October 2022 arXiv papers — page 92

Fred Lu, Joseph Munoz, Maya Fuchs, Tyler LeBlond

We present a framework to statistically audit the privacy guarantee conferred by a differentially private machine learner in practice. While previous works have taken steps toward evaluating privacy loss through poisoning attacks or membership inference, they have been tailored to specific models or have demonstrated low statistical power. Our work develops

Allen Nie, Yannis Flet-Berliac, Deon R. Jordan, William Steenbergen

Offline reinforcement learning (RL) can be used to improve future performance by leveraging historical data. There exist many different algorithms for offline RL, and it is well recognized that these algorithms, and their hyperparameter settings, can lead to decision policies with substantially differing performance. This prompts the need for pipelines that

Jiayu Xie, Yaxuan Wang, Bing Tang

We study the motion of a ring string in the background of the Bardeen-AdS black hole surrounded by the quintessence dark energy. The effects of the magnetic monopole charge, the quintessence state parameter, and the quintessence normalization parameter on the dynamical behavior of the ring string are respectively analyzed. Our numerical results show that the

Amnon Attali, Stav Ashur, Isaac Burton Love, Courtney McBeth

Randomized sampling based algorithms are widely used in robot motion planning due to the problem's intractability, and are experimentally effective on a wide range of problem instances. Most variants do not sample uniformly at random, and instead bias their sampling using various heuristics for determining which samples will provide more information, or are

Dae Woong Ham, Iavor Bojinov, Michael Lindon, Martin Tingley

Randomized experiments have become the standard method for companies to evaluate the performance of new products or services. Beyond aiding managerial decision-making, experiments mitigate risk by limiting the proportion of customers exposed to innovations. Since many experiments are conducted sequentially over time, an emerging strategy to further derisk th

Benjamin Sung

We study an admissible subcategory of the Bondal quiver which conjecturally does not admit any Bridgeland stability conditions. Specifically, we prove that its Serre functor coincides with the spherical twist associated with a $3$-spherical object. As a consequence, we obtain a classification of the spherical objects, deduce the non-existence of Serre-invari

Benjamin Sung

We prove that any non-commutative smooth projective variety with a Bridgeland stability condition of dimension less than $\frac{6}{5}$ must be a smooth projective curve. As a consequence, we deduce the non-existence of such categories with dimension in the interval $(1,\frac{6}{5})$. Moreover, we prove a sharp reconstruction result for smooth projective curv

Alexandria Volkening

Traffic jams on roadways, echo chambers on social media, crowds of moving pedestrians, and opinion dynamics during elections are all complex social systems. These applications may seem disparate, but some of the questions that they motivate are similar from a mathematical perspective. Across these examples, researchers seek to uncover how individual agents -

Zhewei Sun, Yang Xu

The meaning of a slang term can vary in different communities. However, slang semantic variation is not well understood and under-explored in the natural language processing of slang. One existing view argues that slang semantic variation is driven by culture-dependent communicative needs. An alternative view focuses on slang's social functions suggesting th

Tzu-hsun Feng, Annie Dong, Ching-Feng Yeh, Shu-wen Yang

We present the SUPERB challenge at SLT 2022, which aims at learning self-supervised speech representation for better performance, generalization, and efficiency. The challenge builds upon the SUPERB benchmark and implements metrics to measure the computation requirements of self-supervised learning (SSL) representation and to evaluate its generalizability an

J. Sánchez, Y. Omori, C. Chang, L. E. Bleem

We cross-correlate positions of galaxies measured in data from the first three years of the Dark Energy Survey with Compton-$y$-maps generated using data from the South Pole Telescope (SPT) and the {\it Planck} mission. We model this cross-correlation measurement together with the galaxy auto-correlation to constrain the distribution of gas in the Universe.

Brandon RichardWebster, Justin Dulay, Anthony DiFalco, Elisabetta Caldesi

For the last decade, convolutional neural networks (CNNs) have vastly superseded their predecessors in nearly all vision tasks in artificial intelligence, including object recognition. However, despite abundant advancements, they continue to pale in comparison to biological vision. This chasm has prompted the development of biologically-inspired models that

Yi Wang, Yihuang Xiong, Tiannan Yang, Yakun Yuan

This work demonstrates a first-principles-based approach to obtaining finite temperature thermal and electronic transport properties which can be employed to model and understand mesoscale structural evolution during electronic, magnetic, and structural phase transitions. A computationally tractable model was introduced to estimate the temperature dependence

Sam Keller, Matthew Stein, Ognjen Ilic

Additive manufacturing, such as 3D printing, offers unparalleled opportunities for rapid prototyping of complex three-dimensional objects, but typically requires simultaneous building of solid supports to minimize deformation and ensure contact with the printing surface. Here, we theoretically and experimentally investigate the concept of material extrusion

Rajavel Praveen M, Rama R

The $\ell$-Rauzy graph of order $k$ for any infinite word is a directed graph in which an arc $(v_1,v_2)$ is formed if the concatenation of the word $v_1$ and the suffix of $v_2$ of length $k-\ell$ is a subword of the infinite word. In this paper, we consider one of the important aperiodic recurrent words, the infinite Fibonacci word for discussion. We prove

James Halverson, Benjamin Sung, Jiahua Tian

We study electric-magnetic duality in compactifications of M-theory on twisted connected sum (TCS) $G_2$ manifolds via duality with F-theory. Specifically, we study the physics of the D3-branes in F-theory compactified on a Calabi-Yau fourfold $Y$, dual to a compactification of M-theory on a TCS $G_2$ manifold $X$. $\mathcal{N}=2$ supersymmetry is restored i

Ramkumar Natarajan, Garrison L. H. Johnston, Nabil Simaan, Maxim Likhachev

Robots often have to perform manipulation tasks in close proximity to people. As such, it is desirable to use a robot arm that has limited joint torques to not injure the nearby person and interacts with the environment to explore new possibilities for completing a task. By bracing against the environment, robots can expand their reachable workspace, which w

Sabrine Arfaoui

In the present paper, we precisely conduct a q-calculus method for the numerical solutions of PDEs. A nonlinear Schrodinger equation is considered. Instead of the classical discretization methods we consider subdomains according to q-calculus, and provide an approximate solution due to a specific value of the parameter q. Error estimates show that q-calculus

Ian Gleason, João Lourenço

We prove that all $p$-adic period domains (and their non-minuscule analogues) are geometrically connected. This answers a question of Hartl [Har13] and has interesting consequences to the geometry of Shimura and local Shimura varieties.

Anup Singh, Kris Demuynck, Vipul Arora

An ideal audio retrieval system efficiently and robustly recognizes a short query snippet from an extensive database. However, the performance of well-known audio fingerprinting systems falls short at high signal distortion levels. This paper presents an audio retrieval system that generates noise and reverberation robust audio fingerprints using the contras

Eugen Mihailescu

We study invariant measures and thermodynamic formalism for a class of endomorphisms $F_T$ which are only piecewise differentiable on countably many pieces and non-conformal. The endomorphism $F_T$ has parametrized countably generated limit sets in stable fibers. We prove a Global Volume Lemma for $F_T$ implying that the projections of equilibrium measures a

Thomas Brazelton

We formulate an equivariant conservation of number, which proves that a generalized Euler number of a complex equivariant vector bundle can be computed as a sum of local indices of an arbitrary section. This involves an expansion of the Pontryagin--Thom transfer in the equivariant setting. We leverage this result to commence a study of enumerative geometry i

Svetlana Andrusenko, Yurii Gavriluk, Andrei Gusev, Daniil Krichevskiy

The problem of joint data processing from ground-based gravitational and neutrino detectors is considered in order to increase the detection efficiency of collapsing objects in the Galaxy. The development of the "neutrino - gravitational correlation" algorithm is carried out within the framework of the theory of optimal filtration as applied to the well-know

Petr Hliněný, Jan Jedelský

Twin-width is a structural width parameter introduced by Bonnet, Kim, Thomass\'e and Watrigant [FOCS 2020], and has interesting applications in the areas of logic on graphs and in parameterized algorithmics. Very briefly, the essence of twin-width is in a gradual reduction (a contraction sequence) of the given graph down to a single vertex while maintaining

Marco Di Renzo, Vincenzo Galdi, Giuseppe Castaldi

Recently, a circuits-based approach for modeling the mutual coupling of reconfigurable surfaces, which comprise sub-wavelength spaced passive scattering elements coupled with electronic circuits for enabling the reconfiguration of the surface, has been introduced. The approach is based on a finite-length discrete dipole representation of a reconfigurable sur

Allen W. Shafter, Kamil Hornoch, Hana Kučáková, Jingyuan Zhao

The M31 recurrent nova M31N 1926-07c has had five recorded eruptions. Well-sampled light curves of the two most recent outbursts, in January of 2020 (M31N 2020-01b) and September 2022 (M31N 2022-09a), are presented showing that the photometric evolution of the two events were quite similar, with peak magnitudes of $R=17.2\pm0.1$ and $R=17.1\pm0.1$, and $t_2$

Badri Vishal Pandey

Here we study the roots of the doubly infinite family of Jensen polynomials $J_{\mathrm{PL}}^{d,n}(x)$ associated to MacMahon's plane partition function $\mathrm{PL}(n)$. Recently, Ono, Pujahari, and Rolen proved that $\mathrm{PL}(n)$ is log-concave for all $n\geq 12$, which is equivalent to the polynomials $J_{\mathrm{PL}}^{2,n}(x)$ having real roots. Moreo

Marco Di Renzo, Davide Dardari, Nicolo' Decarli

The wireless research community has expressed major interest in the sub-terahertz band for enabling mobile communications in future wireless networks. The sub-terahertz band offers a large amount of available bandwidth and, therefore, the promise to realize wireless communications at optical speeds. At such high frequency bands, the transceivers need to have

Flynn Walsh, Robert O. Ritchie, Mark Asta

Contrary to prior calculations, the Ni-rich ordered structures of the Cr-Ni alloy system are found to be antiferromagnetic under semi-local density-functional theory. The optimization of local magnetic moments significantly increases the driving force for the formation of CrNi$_2$, the only experimentally observed intermetallic phase. This structure's ab ini

Suyash Garg

In this paper, a new formula for {\pi}^(2)(N) is formulated, it is a function that counts the number of semi-primes not exceeding a given number N. A semi-prime is a natural number that is the product of precisely two prime numbers, the two primes in the product may equal each other. Semi-prime numbers are also a case of almost primes. Since a formula for th

Dylan A. Dutton, Daniel E. Reichart, Joshua B. Haislip, Vladimir V. Kouprianov

Built in 2004, the Skynet robotic telescope network originally consisted of six 0.4 m telescopes located at the Cerro-Tololo Inter-American Observatory in the Chilean Andes. The network was designed to carry out simultaneous multi-wavelength observations of gamma-ray bursts (GRBs) when they are only tens of seconds old. To date, the network has been expanded

D. Aristizabal Sierra, J. L. Barrow, B. Dutta, D. Kim

The $\nu$BDX-DRIFT collaboration seeks to detect low-energy nuclear recoils from CE$\nu$NS or BSM interactions at FNAL. Backgrounds due to rock neutrons are an important concern. We present a~\texttt{GENIE} and~\texttt{GEANT4} based model to estimate backgrounds from rock neutrons produced in neutrino-nucleus interactions within the rock walls surrounding th

Benjamin McDonough, Andrea Mari, Nathan Shammah, Nathaniel T. Stemen

Current quantum computers suffer from a level of noise that prohibits extracting useful results directly from longer computations. The figure of merit in many near-term quantum algorithms is an expectation value measured at the end of the computation, which experiences a bias in the presence of hardware noise. A systematic way to remove such bias is probabil

Lam Pham, Dusan Salovic, Anahid Jalali, Alexander Schindler

In this paper, we present a comprehensive analysis of Acoustic Scene Classification (ASC), the task of identifying the scene of an audio recording from its acoustic signature. In particular, we firstly propose an inception-based and low footprint ASC model, referred to as the ASC baseline. The proposed ASC baseline is then compared with benchmark and high-co

Xin Dong, Yuanjing Ji, Matthew Kelsey, Sooraj Radhakrishnan

Study of the transverse structure of the proton is one of the major physics goals of the upcoming Electron Ion Collider (EIC). The gluon transverse momentum dependent distributions (TMD) form an essential focus of this effort and are important towards understanding the angular momentum contribution to proton spin as well as QCD factorization. However, very l

Jiayu Huang, Yutian Pang, Yongming Liu, Hao Yan

Neural Networks (NNs) have been widely {used in supervised learning} due to their ability to model complex nonlinear patterns, often presented in high-dimensional data such as images and text. However, traditional NNs often lack the ability for uncertainty quantification. Bayesian NNs (BNNS) could help measure the uncertainty by considering the distributions

Vindula Jayawardana, Catherine Tang, Sirui Li, Dajiang Suo

Evaluations of Deep Reinforcement Learning (DRL) methods are an integral part of scientific progress of the field. Beyond designing DRL methods for general intelligence, designing task-specific methods is becoming increasingly prominent for real-world applications. In these settings, the standard evaluation practice involves using a few instances of Markov D

Lucas Valentin

Community Question Answering is the field of computational linguistics that deals with problems derived from the questions and answers posted to websites such as Quora or Stack Overflow. Among some of these problems we find the issue of ranking the multiple answers posted in reply to each question by how informative they are in the attempt to solve the origi

Amos Uderzo

This paper considers mathematical programs, whose constraints are expressed by a parameterized vector equilibrium problem. The latter is a well recognized framework, which is able to cover multicriteria optimization, vector variational inequalities and complementarity problems. As the solutions to vector equilibrium problems are here intended in a strong sen

K. Venkataramaniah, Shreesha Rao D. S., C. Scheidenberger

The experimental mass data from the Atomic Mass Compilation - 2012 (AMC12) has been analyzed for two-neutron separation energies (S$_{2n}$), two-proton separation energies (S$_{2p}$), double-beta decay energies (Q$_{2\beta^-}$), and four-beta decay energies (Q$_{4\beta^-}$) and plotted against neutron number and mass number, respectively. A new weighted slop

Yi R. Fung, Tuhin Chakraborty, Hao Guo, Owen Rambow

Norm discovery is important for understanding and reasoning about the acceptable behaviors and potential violations in human communication and interactions. We introduce NormSage, a framework for addressing the novel task of conversation-grounded multi-lingual, multi-cultural norm discovery, based on language model prompting and self-verification. NormSAGE l

Ruchao Fan, Yiming Wang, Yashesh Gaur, Jinyu Li

In this work, we present a simple but effective method, CTCBERT, for advancing hidden-unit BERT (HuBERT). HuBERT applies a frame-level cross-entropy (CE) loss, which is similar to most acoustic model training. However, CTCBERT performs the model training with the Connectionist Temporal Classification (CTC) objective after removing duplicated IDs in each mask

Apostolos Spanakis-Misirlis

In this thesis, we introduce the fundamental equations behind the estimation of the link budget in a communications channel, highlighting the key limitations of conventional systems. Furthermore, we investigate the use of reconfigurable intelligent surfaces as a modern method of overcoming obstruction losses, while making use of numerical methods and computa

Akankshya Majhi, Lars Kool, Jasper van der Gucht, Joshua A. Dijksman

The interaction between a fluid and a wall is described with a certain boundary condition for the fluid velocity at the wall. To understand how fluids behave near a rough wall, the fluid velocity at every point of the rough surface may be provided. This approach requires detailed knowledge of, and likely depends strongly on the roughness. Another approach of

Daniel Gregorek, Nils Hülsmeier, Steffen Paul

The functionality of electronic circuits can be seriously impaired by the occurrence of dynamic hardware faults. Particularly, for digital ultra low-power systems, a reduced safety margin can increase the probability of dynamic failures. This work investigates a deep learning approach to mitigate dynamic fault impact for artificial neural networks. As a theo

Marco Iannotta, David Cáceres Domínguez, Johannes A. Stork, Erik Schaffernicht

Integrating the heterogeneous controllers of a complex mechanical system, such as a mobile manipulator, within the same structure and in a modular way is still challenging. In this work we extend our framework based on Behavior Trees for the control of a redundant mechanical system to the problem of commanding more complex systems that involve multiple low-l

Sungho Shin, Sen Na, Mihai Anitescu

This article presents a dynamic regret analysis for stochastic model predictive control (SMPC) in linear systems with quadratic performance index and additive and multiplicative uncertainties. Under a finite support assumption, the problem can be cast as a finite-dimensional quadratic program, but the problem becomes quickly intractable as the problem size g

Ilaria Colazzo, Maria Ferrara, Marco Trombetti

If $(X,r)$ is a finite non-degenerate set-theoretic solution of the Yang--Baxter equation, the additive group of the structure skew brace $G(X,r)$ is an $FC$-group, i.e. a group whose elements have finitely many conjugates. Moreover, its multiplicative group is virtually abelian, so it is also close to an $FC$-group itself. If one additionally assumes that t

Florestan Brunck

We prove that every 2-dimensional polygonal complex, where each polygon is given a constant curvature metric and belongs to one of finitely many isometry classes can be triangulated using only acute simplices. There is no requirement on the complex to be finite or even locally finite.

Amr Alanwar, Frank J. Jiang, Samy Amin, Karl H. Johansson

A logical zonotope, which is a new set representation for binary vectors, is introduced in this paper. A logical zonotope is constructed by XOR-ing a binary vector with a combination of other binary vectors called generators. Such a zonotope can represent up to 2^n binary vectors using only n generators. It is shown that logical operations over sets of binar

T. Zalialiutdinov, D. Glazov, D. Solovyev

In this work, we consider the thermal correction to the hyperfine interaction in hydrogen, deuterium, and the $^3$He$^+$ ion. This correction is effectively described by one-loop Feynman graphs in the framework of the quantum electrodynamics theory for bound states at a finite temperature. A simple analysis shows the importance of the obtained results for fu

Mikhail Khenner

Two simple kinetic models of Quantum Size Effect-directed nanocluster self-assembly in circular atomic corrals are discussed. The models correspond to an adsorption (either a physisorption or a chemisorption) and an adsorption-diffusion regimes that are typical at low and high temperatures, respectively. Small magnitudes of a variation of the electronic loca

Akhil Kumar

We provide explicit expression of squeezing function for infinitely connected planar domain obtained by removing a convergent sequence of points from the unit disk converging to the boundary of unit disk. We also discuss Fridman invariant associated with this domain as well as some examples of squezzing functions corresponding to polydisk.

Jérémy Saucourt, Antonin Moreau, Julien Lumeau, Hervé Rigneault

Optical detection of ultrasound for photoacoustic imaging provides large bandwidth and high sensitivity at high acoustic frequencies. Higher spatial resolutions can therefore be achieved using Fabry-P\'erot cavity sensors, as compared to conventional piezoelectric detection. However, fabrication constraints during deposition of the sensing polymer layer requ

Zachary Bezemek, Max Heldman

We construct an importance sampling method for computing statistics related to rare events for weakly interacting diffusions. Standard Monte Carlo methods behave exponentially poorly with the number of particles in the system for such problems. Our scheme is based on subsolutions of a Hamilton-Jacobi-Bellman (HJB) Equation on Wasserstein Space which arises i

Ping Yang, Junjie Wang, Ruyi Gan, Xinyu Zhu

We propose a new paradigm for zero-shot learners that is format agnostic, i.e., it is compatible with any format and applicable to a list of language tasks, such as text classification, commonsense reasoning, coreference resolution, and sentiment analysis. Zero-shot learning aims to train a model on a given task such that it can address new learning tasks wi

Sudhakar Mishra, Narayanan Srinivasan, Uma Shanker Tiwary

Understanding the dynamics of emotional experience is an old problem. However, a clear understanding of the mechanism of emotional experience is still far away. In the presented work, we tried to address this problem using a well-established method called microstate analysis using multichannel electroencephalography (EEG). We recorded the brain activity of s

Paola Marigo, Bernhard Aringer, Leo Girardi, Alessandro Bressan

This work introduces new low-temperature gas opacities, in the range 3.2 <= log(T/K) <= 4.5, computed with the AESOPUS code under the assumption of thermodynamic equilibrium (Marigo &_Aringer_2009). In comparison to the previous version AESOPUS 1.0, we updated and expanded molecular absorption to include 80 species, mostly using the recommended line lists cu

Giorgio Torrieri

This work is divided into two parts. The first examines recent proposals for "witnessing" quantum gravity via entanglement from the point of view of Bronstein's original objection to a quantization of gravity. Using techniques from open quantum systems we sketch how unavoidable decoherence from both inertial and gravitational backreaction between probe and d

Sajad Fathi Hafshejani, Zahra Moberfard

In the last few years, various types of machine learning algorithms, such as Support Vector Machine (SVM), Support Vector Regression (SVR), and Non-negative Matrix Factorization (NMF) have been introduced. The kernel approach is an effective method for increasing the classification accuracy of machine learning algorithms. This paper introduces a family of on

Adrián Hinojosa-Calleja

We find sufficient conditions for the existence of an exact uniform modulus continuity for the class of $q$-isotropic Gaussian random fields introduced in [8]. We apply the result to a $d$-dimensional version of the $B^{\gamma}$ Gaussian processes defined in [14].

Birgitta Dresp-Langley

Analysis of grip force signals tailored to hand and finger movement evolution and changes in grip force control during task execution provide unprecedented functional insight into somatosensory cognition. Somatosensory cognition is the basis of our ability to act upon and to transform the physical world around us, to recognize objects on the basis of touch a

Charles Rezk

We show how several useful properties of Ind-constructions in $\infty$-categories extend to arbitrary free colimit completion constructions.

Arcadi Llanza, Nadiya Shvai, Amir Nakib

This paper analyzes the performance of the Fractal Decomposition Algorithm (FDA) metaheuristic applied to low-dimensional continuous optimization problems. This algorithm was originally developed specifically to deal efficiently with high-dimensional continuous optimization problems by building a fractal-based search tree with a branching factor linearly pro

Shiji Lyu

We study some permanence properties of the relative $F$-rational signature defined and studied by Smirnov--Tucker. We show that this invariant is compatible with the gamma-construction, and then derive other main results from the $F$-finite case established by Smirnov--Tucker. We also obtain limited results about the $F$-rational signature defined and studie

Clément Henry, Davide Consoli, Alexandre Dély, Lyes Rahmouni

This paper focuses on fast direct solvers for integral equations in the low-to-moderate-frequency regime obtained by leveraging preconditioned first kind or second kind operators regularized with Laplacian filters. The spectral errors arising from boundary element discretizations are properly handled by filtering that, in addition, allows for the use of low-

Hui Liu, Bo Zhao, Kehuan Zhang, Peng Liu

Although deep neural networks (DNNs) have shown impressive performance on many perceptual tasks, they are vulnerable to adversarial examples that are generated by adding slight but maliciously crafted perturbations to benign images. Adversarial detection is an important technique for identifying adversarial examples before they are entered into target DNNs.

Yimeng Zhang, Akshay Karkal Kamath, Qiucheng Wu, Zhiwen Fan

In this paper, we propose a data-model-hardware tri-design framework for high-throughput, low-cost, and high-accuracy multi-object tracking (MOT) on High-Definition (HD) video stream. First, to enable ultra-light video intelligence, we propose temporal frame-filtering and spatial saliency-focusing approaches to reduce the complexity of massive video data. Se

Zhanteng Xie, Philip Dames

This paper presents two variations of a novel stochastic prediction algorithm that enables mobile robots to accurately and robustly predict the future state of complex dynamic scenes. The proposed algorithm uses a variational autoencoder to predict a range of possible future states of the environment. The algorithm takes full advantage of the motion of the r

Yonatan Carlos Carranza Alarcón, Vu-Linh Nguyen

In this paper, we consider the problem of making skeptical inferences for the multi-label ranking problem. We assume that our uncertainty is described by a convex set of probabilities (i.e. a credal set), defined over the set of labels. Instead of learning a singleton prediction (or, a completed ranking over the labels), we thus seek for skeptical inferences

Itsaso Fernández-Irisarri, Manuel Mañas

The Cholesky factorization of the moment matrix is considered for discrete orthogonal polynomials of hypergeometrical type. We derive the Laguerre-Freud equations when the first moments of the weights are given by the ${}_1F_2$, ${}_2F_2$ and ${}_3F_2$ generalized hypergeometrical functions.

Utkarsh Azad, Helena Zhang

A limiting factor for readout fidelity for superconducting qubits is the relaxation of the qubit to the ground state before the time needed for the resonator to reach its final target state. A technique known as excited state promoted (ESP) readout was proposed to reduce this effect and further improve the readout contrast on superconducting hardware. In thi

Yueqin Yin, Lianghua Huang, Yu Liu, Kaiqi Huang

Recent generative models show impressive results in photo-realistic image generation. However, artifacts often inevitably appear in the generated results, leading to downgraded user experience and reduced performance in downstream tasks. This work aims to develop a plugin post-processing module for diverse generative models, which can faithfully restore imag

Gaurav Arya, Moritz Schauer, Frank Schäfer, Chris Rackauckas

Automatic differentiation (AD), a technique for constructing new programs which compute the derivative of an original program, has become ubiquitous throughout scientific computing and deep learning due to the improved performance afforded by gradient-based optimization. However, AD systems have been restricted to the subset of programs that have a continuou

Chen Cheng, Andrea Montanari

Random matrix theory has become a widely useful tool in high-dimensional statistics and theoretical machine learning. However, random matrix theory is largely focused on the proportional asymptotics in which the number of columns grows proportionally to the number of rows of the data matrix. This is not always the most natural setting in statistics where col

Rawshan Ara Mowri, Madhuri Siddula, Kaushik Roy

Ransomware has appeared as one of the major global threats in recent days. The alarming increasing rate of ransomware attacks and new ransomware variants intrigue the researchers to constantly examine the distinguishing traits of ransomware and refine their detection strategies. Application Programming Interface (API) is a way for one program to collaborate

Philipp Gaggl, Andreas Gsponer, Richard Thalmeier, Simon Waid

The unique electrical and material properties of 4H-silicon-carbide (4H-SiC) make it a promising candidate material for high rate particle detectors. In contrast to the ubiquitously used silicon (Si), 4H-SiC offers a higher carrier saturation velocity and larger breakdown voltage, enabling a high intrinsic time resolution and mitigating pile-up effects. Addi

Penghang Liu, Kshama Dwarakanath, Svitlana S Vyetrenko, Tucker Balch

Human decision-making in real-life deviates significantly from the optimal decisions made by fully rational agents, primarily due to computational limitations or psychological biases. While existing studies in behavioral finance have discovered various aspects of human sub-rationality, there lacks a comprehensive framework to transfer these findings into an

Deepak Bhoriya, Harish Kumar, Praveen Chandrashekar

In this article, we propose high-order finite-difference entropy stable schemes for the two-fluid relativistic plasma flow equations. This is achieved by exploiting the structure of the equations, which consists of three independent flux components. The first two components describe the ion and electron flows, which are modeled using the relativistic hydrody

Ehsan Shahoseini, Kiran S. Kedlaya

The tilting correspondence is a fundamental property of perfectoid fields. In this note, we show that the tilting construction can also be used to detect perfectoid fields among nonarchimedean fields. In particular, for $K$ a complete subfield of $\mathbb{C}_p$ (a completed algebraic closure of $\mathbb{Q}_p$), $K$ is perfectoid if and only if its tilt is no

Quynh T. Nguyen, Louis Schatzki, Paolo Braccia, Michael Ragone

Quantum neural network architectures that have little-to-no inductive biases are known to face trainability and generalization issues. Inspired by a similar problem, recent breakthroughs in machine learning address this challenge by creating models encoding the symmetries of the learning task. This is materialized through the usage of equivariant neural netw

Imogen Montague

Given a spin rational homology sphere $Y$ equipped with a $\mathbb{Z}/m$-action preserving the spin structure, we use the Seiberg--Witten equations to define equivariant refinements of the invariant $\kappa(Y)$ from \cite{Man14}, which take the form of a finite subset of elements in a lattice constructed from the representation ring of a twisted product of $

Chin-Wei Huang, Li-Fu Chen, Borching Su

In an active sensing system, waveforms with good auto-correlations are preferred for accurate parameter estimation. Furthermore, spectral compatibility is required to avoid mutual interference between devices as the electromagnetic environment becomes increasingly crowded. Waveforms should also be unimodular due to hardware limits. In this paper, a new appro

Margaret E. Carrington, Wade N. Cowie, Brett A. Meggison

We study the semi-metal/insulator quantum phase transition in three-dimensional Dirac semi-metals by solving a set of Schwinger-Dyson equations. We study the effect of an anisotropic fermion velocity on the critical coupling of the transition. We consider the influence of several different approximations that are commonly used in the literature and show that

Mansour Tchenegnon, Sylvie Gibet, Thibaut Le Naour

We propose a new loss function that we call Laplacian loss, based on spatio-temporal Laplacian representation of the motion as a graph. This loss function is intended to be used in training models for motion reconstruction through 3D human pose estimation from videos. It compares the differential coordinates of the joints obtained from the graph representati

F. Cangemi, J. Rodriguez, T. Belloni, C. Gouiffès

In black hole X-ray binaries, a non-thermal high-energy component is sometimes detected at energies above 200 keV. The origin of this component is debated and distinct spectral modelizations can lead to different interpretations. High-energy polarimetry measurements with INTEGRAL allow new diagnostics on the physics responsible for the MeV spectral component

Nikhil Bhootpur, Hans Brouwer, Yinglu Tang

Zirconia (ZrO2) has emerged as a promising technical ceramic, both as high temperature structural material and thermal barrier coating material, etc. The traditional synthesis of ZrO2 with spark plasma sintering (SPS) usually requires a sintering temperature as high as 1200C. General interest in lowering the sintering temperature to reduce energy consumption

Pritom Saha Akash, Jie Huang, Kevin Chen-Chuan Chang

We propose a new problem called coordinated topic modeling that imitates human behavior while describing a text corpus. It considers a set of well-defined topics like the axes of a semantic space with a reference representation. It then uses the axes to model a corpus for easily understandable representation. This new task helps represent a corpus more inter

Zhenxing Di, Liping Li, Li Liang, Nina Yu

Representations over diagrams of abelian categories unify quite a few notions appearing widely in literature such as representations of categories, presheaves of modules over categories, representations of species, etc. In this series of papers we study them systematically, characterizing special homological objects in representation category and constructin

Pooya Alinian, Raziyeh Mohammadi, Azadeh Parvaneh, Ali Rejali

Recent economic developments of countries like Japan, Korea, and Singapore, as a result of improvement in the quality of their education, show that having a high-quality education may lead to economic growth. In this article, using some statistical methods, we argue that high quality education can change the economy towards higher growth. Therefore, for the

Hanyang Xing, Jian Liang, Liuming Liu, Peng Sun

The s-wave scattering of $\Sigma_c \bar{D}$ and $\Sigma_c \bar{D}^*$ in the $I(J^P) = \frac{1}{2}(\frac{1}{2}^-)$ channel is calculated in lattice QCD using two ensembles with different volumes but the same lattice spacing $a\sim 0.08\mathrm{fm}$ and pion mass $M_\pi \sim 294\mathrm{MeV}$. The scattering amplitudes near threshold are obtained by L\"uscher's

Prajwal Gatti, Abhirama Subramanyam Penamakuri, Revant Teotia, Anand Mishra

One characteristic that makes humans superior to modern artificially intelligent models is the ability to interpret images beyond what is visually apparent. Consider the following two natural language search queries - (i) "a queue of customers patiently waiting to buy ice cream" and (ii) "a queue of tourists going to see a famous Mughal architecture in India

Soonyoung Cha, Minjeong Kim, Youngjae Kim, Shinyoung Choi

Under strong laser fields, electrons in solids radiate high-harmonic fields by travelling through quantum pathways in Bloch bands in the sub-laser-cycle timescales. Understanding these pathways in the momentum space through the high-harmonic radiation can enable an all-optical ultrafast probe to observe coherent lightwave-driven processes and measure electro

Sunit Shantanu Digamber Fulari

Nature inspired algorithms has brought solutions to complex problems in optimization where the optimization and solution of complex problems is highly complex and nonlinear. There is a need to use proper design of the cost function or the fitness function in terms of the parameters to be optimized, this can be used in solving any type of such problems. In th

Gregory LeClaire Wagner, Navid C. Constantinou, Brandon G. Reichl

Studies of ocean surface transport often invoke the "Eulerian-mean hypothesis": that wave-agnostic general circulation models neglecting explicit surface waves effects simulate the Eulerian-mean ocean velocity time-averaged over surface wave oscillations. Acceptance of the Eulerian-mean hypothesis motivates reconstructing the total, Lagrangian-mean surface v

Parisa Pourghobadian, Kamran Divaani-Aazar, Ahad Rahimi

In this paper, we establish the global analogues of some dualities and equivalences in local algebra by developing the theory of relative Cohen-Macaulay modules. Let R be a commutative Noetherian ring (not necessarily local) with identity and a a proper ideal of R. The notions of a-relative dualizing modules and a-relative big Cohen-Macaulay modules are intr

Krishna Sandeep Ayyagari, Sherin Ann Abraham, Yiyun Yao, Shibani Ghosh

The adoption of distributed energy resources such as photovoltaics (PVs) has increased dramatically during the previous decade. The increased penetration of PVs into distribution networks (DNs) can cause voltage fluctuations that have to be mitigated. One of the key utility assets employed to this end are step-voltage regulators (SVRs). It is desirable to in

Po-Han Hou, Wei-Chih Lin, Hong-Chun Hou, Yu-Hao Huang

With a rising attention for the issue of PM2.5 or PM0.3, particulate matters have become not only a potential threat to both the environment and human, but also a harming existence to instruments onboard International Space Station (ISS). Our team is aiming to relate various concentration of particulate matters to magnetic fields, humidity, acceleration, tem

Chengyuan Liu, Leilei Gan, Kun Kuang, Fei Wu

The aim of Logic2Text is to generate controllable and faithful texts conditioned on tables and logical forms, which not only requires a deep understanding of the tables and logical forms, but also warrants symbolic reasoning over the tables. State-of-the-art methods based on pre-trained models have achieved remarkable performance on the standard test dataset

CMS Collaboration

The first study of the shapes of jets arising from bottom (b) quarks in heavy ion collisions is presented. Jet shapes are studied using charged hadron constituents as a function of their radial distance from the jet axis. Lead-lead (PbPb) collision data at a nucleon-nucleon center-of-mass energy of $\sqrt{s_\mathrm{NN}}$ = 5.02 TeV were recorded by the CMS d