July 2022 arXiv papers — page 28

S. C. Scholten, I. O. Robertson, G. J. Abrahams, Priya Singh

Widefield quantum microscopy based on nitrogen-vacancy (NV) centres in diamond has emerged as a powerful technique for quantitative mapping of magnetic fields with a sub-micron resolution. However, the accuracy of the technique has not been characterised in detail so far. Here we show that optical aberrations in the imaging system may cause large systematic

Bo Feng, Gang Wu

The generalized Lanczos trust-region (GLTR) method is one of the most popular approaches for solving large-scale trust-region subproblem (TRS). Recently, Jia and Wang [Z. Jia and F. Wang, \emph{SIAM J. Optim., 31 (2021), pp. 887--914}] considered the convergence of this method and established some {\it a prior} error bounds on the residual, the solution and

Dan Zhang, Xi Zhou, Zi-Hao Wang, Yan Peng

Ship roll motion in high sea states has large amplitudes and nonlinear dynamics, and its prediction is significant for operability, safety, and survivability. This paper presents a novel data-driven methodology to provide a multi-step prediction of ship roll motions in high sea states. A hybrid neural network is proposed that combines long short-term memory

Toshinori Hayashi, Alessandro A. Trani, Yasushi Suto

We examine the stability of hierarchical triple systems using direct $N$-body simulations without adopting a secular perturbation approximation. We estimate their disruption timescales in addition to the mere stable/unstable criterion, with particular attention to the mutual inclination between the inner and outer orbits. First, we improve the fit to the dyn

Xiao-Yi Liu, Yu Cui, Jia-Pei Deng, Yi-Yan Liu

Metal halide perovskites quantum dots (MHPQDs) have aroused enormous interesting in the photovoltaic and photoelectric because of their marvelous properties and size characteristics. However, one of key problems that how to systematically analyze charge carriers trapping by different defects is still a challenge task. Here, we study nonradiation multiphonon

Qi Zheng, Chen-Yue Hao, Xiao-Feng Zhou, Ya-Xin Zhao

Overlaying two graphene layers with a small twist angle can create a moire superlattice to realize exotic phenomena that are entirely absent in graphene monolayer. A representative example is the predicted formation of localized pseudo-Landau levels (PLLs) with Kagome lattice in tiny-angle twisted bilayer graphene (TBG) with theta < 0.3 deg when the graphene

Xinbin Liang, Yang Yu, Yadong Liu, Kaixuan Liu

Accurately detecting and identifying drivers' braking intention is the basis of man-machine driving. In this paper, we proposed an electroencephalographic (EEG)-based braking intention measurement strategy. We used the Car Learning to Act (Carla) platform to build the simulated driving environment. 11 subjects participated in our study, and each subject drov

Yuta Kozakai

Let $p$ be a prime number, $k$ an algebraically closed field of characteristic $p$, $\tilde{G}$ a finite group, and $G$ a normal subgroup of $\tilde{G}$ having a $p$-power index in $\tilde{G}$. Moreover let $B$ be a block of $kG$ with a cyclic defect group and $\tilde{B}$ be the unique block of $k\tilde{G}$ covering $B$. We study tilting complexes over the b

Yuta Kozakai

We discuss finiteness/infiniteness of $\tau$-tilting modules over tensor products of two symmetric algebras. As an application, we discuss that over block algebras of direct products of finite groups.

Huanpeng Bu, Malik Ashtar, Toni Shiroka, Helen C. Walker

A quantum spin liquid (QSL) is an exotic state in which electron spins are highly entangled, yet keep fluctuating even at zero temperature. Experimental realization of model QSLs has been challenging due to imperfections, such as antisite disorder, strain, and extra or a lack of interactions in real materials compared to the model Hamiltonian. Here we report

Shi Chen, Kenji Fukushima, Yusuke Shimada

We perturbatively compute the Polyakov loop potential at high temperature with finite imaginary angular velocity. This imaginary rotation does not violate the causality and the thermodynamic limit is well defined. We analytically show that the imaginary angular velocity induces the perturbatively confined phase and serves as a new probe to confinement physic

Abhishek Bhardwaj, Wilhiam de Carvalho, Nanduni Nimalsiri, Elizabeth Ratnam

We propose an alternating direction method of multipliers (ADMM)-based algorithm for coordinating the charge and discharge of electric vehicles (EVs) to manage grid voltages while minimizing EV time-of-use energy costs. We prove that by including a Communication-Censored strategy, the algorithm maintains its solution integrity, while reducing peer-to-peer co

Enrique Gabriel Vera, Claudio Canizares, Mehrdad Pirnia

In recent years, the electrification of Canadian Remote Communities (RCs) has received significant attention, as their current electric energy systems are not only expensive, but are also highly polluting due to the prevalence of diesel generators. In addition, RCs' inherent geographic characteristics impose a series of challenges that must be considered whe

Hakho Choi, Jongil Park

In this paper, we investigate a relation between rational blowdown surgery and minimal symplectic fillings of a given Seifert 3-manifold with a canonical contact structure. Consequently, we determine a necessary and sufficient condition for a minimal symplectic filling of a Seifert 3-manifold satisfying certain conditions to be obtained by a sequence of rati

Guangyao Dou, Zheng Zhou, Xiaodong Qu

Using Machine Learning and Deep Learning to predict cognitive tasks from electroencephalography (EEG) signals is a rapidly advancing field in Brain-Computer Interfaces (BCI). In contrast to the fields of computer vision and natural language processing, the data amount of these trials is still rather tiny. Developing a PC-based machine learning technique to i

Ye Qiao, Mohammed Alnemari, Nader Bagherzadeh

This paper proposes a novel two-stage framework for emotion recognition using EEG data that outperforms state-of-the-art models while keeping the model size small and computationally efficient. The framework consists of two stages; the first stage involves constructing efficient models named EEGNet, which is inspired by the state-of-the-art efficient archite

Haoxuan You, Luowei Zhou, Bin Xiao, Noel Codella

Large-scale multi-modal contrastive pre-training has demonstrated great utility to learn transferable features for a range of downstream tasks by mapping multiple modalities into a shared embedding space. Typically, this has employed separate encoders for each modality. However, recent work suggests that transformers can support learning across multiple moda

Jae-woong Lee, Seongmin Park, Joonseok Lee, Jongwuk Lee

Implicit feedback has been widely used to build commercial recommender systems. Because observed feedback represents users' click logs, there is a semantic gap between true relevance and observed feedback. More importantly, observed feedback is usually biased towards popular items, thereby overestimating the actual relevance of popular items. Although existi

Junbo Yin, Jianbing Shen, Xin Gao, David Crandall

Previous works for LiDAR-based 3D object detection mainly focus on the single-frame paradigm. In this paper, we propose to detect 3D objects by exploiting temporal information in multiple frames, i.e., the point cloud videos. We empirically categorize the temporal information into short-term and long-term patterns. To encode the short-term data, we present a

Tal Einav, Yuehaw Khoo, Amit Singer

As experiments continue to increase in size and scope, a fundamental challenge of subsequent analyses is to recast the wealth of information into an intuitive and readily-interpretable form. Often, each measurement only conveys the relationship between a pair of entries, and it is difficult to integrate these local interactions across a dataset to form a coh

Zuyi Chen, Daniel P. Stark, Ryan Endsley, Michael Topping

The onset of the {\it JWST}-era provides a much-improved opportunity to characterize the resolved structure of early star forming systems. Previous {\it Spitzer} observations of $z\gtrsim 6$ galaxies revealed the presence of old stars and luminous HII regions (via [OIII]+H$\beta$ emission), but the poor resolution stunted our ability to map their locations w

Shotaro Z. Baba, Nobuyuki Yoshioka, Yuto Ashida, Takahiro Sagawa

We propose a method based on deep reinforcement learning that efficiently prepares a quantum many-body pure state in thermal or prethermal equilibrium. The main physical intuition underlying the method is that the information on the equilibrium states can be efficiently encoded/extracted by focusing on only a few local observables, relying on the typicality

Junbo Yin, Jin Fang, Dingfu Zhou, Liangjun Zhang

Dominated point cloud-based 3D object detectors in autonomous driving scenarios rely heavily on the huge amount of accurately labeled samples, however, 3D annotation in the point cloud is extremely tedious, expensive and time-consuming. To reduce the dependence on large supervision, semi-supervised learning (SSL) based approaches have been proposed. The Pseu

Junbo Yin, Dingfu Zhou, Liangjun Zhang, Jin Fang

Existing approaches for unsupervised point cloud pre-training are constrained to either scene-level or point/voxel-level instance discrimination. Scene-level methods tend to lose local details that are crucial for recognizing the road objects, while point/voxel-level methods inherently suffer from limited receptive field that is incapable of perceiving large

Runze Yang, Hao Peng, Chunyang Liu, Angsheng Li

Structural entropy is a metric that measures the amount of information embedded in graph structure data under a strategy of hierarchical abstracting. To measure the structural entropy of a dynamic graph, we need to decode the optimal encoding tree corresponding to the best community partitioning for each snapshot. However, the current methods do not support

Ze-Ning Zhang, Hai-Bin Zhang, Xing-Xing Dong, Jin-Lei Yang

In a few years, the COMET experiment at J-PARC and the Mu2e experiment at Fermilab will probe the $\mu-e$ conversion rate in the vicinity of $\mathcal{O}(10^{-17})$ for an Al target with high experimental sensitivity. Within the framework of the minimal supersymmetric extension of the Standard Model with local $B-L$ gauge symmetry (B-LSSM), we analyze the le

Bingjie, Xu, Yunan Wu, Pengxiao Hao

X-ray fluorescence spectroscopy (XRF) plays an important role for elemental analysis in a wide range of scientific fields, especially in cultural heritage. XRF imaging, which uses a raster scan to acquire spectra across artworks, provides the opportunity for spatial analysis of pigment distributions based on their elemental composition. However, conventional

Wenyun Li, Chi-Man Pun

Cross-modal hashing is a successful method to solve large-scale multimedia retrieval issue. A lot of matrix factorization-based hashing methods are proposed. However, the existing methods still struggle with a few problems, such as how to generate the binary codes efficiently rather than directly relax them to continuity. In addition, most of the existing me

Jeremy Brockmann, Marco Salviato

This paper explores the global Mode I fracture energy of a carbon fiber composite subject to a biaxial stress state at a crack tip, specifically in which one stress component is compressive and parallel to the crack. Based on an experimental technique previously coined as The Gap Test and Bazant's Type II Size Effect Law, it is found that there is a monotoni

Yoshiki Ito, Quan Kong, Kenichi Morita, Tomoaki Yoshinaga

Skeleton-based two-person interaction recognition has been gaining increasing attention as advancements are made in pose estimation and graph convolutional networks. Although the accuracy has been gradually improving, the increasing computational complexity makes it more impractical for a real-world environment. There is still room for accuracy improvement a

Yang Liu, Guanbin Li, Liang Lin

Existing visual question answering methods often suffer from cross-modal spurious correlations and oversimplified event-level reasoning processes that fail to capture event temporality, causality, and dynamics spanning over the video. In this work, to address the task of event-level visual question answering, we propose a framework for cross-modal causal rel

Ashima Garg, Depanshu Sani, Saket Anand

Label hierarchies are often available apriori as part of biological taxonomy or language datasets WordNet. Several works exploit these to learn hierarchy aware features in order to improve the classifier to make semantically meaningful mistakes while maintaining or reducing the overall error. In this paper, we propose a novel approach for learning Hierarchy

Robert F. Allen, Flavia Colonna, Glenn R. Easley

Let $\mathcal{L}$ be the space of complex-valued functions $f$ on the set of vertices $T$ of an rooted infinite tree rooted at $o$ such that the difference of the values of $f$ at neighboring vertices remains bounded throughout the tree, and let $\mathcal{L}_{\textbf{w}}$ be the set of functions $f\in \mathcal{L}$ such that $|f(v)-f(v^-)|=O(|v|^{-1})$, where

Rohan Pratap Singh, Mehdi Benallegue, Mitsuharu Morisawa, Rafael Cisneros

Deep reinforcement learning (RL) based controllers for legged robots have demonstrated impressive robustness for walking in different environments for several robot platforms. To enable the application of RL policies for humanoid robots in real-world settings, it is crucial to build a system that can achieve robust walking in any direction, on 2D and 3D terr

Yanan Ye

We show pluriclosed flow preserves the Hermitian-symplectic structures. And we observe that it can actually become a flow of Hermitian-symplectic forms when an extra evolution equation determined by the Bismut-Ricci form is considered. Moreover, we get a topological obstruction to the long-time existence in arbitrary dimension.

Muhammad Asaduzzaman, Simon Catterall

We conduct numerical simulations of a model of four dimensional quantum gravity in which the path integral over continuum Euclidean metrics is approximated by a sum over combinatorial triangulations. At fixed volume the model contains a discrete Einstein-Hilbert term with coupling $\kappa$ and local measure term with coupling $\beta$ that weights triangulati

Zhi Li, Xiangkui Meng, Jiafu Ning, Zhiwei Wang

Let $X$ be a compact K\"ahler manifold and $(L,h)\rightarrow X$ be a pseudoeffective line bundle, such that the curvature $i\Theta_{L,h}\geq 0$ in the sense of currents. The main result of the present paper is that $H^n(X,\mathcal{O}(\Omega^p_X\otimes L)\otimes \mathcal{I}(h))=0$ for $p\geq n-nd(L,h)+1$. This is a generalization of Bogomolov's vanishing theo

Tarek M. Elgindi, Yupei Huang

We consider steady states of the two-dimensional incompressible Euler equations in $\mathbb{T}^2$ and construct smooth and singular steady states around a particular singular steady state. More precisely, we construct families of smooth and singular steady solutions that converge to the Bahouri-Chemin patch.

Xiang Chen, Wenjun Xia, Ziyuan Yang, Hu Chen

Spectral computed tomography (CT) is an emerging technology, that generates a multienergy attenuation map for the interior of an object and extends the traditional image volume into a 4D form. Compared with traditional CT based on energy-integrating detectors, spectral CT can make full use of spectral information, resulting in high resolution and providing a

Oscar Hernan Madrid Padilla

We study the problem of variance estimation in general graph-structured problems. First, we develop a linear time estimator for the homoscedastic case that can consistently estimate the variance in general graphs. We show that our estimator attains minimax rates for the chain and 2D grid graphs when the mean signal has total variation with canonical scaling.

Liang Mao, Yajiang Hao, Lei Pan

Non-Hermitian skin effect (NHSE) is a unique feature studied extensively in non-interacting non-Hermitian systems. In this work, we extend the NHSE originally discovered in non-interacting systems to interacting many-body systems by investigating an exactly solvable non-Hermitian model, i.e., the prototypical Lieb-Liniger Bose gas with imaginary vector poten

Ningning Song, Yuxing Yang

Aims: Try to prove the $n$-dimensional balanced hypercube $BH_n$ is $(2n-2)$-fault-tolerant-prescribed hamiltonian laceability. Methods: Prove it by induction on $n$. It is known that the assertation holds for $n\in\{1,2\}$. Assume it holds for $n-1$ and prove it holds for $n$, where $n\geq 3$. If there are $2n-3$ faulty links and they are all incident with

Robert F. Allen, Katherine Heller, Matthew A. Pons

Here we consider when the difference of two composition operators is compact on the weighted Dirichlet spaces $\mathcal{D}_\alpha$. Specifically we study differences of composition operators on the Dirichlet space $\mathcal{D}$ and $S^2$, the space of analytic functions whose first derivative is in $H^2$, and then use Calder\'{o}n's complex interpolation to

Robert F. Allen, Katherine Heller, Matthew A. Pons

We investigate the isometric composition operators on the analytic Besov spaces. For $1<p<2$ we show that an isometric composition operator is induced only by a rotation of the disk. For $p>2$, we extend previous work on the subject. Finally, we analyze this same problem for the Besov spaces with an equivalent norm.

Daqing Wan, Dingxin Zhang

We study Frobenius eigenvalues of the compactly supported rigid cohomology of a variety defined over a finite field of $q$ elements via Dwork's method. A couple of arithmetic consequences will be drawn from this study. As the first application, we show that the zeta functions for finitely many related affine varieties are capable of witnessing all Frobenius

Zhou Wang, Wenbo Ma, Tao Zhang, Li Zhao

In order to recuperate the ultra-high purity xenon from PandaX-4T dark matter detector to high-pressure gas cylinders in emergency or at the end-of-run situation, a high speed ultra-high purity xenon recuperation system is designed and developed. This system includes a diaphragm pump, the heat management system, the main recuperation pipeline, the reflux pip

Christian Kurniawan, Xiyu Deng, Adhiraj Chakraborty, Assane Gueye

Microfinance, despite its significant potential for poverty reduction, is facing sustainability hardships due to high default rates. Although many methods in regular finance can estimate credit scores and default probabilities, these methods are not directly applicable to microfinance due to the following unique characteristics: a) under-explored (developing

Jingying Zeng

Scientific researchers utilize randomized experiments to draw casual statements. Most early studies as well as current work on experiments with sequential intervention decisions has been focusing on estimating the causal effects among sequential treatments, ignoring the non-compliance issues that experimental units might not be compliant with the treatment a

Paul R. Estrada, Jeffrey N. Cuzzi

Formation of the first planetesimals remains an unsolved problem. Growth by sticking must initiate the process, but multiple studies have revealed a series of barriers that can slow or stall growth, most of them due to nebula turbulence. In a companion paper, we study the influence of these barriers on models of fractal aggregate and solid, compact particle

Zhankui He, Handong Zhao, Tong Yu, Sungchul Kim

Bundle recommender systems recommend sets of items (e.g., pants, shirt, and shoes) to users, but they often suffer from two issues: significant interaction sparsity and a large output space. In this work, we extend multi-round conversational recommendation (MCR) to alleviate these issues. MCR, which uses a conversational paradigm to elicit user interests by

Honghao Huang, Jiajie Teng, Yu Liang, Chengyang Hu

Snapshot compressive imaging (SCI) encodes high-speed scene video into a snapshot measurement and then computationally makes reconstructions, allowing for efficient high-dimensional data acquisition. Numerous algorithms, ranging from regularization-based optimization and deep learning, are being investigated to improve reconstruction quality, but they are st

Paul R. Estrada, Jeffrey N. Cuzzi, Orkan M. Umurhan

Incremental particle growth in turbulent protoplanetary nebulae is limited by a combination of barriers that can slow or stall growth. Moreover, particles that grow massive enough to decouple from the gas are subject to inward radial drift which could lead to the depletion of most disk solids before planetesimals can form. Compact particle growth is probably

Yitian Long

With the rapid growth of multimodal media data on the Web in recent years, hash learning methods as a way to achieve efficient and flexible cross-modal retrieval of massive multimedia data have received a lot of attention from the current Web resource retrieval research community. Existing supervised hashing methods simply transform label information into pa

Ken Mochizuki, Ryusuke Hamazaki

We discover novel transitions characterized by distinguishability of bosons in non-unitary dynamics with parity-time ($\mathcal{PT}$) symmetry. We show that $\mathcal{PT}$ symmetry breaking, a unique transition in non-Hermitian open systems, enhances regions in which bosons can be regarded as distinguishable. This means that classical computers can sample th

J. Divahar, A. J. Roberts, Trent W. Mattner, J. E. Bunder

Numerical schemes for wave-like systems with small dissipation are often inaccurate and unstable due to truncation errors and numerical roundoff errors. Hence, numerical simulations of wave-like systems lacking proper handling of these numerical issues often fail to represent the physical characteristics of wave phenomena. This challenge gets even more intri

Weidong Chen, Dexiang Hong, Yuankai Qi, Zhenjun Han

Referring video object segmentation aims to segment the object referred by a given language expression. Existing works typically require compressed video bitstream to be decoded to RGB frames before being segmented, which increases computation and storage requirements and ultimately slows the inference down. This may hamper its application in real-world comp

Felipe Lepe, David Mora, Gonzalo Rivera, Iván Velásquez

In two dimensions, we propose and analyze an a posteriori error estimator for the acoustic spectral problem based on the virtual element method in $\H(\div;\Omega)$. Introducing an auxiliary unknown, we use the fact that the primal formulation of the acoustic problem is equivalent to a mixed formulation, in order to prove a superconvergence result, necessary

Xuhui Tian, Xinran Lin, Fan Zhong, Xueying Qin

Optimization-based 3D object tracking is known to be precise and fast, but sensitive to large inter-frame displacements. In this paper we propose a fast and effective non-local 3D tracking method. Based on the observation that erroneous local minimum are mostly due to the out-of-plane rotation, we propose a hybrid approach combining non-local and local optim

Tomas Valencia Zuluaga, Shmuel S. Oren

In this paper, we propose a high-level Stochastic steady-state model to analyze the value of co-located energy storage systems for wind power producers that participate in an electricity market through Forward or Day Ahead contracts. In particular, we try to find optimal sizing and contracting and stationary operating policies for profit maximization in the

Thi Nhung Dao, Duc Ninh Le, Margarete Mühlleitner

The new results on the muon anomalous magnetic moment (AMM) published by Fermilab in 2021, did not lead to a reduction of its long-pending deviation from the Standard Model (SM) value by more than 4$\sigma$. The explanation of this discrepancy by adding new particles to the theory puts many new physics models under tension when combined with the null results

Juan B. Gil, Jessica A. Tomasko

In this paper, we investigate pattern avoidance of parity restricted (even or odd) Grassmannian permutations for patterns of sizes 3 and 4. We use a combination of direct counting and bijective techniques to provide recurrence relations, closed formulas, and generating functions for their corresponding enumerating sequences. In addition, we establish some co

Robert F. Allen, Flavia Colonna, Glenn R. Easley

We study the multiplication operators on the weighted Lipschitz space $\mathcal{L}_{\textbf{w}}$ consisting of the complex-valued functions $f$ on the set of vertices of an infinite tree $T$ rooted at $o$ such that $\sup_{v\neq o}|v||f(v)-f(v^-)|<\infty$, where $|v|$ denotes the distance between $o$ and $v$ and $v^-$ is the neighbor of $v$ closest to $o$. Fo

Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan

While directly fine-tuning (FT) large-scale, pretrained models on task-specific data is well-known to induce strong in-distribution task performance, recent works have demonstrated that different adaptation protocols, such as linear probing (LP) prior to FT, can improve out-of-distribution generalization. However, the design space of such adaptation protocol

Travis C. Cuvelier, Takashi Tanaka, Robert W. Heath

In this work we consider discrete-time multiple-input multiple-output (MIMO) linear-quadratic-Gaussian (LQG) control where the feedback consists of variable length binary codewords. To simplify the decoder architecture, we enforce a strict prefix constraint on the codewords. We develop a data compression architecture that provably achieves a near minimum tim

Xiaoxiao Li, Minjia Shi, Shukai Wang

A code $C$ is called $\mathbb{Z}_p\mathbb{Z}_{p^2}$-linear if it is the Gray image of a $\mathbb{Z}_p\mathbb{Z}_{p^2}$-additive code. For any prime number $p$ larger than $3$, the bounds of the rank of $\mathbb{Z}_p\mathbb{Z}_{p^2}$-linear codes are given. For each value of the rank and the pairs of rank and the dimension of the kernel of $\mathbb{Z}_p\mathb

Alin R. Paraschiv, Alina C. Donea, Philip G. Judge

We present observations of recurrent active region coronal jets and derive their thermal and non-thermal properties, by studying the physical properties of the plasma simultaneously at the base footpoint, and along the outflow of jets. The sample of analyzed solar jets were observed by SDO-AIA in Extreme Ultraviolet and by RHESSI in the X-Ray domain. The mai

Pavel Jiroušek, Keigo Shimada, Alexander Vikman, Masahide Yamaguchi

We analyse the dynamical properties of disformally transformed theories of gravity. We show that disformal transformation typically introduces novel degrees of freedom, equivalent to the mimetic dark matter, which possesses a Weyl-invariant formulation. We demonstrate that this phenomenon occurs in a wider variety of disformal transformations than previously

Shuvangkar Chandra Das, Tuyen Vu

This paper presents a real-time cyber-physical (CPS) testbed for power systems with different real attack scenarios on the synchrophasors-phasor measurement units (PMU). The testbed focuses on real-time cyber-security emulation with components including a digital real-time simulator, virtual machines (VM), a communication network emulator, and a package mani

Navdeep Rana, Gopal Dixit

High-harmonic spectroscopy has become an essential ingredient in probing various ultrafast electronic processes in solids with sub-cycle temporal resolution. Despite its immense importance, sensitivity of high-harmonic spectroscopy to phonon dynamics in solids is not well known. This work addresses this critical question and demonstrates the potential of hig

Xuqiang Qin, Justin Sawon

Via wall-crossing, we study the birational geometry of Beauville-Mukai systems on K3 surfaces with Picard rank one. We show that there is a class of walls which are always present in the movable cones of Beauville-Mukai systems. We give a complete description of the birational geometry of rank two Beauville-Mukai systems when the genus of the surface is smal

Rui Guo, Tianyao Huang, Maokun Li, Haiyang Zhang

Electromagnetic (EM) imaging is widely applied in sensing for security, biomedicine, geophysics, and various industries. It is an ill-posed inverse problem whose solution is usually computationally expensive. Machine learning (ML) techniques and especially deep learning (DL) show potential in fast and accurate imaging. However, the high performance of purely

Philipp P. Vieweg, Janet D. Scheel, Rodion Stepanov, Jörg Schumacher

Inverse cascades of kinetic energy and thermal variance in the subset of vertically homogeneous modes in spectral space are found to cause a slow aggregation to a pair of convective supergranules that eventually fill the whole horizontally extended, three-dimensional, turbulent Rayleigh-B\'{e}nard convection layer when a heat flux is prescribed at the top an

Weijian Li, Wei Zhu, E. Ray Dorsey, Jiebo Luo

Medication for neurological diseases such as the Parkinson's disease usually happens remotely away from hospitals. Such out-of-lab environments pose challenges in collecting timely and accurate health status data. Individual differences in behavioral signals collected from wearable sensors also lead to difficulties in adopting current general machine learnin

Chang Liu, Colm-cille P. Caulfield, Dennice F. Gayme

We employ a recently introduced structured input-output analysis (SIOA) approach to analyze streamwise and spanwise wavelengths of flow structures in stably stratified plane Couette flow. In the low-Reynolds number ($Re$) low-bulk Richardson number ($Ri_b$) spatially intermittent regime, we demonstrate that SIOA predicts high amplification associated with wa

Atanu Koley, Nirupam Roy, Emmanuel Momjian, Anuj P. Sarma

Measurement of magnetic fields in dense molecular clouds is essential for understanding the fragmentation process prior to star formation. Radio interferometric observations of CCS 22.3 GHz emission, from the starless core TMC-1C, have been carried out with the Karl G. Jansky Very Large Array to search for Zeeman splitting of the line in order to constrain t

Xuqiang Qin, Justin Sawon

We study wall-crossing for the Beauville-Mukai system of rank three on a general genus two K3 surface. We show that such a system is related to the Hilbert scheme of ten points on the surface by a sequence of flops, whose exceptional loci can be described as Brill-Noether loci. We also obtain Brill-Noether type results for sheaves in the Beauville-Mukai syst

Ryan Cumings-Menon

Constructing a differentially private (DP) estimator requires deriving the maximum influence of an observation, which can be difficult in the absence of exogenous bounds on the input data or the estimator, especially in high dimensional settings. This paper shows that standard notions of statistical depth, i.e., halfspace depth and regression depth, are part

LHAASO Collaboration, F. Aharonian, Q. An, Axikegu

The Large High Altitude Air Shower Observatory (LHAASO) has three sub-arrays, KM2A, WCDA and WFCTA. The flux variations of cosmic ray air showers were studied by analyzing the KM2A data during the thunderstorm on 10 June 2021. The number of shower events that meet the trigger conditions increases significantly in atmospheric electric fields, with maximum fra

Limei Wang, Haoran Liu, Yi Liu, Jerry Kurtin

We consider representation learning for proteins with 3D structures. We build 3D graphs based on protein structures and develop graph networks to learn their representations. Depending on the levels of details that we wish to capture, protein representations can be computed at different levels, \emph{e.g.}, the amino acid, backbone, or all-atom levels. Impor

Yiqiao Li, Jianlong Zhou, Sunny Verma, Fang Chen

Graph neural networks (GNNs) have demonstrated a significant boost in prediction performance on graph data. At the same time, the predictions made by these models are often hard to interpret. In that regard, many efforts have been made to explain the prediction mechanisms of these models from perspectives such as GNNExplainer, XGNN and PGExplainer. Although

Jonathan Ho, Tim Salimans

Classifier guidance is a recently introduced method to trade off mode coverage and sample fidelity in conditional diffusion models post training, in the same spirit as low temperature sampling or truncation in other types of generative models. Classifier guidance combines the score estimate of a diffusion model with the gradient of an image classifier and th

Gonzalo J. Olmo, Emanuele Orazi, Gianfranco Pradisi

We revisit the gauge symmetry related to integrable projective transformations in metric-affine formalism, identifying the gauge field of the Weyl (conformal) symmetry as a dynamical component of the affine connection. In particular, we show how to include the local scaling symmetry as a gauge symmetry of a large class of geometric gravity theories, introduc

Robert Goldblatt, Ian Hodkinson

We develop a method for showing that various modal logics that are valid in their countably generated canonical Kripke frames must also be valid in their uncountably generated ones. This is applied to many systems, including the logics of finite width, and a broader class of multimodal logics of `finite achronal width' that are introduced here.

Motoaki Hirayama, Michael Thobias Schmid, Terumasa Tadano, Takahiro Misawa

We propose silver-based oxides with layered perovskite structure as candidates of exhibiting intriguing feature of strongly correlated electrons. The compounds show unique covalence between Ag d and O p orbitals with the strong electron correlation of their antibonding orbital similar to the copper oxide high-temperature superconductors, but stronger covalen

Marcos R. Fernandes

In this study, I present a theoretical social learning model to investigate how confirmation bias affects opinions when agents exchange information over a social network. Hence, besides exchanging opinions with friends, agents observe a public sequence of potentially ambiguous signals and interpret it according to a rule that includes confirmation bias. Firs

Keegan Boyle, Wenzhao Chen

We show that any strongly negative amphichiral knot with a trivial Alexander polynomial is equivariantly topologically slice.

Yu Nakayama

In two-dimensional string theory, a probe D0-brane does not see the black hole singularity due to a cancellation between its metric coupling and the dilaton coupling. A similar mechanism may work in the Schwarzschild black hole in large $D$ dimensions by considering a suitable wrapped membrane. From the asymptotic observer, the wrapped membrane looks disappe

Joaquin Grefa, Jorge Noronha, Jacquelyn Noronha-Hostler, Israel Portillo

By using the AdS/CFT correspondence, we construct an Einstein-Maxwell-Dilaton model to map the thermodynamics of strongly interacting matter. The holographic model, constrained to reproduce the lattice QCD equation of state at zero baryon chemical potential, predicts a critical end point and a first order phase transition line. We also obtain the equation of

Steven N. Karp, Hugh Thomas

The $q$-Whittaker function $W_λ(\mathbf{x};q)$ associated to a partition $λ$ is a $q$-analogue of the Schur function $s_λ(\mathbf{x})$, and is defined as the $t=0$ specialization of the Macdonald polynomial $P_λ(\mathbf{x};q,t)$. We show combinatorially how to expand $W_λ(\mathbf{x};q)$ in terms of partial flags compatible with a nilpotent endomorphism over

Filipo Sharevski, Amy Devine, Emma Pieroni, Peter Jachim

In this paper we investigate what folk models of misinformation exist through semi-structured interviews with a sample of 235 social media users. Work on social media misinformation does not investigate how ordinary users - the target of misinformation - deal with it; rather, the focus is mostly on the anxiety, tensions, or divisions misinformation creates.

Takafumi Tsukui, Satoru Iguchi, Ikki Mitsuhashi, Kenichi Tadaki

Recent interferometers (e.g. ALMA and NOEMA) allow us to obtain the detailed brightness distribution of the astronomical sources in 3 dimension (R.A., Dec., frequency). However, the interpixel correlation of the noise due to the limited uv coverage makes it difficult to evaluate the statistical uncertainty of the measured quantities and the statistical signi

Stephen J. Cotton

This work develops and illustrates a new method of calculating "chemically accurate" electronic wavefunctions (and energies) via a truncated full configuration interaction (CI) procedure which arguably circumvents the large matrix diagonalization that is the core problem of full CI and is also central to modern selective CI approaches. This is accomplished s

S. Matsukiyo, R. Yamazaki, T. Morita, K. Tomita

A developing supercritical collisionless shock propagating in a homogeneously magnetized plasma of ambient gas origin having higher uniformity than the previous experiments is formed by using high-power laser experiment. The ambient plasma is not contaminated by the plasma produced in the early time after the laser shot. While the observed developing shock d

Jing Geng, Li'e Ma, Xiaoquan Li, Yijun Yan

As a major branch of Non-Photorealistic Rendering (NPR), image stylization mainly uses the computer algorithms to render a photo into an artistic painting. Recent work has shown that the extraction of style information such as stroke texture and color of the target style image is the key to image stylization. Given its stroke texture and color characteristic

Jun Zhang, Daqing Wan

We give a method to construct deep holes for elliptic curve codes. For long elliptic curve codes, we conjecture that our construction is complete in the sense that it gives all deep holes. Some evidence and heuristics on the completeness are provided via the connection with problems and results in finite geometry.

Patrick Rodler

This work proposes a taxonomy for diagnosis computation methods which allows their standardized assessment, classification and comparison. The aim is to (i) give researchers and practitioners an impression of the diverse landscape of available diagnostic techniques, (ii) allow them to easily retrieve the main features as well as pros and cons of the approach

A F M Anhar Uddin Bhuiyan, Zixuan Feng, Hsien-Lien Huang, Lingyu Meng

Epitaxial growth of \k{appa}-phase Ga2O3 thin films are investigated on c-plane sapphire, GaN- and AlNon-sapphire, and (100) oriented yttria stabilized zirconia (YSZ) substrates via metalorganic chemical vapor deposition (MOCVD). The structural and surface morphological properties are investigated by comprehensive material characterization. Phase pure \k{app

Wenpin Tang, David D. Yao

We develop a continuous-time control approach to optimal trading in a Proof-of-Stake (PoS) blockchain, formulated as a consumption-investment problem that aims to strike the optimal balance between a participant's (or agent's) utility from holding/trading stakes and utility from consumption. We present solutions via dynamic programming and the Hamilton-Jacob

Cy Chan, Anu Kuncheria, Jane Macfarlane

The rapid introduction of mobile navigation aides that use real-time road network information to suggest alternate routes to drivers is making it more difficult for researchers and government transportation agencies to understand and predict the dynamics of congested transportation systems. Computer simulation is a key capability for these organizations to a

Jiahui Zhang, Shitao Tang, Kejie Qiu, Rui Huang

Visual relocalization has been a widely discussed problem in 3D vision: given a pre-constructed 3D visual map, the 6 DoF (Degrees-of-Freedom) pose of a query image is estimated. Relocalization in large-scale indoor environments enables attractive applications such as augmented reality and robot navigation. However, appearance changes fast in such environment