August 2022 arXiv papers — page 100

Zhang XueGuang

In the Letter, a new candidate for central tidal disruption event (TDE) is reported in SDSS J014124+010306 (=SDSS J0141) with broad Mg~{\sc ii} line at redshift $z=1.06$. Based on long-term photometric $ugriz$-band variabilities from SDSS Stripe82 Database and PHOTOOBJALL database, a central TDE is preferred with a 1.3${\rm M_\odot}$ main-sequence star tidal

Sonya Ravindranath Waddell, John M. Abowd, Camille Busette, Mark Hugo Lopez

This article is an edited transcript of the session of the same name at the 38th Annual NABE Economic Policy Conference: Policy Options for Sustainable and Inclusive Growth. The panelists are experts from government and private research organizations.

Aniello Panariello, Angelo Porrello, Simone Calderara, Rita Cucchiara

This work tackles Weakly Supervised Anomaly detection, in which a predictor is allowed to learn not only from normal examples but also from a few labeled anomalies made available during training. In particular, we deal with the localization of anomalous activities within the video stream: this is a very challenging scenario, as training examples come only wi

Jifeng Xia, Ningyu Tang, Qijun Zhi, Sihan Jiao

The distribution of ultraviolet (UV) radiation field provides critical constraints on the physical environments of molecular clouds. Within 1 kpc of our solar system and fostering protostars of different masses, the giant molecular clouds in the Gould Belt present an excellent opportunity to resolve the UV field structure in star forming regions. We performe

Anup Kumar Bera, Arun Singh Dev, Dileep Kumar

The artificial tailoring of magnetic anisotropy by manipulation of interfacial morphology and film structure are of fundamental interest from application point of view in spintronic and magnetic memory devices. This letter reports an approach of engineering and enhancing the strength of oblique incidence ion beam erosion (IBE) induced in-plane uniaxial magne

Panagiotis Koutsogiannakis, Davide Bigoni, Francesco Dal Corso

A highly deformable rod, modelled as the extensible elastica, is connected to a movable clamp at one end and to a pin sliding along a frictionless curved profile at the other. Bifurcation analysis shows that axial compliance provides a stabilizing effect in compression, but unstabilizing in tension. Moreover, with varying the constraint's curvature at the or

Menno A. Veerman, Bart J. H. van Stratum, Chiel C. van Heerwaarden

We present simulations of cumulus convection over land with shortwave radiation computed by a Monte Carlo ray tracer coupled to the flow solver. Ray tracing delivers very realistic in-cloud heating rates and global horizontal irradiance fields. The necessary performance of the ray tracer has been enabled by the raw power of GPU computing and from techniques

Hang Li, Walber H. Brito, Eduardo B. Guedes, Alla Chikina

Developing reliable methods for modulating the electronic structure of the two-dimensional electron gas (2DEG) in SrTiO3 is crucial for utilizing its full potential and inducing novel properties. Here, we show that relatively simple surface preparation reconstructs the 2DEG of SrTiO3 (STO) surface, leading to a Lifshitz-like transition. Combining experimenta

Javier Rivera-Dean, Philipp Stammer, Andrew S. Maxwell, Theocharis Lamprou

Light-matter entanglement plays a fundamental role in many applications of quantum information science. Thus, finding processes where it can be observed is an important task. Here, we address this matter by theoretically investigating the entanglement between light and electrons generated in above-threshold ionization (ATI) process. The study is based on the

Dasong Li, Yi Zhang, Ka Chun Cheung, Xiaogang Wang

In various learning-based image restoration tasks, such as image denoising and image super-resolution, the degradation representations were widely used to model the degradation process and handle complicated degradation patterns. However, they are less explored in learning-based image deblurring as blur kernel estimation cannot perform well in real-world cha

Brittany Terese Fasy, Amit Patel

The combinatorial interpretation of the persistence diagram as a M\"obius inversion was recently shown to be functorial. We employ this discovery to recast the Persistent Homology Transform of a geometric complex as a representation of a cellulation on $\mathbb{S}^n$ to the category of combinatorial persistence diagrams. Detailed examples are provided. We ho

Dmitrii Karp, Yi Zhang

We find two series expansions for Legendre's second incomplete elliptic integral $E(\lambda, k)$ in terms of recursively computed elementary functions. Both expansions converge at every point of the unit square in the $(\lambda, k)$ plane. Partial sums of the proposed expansions form a sequence of approximations to $E(\lambda,k)$ which are asymptotic when $\

Zhenyu Bu, Kai-Ni Wang, Guang-Quan Zhou

Renal cancer is one of the most prevalent cancers worldwide. Clinical signs of kidney cancer include hematuria and low back discomfort, which are quite distressing to the patient. Some surgery-based renal cancer treatments like laparoscopic partial nephrectomy relys on the 3D kidney parsing on computed tomography angiography (CTA) images. Many automatic segm

Shanwlee Sow Mondal, James A. Klimchuk, Aveek Sarkar

Recent high-resolution imaging and spectroscopic observations have generated renewed interest in spicules' role in explaining the hot corona. Some studies suggest that some spicules, often classified as type II, may provide significant mass and energy to the corona. Here we use numerical simulations to investigate whether such spicules can produce the observ

Christophe Andrieu, Anthony Lee, Sam Power, Andi Q. Wang

We develop a theory of weak Poincar\'e inequalities to characterize convergence rates of ergodic Markov chains. Motivated by the application of Markov chains in the context of algorithms, we develop a relevant set of tools which enable the practical study of convergence rates in the setting of Markov chain Monte Carlo methods, but also well beyond.

Yaman Güçlü, Said Hadjout, Martin Campos Pinto

We present a framework for the structure-preserving approximation of partial differential equations on mapped multipatch domains, extending the classical theory of finite element exterior calculus (FEEC) to discrete de Rham sequences which are broken, i.e., fully discontinuous across the patch interfaces. Following the Conforming/Nonconforming Galerkin (CONG

Jelena Radović, Nebojša Mudrinski

We obtain a characterization of the binary commutator on completely simple semigroups, using their Rees matrix representation. Consequently, we prove that a regular semigroup is nilpotent (solvable) if and only if it is simple, and all its $\mathcal{H}$-classes are nilpotent (solvable) groups.

Dragana Bajovic

This paper studies probabilistic rates of convergence for consensus+innovations type of algorithms in random, generic networks. For each node, we find a lower and also a family of upper bounds on the large deviations rate function, thus enabling the computation of the exponential convergence rates for the events of interest on the iterates. Relevant applicat

Valentin V. Gorokhovik

We introduce an extended tangent cone of high order to a set and study its properties. Then we use this local approximation for deriving high-order necessary conditions for local minimizers of constrained optimization problems.

Claudio Cazorla

Due to critical environmental issues there is a pressing need to switch from current refrigeration methods based on compression of greenhouse gases to novel solid-state cooling technologies. Solid-state cooling capitalizes on the thermal response of materials to external fields named "caloric effect". The barocaloric (BC) effect driven by hydrostatic pressur

Zezhi Shao, Zhao Zhang, Fei Wang, Wei Wei

Multivariate Time Series (MTS) forecasting plays a vital role in a wide range of applications. Recently, Spatial-Temporal Graph Neural Networks (STGNNs) have become increasingly popular MTS forecasting methods due to their state-of-the-art performance. However, recent works are becoming more sophisticated with limited performance improvements. This phenomeno

Alexander Rind, Djordje Slijepčević, Matthias Zeppelzauer, Fabian Unglaube

Three-dimensional clinical gait analysis is essential for selecting optimal treatment interventions for patients with cerebral palsy (CP), but generates a large amount of time series data. For the automated analysis of these data, machine learning approaches yield promising results. However, due to their black-box nature, such approaches are often mistrusted

Shubhendu Jena, Franck Multon, Adnane Boukhayma

We revisit NPBG, the popular approach to novel view synthesis that introduced the ubiquitous point feature neural rendering paradigm. We are interested in particular in data-efficient learning with fast view synthesis. We achieve this through a view-dependent mesh-based denser point descriptor rasterization, in addition to a foreground/background scene rende

Paul Trust, Ahmed Zahran, Rosane Minghim

The need for timely data analysis for economic decisions has prompted most economists and policy makers to search for non-traditional supplementary sources of data. In that context, text data is being explored to enrich traditional data sources because it is easy to collect and highly abundant. Our work focuses on studying the potential of textual data, in p

Victor Garcia-Lopez, Niccolo Giaconi, Lorenzo Poggini, Amelie Juhin

The deposition of a monolayer by direct self-assembly from solution of an active spin-crossover (SCO) complex via chemisorption has been achieved starting from the perchlorate salt of Co(II) bis(4-(4-carboxyphenyl)-2,2:6,2-terpyridine). MALDI-TOF MS, Raman spectroscopy and X-ray photoelectron spectroscopy (XPS) confirm the presence of an intact monolayer of

Alexander Bruns, Chia-Yu Hsu, Sergiy Stryzhenko, Enno Giese

Nonclassical photon sources of high brightness are key components of quantum communication technologies. We here demonstrate the generation of narrowband, nonclassical photon pairs by employing spontaneous four-wave mixing in an optically-dense ensemble of cold atoms within a hollow-core fiber. The brightness of our source approaches the limit of achievable

Alexander Chervov, Andrei Zinovyev

The cell cycle is one of the most fundamental biological processes important for understanding normal physiology and various pathologies such as cancer. Single cell RNA sequencing technologies give an opportunity to analyse the cell cycle transcriptome dynamics in an unprecedented range of conditions (cell types and perturbations), with thousands of publicly

Ijaz Gul, Changyue Liu, Yuan Xi, Zhicheng Du

Objectives The review is dedicated to evaluate the current monkeypox virus (MPXV) detection methods, discuss their pros and cons, and provide recommended solutions to the problems. Methods The literature for this review is identified through searches in PubMed, Web of Science, Google Scholar, ResearchGate, and Science Direct advanced search for articles publ

Xuxiang Jiang, Yinhao Xiao, Jun Wang, Wei Zhang

Vulnerability identification is crucial for cyber security in the software-related industry. Early identification methods require significant manual efforts in crafting features or annotating vulnerable code. Although the recent pre-trained models alleviate this issue, they overlook the multiple rich structural information contained in the code itself. In th

Julia Sauter

This is a generalization of some results of Ma-Sauter from module categories over artin algebras to more general functor categories (and partly to exact categories). In particular, we generalize the definition of a faithfully balanced module to a faithfully balanced subcategory and find the generalizations of dualities and characterizations from Ma-Sauter.

Ali Araabi, Christof Monz, Vlad Niculae

Neural Machine Translation (NMT) is an open vocabulary problem. As a result, dealing with the words not occurring during training (a.k.a. out-of-vocabulary (OOV) words) have long been a fundamental challenge for NMT systems. The predominant method to tackle this problem is Byte Pair Encoding (BPE) which splits words, including OOV words, into sub-word segmen

Marvin Edelmann, Malek M. Sedigheh, Yi Hua, Erwin C. Vargas

In this work, we investigate an approach to scale up the output pulse energy in an all polarization-maintaining 17 MHz Yb-doped fiber oscillator via implementation of 25 um core-diameter large-mode-area fibers. The artificial saturable absorber in form of a Kerr-type self-stabilized fiber-interferometer enables highly stable mode-locked steady-states in the

K. Mahesh Krishna

We recently formulated important Modular Bourgain-Tzafriri Restricted Invertibility Conjectures and Modular Johnson-Lindenstrauss Flattening Conjecture in the Appendix of \textit{[arXiv: 2207.12799.v1]}. For the sake of wide accessibility we give a self-contained treatment of them.

R. J. Morton, R. Sharma, E. Tajfirouze, H. Miriyala

The solar atmosphere is known to be replete with magneto-hydrodynamic wave modes, and there has been significant investment in understanding how these waves propagate through the Sun's atmopshere and deposit their energy into the plasma. The waves' journey is made interesting by the vertical variation in plasma quantities that define the solar atmosphere. In

Hui Guo, Tao Wang, Taishan Yi

This paper is concerned with the qualitative properties of the positive ground state solutions to the nonlocal Choquard type equation on a ball $B_R$. First, we prove the radial symmetry of the positive ground state solutions by using Talenti's inequality. Next we develop Newton's Theorem and then resort to the contraction mapping principle to establish the

Yingzi Fan, Longfei Han, Yue Zhang, Lechao Cheng

Both visual and auditory information are valuable to determine the salient regions in videos. Deep convolution neural networks (CNN) showcase strong capacity in coping with the audio-visual saliency prediction task. Due to various factors such as shooting scenes and weather, there often exists moderate distribution discrepancy between source training data an

Fabian Ritz, Thomy Phan, Andreas Sedlmeier, Philipp Altmann

The development of Machine Learning (ML) models is more than just a special case of software development (SD): ML models acquire properties and fulfill requirements even without direct human interaction in a seemingly uncontrollable manner. Nonetheless, the underlying processes can be described in a formal way. We define a comprehensive SD process model for

Carolina Cuesta-Lazaro, Takahiro Nishimichi, Yosuke Kobayashi, Cheng-Zong Ruan

In this series of papers, we present a simulation-based model for the non-linear clustering of galaxies based on separate modelling of clustering in real space and velocity statistics. In the first paper, we present an emulator for the real-space correlation function of galaxies, whereas the emulator of the real-to-redshift space mapping based on velocity st

Zhijing Wu, Hua Xu, Jingliang Fang, Kai Gao

Continual Machine Reading Comprehension aims to incrementally learn from a continuous data stream across time without access the previous seen data, which is crucial for the development of real-world MRC systems. However, it is a great challenge to learn a new domain incrementally without catastrophically forgetting previous knowledge. In this paper, MA-MRC,

Zhipeng Luo, Changqing Zhou, Liang Pan, Gongjie Zhang

With the prevalence of LiDAR sensors in autonomous driving, 3D object tracking has received increasing attention. In a point cloud sequence, 3D object tracking aims to predict the location and orientation of an object in consecutive frames given an object template. Motivated by the success of transformers, we propose Point Tracking TRansformer (PTTR), which

Pengfei Ni, Rang Liu, Ming Li, Qian Liu

Hybrid analog and digital beamforming has emerged as a key enabling technology for millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) communication systems since it can balance the trade-off between system performance and hardware efficiency. Owing to the strong ability of central control, cooperative networks show great potential to enha

Hsuan-Wei Lee, Colin Cleveland, Attila Szolnoki

Motion is a typical reaction among animals and humans trying to reach better conditions in a changing world. This aspect has been studied intensively in social dilemmas where competing players' individual and collective interests are in conflict. Starting from the traditional public goods game model, where players are locally fixed and unconditional cooperat

Shoujin Wang, Xiuzhen Zhang, Yan Wang, Huan Liu

Recommender systems (RSs) aim to help users to effectively retrieve items of their interests from a large catalogue. For a quite long period of time, researchers and practitioners have been focusing on developing accurate RSs. Recent years have witnessed an increasing number of threats to RSs, coming from attacks, system and user generated noise, system bias

Bram Vanherle, Tim Vervoort, Nick Michiels, Philippe Bekaert

Capturing an event from multiple camera angles can give a viewer the most complete and interesting picture of that event. To be suitable for broadcasting, a human director needs to decide what to show at each point in time. This can become cumbersome with an increasing number of camera angles. The introduction of omnidirectional or wide-angle cameras has all

Tzu-Yun Chien, Chih-Ya Shen

With the increasing application value of machine learning, the intellectual property (IP) rights of deep neural networks (DNN) are getting more and more attention. With our analysis, most of the existing DNN watermarking methods can resist fine-tuning and pruning attack, but distillation attack. To address these problem, we propose a new DNN watermarking fra

Randhir Singh

Transverse Spherocity is an event structure variable which provide an effective way to disentangle the data into hard and soft components of the processes corresponding to events with small and large numbers of multi-parton interactions (MPI), respectively. Recent experimental results in small systems from the LHC suggest the importacnce of transverse sphero

Marangon Francesco, Baumgartner David, Planchette Carole

Scalable technologies for the production of bio-compatible complex microfibers with controllable size and composition at competitively high throughput are urgently needed in order to meet the growing demand for such microstructures in pharmaceutical or biomedical applications. Here, we introduce a new in-air microfluidic strategy with throughput of > 1400 ml

Pengfei Ni, Ming Li, Rang Liu, Qian Liu

Cell-free networks are regarded as a promising technology to meet higher rate requirements for beyond fifth-generation (5G) communications. Most works on cell-free networks focus on either fully centralized beamforming to maximally enhance system performance, or fully distributed beamforming to avoid extensive channel state information (CSI) exchange among a

Eriola Hoxhaj, Jean Michel Menjanahary, Josef Schicho

The task of recognizing an algebraic surface from a single apparent contour can be reduced to the recovering of a homogeneous equation in four variables from its discriminant. In this paper, we use the fact that Darboux cyclides have a singularity along the absolute conic in order to recognize them up to Euclidean similarity transformations.

Emil Blixt Hansen, Helge Langseth, Nadeem Iftikhar, Simon Bøgh

Within the field of prognostics and health management (PHM), health indicators (HI) can be used to aid the production and, e.g. schedule maintenance and avoid failures. However, HI is often engineered to a specific process and typically requires large amounts of historical data for set-up. This is especially a challenge for SMEs, which often lack sufficient

Matthew Fayers, Lucia Morotti

For any finite group $G$ and any prime $p$ one can ask which ordinary irreducible representations remain irreducible in characteristic $p$, or more generally, which representations remain homogeneous in characteristic $p$. In this paper we address this question for $p=3$ when $G$ is a proper double cover of the symmetric or alternating group. We obtain a cla

Weiwei Jiang, Kangning Yang, Maximiliane Windl, Francesco Chiossi

A growing number of wearable devices is becoming increasingly non-invasive, readily available, and versatile for measuring different physiological signals. This renders them ideal for inferring the emotional states of their users. Despite the success of wearable devices in recent emotion studies, there are still several challenges to be addressed. In this po

Yasamin Kowsari

User identification has been a major field of research in privacy and security topics. Users might utilize multiple Online Social Networks (OSNs) to access a variety of text, videos, and links, and connect to their friends. Identifying user profiles corresponding to multiple virtual activities of users across social networks is significant for the developmen

M. Küß, F. Porrati, A. Hörner, M. Weiler

The interaction between surface acoustic waves (SAWs) and spin waves (SWs) in a piezoelectric-magnetic thin film heterostructure yields potential for the realization of novel microwave devices and applications in magnonics. In the present work, we characterize magnetoacoustic waves in three adjacent magnetic micro-stripes made from CoFe+Ga, CoFe, and CoFe+Pt

Jana C. Massing, Ashkaan Fahimipour, Carina Bunse, Jarone Pinhassi

Progress in molecular methods has enabled the monitoring of bacterial populations in time. Nevertheless, understanding community dynamics and its links with ecosystem functioning remains challenging due to the tremendous diversity of microorganisms. Conceptual frameworks that make sense of time-series of taxonomically-rich bacterial communities, regarding th

C. M. R. Rocha, H. Linnartz, A. J. C. Varandas

SiC$_2$ is a fascinating molecule due to its unusual bonding and astrophysical importance. In this work, we report the first global potential energy surface (PES) for ground-state SiC$_2$ using the combined-hyperbolic-inverse-power-representation (CHIPR) method and accurate ab initio energies. The calibration grid data is obtained via a general dual-level pr

Amirhossein Akbar Tabatabai, Rosalie Iemhoff, Raheleh Jalali

In this paper, a proof-theoretic method to prove uniform Lyndon interpolation for non-normal modal and conditional logics is introduced and applied to show that the logics $\mathsf{E}$, $\mathsf{M}$, $\mathsf{EN}$, $\mathsf{MN}$, $\mathsf{MC}$, $\mathsf{K}$, and their conditional versions, $\mathsf{CE}$, $\mathsf{CM}$, $\mathsf{CEN}$, $\mathsf{CMN}$, $\maths

Pengyu Wang, Chaoqun Wang, Jiankun Wang, Max Q. -H. Meng

This paper introduces a quadrotor's autonomous take-off and landing system on a moving platform. The designed system addresses three challenging problems: fast pose estimation, restricted external localization, and effective obstacle avoidance. Specifically, first, we design a landing recognition and positioning system based on the AruCo marker to help the q

Fanhao Kong, Wenhao Zhao

We prove a frequency-independent bound on trigonometric functions of a class of singular Gaussian random fields, which arise naturally from weak universality problems for singular stochastic PDEs. This enables us to reduce the regularity assumption on the nonlinearity of the microscopic models in KPZ and dynamical $\Phi^4_3$ in [HX19] and [FG19] to that requ

Ge Huang, Tao Luo, Philip Dalladay-Simpson, Liu-Cheng Chen

Clathrate hydride \emph{Fm}\={3}\emph{m}-LaH$_{10}$ has been proven as the most extraordinary superconductor with the critical temperature $T_c$ above 250 K upon compression of hundreds of GPa in recent years. A general hope is to reduce the stabilization pressure and maintain the high $T_c$ value of the specific phase in LaH$_{10}$. However, strong structur

Shoko Niwa, Miki Tanaka, Hitoshi Kiya

SNS providers are known to carry out the recompression and resizing of uploaded videos/images, but most conventional methods for detecting tampered videos/images are not robust enough against such operations. In addition, videos are temporally operated such as the insertion of new frames and the permutation of frames, of which operations are difficult to be

Yong Yang, Jing-Kun Zhao, Miho N. Ishigaki, Masashi Chiba

Context. Several dynamically cold streams have been associated with certain globular clusters (GCs) based on orbital energies and angular momenta. Some of these streams are surprisingly far apart from their progenitors and one such pair is Triangulum and NGC 5824. Triangulum can be considered as a piece of NGC 5824 leading tail since the cluster's future orb

Xin Fu

Let $(X, L)$ be a polarized Calabi Yau variety (or canonical polarized variety) with crepant singularity. Suppose $\omega_{KE} \in c_1(L)$ (or $\omega_{KE} \in c_1(K_X)$) is the unique Ricci flat current (or Kahler Einstein current with negative scalar curvature) with local bounded potential constructed in [18], we show that the local tangent at any point $p

S. W. Hsiao, P. Y. Chu

Malicious software (malware) causes much harm to our devices and life. We are eager to understand the malware behavior and the threat it made. Most of the record files of malware are variable length and text-based files with time stamps, such as event log data and dynamic analysis profiles. Using the time stamps, we can sort such data into sequence-based dat

Xin Jin, Wu Zhou, Xinghui Zhou, Shuai Cui

Aesthetic assessment of images can be categorized into two main forms: numerical assessment and language assessment. Aesthetics caption of photographs is the only task of aesthetic language assessment that has been addressed. In this paper, we propose a new task of aesthetic language assessment: aesthetic visual question and answering (AVQA) of images. If we

Kiminori Hattori, Kodai Ishikawa, Yuma Kaneko

The one-dimensional Rice-Mele lattice consisting of two-site unit cells enables topological charge pumping at low enough temperatures. We show here that energy pumping is feasible in this system. We analyze energy polarization using the second-quantization formalism and connect it to intercell energy current by the relevant continuity equation. Following thi

Sharan Mourya, Amit Kumar Dutta

Maximum likelihood (ML) detection is an optimal signal detection scheme, which is often difficult to implement due to its high computational complexity, especially in a multiple-input multiple-output (MIMO) scenario. In a system with $N_t$ transmit antennas employing $M$-ary modulation, the ML-MIMO detector requires $M^{N_t}$ cost function (CF) evaluations f

Chung-Lin Shan

In this article, as an extension of our study on the angular distribution of the recoil flux of WIMP-scattered target nuclei, we demonstrate a possibility of determining the mass of incident halo WIMPs by using or combining "ridge-crater" structures of the angular recoil-energy spectra with different target nuclei observed in directional direct Dark Matter d

Federico Bianchi, Stefano Speziali, Andrea Marini, Massimiliano Proietti

In this work, we describe in detail how Deep Learning and Computer Vision can help to detect fault events of the AirTender system, an aftermarket motorcycle damping system component. One of the most effective ways to monitor the AirTender functioning is to look for oil stains on its surface. Starting from real-time images, AirTender is first detected in the

Liu-Cheng Chen, Tao Luo, Philip Dalladay-Simpson, Ge Huang

Inspired by the high critical temperature in yttrium superhydride and the low stabilized pressure in superconducting cerium superhydride, we carry out four independent runs to synthesize yttrium-cerium alloy hydrides. The phases examined by the Raman scattering and x-ray diffraction measurements. The superconductivity is detected with the zero-resistance sta

Yu Zheng, Chen Gao, Jingtao Ding, Lingling Yi

Recommender systems are prone to be misled by biases in the data. Models trained with biased data fail to capture the real interests of users, thus it is critical to alleviate the impact of bias to achieve unbiased recommendation. In this work, we focus on an essential bias in micro-video recommendation, duration bias. Specifically, existing micro-video reco

Angelo A. Casulli, Leonardo Robol

The use of fractional differential equations is a key tool in modeling non-local phenomena. Often, an efficient scheme for solving a linear system involving the discretization of a fractional operator is evaluating the matrix function $x = \mathcal A^{-\alpha} c$, where $\mathcal A$ is a discretization of the classical Laplacian, and $\alpha$ a fractional ex

Pawel Pfeffer

A tunneling transistor without heterojunction as a theoretical design, or more precisely controlled electron current transmission by barrier potential, is under consideration. The electrons from the conduction band of the source tunnel through the forbidden gap $E_g$ of the channel to the conduction band of the drain. The tunneling current $J$ calculations m

Yuecong Xu, Jianfei Yang, Haozhi Cao, Min Wu

To enable video models to be applied seamlessly across video tasks in different environments, various Video Unsupervised Domain Adaptation (VUDA) methods have been proposed to improve the robustness and transferability of video models. Despite improvements made in model robustness, these VUDA methods require access to both source data and source model parame

Marvin Geiselhart, Ahmed Elkelesh, Jannis Clausius, Fei Liang

Finding optimal message quantization is a key requirement for low complexity belief propagation (BP) decoding. To this end, we propose a floating-point surrogate model that imitates quantization effects as additions of uniform noise, whose amplitudes are trainable variables. We verify that the surrogate model closely matches the behavior of a fixed-point imp

Yichang Shou, Yan Wang, Lili Miao, Shizhen Chen

Cascaded operations play an important role in traditional electronic computing systems for the realization of advanced strategies. Here, we introduce the idea of cascaded operations into all-optical spatial analog computing. The single function of the firstorder operation is difficult to meet the requirements of practical applications in image recognition. T

Sania Gul, Muhammad Salman Khan, Syed Waqar Shah

Reverberations are unavoidable in enclosures, resulting in reduced intelligibility for hearing impaired and non native listeners and even for the normal hearing listeners in noisy circumstances. It also degrades the performance of machine listening applications. In this paper, we propose a novel approach of binaural dereverberation of a single speech source,

Ardra A, Mohan Mallick, Sarath Sasi

We obtain shape derivative formulae for the first eigenvalue of the Robin $p$-Laplace operator. This result is used to study the variation of the first eigenvalue with respect to perturbations of the domain. In particular, we prove that for large values of the boundary parameter, the first eigenvalue is monotonic with respect to domain inclusion for smooth d

Ben Bakker, Jacob Tsimerman

We prove a functional transcendence theorem for the integrals of algebraic forms in families of algebraic varieties. This allows us to prove a geometric version of Andr\'e's generalization of the Grothendieck period conjecture, which we state using the formalism of Nori motives. More precisely, we prove a version of the Ax--Schanuel conjecture for the compar

Yuki Sano, Masaya Norimoto, Naoki Ishikawa

In this paper, we propose a novel method of formulating an NP-hard wireless channel assignment problem as a higher-order unconstrained binary optimization (HUBO), where the Grover adaptive search (GAS) is used to provide a quadratic speedup for solving the problem. The conventional method relies on a one-hot encoding of the channel indices, resulting in a qu

Georgios Karakasidis, Tamás Grósz, Mikko Kurimo

It is common knowledge that the quantity and quality of the training data play a significant role in the creation of a good machine learning model. In this paper, we take it one step further and demonstrate that the way the training examples are arranged is also of crucial importance. Curriculum Learning is built on the observation that organized and structu

Satoshi Nawata, Runkai Tao, Daisuke Yokoyama

These lecture notes provide a comprehensive introduction to 2d conformal field theory, covering foundational topics such as free fields, minimal models, Zamolodchikov's $c$-theorem, Wess-Zumino-Witten models, modular invariant partition functions, and the connections to entanglement entropy. The material presented is based on lectures at the Southeast Univer

Satoshi Nawata, Runkai Tao, Daisuke Yokoyama

These are lecture notes on string theory at Fudan University.

Anouar Moustaj, Malte Röntgen, Christian V. Morfonios, Peter Schmelcher

The Fibonacci chain, i.e., a tight-binding model where couplings and/or on-site potentials can take only two different values distributed according to the Fibonacci word, is a classical example of a one-dimensional quasicrystal. With its many intriguing properties, such as a fractal eigenvalue spectrum, the Fibonacci chain offers a rich platform to investiga

J. Ebad-Allah, S. Rojewski, Y. L. Zhu, Z. Q. Mao

Polarization-dependent reflectivity measurements were carried out over a broad frequency range on single-crystalline ZrGeSe and ZrGeS compounds, which are closely related to the prototype nodal-line semimetal ZrSiS. These measurements revealed the strongly anisotropic character of both ZrGeSe and ZrGeS, with a reduced plasma frequency for the out-of-plane di

Yong Yang, Jing-Kun Zhao, Xiang-Xiang Xue, Xian-Hao Ye

We report the discovery of a cold stream near the southern Galactic pole (dubbed as SGP-S) detected in $Gaia$ Early Data Release 3. The stream is at a heliocentric distance of $\sim$ 9.5 kpc and spans nearly 58$^\circ$ by 0.6$^\circ$ on sky. The colour-magnitude diagram of SGP-S indicates an old and metal-poor (age $\sim$ 12 Gyr, [M/H] $\sim$ -2.0 dex) stell

Mai Yamashita, Yoichi Itoh, Yumiko Oasa

Zero-age main-sequence (ZAMS) stars are considered to have enormous starspots and show strong chromospheric emission lines because of their strong surface magnetic field. We discuss the dynamo activities of ZAMS stars with respect to their periodic light variation caused by a starspot and with respect to the strength of the chromospheric emission lines. The

Yuanyuan Chen, Zichen Chen, Pengcheng Wu, Han Yu

Large-scale neural networks possess considerable expressive power. They are well-suited for complex learning tasks in industrial applications. However, large-scale models pose significant challenges for training under the current Federated Learning (FL) paradigm. Existing approaches for efficient FL training often leverage model parameter dropout. However, m

Xiaohui Liu, Yuzi Liu, Petra Laketa, Stanislav Nagy

The scatter halfspace depth (sHD) is an extension of the location halfspace (also called Tukey) depth that is applicable in the nonparametric analysis of scatter. Using sHD, it is possible to define minimax optimal robust scatter estimators for multivariate data. The problem of exact computation of sHD for data of dimension $d \geq 2$ has, however, not been

Zhekun He, Jun Hu, Huang Lin

We define a unified trace form $\tau$ on the cyclotomic Hecke algebras $\mathscr{H}_{n,K}$ of type $A$, which generalize both Malle-Mathas' trace form on the non-degenerate version (with Hecke parameter $\xi\neq 1$) and Brundan-Kleshchev's trace form on the degenerate version. We use seminormal basis theory to construct a pair of dual bases for $\mathscr{H}_

Xi Lu, Hongwei Lin

Ray tracing algorithm is a category of rendering algorithms that calculate the color of pixels by simulating the physical movements of a huge amount of rays and calculating their energies, which can be implemented in parallel. Meanwhile, the superposition and entanglement property make quantum computing a natural fit for parallel tasks.Here comes an interest

Weiming Sun, Zimao Zhang

Fourier series multiscale method, a concise and efficient analytical approach for multiscale computation, will be developed out of this series of papers. In the third paper, the analytical analysis of multiscale phenomena inherent in the 2r-th order linear differential equations with constant coefficients and subjected to general boundary conditions is addre

Kenneth J. Falconer, Jiaxin Hu, Junda Zhang

This paper seeks conditions that ensure that the attractor of a graph directed iterated function system (GD-IFS) cannot be realised as the attractor of a standard iterated function system (IFS). For a strongly connected directed graph, it is known that, if all directed circuits go through a vertex, then for any GD-IFS of similarities on $\mathbb{R}$ based on

Zheng Cao, Yi Zhen, Gang Fan, Sheng Gao

The emergence of metaverse brings tremendous evolution to Non-Fungible Tokens (NFTs), which could certify the ownership the unique digital asset in the cyber world. The NFT market has garnered unprecedented attention from investors and created billions of dollars in transaction volume. Meanwhile, securing NFT is still a challenging issue. Recently, numerous

Yaoming Chu, Jianming Cai

Recently, we find a physical limit on energy consumption of quantum metrology, and demonstrate that it essentially arises from the erasure of quantum Fisher information (QFI) which determines the best achievable measurement precision. Here, we provide more details in order to further elaborate the essence of this principle.

Fabrice Guillemin

In this paper, we analyze the number of departures from an initially empty $M/M/\infty$ system in a finite time interval. We observe the system during an exponentially distributed period of time starting from the time origin. We then consider the absorbed Markov chain describing the number of arrivals and departures in the system until the observer leaves th

Pouya Honaryar

Let $M$ be a compact closed manifold of variable negative curvature. Fix an element $\operatorname{id} \neq \gamma$ in the fundamental group $\Gamma$ of $M$, and denote the set of elements in $\Gamma$ that are conjugate to $\gamma$ by $\operatorname{Conj}_\gamma$. For two points $x, y$ in the universal cover of $M$, we obtain asymptotics for the number of $\

Ling-Na Wu, Jens Nettersheim, Julian Feß, Alexander Schnell

Phase transitions correspond to the singular behavior of physical systems in response to continuous control parameters like temperature or external fields. Near continuous phase transitions, associated with the divergence of a correlation length, universal power-law scaling behavior with critical exponents independent of microscopic system details is found.

Zhengang Li, Mengshu Sun, Alec Lu, Haoyu Ma

Vision transformers (ViTs) are emerging with significantly improved accuracy in computer vision tasks. However, their complex architecture and enormous computation/storage demand impose urgent needs for new hardware accelerator design methodology. This work proposes an FPGA-aware automatic ViT acceleration framework based on the proposed mixed-scheme quantiz

Lucas N. Ferreira, Lili Mou, Jim Whitehead, Levi H. S. Lelis

This paper presents a new approach for controlling emotion in symbolic music generation with Monte Carlo Tree Search. We use Monte Carlo Tree Search as a decoding mechanism to steer the probability distribution learned by a language model towards a given emotion. At every step of the decoding process, we use Predictor Upper Confidence for Trees (PUCT) to sea