in recent years. However, how to recognize emotions with limited labels has become a new research and application bottleneck. To address the issue, this paper proposes a Self-supervised Group Meiosis Contrastive

Nigamaa Nayakanti, Rami Al-Rfou, Aurick Zhou, Kratarth Goel

Motion forecasting for autonomous driving is a challenging task because complex driving scenarios result in a heterogeneous mix of static and dynamic inputs. It is an open problem how best to represent and fuse information about road geometry, lane connectivity, time-varying traffic light state, and history of a dynamic set of agents and their interactions i

Alexander Dietmüller, Siddhant Ray, Romain Jacob, Laurent Vanbever

Generalizing machine learning (ML) models for network traffic dynamics tends to be considered a lost cause. Hence for every new task, we design new models and train them on model-specific datasets closely mimicking the deployment environments. Yet, an ML architecture called_Transformer_ has enabled previously unimaginable generalization in other domains. Now

Xiaolei Diao, Daqian Shi, Hao Tang, Qiang Shen

The long-tail effect is a common issue that limits the performance of deep learning models on real-world datasets. Character image datasets are also affected by such unbalanced data distribution due to differences in character usage frequency. Thus, current character recognition methods are limited when applied in the real world, especially for the categorie

Simone D'Onofrio, Federica Fragomeno, Claudio Gambino, Fabio Riccioni

The metric and the electromagnetic potential generated by a static, spherically symmetric charged massive object in any dimension are given by the Reissner-Nordstr\"om-Tangherlini solution. We derive the expansion of this solution up to third post-Minkowskian order by computing the classical contribution of scattering amplitudes describing the emission of ei