November 2022 arXiv papers — page 81

Ekta Prashnani, Michael Goebel, B. S. Manjunath

We propose PhaseForensics, a DeepFake (DF) video detection method that leverages a phase-based motion representation of facial temporal dynamics. Existing methods relying on temporal inconsistencies for DF detection present many advantages over the typical frame-based methods. However, they still show limited cross-dataset generalization and robustness to co

Florian Bossmann, Wenze Wu

Object recognition and reconstruction is of great interest in many research fields. Detecting pedestrians or cars in traffic cameras or tracking seismic waves in geophysical exploration are only two of many applications. Recently, the authors developed a new method - Object reconstruction using K-approximation (ORKA) - to extract such objects out of given da

Juan Martínez-Sykora, Bart De Pontieu, Viggo H. Hansteen, Paola Testa

The ponderomotive force is suggested to be the main mechanism to produce the so-called first ionization potential (FIP) effect - the enrichment of low FIP elements observed in the outer solar atmosphere. It is well known that the ionization of these elements occurs within the chromosphere. Therefore, this phenomenon is intimately tied to the plasma state in

Ahmed S. Alahmed, Lang Tong

We propose a social welfare maximizing mechanism for an energy community that aggregates individual and shared community resources under a general net energy metering (NEM) policy. Referred to as Dynamic NEM, the proposed mechanism adopts the standard NEM tariff model and sets NEM prices dynamically based on the total shared renewables within the community.

Ananya Kumar, Ruoqi Shen, Sebastien Bubeck, Suriya Gunasekar

SGD and AdamW are the two most used optimizers for fine-tuning large neural networks in computer vision. When the two methods perform the same, SGD is preferable because it uses less memory (12 bytes/parameter with momentum and 8 bytes/parameter without) than AdamW (16 bytes/parameter). However, on a suite of downstream tasks, especially those with distribut

Tomasz Gałązka, Yong Jiao, Adam Osękowski, Lian Wu

The purpose of the paper is to establish weighted maximal $L_p$-inequalities in the context of operator-valued martingales on semifinite von Neumann algebras. The main emphasis is put on the optimal dependence of the $L_p$ constants on the characteristic of the weight involved. As applications, we establish weighted estimates for the noncommutative version o

Jiajian Guan, Yue He, Bin Liao, Xu Zhang

Atomic heating is a fundamental phenomenon governed by the thermal spike effect during energetic deposition. This work presented another insight into thermal spike using a coupled classical oscillator model instead of a typical heat diffusion model. The temperature profile of deposited atoms was replaced by oscillator amplitude as an energy descriptor. Solvi

H. J. Xia, X. Y. Wu, H. Mei, J. M. Yao

The beyond mean-field approach for low-lying hypernuclear states is extended by mixing the configurations associated with both single-particle and quadrupole-octupole collective excitations within the generator coordinate method based on a covariant density functional theory. The method is demonstrated in the application to the low-lying states of $^{21}_\La

F. Combes, N. Gupta, S. Muller, S. Balashev

The BL Lac PKS 1413+135 was observed by the Large Survey Project "MeerKAT Absorption Line Survey" (MALS) in the L-band, at 1139 MHz and 1293-1379 MHz, targeting the HI and OH lines in absorption at z = 0.24671. The radio continuum is thought to come from a background object at redshift lower than 0.5, as suggested by the absence of gravitational images. The

Xiangdong Zhang, Jinbo Hu, Nan Zhao

Random motion of spins is usually detrimental in magnetic resonance experiments. The spin diffusion in non-uniform magnetic fields causes broadening of the resonance and limits the sensitivity and the spectral resolution in applications like magnetic resonance spectroscopy. Here, by observation of the parity-time ($PT$) phase transition of diffusive spins in

Hongxiao Wang, Zoe L. Jiang, Yanmin Zhao, Siu-Ming Yiu

In recent years, distributed machine learning has garnered significant attention. However, privacy continues to be an unresolved issue within this field. Multi-key homomorphic encryption over torus (MKTFHE) is one of the promising candidates for addressing this concern. Nevertheless, there may be security risks in the decryption of MKTFHE. Moreover, to our b

Md. Istiaq Ansari, Taufiq Hasan

Pattern recognition from audio signals is an active research topic encompassing audio tagging, acoustic scene classification, music classification, and other areas. Spectrogram and mel-frequency cepstral coefficients (MFCC) are among the most commonly used features for audio signal analysis and classification. Recently, deep convolutional neural networks (CN

L. -J. Liu, R. M. J. Janssen, C. M. Bradford, S. Hailey-Dunsheath

We report on the kinetic inductance detector (KID) array focal plane assembly design for the Terahertz Intensity Mapper (TIM). Each of the 2 arrays consists of 4 wafer-sized dies (quadrants), and the overall assembly must satisfy thermal and mechanical requirements, while maintaining high optical efficiency and a suitable electromagnetic environment for the

Cedric Nimpa Fondje, Shuowen Hu, Benjamin S. Riggan

Interest in thermal to visible face recognition has grown significantly over the last decade due to advancements in thermal infrared cameras and analytics beyond the visible spectrum. Despite large discrepancies between thermal and visible spectra, existing approaches bridge domain gaps by either synthesizing visible faces from thermal faces or by learning t

Lei Qian, Zhichen Pan, Hongfei Liu, Hengqian Gan

We present the estimation of the solar observation with the Five-hundred-meter Aperture Spherical radio Telescope (FAST). For both the quite Sun and the Sun with radio bursts, when pointing directly to the Sun, the total power received by FAST would be out of the safe operational range of the signal chain, even resulting in the damage to the receiver. As a c

F. Diaz-Guerra, A. Jimenez-Molina

The existing approaches to identify personalized salience zones of a Web page do not consider the dynamic behavior in time of the Web user's gaze or the alterations of its content. For this reason, this paper proposes the concept of visit intention, an indicator of the visual attention of a Web user in a certain period of time, short span time windows, in di

Heena Khanchandani, Rolf Rolli, Hans-Christian Schneider, Christoph Kirchlechner

Metallic materials, especially steel, underpin transportation technologies. High-manganese twinning induced plasticity (TWIP) austenitic steels exhibit exceptional strength and ductility from twins, low-energy microstructural defects that form during plastic loading. Their high-strength could help light-weighting vehicles, and hence cut carbon emissions. TWI

Sheng-Zhong Song, Zheng-Da Huang

We consider using the preconditioned-Krylov subspace method to solve the system of linear equations with a three-by-three block structure. By making use of the three-by-three block structure, eight inexact block factorization preconditioners, which can be put into a same theoretical analysis frame, are proposed based on a kind of inexact factorization. By ge

Balume Mburano, Weisheng Si, Qing Cao, Wei Xing Zheng

Only when understanding hackers' tactics, can we thwart their attacks. With this spirit, this paper studies how hackers can effectively launch the so-called 'targeted node attacks', in which iterative attacks are staged on a network, and in each iteration the most important node is removed. In the existing attacks for weighted networks, the node importance i

Yanming Su, Minyong Guo, Haopeng Yan, Bin Chen

We consider the light emitters moving freely along the geodesics on the equatorial plane near a Kerr black hole and study the observability of these emitters. To do so, we assume these emitters emit the photons isotropically and monochromatically, and we compute the photon escaping probability (PEP) and the maximum observable blueshift (MOB) of the photons t

Rishabh Jain, Mayur Hemani, Duygu Ceylan, Krishna Kumar Singh

Numerous pose-guided human editing methods have been explored by the vision community due to their extensive practical applications. However, most of these methods still use an image-to-image formulation in which a single image is given as input to produce an edited image as output. This objective becomes ill-defined in cases when the target pose differs sig

Masamichi Zaizen, Hiroki Nagakura

Neutrino-neutrino forward scatterings potentially induce collective neutrino oscillation in dense neutrino gases in astrophysical sites such as core-collapse supernovae (CCSN) and binary neutron star mergers (BNSM). In this paper, we present a detailed study of fast neutrino-flavor conversion (FFC), paying special attention to asymptotic states, by linear st

Yuecong Xu, Haozhi Cao, Zhenghua Chen, Xiaoli Li

Video analysis tasks such as action recognition have received increasing research interest with growing applications in fields such as smart healthcare, thanks to the introduction of large-scale datasets and deep learning-based representations. However, video models trained on existing datasets suffer from significant performance degradation when deployed di

Hanan Quispe, Jorshinno Sumire, Patricia Condori, Edwin Alvarez

The development of autonomous vehicles arises new challenges in urban traffic scenarios where vehicle-pedestrian interactions are frequent e.g. vehicle yields to pedestrians, pedestrian slows down due approaching to the vehicle. Over the last years, several datasets have been developed to model these interactions. However, available datasets do not cover nea

Dor Minzer, Kai Zheng

The Cube versus Cube test is a variant of the well-known Plane versus Plane test of Raz and Safra, in which to each $3$-dimensional affine subspace $C$ of $\mathbb{F}_q^n$, a polynomial of degree at most $d$, $T(C)$, is assigned in a somewhat locally consistent manner: taking two cubes $C_1, C_2$ that intersect in a plane uniformly at random, the probability

Wei Wang, Hourieh Khalajzadeh, Anuradha Madugalla, Jennifer Mcintosh

eHealth technologies have been increasingly used to foster proactive self-management skills for patients with chronic diseases. However, it is challenging to provide each user with their desired support due to the dynamic and diverse nature of the chronic disease and its impact on users. Many such eHealth applications support aspects of `adaptive user interf

Vasilios Karanikolas, Takuya Iwasaki, Joel Henzie, Naoki Ikeda

High-quality emission centers in two-dimensional materials are promising components for future photonic and optoelectronic applications. Carbon-enriched hexagonal boron nitride (hBN:C) layers host atom-like color-center (CC) defects with strong and robust photoemission up to room temperature. Placing the hBN:C layers on top of Ag triangle nanoparticles (NPs)

Adway Kumar Das, Anandamohan Ghosh

The competition between strength and correlation of coupling terms in a Hamiltonian defines numerous phenomenological models exhibiting spectral properties interpolating between those of Poisson (integrable) and Wigner-Dyson (chaotic) ensembles. It is important to understand how the off-diagonal terms of a Hamiltonian evolve as one or more symmetries of an i

Kali Krishna Kota, Praful D. Mankar, Harpreet S. Dhillon

This paper considers beamforming for a reconfigurable intelligent surface (RIS)-aided multiple input single output (MISO) communication system in the presence of Rician multipath fading. Our aim is to jointly optimize the transmit beamformer and RIS phase shift matrix for maximizing the mean signal-to-noise (SNR) of the combined signal received over direct a

Miku Ishizaki, Naomichi Hatano, Hiroyasu Tajima

Quantum thermodynamics explores novel thermodynamic phenomena that emerge when interactions between macroscopic systems and microscopic quantum ones go into action. Among various issues, quantum heat engines, in particular, have attracted much attention as a critical step in theoretical formulation of quantum thermodynamics and investigation of efficient use

Chen-Yu Chi

A p-adic analogue of the pseudonorm version of the birational Torelli type theorem is obtained via a comparison theorem of image closures. Among other results obtained, we have a criterion for existence of rational points of canonically polarized surfaces over finite fields.

Koki Kizawa, Ryoichi Shinkuma, Gabriele Trovato

This paper proposes an edge computing system that enables estimating physical activities of people in offices from time-series point-cloud data, obtained by using a light-detection-and-ranging (LIDAR) sensor network. The paper presents that the proposed system successfully constructs the model for estimating the number of typed characters from time-series po

Garima Rajpoot, Komal Kumari, Sandeep Joshi, Sudhir Ranjan Jain

We present a systematic treatment of a 0-\texorpdfstring{$\pi$}{Lg} qubit in the presence of a time-dependent external flux. A gauge-invariant Lagrangian and the corresponding Hamiltonian is obtained. The effect of the flux noise on the qubit relaxation is obtained using perturbation theory. Under a time-dependent drive of sinusoidal form, the survival proba

Hongyan Jiang, Maoran Zhu, Yanyan Fu, Yuanxin Wu

The acquisition of attitude, velocity, and position is an essential task in the field of inertial navigation, achieved by integrating the measurements from inertial sensors. Recently, the ultra-precision inertial navigation computation has been tackled by the functional iteration approach (iNavFIter) that drives the non-commutativity errors almost to the com

Benjamin Zhang, Khee-Gan Lee, Alex Krolewski, Jingjing Shi

Galaxy formation theories predict that galaxy shapes and angular momenta have non-random alignments with the cosmic web. This leads to so-called intrinsic alignment between pairs of galaxies, which is important to quantify as a nuisance parameter for weak lensing. We study galaxy-cosmic web alignment in the IllustrisTNG suite of hydrodynamical simulations at

Sangdon Park, Osbert Bastani, Taesoo Kim

Blockchains with smart contracts are distributed ledger systems that achieve block-state consistency among distributed nodes by only allowing deterministic operations of smart contracts. However, the power of smart contracts is enabled by interacting with stochastic off-chain data, which in turn opens the possibility to undermine the block-state consistency.

A. D. Alhaidari, T. J. Taiwo

Starting with an orthogonal polynomial sequence $\{p_n(s)\}_{n=0}^\infty$ that has a discrete spectrum, we design an energy spectrum formula, $E_k = f (s_k)$, where $|{s_k\}$ is the finite or infinite discrete spectrum of the polynomial. Using a recent approach for doing quantum mechanics based, not on potential functions but, on orthogonal energy polynomial

Oriol Solé Pi

This work revolves around the two following questions: Given a convex body $C\subset\mathbb{R}^d$, a positive integer $k$ and a finite set $S\subset\mathbb{R}^d$ (or a finite Borel measure $\mu$ on $\mathbb{R}^d$), how many homothets of $C$ are required to cover $S$ if no homothet is allowed to cover more than $k$ points of $S$ (or have measure larger than $

H. M. Ikhlaq, S. Hayat, H. M. A. Siddiqui

Dominating sets and resolving sets have important applications in control theory and computer science. In this paper, we introduce an edge-analog of the classical dominant metric dimension of graphs. By combining the concepts of a vertex-edge dominating set and an edge resolving set, we introduce the notion of a vertex-edge dominant edge resolving set of a g

Takeru Matsuda

For the multivariate linear regression model with unknown covariance, the corrected Akaike information criterion is the minimum variance unbiased estimator of the expected Kullback--Leibler discrepancy. In this study, based on the loss estimation framework, we show its inadmissibility as an estimator of the Kullback--Leibler discrepancy itself, instead of th

Chuer Pan, Brian Okorn, Harry Zhang, Ben Eisner

How do we imbue robots with the ability to efficiently manipulate unseen objects and transfer relevant skills based on demonstrations? End-to-end learning methods often fail to generalize to novel objects or unseen configurations. Instead, we focus on the task-specific pose relationship between relevant parts of interacting objects. We conjecture that this r

Jeongwhan Choi, Seoyoung Hong, Noseong Park, Sung-Bae Cho

Collaborative filtering is one of the most fundamental topics for recommender systems. Various methods have been proposed for collaborative filtering, ranging from matrix factorization to graph convolutional methods. Being inspired by recent successes of graph filtering-based methods and score-based generative models (SGMs), we present a novel concept of blu

Xikun Li

We consider the optimal control problem in a two-qubit system with bounded amplitude. Two cases are studied: quantum state preparation and entanglement creation. Cost functions, fidelity and concurrence, are optimized over bang-off controls for different values of the total duration, respectively. For quantum state preparation problem, three critical time po

Abhijit Suprem

The Zero-Shot Learning (ZSL) task attempts to learn concepts without any labeled data. Unlike traditional classification/detection tasks, the evaluation environment is provided unseen classes never encountered during training. As such, it remains both challenging, and promising on a variety of fronts, including unsupervised concept learning, domain adaptatio

Yang Yang, Hongjian Sun, Jialei Gong, Di Yu

Nonlinear dimensionality reduction lacks interpretability due to the absence of source features in low-dimensional embedding space. We propose an interpretable method featMAP to preserve source features by tangent space embedding. The core of our proposal is to utilize local singular value decomposition (SVD) to approximate the tangent space which is embedde

Chun-Chih Kuo, Ted Tsei Kuo, Chia-Yu Lin

Communication costs within Federated learning hinder the system scalability for reaching more data from more clients. The proposed FL adopts a hub-and-spoke network topology. All clients communicate through the central server. Hence, reducing communication overheads via techniques such as data compression has been proposed to mitigate this issue. Another cha

Zhongchu Ni, Sai Li, Xiaowei Deng, Yanyan Cai

Quantum error correction (QEC) aims to protect logical qubits from noises by utilizing the redundancy of a large Hilbert space, where an error, once it occurs, can be detected and corrected in real time. In most QEC codes, a logical qubit is encoded in some discrete variables, e.g., photon numbers. Such encoding schemes make the codewords orthogonal, so that

Bo Gao

We introduce and discuss the concept of \textit{arrangement}, traditionally found in the context of chemical reactions and few-body rearrangement collisions, in the general context of an $N$-body quantum system. We show that the ability for particles to attract and bind is a key source of complexity of an $N$-body quantum system, and \textit{arrangement} is

Ahmad Chaddad, Qizong lu, Jiali Li, Yousef Katib

Artificial intelligence (AI) continues to transform data analysis in many domains. Progress in each domain is driven by a growing body of annotated data, increased computational resources, and technological innovations. In medicine, the sensitivity of the data, the complexity of the tasks, the potentially high stakes, and a requirement of accountability give

Michael Nayak, Christina Straight, Evelyn Kent, Jarred Langhals

Fundamental big-picture challenges face the enterprise of burgeoning space test, which may also have an impact on the syllabus and training of a possible future Space Test Pilot School. Test fundamentals and test conduct under stresses of time and fuel will be where the rubber meets the road. This paper specifically discusses four of those challenges, and th

Da-Wei Luo, Xiao-Feng Qian, Ting Yu

We study the remote entanglement generation between macroscopic microwave magnon modes in a coupled cavity system. The cavities are connected via an optical fiber, which necessitates the use of a frequency conversion inside the cavity. The converter may be implemented via a rare-earth doped crystal acting like an effective three-level system. The entanglemen

Sishu Shankar Muni, Zeric Tabekoueng Njitacke, Cyrille Feudjio, Theophile Fozin

In this paper, we have introduced and investigated the collective behavior of a network of memristive Hindmarsh-Rose (HR) neurons. The proposed model was built considering the memristive autapse of the traditional 2D HR neuron. Using the one-parameter bifurcation diagram and its corresponding maximal Lyapunov exponent graph, we showed that the proposed model

Xurong Xie, Xunying Liu, Hui Chen, Hongan Wang

Modeling the speaker variability is a key challenge for automatic speech recognition (ASR) systems. In this paper, the learning hidden unit contributions (LHUC) based adaptation techniques with compact speaker dependent (SD) parameters are used to facilitate both speaker adaptive training (SAT) and unsupervised test-time speaker adaptation for end-to-end (E2

Javier A. Arroyo-Figueroa

We present in this paper a cryptocurrency called Mobile Fungible Token (MFT) or "MiftyCoin", which is mined with Proof of Human Work (PoH). Blocks in MFT's blockchain are mined by users solving unique 24-tile puzzles autogenerated as a function of block hash values. Each tile in the puzzle is a 4-sided domino-like square, where the number of dots per square

Yan Liang, Pu Shen, Li-Na Ji, Zheng Yuan Xue

Quantum computation has demonstrated advantages over classical computation for special hard problems, where a set of universal quantum gates is essential. Geometric phases, which have built-in resilience to local noise, have been used to construct quantum gates with excellent performance. However, this advantage has been smeared in previous schemes. Here, we

Donatella Danielli, Alaa Haj Ali

In this article we give a brief overview of some known results in the theory of obstacle-type problems associated with a class of fourth-order elliptic operators, and we highlight our recent work with collaborators in this direction. Obstacle-type problems governed by operators of fourth order naturally arise in the linearized Kirchhoff-Love theory for plate

Andong Deng, Taojiannan Yang, Chen Chen, Qian Chen

Correctly recognizing the behaviors of children with Autism Spectrum Disorder (ASD) is of vital importance for the diagnosis of Autism and timely early intervention. However, the observation and recording during the treatment from the parents of autistic children may not be accurate and objective. In such cases, automatic recognition systems based on compute

LISA Pathfinder Collaboration, M. Armano, H. Audley, J. Baird

A comprehensive summary of the measurements made to characterize test mass charging due to the space environment during the LISA Pathfinder mission is presented. Measurements of the residual charge of the test mass after release by the grabbing and positioning mechanism, show that the initial charge of the test masses was negative after all releases, leaving

L. -J. Liu, R. M. J Janssen, C. M. Bradford, S. Hailey-Dunsheath

The Terahertz Intensity Mapper (TIM) is designed to probe the star formation history in dust-obscured star-forming galaxies around the peak of cosmic star formation. This will be done via measurements of the redshifted 157.7 um line of singly ionized carbon ([CII]). TIM employs two R $\sim 250$ long-slit grating spectrometers covering 240-420 um. Each is equ

Mine Gokce Dogan, Martina Cardone, Christina Fragouli

This paper aims to develop resilient transmission mechanisms to suitably distribute traffic across multiple paths in an arbitrary millimeter-wave (mmWave) network. The main contributions include: (a) the development of proactive transmission mechanisms that build resilience against network disruptions in advance, while achieving a high end-to-end packet rate

Mason Ma, Alisa Ren, Christopher Tyler, Jaydeep Karandikar

Machining dynamics research lays a solid foundation for machining operations by providing stable combinations of spindle speed and depth of cut. Furthermore, machine learning has been applied to predict tool life as a function of cutting speed. However, the existing research does not consider the discrete-event dynamics in machine shop, i.e., the machine too

Lukasz Komza, Polnop Samutpraphoot, Mutasem Odeh, Yu-Lung Tang

Silicon is the ideal material for building electronic and photonic circuits at scale. Spin qubits and integrated photonic quantum technologies in silicon offer a promising path to scaling by leveraging advanced semiconductor manufacturing and integration capabilities. However, the lack of deterministic quantum light sources, two-photon gates, and spin-photon

Dandan Fan, Huiqiu Lin

Let $G$ be a connected graph. If $G$ contains a matching of size $k$, and every matching of size $k$ is contained in a perfect matching of $G$, then $G$ is said to be \emph{$k$-extendable}. A $k$-regular spanning subgraph of $G$ is called a \textit{$k$-factor}. In this paper, we provide spectral conditions for a (balanced bipartite) graph with minimum degree

Yunjia Xi, Jianghao Lin, Weiwen Liu, Xinyi Dai

Reranking, as the final stage of multi-stage recommender systems, refines the initial lists to maximize the total utility. With the development of multimedia and user interface design, the recommendation page has evolved to a multi-list style. Separately employing traditional list-level reranking methods for different lists overlooks the inter-list interacti

Jieqi Shi, Peiliang Li, Xiaozhi Chen, Shaojie Shen

The image-based 3D object detection task expects that the predicted 3D bounding box has a ``tightness'' projection (also referred to as cuboid), which fits the object contour well on the image while still keeping the geometric attribute on the 3D space, e.g., physical dimension, pairwise orthogonal, etc. These requirements bring significant challenges to the

Arushi Bodas, Raman Sundrum

It is well-known that first order phase transitions in the early universe can be a powerful source of observable stochastic gravitational wave backgrounds. Any such gravitational wave background must exhibit large-scale anisotropies at least as large as those seen in the CMB $\sim 10^{-5}$, providing a valuable new window onto the (inflationary) origins of p

Mallory Wang, Ismael Mendoza, Cheng Wang, Camille Avestruz

Coadded astronomical images are created by stacking multiple single-exposure images. Because coadded images are smaller in terms of data size than the single-exposure images they summarize, loading and processing them is less computationally expensive. However, image coaddition introduces additional dependence among pixels, which complicates principled stati

Tailin Zhou, Jun Zhang, Danny H. K. Tsang

Federated learning allows multiple clients to collaboratively train a model without exchanging their data, thus preserving data privacy. Unfortunately, it suffers significant performance degradation due to heterogeneous data at clients. Common solutions involve designing an auxiliary loss to regularize weight divergence or feature inconsistency during local

Jie Ding, Ruiming Ma, Zhigui Lin, Zhi Ling

This paper demonstrates a lower and upper solution method to investigate the asymptotic behaviour of the conservative reaction-diffusion systems associated with Markovian process algebra models. In particular, we have proved the uniform convergence of the solution to its constant equilibrium for a case study as time tends to infinity, together with experimen

Melissa Li, Claudio U. Hail, Souvik Biswas, Harry A. Atwater

Two-dimensional transition metal dichalcogenides (2D TMDCs) are promising candidates for ultra-thin active nanophotonic elements due to the strong tunable excitonic resonances that dominate their optical response. Here we demonstrate dynamic beam steering by an active van der Waals metasurface that leverages large complex refractive index tunability near exc

Taro Kanao, Hayato Goto

High-performance Ising machines for solving combinatorial optimization problems have been developed with digital processors implementing heuristic algorithms such as simulated bifurcation (SB). Although Ising machines have been designed for second-order cost functions, there are practical problems expressed naturally by higher-order cost functions. In this w

Yenho Chen, Carl W. Harris, Xiaoyu Ma, Zheng Li

We propose a decoding-based approach to detect context effects on neural codes in longitudinal neural recording data. The approach is agnostic to how information is encoded in neural activity, and can control for a variety of possible confounding factors present in the data. We demonstrate our approach by determining whether it is possible to decode location

M. Bayar, A. Martinez Torres, K. P. Khemchandani, R. Molina

In this work we investigate the possibility of the formation of states from the dynamics involved in the $D^*D^*D^*$ system by considering that two $D^*$'s generate a $J^P=1^+$ bound state, with isospin 0, which has been predicted in an earlier theoretical work. We solve the Faddeev equations for this system within the fixed center approximation and find the

Ziyan Chen, Heng Wu, Jing Cheng

The current ghost imaging phase reconstruction schemes require either complex optical systems, Fourier transform steps, or iterative algorithms, which may increase the difficulty of system design, cause phase retrieval error or take too much time. To address this problem, we propose a five-step phase-shifting method in which no complex optical systems, Fouri

Debra Meloy Elmegreen, Bruce G. Elmegreen, John S. Gallagher, Ralf Kotulla

Tadpole galaxies are metal-poor dwarfs with typically one dominant star-forming region, giving them a head-tail structure when inclined. A metallicity drop in the head suggests that gas accretion with even lower metallicity stimulated the star formation. Here we present multiband HST WFC3 and ACS images of four nearby (<25 Mpc) tadpoles, SBS0, SBS1, Kiso 386

Shuohang Wu, Zi Cai

The time evolution of a physical system is generally described by a differential equation, which can be solved numerically by adopting a difference scheme with space-time discretization. This discretization, as a numerical artifact, results in accumulated errors during evolution thus usually plays a negative role in simulations. In a quantum circuit, however

Luoqian Jiang, Yifan He, Jian Chen

Visual question answering (VQA) is a challenging task to provide an accurate natural language answer given an image and a natural language question about the image. It involves multi-modal learning, i.e., computer vision (CV) and natural language processing (NLP), as well as flexible answer prediction for free-form and open-ended answers. Existing approaches

Zhangchi Chen

The classical Hard Lefschetz theorem (HLT), Hodge-Riemann bilinear relation theorem (HRR) and Lefschetz decomposition theorem (LD) are stated for a power of a K\"ahler class on a compact K\"ahler manifold. These theorems are not true for an arbitrary class, even if it contains a smooth strictly positive representative. Dinh-Nguy\^en proved the mixed HLT, HRR

Hesham M. Eraqi, Mohamed N. Moustafa, Jens Honer

Conditional imitation learning (CIL) trains deep neural networks, in an end-to-end manner, to mimic human driving. This approach has demonstrated suitable vehicle control when following roads, avoiding obstacles, or taking specific turns at intersections to reach a destination. Unfortunately, performance dramatically decreases when deployed to unseen environ

Yuki Nakayama, Yoshihiko Okamoto, Daigorou Hirai, Koshi Takenaka

The electrical resistivity, magnetic susceptibility, and heat capacity of sintered samples of Ca2Ir2O7, in which pentavalent Ir atoms with 5d4 electron configuration form a pyrochlore structure, have been studied. The obtained experimental data strongly suggest that Ca2Ir2O7 is metallic below room temperature and exhibits no electronic or magnetic phase tran

Jing Zhang, Caishi Wang, Lixia Zhang, Lu Zhang

Let $M$ be a discrete-time normal martingale that has the chaotic representation property. Then, from the space of square integrable functionals of $M$, one can construct generalized functionals of $M$. In this paper, by using a type of weights, we introduce a class of continuous linear operators acting on generalized functionals of $M$, which we call genera

Vasantha Ramani, Miguel Martin, Pandarasamy Arjunan, Adrian Chong

This work presents a study on the characterization of the air-conditioning (AC) usage pattern of non-residential buildings from thermal images collected from an urban-scale infrared (IR) observatory. To achieve this first, an image processing scheme, for cleaning and extraction of the temperature time series from the thermal images is implemented. To test th

Kexuan Li

Variable selection problem for the nonlinear Cox regression model is considered. In survival analysis, one main objective is to identify the covariates that are associated with the risk of experiencing the event of interest. The Cox proportional hazard model is being used extensively in survival analysis in studying the relationship between survival times an

Yujin Zhu, Zilong Zhao, Robert Birke, Lydia Y. Chen

Tabular data synthesis is an emerging approach to circumvent strict regulations on data privacy while discovering knowledge through big data. Although state-of-the-art AI-based tabular data synthesizers, e.g., table-GAN, CTGAN, TVAE, and CTAB-GAN, are effective at generating synthetic tabular data, their training is sensitive to column permutations of input

Ellis Hoag, Kyungwoo Lee, Julián Mestre, Sergey Pupyrev

Function layout, also referred to as function reordering or function placement, is one of the most effective profile-guided compiler optimizations. By reordering functions in a binary, compilers are able to greatly improve the performance of large-scale applications or reduce the compressed size of mobile applications. Although the technique has been studied

Stephen Mussmann, Julia Reisler, Daniel Tsai, Ehsan Mousavi

Active learning has been studied extensively as a method for efficient data collection. Among the many approaches in literature, Expected Error Reduction (EER) (Roy and McCallum) has been shown to be an effective method for active learning: select the candidate sample that, in expectation, maximally decreases the error on an unlabeled set. However, EER requi

Gordon W. Semenoff

The flat band of edge states which occur in the simple tight-binding lattice model of graphene with a zig-zag edge have long been conjectured to take up a ferromagnetic configuration. In this work we demonstrate that, for a large class of interaction Hamiltonians which can be added to the tight-binding model, and at the first order in perturbation theory, th

Xueqiang Zhu, Sheng-Qin Feng

We study the properties of the shear viscosity coefficient of quark matter at finite temperature and chemical potential near chiral phase transition in a strong background magnetic field. A strong magnetic field induces anisotropic features, phase-space Landau-level quantization, and if the magnetic field is sufficiently strong, interferes with prominent QCD

Mahya Aghaee, Urszula Ledzewicz, Michael Robbins, Natalie Bezman

While many novel therapies have been approved in recent years for treating patients with multiple myeloma, there is still no established curative regimen, especially for patients with high risk disease. In this work, we use a mathematical modeling approach to determine combination therapy regimens that maximize healthy lifespan for patients with multiple mye

Sloane J. Wiktorowicz, Agnieszka Słowikowska, Larissa A. Nofi, Nicole Rider

The POLISH2 optical polarimeter has been in operation at the Lick Observatory 3-m Shane telescope since 2011, and it was commissioned at the Gemini North 8-m in 2016. This instrument primarily targets exoplanets, asteroids, and the Crab pulsar, but it has also been used for a wide variety of planetary, galactic, and supernova science. POLISH2's photoelastic

Claudio Pita-Ruiz

We introduce poly-Bernoulli polynomials in two variables by using a generalization of Stirling numbers of the second kind that we studied in a previous work. We prove the bi-variate poly-Bernoulli polynomial version of some known results on standard Bernoulli polynomials, as the addition formula and the binomial formula. We also prove a result that allows us

Bingchen Zhao, Yuling Gu, Jessica Zosa Forde, Naomi Saphra

At NeurIPS, American and Chinese institutions cite papers from each other's regions substantially less than they cite endogamously. We build a citation graph to quantify this divide, compare it to European connectivity, and discuss the causes and consequences of the separation.

Viggo Hansteen, Juan Martinez Sykora, Mats Carlsson, Bart De Pontieu

The Mg II h&k lines are amongst the best diagnostic tools of the upper solar chromosphere. This region of the atmosphere is of particular interest as it is the lowest region of the Sun's atmosphere where the magnetic field is dominant in the energetics and dynamics, defining its structure. While highly successful in the photosphere and lower to mid chromosph

Mohamed Swailem, Uwe C. Täuber

We study the stochastic spatial Lotka-Volterra (LV) model for predator-prey interaction subject to a periodically varying carrying capacity. The LV model with on-site lattice occupation restrictions that represent finite food resources for the prey exhibits a continuous active-to-absorbing phase transition. The active phase is sustained by spatio-temporal pa

Xiaonan Lu, Mark Cannon

For constrained linear systems with bounded disturbances and parametric uncertainty, we propose a robust adaptive model predictive control strategy with online parameter estimation. Constraints enforcing persistently exciting closed loop control actions are introduced for a set-membership parameter identification scheme. The algorithm requires the online sol

Vikram V. Dwarkadas

We report on Chandra X-ray observations of ASASSN-18tb/SN 2018fhw, a low luminosity Type Ia supernova that showed a H line in its optical spectrum. No X-ray emission was detected at the location of the SN. Upper limits to the luminosity of up to 3 $\times 10^{39}$ erg s$^{-1}$ are calculated, depending on the assumed spectral model, temperature and column de

Brian Testa, Yi Xiao, Harshit Sharma, Avery Gump

Smart speaker voice assistants (VAs) such as Amazon Echo and Google Home have been widely adopted due to their seamless integration with smart home devices and the Internet of Things (IoT) technologies. These VA services raise privacy concerns, especially due to their access to our speech. This work considers one such use case: the unaccountable and unauthor

Yunxiao Chen, Xiaoou Li

Matrix completion is a class of machine learning methods that concerns the prediction of missing entries in a partially observed matrix. This paper studies matrix completion for mixed data, i.e., data involving mixed types of variables (e.g., continuous, binary, ordinal). We formulate it as a low-rank matrix estimation problem under a general family of non-l

U. van Kolck

Weinberg's contributions to the power counting and derivation of few-nucleon forces in Chiral EFT are briefly recalled. Subsequent improvements are reviewed, concluding with the recent suggestion of a combinatorial enhancement.

Valentin A. Skvortsov, Piotr Sworowski

We locate Musial\,\&\,Sagher's concept of HK$_r$-inte\-gration within the approximate Henstock--Kurzweil integral theory. If to restrict HK$_r$-integral by requirement that the indefinite HK$_r$-integral is {\em continuous}, then it is included even in the classical Denjoy--Khintchine integral. We provide a direct argument demonstrating that this inclusion i