November 2022 arXiv papers — page 119

Claude Semay, Maud Balcaen

The envelope theory is a reliable and easy to implement method to solve time independent Schr\"odinger-like equations (eigenvalues and eigenvectors). It is particularly useful to solve many-body systems since the computational cost is independent from the number of particles. The purpose of this paper is twofold. First, we want to make known a method that is

Antonia van Betteray, Matthias Rottmann, Karsten Kahl

Current state-of-the-art deep neural networks for image classification are made up of 10 - 100 million learnable weights and are therefore inherently prone to overfitting. The complexity of the weight count can be seen as a function of the number of channels, the spatial extent of the input and the number of layers of the network. Due to the use of convoluti

Conghua Liu, Jin Wang

In the recent proposal [Phys. Rev. Lett. 129, 191101 (2022)], the black holes were viewed as topological thermodynamic defects by using the generalized off-shell free energy. In this paper, we follow such proposal to study the local and global topological natures of the Gauss-Bonnet black holes in AdS space. The local topological natures are reflected by the

Enes Altinisik, Hassan Sajjad, Husrev Taha Sencar, Safa Messaoud

Adversarial training is widely acknowledged as the most effective defense against adversarial attacks. However, it is also well established that achieving both robustness and generalization in adversarially trained models involves a trade-off. The goal of this work is to provide an in depth comparison of different approaches for adversarial training in langu

Bikshapathi Gouda, Italo Atzeni, Antti Tölli

We consider multi-group multicast precoding designs for cell-free massive multiple-input multiple-output (MIMO) systems. To optimize the transmit and receive beamforming strategies, we focus on minimizing the sum of the maximum mean squared errors (MSEs) over the multicast groups, which is then approximated with the sum MSE to simplify the computation and si

Yujin Jeong, Seongbeom Park, Suhong Moon, Jinkyu Kim

Artificial intelligence is currently powering diverse real-world applications. These applications have shown promising performance, but raise complicated ethical issues, i.e. how to embed ethics to make AI applications behave morally. One way toward moral AI systems is by imitating human prosocial behavior and encouraging some form of good behavior in system

Abishek Thangamuthu, Gunjan Kumar, Suresh Bishnoi, Ravinder Bhattoo

Recently, graph neural networks have been gaining a lot of attention to simulate dynamical systems due to their inductive nature leading to zero-shot generalizability. Similarly, physics-informed inductive biases in deep-learning frameworks have been shown to give superior performance in learning the dynamics of physical systems. There is a growing volume of

Henning Krause

For any ring we propose the construction of a cover which increases the finitistic dimension on one side and decreases the finitistic dimension to zero on the opposite side. This complements recent work of Cummings.

Ksenia Bestuzheva, Ambros Gleixner, Helena Völker

Certificates of polynomial nonnegativity can be used to obtain tight dual bounds for polynomial optimization problems. We consider Sums of Nonnegative Circuit (SONC) polynomials certificates, which are well suited for sparse problems since the computational cost depends only on the number of terms in the polynomials and does not depend on the degrees of the

Sudeepini Darapu, Subrata Ghosh, Abhishek Senapati, Chittaranjan Hens

Developing methods to analyse infection spread is an important step in the study of pandemic and containing them. The principal mode for geographical spreading of pandemics is the movement of population across regions. We are interested in identifying regions (cities, states, or countries) which are influential in aggressively spreading the disease to neighb

Luciano Baresi, Giovanni Quattrocchi

In recent years, Web services are becoming more and more intelligent (e.g., in understanding user preferences) thanks to the integration of components that rely on Machine Learning (ML). Before users can interact (inference phase) with an ML-based service (ML-Service), the underlying ML model must learn (training phase) from existing data, a process that req

Yaping Xu, Ze Zhou

Let $J$ be a simple closed curve in $\mathbb R^{k}$ $(k\geq2)$ that is differentiable with non-zero derivative at a point $A_0\in J$. For a tuple of positive reals $a_1,\cdots,a_n$ $(n\geq3)$, each of which is less than the sum of the others, we show that there exists a polygon $Q_n$ inscribed in $J$ with sides of lengths proportional to $(a_1,\cdots,a_n)$.

L. Temdie, V. Castel, C. Dubs, G. Pradhan

We report unidirectional transmission of micron-wide spin waves beams in a 55 nm thin YIG. We downscaled a chiral coupling technique implementing Ni80Fe20 nanowires arrays with different widths and lattice spacing to study the non-reciprocal transmission of exchange spin waves down to lambda = 80 nm. A full spin wave spectroscopy analysis of these high wavev

V. Arvind Rameshwar, Navin Kashyap

The paper considers coding schemes derived from Reed-Muller (RM) codes, for transmission over input-constrained memoryless channels. Our focus is on the $(d,\infty)$-runlength limited (RLL) constraint, which mandates that any pair of successive $1$s be separated by at least $d$ $0$s. In our study, we first consider $(d,\infty)$-RLL subcodes of RM codes, taki

Abinash Kumar Shaw, Arnab Chakraborty, Mohd Kamran, Raghunath Ghara

The redshifted 21-cm radiation from the atomic hydrogen (HI) provides an excellent direct probe to study the evolution of HI in IGM and thus reveal the nature of the first luminous objects, their evolution and role during Cosmic Dawn (CD) and Epoch of Reionization (EoR), and formation and evolution of the structures thereafter. Direct mapping of the HI densi

Krzysztof Bogdan, Markus Kunze

Motivated by the notion of isotropic $\alpha$-stable L\'evy processes confined, by reflections, to a bounded open Lipschitz set $D\subset \mathbb{R}^d$, we study some related analytical objects. Thus, we construct the corresponding transition semigroup, identify its generator and prove exponential speed of convergence of the semigroup to a unique stationary

Daria Uccheddu

Inspired by a didactic experience in an academic environment, and following the idea given by M. Villa in \cite{Villa}, we illustrate two different proofs of an important result in Euclidean geometry studied in the first two years of Italian secondary schools. Specifically, we propose the proof of Varignon's Theorem from both the classical synthetic and the

Lucas Pesenti, Adrian Vladu

We introduce a new algorithmic framework for discrepancy minimization based on regularization. We demonstrate how varying the regularizer allows us to re-interpret several breakthrough works in algorithmic discrepancy, ranging from Spencer's theorem [Spencer 1985, Bansal 2010] to Banaszczyk's bounds [Banaszczyk 1998, Bansal-Dadush-Garg 2016]. Using our techn

Saswato Sen, Christof Wetterich, Masatoshi Yamada

We compute scaling solutions of functional flow equations for quantum gravity in a general truncation with up to four derivatives of the metric. They connect the asymptotically free ultraviolet fixed point, which is accessible to perturbation theory, to the non-perturbative infrared region. The existence of such scaling solutions is necessary for a renormali

Heinz Hofbauer, Fernando Alonso-Fernandez, Josef Bigun, Andreas Uhl

In this study the authors will look at the detection and segmentation of the iris and its influence on the overall performance of the iris-biometric tool chain. The authors will examine whether the segmentation accuracy, based on conformance with a ground truth, can serve as a predictor for the overall performance of the iris-biometric tool chain. That is: I

Kosuke Namekata, Hiroyuki Maehara, Satoshi Honda, Yuta Notsu

Solar flares are often accompanied by filament/prominence eruptions, sometimes leading to coronal mass ejections (CMEs). By analogy, we expect that stellar flares are also associated with stellar CMEs whose properties are essential to know the impact on exoplanet habitability. Probable detections of stellar CMEs are still rare, but in this decade, there are

Piyush Sharda, Anish M. Amarsi, Kathryn Grasha, Mark R. Krumholz

Star formation models predict that the metal-poor initial mass function (IMF) can be substantially different from that observed in the metal-rich Milky Way. This changeover occurs because metal-poor gas clouds cool inefficiently due to their lower abundance of metals and dust. However, predictions for the metal-poor IMF to date rely on assuming Solar-scaled

Luciano Loris Viteritti, Riccardo Rende, Federico Becca

The Transformer architecture has become the state-of-art model for natural language processing tasks and, more recently, also for computer vision tasks, thus defining the Vision Transformer (ViT) architecture. The key feature is the ability to describe long-range correlations among the elements of the input sequences, through the so-called self-attention mec

Haoning Zhang, Junwei Bao, Haipeng Sun, Youzheng Wu

Dialogue state tracking (DST) aims to convert the dialogue history into dialogue states which consist of slot-value pairs. As condensed structural information memorizing all history information, the dialogue state in the last turn is typically adopted as the input for predicting the current state by DST models. However, these models tend to keep the predicte

Sarah A. M. Loos, Saeed Arabha, Ali Rajabpour, Ali Hassanali

We study the heat transfer between two nanoparticles held at different temperatures that interact through nonreciprocal forces, by combining molecular dynamics simulations with stochastic thermodynamics. Our simulations reveal that it is possible to construct nano refrigerators that generate a net heat transfer from a cold to a hot reservoir at the expense o

Jeff Strasdas, Benjamin Pestka, Milosz Rybak, Adam K. Budniak

Exfoliated magnetic 2D materials enable versatile tuning of magnetization, e.g., by gating or providing proximity-induced exchange interaction. However, their electronic band structure after exfoliation has not been probed, most likely due to their photochemical sensitivity. Here, we provide micron-scale angle-resolved photoelectron spectroscopy of the exfol

Patrik Hammersborg, Inga Strümke

Self-trained autonomous agents developed using machine learning are showing great promise in a variety of control settings, perhaps most remarkably in applications involving autonomous vehicles. The main challenge associated with self-learned agents in the form of deep neural networks, is their black-box nature: it is impossible for humans to interpret deep

Azade Farshad, Yousef Yeganeh, Helisa Dhamo, Federico Tombari

Graph representation of objects and their relations in a scene, known as a scene graph, provides a precise and discernible interface to manipulate a scene by modifying the nodes or the edges in the graph. Although existing works have shown promising results in modifying the placement and pose of objects, scene manipulation often leads to losing some visual c

Georg Wolschin

A nonlinear diffusion equation is proposed to account for thermalization in fermionic and bosonic systems through analytical solutions. For constant transport coefficients, exact time-dependent solutions are derived through nonlinear transformations, and the corresponding local equilibration times are deduced. Fermi-Dirac and Bose-Einstein distributions emer

Jafar Shamsi, María José Avedillo, Bernabé Linares-Barranco, Teresa Serrano-Gotarredona

Analog implementation of Oscillatory Neural Networks (ONNs) has the potential to implement fast and ultra-low-power computing capabilities. One of the drawbacks of analog implementation is component mismatches which cause desynchronization and instability in ONNs. Emerging devices like memristors and VO2 are particularly prone to variations. In this paper, w

Kamran Pentland, Massimiliano Tamborrino, T. J. Sullivan

Stochastic parareal (SParareal) is a probabilistic variant of the popular parallel-in-time algorithm known as parareal. Similarly to parareal, it combines fine- and coarse-grained solutions to an ordinary differential equation (ODE) using a predictor-corrector (PC) scheme. The key difference is that carefully chosen random perturbations are added to the PC t

Buse Sibel Korkmaz, Marta Zagórowska, Mehmet Mercangöz

We consider the problem of decision-making under uncertainty in an environment with safety constraints. Many business and industrial applications rely on real-time optimization to improve key performance indicators. In the case of unknown characteristics, real-time optimization becomes challenging, particularly because of the satisfaction of safety constrain

Patrick E. Farrell, Lawrence Mitchell, L. Ridgway Scott

In recent years a great deal of attention has been paid to discretizations of the incompressible Stokes equations that exactly preserve the incompressibility constraint. These are of substantial interest because these discretizations are pressure-robust, i.e. the error estimates for the velocity do not depend on the error in the pressure. Similar considerati

David Martínez-Gómez, Ramón Oliver, Elena Khomenko, Manuel Collados

In this paper we present a numerical study of the dynamics of partially ionized coronal rain blobs. We use a two-fluid model to perform a high-resolution 2D simulation that takes into account the collisional interaction between the charged and neutral particles contained in the plasma. We follow the evolution of a cold plasma condensation as it falls through

Floris Balm, Nicolas Chagnet, Sam Arend, Joost Aretz

High $T_c$ cuprate strange metals are noted for a DC-resistivity that scales linearly with $T$ from the onset of superconductivity to the crystal melting temperature, indicative of a Planckian dissipation life time $\tau_{\hbar}\simeq \hbar /(k_B T)$. At the same time, the optical conductivity ceases to be of Drude form at high temperatures, suggesting a cha

Zvika Brakerski

We propose to study equivalence relations between phenomena in high-energy physics and the existence of standard cryptographic primitives, and show the first example where such an equivalence holds. A small number of prior works showed that high-energy phenomena can be explained by cryptographic hardness. Examples include using the existence of one-way funct

Yang Liu, Jie Song, Wei Qin, Ye-Hong Chen

Spin squeezing is one of the most attractive methods for realizing high-precision metrology. In this paper, we propose a protocol for generating spin squeezing in an atomic ensemble via a fully quantum degenerate parametric amplifier. We discuss the properties of generating spin squeezing with and without driving the pump cavity. Numerical simulation results

Marta Alvir, Luka Grbčić, Ante Sikirica, Lado Kranjčević

In this paper, negatively inclined buoyant jets, which appear during the discharge of wastewater from processes such as desalination, are observed. To minimize harmful effects and assess environmental impact, a detailed numerical investigation is necessary. The selection of appropriate geometry and working conditions for minimizing such effects often require

Yang Zhou, Yuda Song, Hui Qian, Xin Du

Image restoration tasks have achieved tremendous performance improvements with the rapid advancement of deep neural networks. However, most prevalent deep learning models perform inference statically, ignoring that different images have varying restoration difficulties and lightly degraded images can be well restored by slimmer subnetworks. To this end, we p

Selomit Ramírez-Uribe

The first application of a quantum algorithm to Feynman loop integrals is reviewed. The connection between quantum computing and perturbative quantum field theory is feasible due to fact that the two on-shell states of a Feynman propagator are naturally encoded in a qubit. The particular problem to be addressed is the identification of the causal singular co

Fei Shen, Mengwan Wei, Junchi Ren

Object re-identification method is made up of backbone network, feature aggregation, and loss function. However, most backbone networks lack a special mechanism to handle rich scale variations and mine discriminative feature representations. In this paper, we firstly design a hierarchical similarity graph module (HSGM) to reduce the conflict of backbone and

Sebastian Ebert, Alice Shoshana Jakobovits, Katja Filippova

Realizing when a model is right for a wrong reason is not trivial and requires a significant effort by model developers. In some cases an input salience method, which highlights the most important parts of the input, may reveal problematic reasoning. But scrutinizing highlights over many data instances is tedious and often infeasible. Furthermore, analyzing

Smitha S., Sudheesh K. K., Sreedevi E. P.

In this work, we study the properties of cumulative residual entropy generating function. We then introduce dynamic cumulative residual entropy generating function (DCREGF). It is shown that the DCREGF determines the distribution uniquely. We study some characterization results using the relationship between DCREGF and hazard rate and mean residual life func

Hamza Amrani, Daniela Micucci, Paolo Napoletano

One of the main problems in applying deep learning techniques to recognize activities of daily living (ADLs) based on inertial sensors is the lack of appropriately large labelled datasets to train deep learning-based models. A large amount of data would be available due to the wide spread of mobile devices equipped with inertial sensors that can collect data

Reginald Christian Bernardo, Daniela Grandón, Jackson Levi Said, Víctor H. Cárdenas

We look at dark energy from a biology inspired viewpoint by means of the Approximate Bayesian Computation (ABC) and late time cosmological observations. We find that dynamical dark energy comes out on top, or in the ABC language naturally selected, over the standard $\Lambda$CDM cosmological scenario. We confirm this conclusion is robust to whether baryon ac

Jiakun Lei, Tao Meng, Kun Wang, Weijia Wang

This paper focuses on the issue of how to realize spacecraft attitude control with guaranteed performance while conspicuously reducing the actuator acting frequency simultaneously. The prescribed performance control (PPC) scheme is often employed for the control with guaranteed performance. However, conventional PPC controllers are designed from the perspect

Toshali Mitra, Sukrut Mondkar, Ayan Mukhopadhyay, Anton Rebhan

Hybrid fluid models, consisting of two sectors with more weakly and more strongly self-interacting degrees of freedom coupled consistently as in the semi-holographic framework, have been shown to exhibit an attractor surface for Bjorken flow. Retaining only the simple viscid fluid descriptions of both sectors, we find that, on the attractor surface, the hydr

Birk Berger, Denis Eremin, Moritz Oberberg, Dennis Engel

In magnetized capacitively coupled radio-frequency discharges operated at low pressure the influence of the magnetic flux density on discharge properties has been studied recently both by experimental investigations and in simulations. It was found that the Magnetic Asymmetry Effect allows for a control of the DC self-bias and the ion energy distribution by

Ding-Hui Xu, Shu-Jun Rong

The recent reported Glashow resonance (GR) event shows a promising prospect in the test of the Lorentz violation (LV) by the high-energy astrophysical neutrinos (HANs) around the resonant energy. However, since the production source and the energy spectra of HANs are uncertain at present, moderate LV effects may be concealed at the TeV energy-scale. In this

Asaf Ferber, Jie Han, Dingjia Mao

Given a family of graphs $G_1,\dots,G_{n}$ on the same vertex set $[n]$, a rainbow Hamilton cycle is a Hamilton cycle on $[n]$ such that each $G_c$ contributes exactly one edge. We prove that if $G_1,\dots,G_{n}$ are independent samples of $G(n,p)$ on the same vertex set $[n]$, then for each $\varepsilon>0$, whp, every collection of spanning subgraphs $H_c\s

Elie Cali, Alexander Hinsen, Benedikt Jahnel, Jean-Philippe Wary

The present paper features results on global survival and extinction of an infection in a multi-layer network of mobile agents. Expanding on a model first presented in [CHJW22], we consider an urban environment, represented by line-segments in the plane, in which agents move according to a random waypoint model based on a Poisson point process. Whenever two

Ryo Uchiumi

For a graph with edge ordering, a linear order on the edge set, we obtain a permutation of vertices by considering the edges as transpositions of endvertices. It is known from D\'enes' results that the permutation of a tree is a full cyclic for any edge ordering. As a corollary, D\'enes counted up the number of representations of a full cyclic permutation by

Fateme Abbasi, Marek Adamczyk, Miguel Bosch-Calvo, Jarosław Byrka

In the Submodular Facility Location problem (SFL) we are given a collection of $n$ clients and $m$ facilities in a metric space. A feasible solution consists of an assignment of each client to some facility. For each client, one has to pay the distance to the associated facility. Furthermore, for each facility $f$ to which we assign the subset of clients $S^

Bernard Deconinck, Sergey A. Dyachenko, Pavel M. Lushnikov, Anastassiya Semenova

We study the stability of Stokes waves on a free surface of an ideal fluid of infinite depth. For small steepness the modulational instability dominates the dynamics, but its growth rate is vastly surpassed for steeper waves by an instability due to disturbances localized at the wave crest, explaining why long propagating ocean swell consists of small-amplit

Francisco Lázaro, Balázs Matuz

We consider a set reconciliation setting in which two parties hold similar sets which they would like to reconcile In particular, we focus on set reconciliation based on invertible Bloom lookup tables (IBLTs), a probabilistic data structure inspired by Bloom filters but allowing for more complex operations. IBLT-based set reconciliation schemes have the adva

Smita G. Rao, Boburjon Mukhamedov, Gyula Nagy, Eric N. Tseng

As a single-phase alloy, CrFeCoNi is a face centered cubic (fcc) material related to the archetypical high-entropy Cantor alloy CrFeCoNiMn. For thin films, CrFeCoNi of approximately equimolar composition tends to assume an fcc structure when grown at room temperature by magnetron sputtering. However, the single-phase solid solution state is typically not ach

Zeqian Li, Keyu Qiu, Chenxu Jiao, Wen Zhu

This paper describes a French dialect recognition system that will appropriately distinguish between different regional French dialects. A corpus of five regions - Monaco, French-speaking, Belgium, French-speaking Switzerland, French-speaking Canada and France, which is targeted forconstruction by the Sketch Engine. The content of the corpus is related to th

Francesco Vitale, Daniel Repp, Thomas Siefke, Uwe Zeitner

Tailoring the emission of plasmonic nanowire-based lasers represents one of the major challenges in the field of nanoplasmonics, given the envisaged integration of such devices into on-chip all-optical circuits. In this study, we proposed a mode selection scheme based on distributed feedback, achieved via the external coupling of single zinc oxide nanowires

Abhishek Senapati, Adam Mertel, Weronika Schlechte-Welnicz, Justin M. Calabrese

Human mobility contributes to the fast spatio-temporal propagation of infectious diseases. During an outbreak, monitoring the infection situation on either side of an international border is very crucial as there is always a higher risk of disease importation associated with cross-border migration. Mechanistic models are effective tools to investigate the co

Simon Müller, Ravit Helled

Determining the composition of giant exoplanets is crucial for understanding their origin and evolution. However, the planetary bulk composition is not measured directly but must be deduced from a combination of mass-radius measurements, knowledge of the planetary age and evolution simulations. Accurate determinations of stellar ages, mass-radius, and atmosp

Mamutjan Ababekri, Ren-Tong Guo, Feng Wan, B. Qiao

Vortex $\gamma$ photons with intrinsic orbital angular momenta (OAM) possess a wealth of applications in various fields, e.g.-strong-laser physics, nuclear physics, particle physics and astrophysics-yet their generation remains unsettled. In this work, we investigate the generation of vortex $\gamma$ photons via nonlinear Compton scattering of ultrarelativis

Guanghui Huang

Under the null hypothesis, the marginal probability of the positive response is symmetric at any specified correlated coefficient, and the discordance probability is also symmetric to the positive response probability. The marginal distribution function of the discordant observation is monotonically decreasing with the increase of the discordance probability

Delio Mugnolo, Vyacheslav Pivovarchik

We propose a simple method for resolution of co-spectrality of Schr\"odinger operators on metric graphs. Our approach consists of attaching a lead to them and comparing the $S$-functions of the corresponding scattering problems on these (non-compact) graphs. We show that in several cases -- including general graphs on at most 6 vertices, general trees on at

Seryung Ahn, Jiyeon Kim, Bongjae Kim, Sooran Kim

Li-ion conductivity is one of the essential properties that determine the performance of cathode materials for Li-ion batteries. Here, using the density functional theory, we investigate the polaron stability and its effect on the Li-ion diffusion in layered LiCoO2 with different magnetic orderings. The localized Co4+ polaron appears in the magnetic configur

Daniël Veldman, Alexandra Borkowski, Enrique Zuazua

RBM-MPC is a computationally efficient variant of Model Predictive Control (MPC) in which the Random Batch Method (RBM) is used to speed up the finite-horizon optimal control problems at each iteration. In this paper, stability and convergence estimates are derived for RBMMPC of unconstrained linear systems. The obtained estimates are validated in a numerica

J. Ablinger, A. Behring, J. Blümlein, A. De Freitas

We calculate the gluonic massive operator matrix elements in the unpolarized and polarized cases, $A_{gg,Q}(x,\mu^2)$ and $\Delta A_{gg,Q}(x,\mu^2)$, at three-loop order for a single mass. These quantities contribute to the matching of the gluon distribution in the variable flavor number scheme. The polarized operator matrix element is calculated in the Lari

Asghar Ullah, M. Tahir Naseem, Özgür E. Müstecaplıoğlu

The precise measurement of low temperatures is significant for both the fundamental understanding of physical processes and technological applications. In this work, we present a method for low-temperature measurement that improves thermal range and sensitivity by generating quantum coherence in a thermometer probe. Typically, in temperature measurements, th

Sergey Kirgizov, José Luis Ramírez

We introduce the $k$-bonacci polyominoes, a new family of polyominoes associated with the binary words avoiding $k$ consecutive $1$'s, also called generalized $k$-bonacci words. The polyominoes are very entrancing objects, considered in combinatorics and computer science. The study of polyominoes generates a rich source of combinatorial ideas. In this paper

Alberto Sainz Dalda, Bart De Pontieu

The flare activity of the Sun has been studied for decades, using both space- and ground-based telescopes. In particular, the Interface Region Imaging Spectrograph (IRIS) provides unique diagnostics to investigate the thermodynamics of flares in the solar atmosphere. The Mg II h&k and Mg II UV triple lines provide key information about the thermodynamics of

Patrick Kopper, Anna Schwarz, Stephen M. Copplestone, Philip Ortwein

Particle-laden flows occur in a wide range of disciplines, from atmospheric flows to renewable energy to turbomachinery. They generally pose a challenging environment for the numerical prediction of particle-induced phenomena due to their often complex geometry and highly instationary flow field which covers a wide range of spatial and temporal scales. At th

Anguo Dong, Cuiyun Gao, Yan Jia, Qing Liao

Aspect-based sentiment analysis (ABSA) aims at extracting opinionated aspect terms in review texts and determining their sentiment polarities, which is widely studied in both academia and industry. As a fine-grained classification task, the annotation cost is extremely high. Domain adaptation is a popular solution to alleviate the data deficiency issue in ne

Satyendra Singh Rawat, Amit Kumar Mishra

Learning classifiers using skewed or imbalanced datasets can occasionally lead to classification issues; this is a serious issue. In some cases, one class contains the majority of examples while the other, which is frequently the more important class, is nevertheless represented by a smaller proportion of examples. Using this kind of data could make many car

Julian Frederik Schumann, Jens Kober, Arkady Zgonnikov

Autonomous vehicles currently suffer from a time-inefficient driving style caused by uncertainty about human behavior in traffic interactions. Accurate and reliable prediction models enabling more efficient trajectory planning could make autonomous vehicles more assertive in such interactions. However, the evaluation of such models is commonly oversimplistic

Andreas Strömbergsson, Anders Södergren

We prove a generalized version of Rogers' mean value formula in the space $X_n$ of unimodular lattices in $R^n$, which gives the mean value of a multiple sum over a lattice $L$ and its dual $L^*$. As an application, we prove that for $L$ random with respect to the SL$(n,R)$-invariant probability measure, in the limit of large dimension $n$, the volumes deter

Chunming Jiang, Yilei Zhang

Spiking neural networks (SNNs) are receiving increasing attention due to their low power consumption and strong bio-plausibility. Optimization of SNNs is a challenging task. Two main methods, artificial neural network (ANN)-to-SNN conversion and spike-based backpropagation (BP), both have their advantages and limitations. For ANN-to-SNN conversion, it requir

Viktor Schlegel, Erick Mendez-Guzman, Riza Batista-Navarro

Progress on many Natural Language Processing (NLP) tasks, such as text classification, is driven by objective, reproducible and scalable evaluation via publicly available benchmarks. However, these are not always representative of real-world scenarios where text classifiers are employed, such as sentiment analysis or misinformation detection. In this positio

Yuto Hosaka, David Andelman, Shigeyuki Komura

We discuss the lateral dynamics of two active force dipoles, which interact with each other via hydrodynamic interactions in a thin fluid layer that is active and chiral. The fluid layer is modeled as a two-dimensional (2D) compressible fluid with an odd viscosity, while the force dipole (representing an active protein or enzyme) induces a dipolar flow. Taki

Subhaditya Bhattacharya, Sanjoy Biswas, Kuntal Pal, Jose Wudka

We analyse the single top production in association with the Higgs at the Large Hadron Collider (LHC) using Standard Model (SM) effective operators upto dimension six. We show that the presence of effective operators can significantly alter the existing bound on the top-Higgs Yukawa coupling. We analyse events at the LHC with 35.9 and 137(140) fb$^{-1}$ inte

A. M. Romshin, A. A. Osypov, I. Yu. Popova, V. E. Zeeb

A production of heat by mitochondria is critical for maintaining body temperature, regulating metabolic rate and preventing oxidative damage to mitochondria and cells. Up to now mitochondrion heat production was characterized only by methods based on fluorescent probes which are sensitive to environmental variations (viscosity, pH, ionic strength, quenching

Siyao Li, Giuseppe Caire

Millimeter-wave (mmWave) communication is one of the key enablers for 5G systems as it provides larger system bandwidth and the possibility of packing numerous antennas in a small form factor for highly directional communication. In order to materialize the potentially very high beamforming gain, the transmitter and receiver beams need to be aligned. Practic

Amit Samaddar, S. Surendra Singh

We analyze the cosmological solutions of $f(T,B)$ gravity using dynamical system analysis where $T$ is the torsion scalar and $B$ be the boundary term scalar. In our work, we assume two specific cosmological models. For first model, we consider $ f(T,B)=f_{0}(B^{k}+T^{m})$, where $k$ and $m$ are constants. For second model, we consider $f(T,B)=f_{0}T B$. We

Abhishek Raghav, Ryo Maezono, Kenta Hongo, Sandro Sorella

Herein, we report accurate atomization energy calculations for 55 molecules in the Gaussian-2 (G2) set using lattice regularized diffusion Monte Carlo (LRDMC). We compare the Jastrow-Slater determinant ansatz with a more flexible JsAGPs (Jastrow correlated antisymmetrized geminal power with singlet correlation) ansatz. AGPs is built from pairing functions, w

Meng Chen, Li Lu, Jiadi Yu, Yingying Chen

Faced with the threat of identity leakage during voice data publishing, users are engaged in a privacy-utility dilemma when enjoying convenient voice services. Existing studies employ direct modification or text-based re-synthesis to de-identify users' voices, but resulting in inconsistent audibility in the presence of human participants. In this paper, we p

Kjeld Beeks, Tomas Sikorsky, Veronika Rosecker, Martin Pressler

We have grown $^{232}$Th:CaF$_2$ and $^{229}$Th:CaF$_2$ single crystals for investigations on the VUV laser-accessible first nuclear excited state of $^{229}$Th. To reach high doping concentrations despite the extreme scarcity (and radioactivity) of $^{229}$Th, we have scaled down the crystal volume by a factor 100 compared to established commercial or scien

Avinaba Mukherjee, Raka Dasgupta

We investigate the dynamics of a population-imbalanced two-species fermionic system trapped in an optical lattice. The paired fermions here can form bosonic molecules via Feshbach coupling in the presence of an external magnetic field. It is shown that the natural fluctuations of the condensate fraction are periodic beyond a threshold Feshbach detuning; and

Guanzhong Li, Lvzhou Li

The element distinctness problem is to determine whether a string $x=(x_1,\ldots,x_N)$ of $N$ elements contains two elements of the same value (a.k.a colliding pair), for which Ambainis proposed an optimal quantum algorithm. The idea behind Ambainis' algorithm is to first reduce the problem to the promised version in which $x$ is promised to contain at most

Shanshan Wang, Soumya Tripathy, Annamaria Mesaros

In Self-Supervised Learning (SSL), various pretext tasks are designed for learning feature representations through contrastive loss. However, previous studies have shown that this loss is less tolerant to semantically similar samples due to the inherent defect of instance discrimination objectives, which may harm the quality of learned feature embeddings use

Jian Gao, Yu Jiang, Zhe Liu, Xin Yang

Clone detection is widely exploited for software vulnerability search. The approaches based on source code analysis cannot be applied to binary clone detection because the same source code can produce significantly different binaries. In this paper, we present BinSeeker, a cross-platform binary seeker that integrates semantic learning and emulation. With the

Mert Kalfa, Sadik Yagiz Yetim, Arda Atalik, Mehmetcan Gok

Semantic signal processing and communications are poised to play a central part in developing the next generation of sensor devices and networks. A crucial component of a semantic system is the extraction of semantic signals from the raw input signals, which has become increasingly tractable with the recent advances in machine learning (ML) and artificial in

Or Kedar, Jake P. Solomon

Let $L\subset X$ be a not necessarily orientable relatively $Pin$ Lagrangian submanifold in a symplectic manifold $X$. We construct a family of cyclic unital curved $A_\infty$ structures on differential forms on $L$ with values in the local system of graded non-commutative rings given by the tensor algebra of the orientation local system of $L$. The family o

Giovanni Scilla, Bianca Stroffolini

We study partial H\"older regularity for nonlinear elliptic systems in divergence form with double-phase growth, modeling double-phase non-Newtonian fluids in the stationary case.

Apollonas S. Matsoukas-Roubeas, Federico Roccati, Julien Cornelius, Zhenyu Xu

The construction of exactly-solvable models has recently been advanced by considering integrable $T\bar{T}$ deformations and related Hamiltonian deformations in quantum mechanics. We introduce a broader class of non-Hermitian Hamiltonian deformations in a nonrelativistic setting, to account for the description of a large class of open quantum systems, which

A. Naghdi, F. J. Dominguez-Gutierrez, W. Y. Huo, K. Karimi

Chemical short-range order (CSRO) is believed to be a key contributor to the exceptional properties of multicomponent alloys. However, direct validation and confirmation of CSRO has been highly elusive in most compounds. Recent studies for equiatomic NiCoCr alloys have shown that thermal treatments (i.e., annealing/aging) may facilitate and manipulate CSRO.

Yuming Liu, Lleonard Rubio y Degrassi, Can Wen

We compare the first Hochschild cohomology groups of finite dimensional monomial algebras under gluing two idempotents. We also compare the fundamental groups and the Hochschild cohomology groups in other degrees. In particular, we will study the case of gluing a source and a sink, that is, when we obtain a stable equivalence.

Paul Duetting, Tomer Ezra, Michal Feldman, Thomas Kesselheim

We study a natural combinatorial single-principal multi-agent contract design problem, in which a principal motivates a team of agents to exert effort toward a given task. At the heart of our model is a reward function, which maps the agent efforts to an expected reward of the principal. We seek to design computationally efficient algorithms for finding opti

Lingyan Xue, Xinyu Zhang, Weidong Jiang, Kai Huo

Machine learning and deep learning classification models are data-driven, and the model and the data jointly determine their classification performance. It is biased to evaluate the model's performance only based on the classifier accuracy while ignoring the data separability. Sometimes, the model exhibits excellent accuracy, which might be attributed to its

Jun Chen, Wei Rao, Zilin Wang, Zhiyong Wu

FullSubNet has shown its promising performance on speech enhancement by utilizing both fullband and subband information. However, the relationship between fullband and subband in FullSubNet is achieved by simply concatenating the output of fullband model and subband units. It only supplements the subband units with a small quantity of global information and

Siyang Xiong

We study Nash implementation by stochastic mechanisms, and provide a surprisingly simple full characterization, which is in sharp contrast to the classical, albeit complicated, full characterization in Moore and Repullo (1990).

Fatima Ezzahra Airod, Mattia Merluzzi, Antonio Clemente, Emilio Calvanese Strinati

Wireless traffic is exploding, due to the myriad of new connections and the exchange of capillary data at the edge of the networks to operate real-time processing and decision making. The latter especially affects the uplink traffic, which will grow in 6G and beyond networks, calling for new optimization metrics that include energy, service delay, and electr

Zihan Li, Jonathan Scarlett

We consider optimizing a function network in the noise-free grey-box setting with RKHS function classes, where the exact intermediate results are observable. We assume that the structure of the network is known (but not the underlying functions comprising it), and we study three types of structures: (1) chain: a cascade of scalar-valued functions, (2) multi-