May 2022 arXiv papers — page 156

Arup Kumar Paul, Manas Ranjan Sahu, Kenji Watanabe, Takashi Taniguchi

The ground state of a graphene sheet at charge neutrality in a perpendicular magnetic field remains enigmatic, with various experiments supporting canted antiferromagnetic, bond ordered, and even charge density wave phases. A promising avenue to elucidating the nature of this state is to sandwich it between regions of different filling factors, and study spi

Guanghui Wang, Long Feng

High-dimensional changepoint inference that adapts to various change patterns has received much attention recently. We propose a simple, fast yet effective approach for adaptive changepoint testing. The key observation is that two statistics based on aggregating cumulative sum statistics over all dimensions and possible changepoints by taking their maximum a

Chi Zhang, Yujie Zhu, Xiangyu Hu

In the previous work, Zhang et al. proposed a multi-resolution smoothed particle hydrodynamics (SPH) method for fluid-structure interactions (FSI) with achieving an optimized computational efficiency meanwhile maintaining good numerical robustness and accuracy. In the present paper, this multi-resolution SPH framework where different spatial-temporal discret

Xinjia Li, Boyu Chen, Wenlian Lu

The performance of federated learning in neural networks is generally influenced by the heterogeneity of the data distribution. For a well-performing global model, taking a weighted average of the local models, as done by most existing federated learning algorithms, may not guarantee consistency with local models in the space of neural network maps. In this

Felix Stahlberg, Shankar Kumar

The softmax layer in neural machine translation is designed to model the distribution over mutually exclusive tokens. Machine translation, however, is intrinsically uncertain: the same source sentence can have multiple semantically equivalent translations. Therefore, we propose to replace the softmax activation with a multi-label classification layer that ca

G. Sainath, A. Nagesha

It is well known that the twinning is an important mode of plastic deformation in nanocrystalline materials. As a result, it is expected that the twin can interact with different grain boundaries (GBs) during the plastic deformation. Understanding these twin-GB interactions is crucial for our understanding of mechanical behavior of materials. In this work, t

Adrien Banse, Zheming Wang, Raphaël M. Jungers

We present a framework based on multiple Lyapunov functions to find probabilistic data-driven guarantees on the stability of unknown constrained switching linear systems (CSLS), which are switching linear systems whose switching signal is constrained by an automaton. The stability of a CSLS is characterized by its constrained joint spectral radius (CJSR). In

Jie Du, Xujian Yang, Kecheng Jin, Xuanzheng Qi

Nosie is an important cause of low quality Optical coherence tomography (OCT) image. The neural network model based on Convolutional neural networks(CNNs) has demonstrated its excellent performance in image denoising. However, OCT image denoising still faces great challenges because many previous neural network algorithms required a large number of labeled d

Maxim V. Barkov, Praveen Sharma, Konstantinos N. Gourgouliatos, Maxim Lyutikov

Many explosive astrophysical events, like magnetars' bursts and flares, are magnetically driven. We consider dynamics of such magnetic explosions - relativistic expansion of highly magnetized and highly magnetically over-pressurized clouds. The corresponding dynamics is qualitatively different from fluid explosions due to the topological constraint of th

Melissa Sanabria, Frédéric Precioso, Pierre-Alexandre Mattei, Thomas Menguy

Video content is present in an ever-increasing number of fields, both scientific and commercial. Sports, particularly soccer, is one of the industries that has invested the most in the field of video analytics, due to the massive popularity of the game and the emergence of new markets. Previous state-of-the-art methods on soccer matches video summarization r

Wei Jiang, Hans D. Schotten

To meet the demand of supreme data rates in terabits-per-second, the next-generation mobile system needs to exploit the abundant spectrum in the millimeter-wave and terahertz bands. However, high-frequency transmission heavily relies on large-scale antenna arrays to reap high beamforming gain, used to compensate for severe propagation loss. It raises a probl

Xinyuan Lu, Shengyuan Huang, Li Niu, Wenyan Cong

Video harmonization aims to adjust the foreground of a composite video to make it compatible with the background. So far, video harmonization has only received limited attention and there is no public dataset for video harmonization. In this work, we construct a new video harmonization dataset HYouTube by adjusting the foreground of real videos to create syn

Lei Wang, Jiangxu Huang, Kun He

The lattice Boltzmann method is adopted to solve the liquid-vapor phase change problems in this article. By modifying the collision term for the temperature evolution equation, a new thermal lattice Boltzmann model is constructed. As compared with previous studies, the most striking feature of the present approach is that it could avoid the calculations of b

Soheyla Feyzbakhsh

Consider the moduli space $M_C(r; K_C)$ of stable rank r vector bundles on a curve $C$ with canonical determinant, and let $h$ be the maximum number of linearly independent global sections of these bundles. If $C$ embeds in a K3 surface $X$ as a generator of $Pic(X)$ and the genus $g$ of $C$ is sufficiently high, we show the Brill-Noether locus $BN_C \subset

Rohit Tiwari, Juhi Oudichhya, Ajay Kumar Rai

The mass spectra of light-heavy tetraquarks $cq\bar{c}\bar{q}$ (q= u, d) are computed in a non-relativistic diquark model with one-gluon exchange plus confining potential. In the diquark model, a $cq\bar{c}\bar{q}$ state is regarded to be made of a light-heavy diquark (qc) and an antidiquark $\bar{q}\bar{c}$ in triplet and antitriplet colour configuration re

Mayuri Nakagawa, Makoto Okano, Shinichi Watanabe

We report on the measurement of terahertz electric-field vector waveforms by using a system that contains no mechanical moving parts. It is known that two phase-locked femtosecond lasers with different repetition rates can be used to perform time-domain spectroscopy without using a mechanical delay stage. Furthermore, an electro-optic modulator can be used t

Zherui Fan, Subhajit Goswami

The metric associated with the Liouville quantum gravity (LQG) surface has been constructed through a series of recent works and several properties of its associated geodesics have been studied. In the current article we confirm the folklore conjecture that the Euclidean Hausdorff dimension of LQG geodesics is stirctly greater than 1 for all values of the so

P. V. Bilimogga, K. A. Oman, M. A. W. Verheijen, J. M. van der Hulst

We investigate the effect of observational constraints such as signal-to-noise, resolution and column density level on the HI morphological asymmetry ($\mathrm{A}_\mathrm{mod}$) and the effect of noise on the HI global profile ($\mathrm{A}_\mathrm{flux}$) asymmetry indices. Using mock galaxies from the EAGLE simulations we find an optimal combination of the

Taoufik Meklachi

The need of mathematically formulate relations between composite materials' properties and its resonance response is growing. This is due the fast technological advancement in micro-material manufacturing, present in chips for instance. In this paper two theorems are presented, providing formulas of scattering resonance of double-layered and multilayered

A. Rodin, B. A. Olsen, M. Choi, A. Tan

Using a non-perturbative classical model, we numerically investigate the dynamics of mobile particles interacting with an infinite chain of harmonic oscillators, an abstraction of ionic conduction through solid-state materials. We show that coupling between the mobile particles and a single mass of the chain is sufficient to induce dissipation of the mobile

Aditya Ahuja

Classical and contemporary distributed consensus protocols, may they be for binary agreement, state machine replication, or blockchain consensus, require all protocol participants in a peer-to-peer system to agree on exactly the same information as part of the consensus payload. Although this model of consensus is extensively studied, and is useful for most

Han Yuecai, Zhang Dingwen

In this paper, we investigate the parameter estimation problem for reflected OU processes. Both the estimates based on continuously observed processes and discretely observed processes are considered. The explicit formulas for the estimators are derived using the least squares method. Under some regular conditions, we obtain the consistency and establish the

Yi Zheng, Mu Yang, Zheng-Hao Liu, Jin-Shi Xu

The task of wavefront sensing is to measure the phase of the optical field. Here, we demonstrate that the widely used Shack-Hartmann wavefront sensor detects the weak value of transverse momentum, usually achieved by the method of quantum weak measurement. We extend its input states to partially coherent states and compare it with the weak measurement wavefr

Jayeeta Chattopadhyay, Sriram Ramaswamy, Chandan Dasgupta, Prabal K. Maiti

In equilibrium hard-rod fluids, and in effective hard-rod descriptions of anisotropic soft-particle systems, the transition from the isotropic (I) phase to the nematic phase (N) is observed above the rod aspect ratio L/D = 3.70 as predicted by Onsager. We examine the fate of this criterion in a molecular dynamics study of a system of soft repulsive spherocyl

Yoshua Bengio, Prateek Gupta, Dylan Radovic, Maarten Scholl

Insufficient Social Cost of Carbon (SCC) estimation methods and short-term decision-making horizons have hindered the ability of carbon emitters to properly correct for the negative externalities of climate change, as well as the capacity of nations to balance economic and climate policy. To overcome these limitations, we introduce Retrospective Social Cost

Rui Shu, Tianpei Xia, Huy Tu, Laurie Williams

Background: Most of the existing machine learning models for security tasks, such as spam detection, malware detection, or network intrusion detection, are built on supervised machine learning algorithms. In such a paradigm, models need a large amount of labeled data to learn the useful relationships between selected features and the target class. However, s

Debopriyo Banerjee, Harsh Maheshwari, Lucky Dhakad1, Arnab Bhattacharya1

Fashion recommendation has witnessed a phenomenal growth of research, particularly in the domains of shop-the-look, contextaware outfit creation, personalizing outfit creation etc. Majority of the work in this area focuses on better understanding of the notion of complimentary relationship between lifestyle items. Quite recently, some works have realised tha

Yonatan Carlos Carranza Alarcón, Sébastien Destercke

In this paper, we consider the problem of making distributionally robust, skeptical inferences for the multi-label problem, or more generally for Boolean vectors. By distributionally robust, we mean that we consider a set of possible probability distributions, and by skeptical we understand that we consider as valid only those inferences that are true for ev

Runzhou Tao, Yunong Shi, Jianan Yao, Xupeng Li

This paper presents Giallar, a fully-automated verification toolkit for quantum compilers. Giallar requires no manual specifications, invariants, or proofs, and can automatically verify that a compiler pass preserves the semantics of quantum circuits. To deal with unbounded loops in quantum compilers, Giallar abstracts three loop templates, whose loop invari

Bowen Liang, Pidong Wang, Yuan Cao

Label smoothing is ubiquitously applied in Neural Machine Translation (NMT) training. While label smoothing offers a desired regularization effect during model training, in this paper we demonstrate that it nevertheless introduces length biases in the beam search decoding procedure. Our analysis shows that label smoothing implicitly applies a length penalty

Takehiro Kashiyama, Yanbo Pang, Yoshihide Sekimoto, Takahiro Yabe

People flow data are utilized in diverse fields such as urban and commercial planning and disaster management. However, people flow data collected from mobile phones, such as using global positioning system and call detail records data, are difficult to obtain because of privacy issues. Even if the data were obtained, they would be difficult to handle. This

Kun Zhou, Beichen Zhang, Wayne Xin Zhao, Ji-Rong Wen

Recently, contrastive learning has been shown to be effective in improving pre-trained language models (PLM) to derive high-quality sentence representations. It aims to pull close positive examples to enhance the alignment while push apart irrelevant negatives for the uniformity of the whole representation space. However, previous works mostly adopt in-batch

Vilas Patwardhan

A simplex in n dimensions is defined by the usual (n+1) linear inequality constraints in n dimensions. Here we consider simplexes which are bounded sets. The harmonic center has been defined earlier for polytopes in general. A relationship between the rows of A is derived here, which must be satisfied for the simplex to be bounded. Using this condition, an i

Wei Sun, Xian-Hui Ge

We consider a four-dimensional charged hyperbolic black hole as working matter to establish a black hole holographic heat engine, and use the rectangular cycle to obtain the heat engine efficiency. We find that when the increasing of entropy is zero, the heat engine efficiency of the hyperbolic black hole becomes the well-known Carnot efficiency. We also fin

Masafumi Fukuma, Nobuyuki Matsumoto, Yusuke Namekawa

The numerical sign problem is a major obstacle to the quantitative understanding of many important physical systems with first-principles calculations. Typical examples for such systems include finite-density QCD, strongly-correlated electron systems and frustrated spin systems, as well as the real-time dynamics of quantum systems. In this talk, we argue tha

Ka Hung Chan, Shengwang Du, Xian Chen

We theorize the surface step characterization by reflected incoherent-light differential interference microscopy with consideration of the optical diffraction effect. With the integration of localization analysis, we develop a quantitative differential interference optical system, by which we demonstrate that the axial resolution of measuring surface height

Ryotaro Harada

In 1995, Thakur invented and studied positive characteristic analogues of hypergeometric functions. In this paper, we interpret the special values of those functions as periods of a pre-$t$-motive. As a consequence, we show their transcendence and linear independence results by using Chang's refined version of the Anderson-Brownawell-Papanikolas criterio

Sahil Sharma, Vijay Kumar Bhat, Sohan Lal

Chemical graph theory is commonly used to analyse and comprehend chemical structures and networks, as well as their features. The resolvability parameters for graph $G$= $(V,E)$ are a relatively new advanced field in which the complete structure is built so that each vertex (atom) or edge (bond) represents a distinct position. In this article, we study the r

Jack Lindsey, James B Aimone

In this work we develop a model of predictive learning on neuromorphic hardware. Our model uses the on-chip plasticity capabilities of the Loihi chip to remember observed sequences of events and use this memory to generate predictions of future events in real time. Given the locality constraints of on-chip plasticity rules, generating predictions without int

Zhaonan Wang, Yingpu Deng

The problem of representing a given positive integer as a sum of four squares of integers has been widely concerned for a long time, and for a given positive odd $n$ one can find a representation by doing arithmetic in a maximal order of quaternion algebra once a pair of (positive) integers $x,y$ with $x^2+y^2\equiv-1\mod n$ is given. In this paper, we intro

Siegfred Baluyot, Caroline L. Turnage-Butterbaugh

We study the family of Dirichlet $L$-functions of all even primitive characters of conductor at most $Q$, where $Q$ is a parameter tending to $\infty$. For an arbitrary positive integer $k$, we approximate the twisted $2k$th moment of this family by using Dirichlet polynomial approximations of $L^k(s,χ)$ of length $X$, with $Q<X<Q^2$. Assuming the Generalize

Chenchen Ding

Let $f (\cdot)$ be the absolute frequency of words and $r$ be the rank of words in decreasing order of frequency, then the following function can fit the rank-frequency relation \[ f (r;s,t) = \left(\frac{r_{\tt max}}{r}\right)^{1-s} \left(\frac{r_{\tt max}+t \cdot r_{\tt exp}}{r+t \cdot r_{\tt exp}}\right)^{1+(1+t)s} \] where $r_{\tt max}$ and $r_{\tt exp}$

Yaxin Li, Xiaorui Liu, Han Xu, Wentao Wang

Deep Neural Network (DNN) are vulnerable to adversarial attacks. As a countermeasure, adversarial training aims to achieve robustness based on the min-max optimization problem and it has shown to be one of the most effective defense strategies. However, in this work, we found that compared with natural training, adversarial training fails to learn better fea

Emmanuel Coffie

It is well documented from various empirical studies that the volatility process of an asset price dynamics is stochastic. This phenomenon called for a new approach to describing the random evolution of volatility through time with stochastic models. In this paper, we propose a mean-reverting theta-rho model for asset price dynamics where the volatility diff

Shoujie Tong, Qingxiu Dong, Damai Dai, Yifan song

Fine-tuning pretrained language models (PLMs) on downstream tasks has become common practice in natural language processing. However, most of the PLMs are vulnerable, e.g., they are brittle under adversarial attacks or imbalanced data, which hinders the application of the PLMs on some downstream tasks, especially in safe-critical scenarios. In this paper, we

Taichi Kato

I analyzed All-Sky Automated Survey for Supernovae (ASAS-SN) Sky Patrol data of ES Dra and classified it to be a Z Cam star with VY Scl-type fading episodes. An analysis of Transiting Exoplanet Survey Satellite (TESS) observations showed that this object shows shallow eclipses and that the orbital period is 0.17749895(17) d. Negative superhumps with a period

Thuan N. A. Trang, Thieu N. Vo, Khuong D. Nguyen

This work seeks to improve the generalization and robustness of existing neural networks for 3D point clouds by inducing group equivariance under general group transformations. The main challenge when designing equivariant models for point clouds is how to trade-off the performance of the model and the complexity. Existing equivariant models are either too c

Apurva Patil, Alfredo Duarte, Aislinn Smith, Takashi Tanaka

This paper addresses a continuous-time continuous-space chance-constrained stochastic optimal control (SOC) problem via a Hamilton-Jacobi-Bellman (HJB) partial differential equation (PDE). Through Lagrangian relaxation, we convert the chance-constrained (risk-constrained) SOC problem to a risk-minimizing SOC problem, the cost function of which possesses the

Dajun Du, Changda Zhang, Xue Li, Minrui Fei

Dynamic watermarking schemes can enhance the cyber attack detection capability of networked control systems (NCSs). This paper presents a linear event-triggered solution to conventional dynamic watermarking (CDW) schemes. Firstly, the limitations of CDW schemes for event-triggered state estimation based NCSs are investigated. Secondly, a new event-triggered

Sei Saito, Masaomi Tanaka, Ryo Sawada, Takashi J. Moriya

Explosion mechanism of core-collapse supernovae is not fully understood yet. In this work, we give constraints on the explosion timescale based on $^{56}$Ni synthesized by supernova explosions. First, we systematically analyze multi-band light curves of 82 stripped-envelope supernovae (SESNe) to obtain bolometric light curves, which is among the largest samp

Shuohang Wu, Zi Cai

Typically, it is assumed that a high-energy eigenstate of a generic interacting quantum many-body Hamiltonian is thermal and obeys the eigenstate thermalization hypothesis. In this work, we show that the paramagnetic phase of a quantum Hopfield neural network model is delocalized but nonergodic. The combination of permutational symmetry and frustration in th

Jinho Choi, Seng W. Loke, Jihong Park

Traditionally, studies on technical communication (TC) are based on stochastic modeling and manipulation. This is not sufficient for semantic communication (SC) where semantic elements are logically connected, rather than stochastically correlated. To fill this void, by leveraging a logical programming language called probabilistic logic (ProbLog), we propos

Angelica Chen, Vicky Zayats, Daniel D. Walker, Dirk Padfield

In modern interactive speech-based systems, speech is consumed and transcribed incrementally prior to having disfluencies removed. This post-processing step is crucial for producing clean transcripts and high performance on downstream tasks (e.g. machine translation). However, most current state-of-the-art NLP models such as the Transformer operate non-incre

Yujian Liu, Xinliang Frederick Zhang, David Wegsman, Nick Beauchamp

Ideology is at the core of political science research. Yet, there still does not exist general-purpose tools to characterize and predict ideology across different genres of text. To this end, we study Pretrained Language Models using novel ideology-driven pretraining objectives that rely on the comparison of articles on the same story written by media of dif

Bram Wasti, José Pablo Cambronero, Benoit Steiner, Hugh Leather

We present LoopStack, a domain specific compiler stack for tensor operations, composed of a frontend, LoopTool, and an efficient optimizing code generator, LoopNest. This stack enables us to compile entire neural networks and generate code targeting the AVX2, AVX512, NEON, and NEONfp16 instruction sets while incorporating optimizations often missing from oth

Zhewei Sun, Richard Zemel, Yang Xu

Slang is a predominant form of informal language making flexible and extended use of words that is notoriously hard for natural language processing systems to interpret. Existing approaches to slang interpretation tend to rely on context but ignore semantic extensions common in slang word usage. We propose a semantically informed slang interpretation (SSI) f

Stephen Powers, Carlo Pinciroli

Collective behaviors are typically hard to model. The scale of the swarm, the large number of interactions, and the richness and complexity of the behaviors are factors that make it difficult to distill a collective behavior into simple symbolic expressions. In this paper, we propose a novel approach to symbolic regression designed to facilitate such modelin

Tianyuan Zhang, Xuanyao Chen, Yue Wang, Yilun Wang

Accurate and consistent 3D tracking from multiple cameras is a key component in a vision-based autonomous driving system. It involves modeling 3D dynamic objects in complex scenes across multiple cameras. This problem is inherently challenging due to depth estimation, visual occlusions, appearance ambiguity, etc. Moreover, objects are not consistently associ

Deepanshu Kush, Shubhangi Saraf

We prove strengthened lower bounds for constant-depth set-multilinear formulas. More precisely, we show that over any field, there is an explicit polynomial $f$ in VNP defined over $n^2$ variables, and of degree $n$, such that any product-depth $Δ$ set-multilinear formula computing $f$ has size at least $n^{Ω\left( n^{1/Δ}/Δ\right)}$. The hard polynomial $f$

Jon A. Steingrimsson, David H. Barker, Ruofan Bie, Issa J. Dahabreh

Causally interpretable meta-analysis combines information from a collection of randomized controlled trials to estimate treatment effects in a target population in which experimentation may not be possible but covariate information can be collected from a simple random sample. In such analyses, a key practical challenge is systematically missing data when so

Nathan B. Agmon, Bruno Balthazar, Minjae Cho, Victor A. Rodriguez

We study D-instanton contributions to supergraviton scattering amplitudes in the ten-dimensional type IIB superstring theory beyond the leading non-perturbative order. In particular, we determine the one-D-instanton contribution to maximal R-symmetry violating (MRV) amplitudes with arbitrary momenta at the first subleading order in string coupling, as well a

Naphan Benchasattabuse, Takahiko Satoh, Michal Hajdušek, Rodney Van Meter

We propose an algorithm using a modified variant of amplitude amplification to solve combinatorial optimization problems via the use of a subdivided phase oracle. Instead of dividing input states into two groups and shifting the phase equally for all states within the same group, the subdivided phase oracle changes the phase of each input state uniquely in p

Philippe Lebacque, Kohji Matsumoto, Yumiko Umegaki

We consider the value distribution of logarithms of symmetric square L-functions associated with newforms of even weight and prime power level at real s> 1/2. We prove that certain averages of those values can be written as integrals involving a density function which is related with the Sato-Tate measure. Moreover, we discuss the case of symmetric power L-f

Hongquan Zhu, Xincheng He, Lei Xu

When changing code, developers sometimes neglect updating the related comments, bringing inconsistent or outdated comments. These comments increase the cost of program understanding and greatly reduce software maintainability. Researchers have put forward some solutions, such as CUP and HEBCUP, which update comments efficiently for simple code changes (i.e.

Kejun Chen, Yu Zhang

With an increasing high penetration of solar photovoltaic generation in electric power grids, voltage phasors and branch power flows experience more severe fluctuations. In this context, probabilistic power flow (PPF) study aims at characterizing the statistical properties of the state of the system with respect to the random power injections. To avoid repea

Xiaowei Su, Lidong Wang, Zihong Tian

Motivated by the application in geometric orthogonal codes (GOCs), Wang et al. introduced the concept of generalized perfect difference families (PDFs), and established the equivalence between GOCs and a certain type of generalized PDFs recently. Based on the relationship, we discuss the existence problem of generalized $(n\times m,K,1)$-PDFs in this paper.

Sawsan Khaskeia, Robert Shwartz

The OGS for non-abelian groups is an interesting generalization of the basis of finite abelian groups. The definition of OGS states that every element of a group has a unique presentation as a product of some powers of specific generators of the group, in a specific given order. In case of the symmetric groups Sn there is a paper of R. Shwartz, which demonst

Ran Li, Jin Wang

We provide a comprehensive study on the non-Markovian dynamics of the black hole phase transitions based on the underlying free energy landscape. By assuming that the transition processes between different black hole states are stochastic, the non-Markovian dynamics of the black hole phase transition is governed by the generalized Langevin equation with the

Hailong Sheng, Chao Yang

A new penalty-free neural network method, PFNN-2, is presented for solving partial differential equations, which is a subsequent improvement of our previously proposed PFNN method [1]. PFNN-2 inherits all advantages of PFNN in handling the smoothness constraints and essential boundary conditions of self-adjoint problems with complex geometries, and extends t

L. F. Chacón-Cortés, C. A. Garcia-Bibiano, W. A. Zúñiga-Galindo

We introduce a new family of p-adic non-linear evolution equations. We establish the local well-posedness of the Cauchy problem for these equations in Sobolev-type spaces. For a certain subfamily, we show that the blow-up phenomenon occurs and provide numerical simulations showing this phenomenon.

Katherine Vieira, Giovanni Carraro, Vladimir Korchagin, Artem Lutsenko

We present a detailed analysis of kinematics of the Milky Way disk in solar neighborhood using GAIA DR3 catalog. To determine the local kinematics of the stellar disks of the Milky Way galaxy we use a complete sample of 278,228 red giant branch (RGB) stars distributed in a cylinder, centered at the Sun with a 1 kpc radius and half-height of 0.5 kpc. We deter

Benedikt Bitterli, Eugene d&#39;Eon

We consider the problem of multiple scattering on Smith microfacets. This problem is equivalent to computing volumetric light transport in a homogeneous slab. Although the symmetry of the slab allows for significant simplification, fully analytic solutions are scarce and not general enough for most applications. Standard Monte Carlo simulation, although gene

Vincent R. Pascuzzi, Ning Bao, Ang Li

The quantum information science community has seen a surge in new algorithmic developments across scientific domains. These developments have demonstrated polynomial or better improvements in computational and space complexity, incentivizing further research in the field. However, despite recent progress, many works fail to provide quantitative estimates on

Johanna K. Jochum, Thomas Saerbeck, Vera Lazenka, Vincent Joly

The influence of a patterned substrate on obliquely deposited, exchange biased Co/CoO films was studied. It was found that substrates decorated with nanoparticle patterns provide the option to manipulate the orientation of the magnetic easy axis in obliquely deposited thin films. The complementary methods of SQUID magnetometry and polarized neutron reflectom

Anjali Parashar, Priyank Srivastava, Anuradha M. Annaswamy

This paper presents a framework to solve constrained optimization problems in an accelerated manner based on High-Order Tuners (HT). Our approach is based on reformulating the original constrained problem as the unconstrained optimization of a loss function. We start with convex optimization problems and identify the conditions under which the loss function

Emilio Ferrucci

A branched rough path $X$ consists of a rough integral calculus for $X \colon [0, T] \to \mathbb R^d$ which may fail to satisfy integration by parts. Using Kelly&#39;s bracket extension [Kel12], we define a notion of pushforward of branched rough paths through smooth maps, which leads naturally to a definition of branched rough path on a smooth manifold. Onc

Péter L. Erdős, Gergely Harcos, Shubha R. Kharel, Péter Maga

Let us call a simple graph on $n\geq 2$ vertices a prime gap graph if its vertex degrees are $1$ and the first $n-1$ prime gaps. We show that such a graph exists for every large $n$, and in fact for every $n\geq 2$ if we assume the Riemann hypothesis. Moreover, an infinite sequence of prime gap graphs can be generated by the so-called degree preserving growt

Jiti Gao, Bin Peng, Yayi Yan

In this paper, we propose a simple inferential method for a wide class of panel data models with a focus on such cases that have both serial correlation and cross-sectional dependence. In order to establish an asymptotic theory to support the inferential method, we develop some new and useful higher-order expansions, such as Berry-Esseen bound and Edgeworth

Clara Rojas, Rafael Hernández-Jiménez

In this work, we study the effects on the relevant observational parameters of an inflationary universe from a chaotic potential with a step. We numerically evolve the perturbation equations within both cold inflation and warm inflation. On the one hand, in a cold inflation scenario we analyse the scalar power spectrum $P_{\mathcal{R}}$ in terms of the numbe

Angelo Ziletti, Alan Akbik, Christoph Berns, Thomas Herold

Medical coding (MC) is an essential pre-requisite for reliable data retrieval and reporting. Given a free-text reported term (RT) such as "pain of right thigh to the knee", the task is to identify the matching lowest-level term (LLT) - in this case "unilateral leg pain" - from a very large and continuously growing repository of standardized medical terms. Ho

Elisabetta Prencipe

The X(3872) is one of the most puzzling resonances ever observed. First seen by the Belle Collaboration in 2003, it solicited the effort of a hundred of experimental physicists and dozens of theorists, who nowadays are trying yet to shed light on the nature of this peculiar resonant state. It was seen in several decay modes and different production mechanism

Nolan H. Hamilton, Errin Fulp

Classification systems are often deployed in resource-constrained settings where labels must be assigned to inputs on a budget of time, memory, etc. Budgeted, sequential classifiers (BSCs) address these scenarios by processing inputs through a sequence of partial feature acquisition and evaluation steps with early-exit options. This allows for an efficient e

Luca Amendola, Massimo Pietroni, Miguel Quartin

We introduce a methodology to extend the Fisher matrix forecasts to mildly non-linear scales without the need of selecting a cosmological model. We make use of standard non-linear perturbation theory for biased tracers complemented by counterterms, and assume that the cosmological distances can be measured accurately with standard candles. Instead of choosin

Naomichi Yutani, Yoshiki Toba, Shunsuke Baba, Keiichi Wada

Dust Obscured Galaxies (DOGs), which are observationally characterized as faint in the optical and bright in the infrared, are the final stage of galaxy mergers and are essential objects in the evolution of galaxies and active galactic nuclei (AGNs). However, the relationship between torus-scale gas dynamics around AGNs and DOGs lifetime remain unclear. We o

Michael Lashkevich

The $GL(1|1)$ WZW model in the free field realization that uses the $bc$ system is revisited. By bosonizing the $bc$ system we describe the Neveu--Schwarz and Ramond sector modules $\mathcal V^{\text{NS}}_{en}=\bigoplus_{l\in\mathbb Z}\mathcal V^l_{en}$ and $\mathcal V^{\text{R}}_{en}=\bigoplus_{l\in\mathbb Z+{1\over2}}\mathcal V^l_{en}$ in terms of the subs

Pedro Henrique Croti Siqueira, Maurício Richartz

We use the continued fraction method to determine the eigenfrequencies associated with a scalar field around a Kerr-like black hole. The Kerr-like metric considered in this article is a subclass of the general parametrization of axisymmetric black holes proposed by Konoplya, Rezzolla and Zhidenko. In addition to its mass $M$ and specific angular momentum $a$

Daniel Boyanovsky

We study the thermalization of a scalar field $Φ$ coupled to two other scalar fields $χ_{1,2}$ that constitute a bath in thermal equilibrium. For a range of masses the $Φ$ propagator features threshold and infrared divergences, a vanishing residue at the (quasi) particle pole and vanishing \emph{on-shell} decay rates thereby preventing the equilibration of $

Giulia Gugiatti, Franco Rota

Motivated by homological mirror symmetry, this paper constructs explicit full exceptional collections for the canonical stacks associated with the series of log del Pezzo surfaces constructed by Johnson and Kollár. These surfaces have cyclic quotient, non-Gorenstein, singularities. The construction involves both the $\mathrm{GL}(2,\mathbb{C})$ McKay correspo

Sergey A. Lizunov, Alexander V. Bulgakov, Eleanor E. B. Campbell, Nadezhda M. Bulgakova

The ultrafast laser-induced solid-liquid phase transition in metals is still not clearly understood and its accurate quantitative description remains a challenge. Here we systematically investigated, both experimentally and theoretically, the melting of gold by single femto- and picosecond near-infrared laser pulses. Two laser systems with wavelengths of 800

Masahiro Kaneko, Aizhan Imankulova, Danushka Bollegala, Naoaki Okazaki

Masked Language Models (MLMs) pre-trained by predicting masked tokens on large corpora have been used successfully in natural language processing tasks for a variety of languages. Unfortunately, it was reported that MLMs also learn discriminative biases regarding attributes such as gender and race. Because most studies have focused on MLMs in English, the bi

Erik J. Wasleske, Vivienne F. Baldassare, Christopher M. Carroll

We searched the Northern Hemisphere Fields of the GALEX Time-Domain Survey (TDS) for galaxies with UV variability indicative of active galactic nuclei (AGNs). We identified 48 high-probability candidate AGNs from a parent sample of 1819 galaxies in the NASA Sloan Atlas (NSA) catalog. We further characterized these systems using optical spectroscopic diagnost

Bohan Li, Lie-Liang Yang, Robert G Maunder, Songlin Sun

In-band full duplex cell-free (CF) systems suffer from severe self-interference and cross-link interference, especially when CF systems are operated in distributed way. To this end, we propose the multicarrier-division duplex as an enabler for achieving full-duplex operation in the distributed CF massive MIMO systems, where downlink and uplink transmissions

Caitlin Freeman, Michael Maynard, Vishesh Vikas

Imagine a swarm of terrestrial robots that can explore an environment, and, upon completion of this task, reconfigure into a spherical ball and roll out. This dimensional change alters the dynamics of locomotion and can assist them to maneuver variable terrains. The sphere-plane reconfiguration is equivalent to projecting a spherical shell onto a plane, an o

Renato G. Bettiol, McFeely Jackson Goodman

Following Gromov, a Riemannian manifold is called area-extremal if any modification that increases scalar curvature must decrease the area of some tangent 2-plane. We prove that large classes of compact 4-manifolds, with or without boundary, with nonnegative sectional curvature are area-extremal. We also show that all regions of positive sectional curvature

J. A. Aguilar-Saavedra, J. A. Casas

We discuss quantum entanglement in top pair production at the LHC. Near the $t \bar t$ threshold, entanglement observables are enhanced by suppressing the contribution of $q \bar q$ subprocesses, which is achieved by a simple cut on the velocity of the $t \bar t$ system in the laboratory frame. Furthermore, we design new observables that directly measure the

Sourav Pal

A distinguished variety in the polydisc $\mathbb D^n$ is an affine complex algebraic variety that intersects $\mathbb D^n$ and exits the domain through the $n$-torus $\mathbb T^n$ without intersecting any other part of the topological boundary of $\mathbb D^n$. We find two different characterizations for a distinguished variety in the polydisc $\mathbb D^n$

S. Majumder, M. Tripathi, D. O. de Souza, A. Sagdeo

Coupling between different interactions allows to control physical aspects in multifunctional materials by perturbing any of the degrees of freedom. Here, we aim to probe the correlation among structural, electronic and magnetic observables of Sm$ _{2} $NiMnO$ _{6} $ ferromagnetic insulator double perovskite. Our employed methodology includes thermal evoluti

Niels Geerits, Hartmut Lemmel, Anna-Sophie Berger, Stephan Sponar

A combination of aluminium prisms inserted into a nested loop interferometer is used to generate a neutron phase vortex lattice with significant extrinsic orbital angular momentum, L_z=0.35, on a length scale of 220 microns, transverse to the propagation direction. Our method is a generalization of recently developed magnetic methods, such that we can exploi

Jenni Raitoharju, Alexandros Iosifidis

In this paper, we formulate a new generalized reference kernel hoping to improve the original base kernel using a set of reference vectors. Depending on the selected reference vectors, our formulation shows similarities to approximate kernels, random mappings, and Non-linear Projection Trick. Focusing on small-scale one-class classification, our analysis and

Atin Gayen, M. Ashok Kumar

This paper generalizes the notion of sufficiency for estimation problems beyond maximum likelihood. In particular, we consider estimation problems based on Jones et al. and Basu et al. likelihood functions that are popular among distance-based robust inference methods. We first characterize the probability distributions that always have a fixed number of suf