January 2022 arXiv papers — page 69

Jaiyoung Park, Michael Jaemin Kim, Wonkyung Jung, Jung Ho Ahn

Hybrid private inference (PI) protocol, which synergistically utilizes both multi-party computation (MPC) and homomorphic encryption, is one of the most prominent techniques for PI. However, even the state-of-the-art PI protocols are bottlenecked by the non-linear layers, especially the activation functions. Although a standard non-linear activation function

Libo Chen

As an integral part of assessing the seismic performance of structures, the probabilistic seismic demand-intensity relationship has been widely studied. In this study, the phenomenon of heteroscedasticity in probabilistic seismic demand models was systematically investigated. A brief review of the definition, diagnosis, and conventional treatment of heterosc

Daxin Xu

Faltings conjectured that under the p-adic Simpson correspondence, finite dimensional p-adic representations of the geometric étale fundamental group of a smooth proper p-adic curve X are equivalent to semi-stable Higgs bundles of degree zero over X. In this article, we establish, over a p-adic curve of genus $g\ge 2$, an equivalence between these representa

Hengcan Shi, Munawar Hayat, Yicheng Wu, Jianfei Cai

Object proposal generation is an important and fundamental task in computer vision. In this paper, we propose ProposalCLIP, a method towards unsupervised open-category object proposal generation. Unlike previous works which require a large number of bounding box annotations and/or can only generate proposals for limited object categories, our ProposalCLIP is

Mathias Schubert, Sean Knight, Steffen Richter, Philipp Kühne

We report on terahertz (THz) electron paramagnetic resonance generalized spectroscopic ellipsometry (THz-EPR-GSE). Measurements of the field and frequency dependencies of the magnetic response due to the spin transitions associated with the nitrogen defect in 4H-SiC are shown as an example. THz-EPR-GSE dispenses with the need of a cavity, permits independent

Luis Alvarez, Cristine Pinto, Vladimir Ponczek

Is homophily in social and economic networks driven by a taste for homogeneity (preferences) or by a higher probability of meeting individuals with similar attributes (opportunity)? This paper studies identification and estimation of an iterative network game that distinguishes between these two mechanisms. Our approach enables us to assess the counterfactua

Davoud Adinehloo, Weilu Gao, Ali Mojibpour, Junichiro Kono

The electrical conductivity of a macroscopic assembly of nanomaterials is determined through a complex interplay of electronic transport within and between constituent nano-objects. Phonons play dual roles in this situation: their increased populations tend to reduce the conductivity via electron scattering while they can boost the conductivity by assisting

Xiuyi Fan, Francesca Toni

It is widely acknowledged that transparency of automated decision making is crucial for deployability of intelligent systems, and explaining the reasons why some decisions are "good" and some are not is a way to achieving this transparency. We consider two variants of decision making, where "good" decisions amount to alternatives (i) meeting "most" goals, an

Evan Johnson, Alan Hastings

The storage effect is a general explanation for coexistence in a variable environment. The generality of the storage effect is both a strength - it can be quantified in many systems - and a challenge - there is not a clear relationship between the abstract conditions for storage effect and species' life-history traits (e.g., dormancy, stage-structure, non-ov

Wenjie Dou, Joonho Lee, David R. Reichman, Roi Baer

We develop a time dependent second order Green's function theory (GF2) for calculating neutral excited states in molecules. The equation of motion for the lesser Green's function (GF) is derived within the adiabatic approximation to the Kadanoff-Baym (KB) equation using the second order Born approximation for the self-energy. In the linear response regime, w

Takao Watanabe

For an infinite word $x$, Bugeaud and Kim introduced a quantity $\mathrm{rep}(x)$ called the exponent of repetition of $x$. We prove that $\mathrm{rep}(x) = \mathrm{rep}(y)$ holds for a Sturmian word $x$ and every suffix $y$ of $x$. Let $c$ be the characteristic Sturmian word of slope $\theta$. When $\theta$ is a quadratic irrational, a formula of $\mathrm{r

Fuad M. Saradzhev

The generalized Levy-Leblond equation (GLL) is used to study the bound state problem for a non-relativistic Fermi field in external potentials. A condition when the rest energy term can be removed from the GLL equation is determined. For external potentials which do not obey the condition, the bound state spectrum is affected non-trivially by the rest energy

Evan C. Johnson, Oscar Godoy, Alan Hastings

The storage effect is a well-known explanation for coexistence in temporally varying environments. Like many complex ecological theories, the storage effect is often used as an explanation for observed coexistence on the basis of heuristic understanding, rather than careful application of a detailed model. One interpretation states that species coexist by sp

Hengcan Shi, Munawar Hayat, Jianfei Cai

Referring expression grounding is an important and challenging task in computer vision. To avoid the laborious annotation in conventional referring grounding, unpaired referring grounding is introduced, where the training data only contains a number of images and queries without correspondences. The few existing solutions to unpaired referring grounding are

Kazuma Iwamoto, Tsubasa Ochiai, Marc Delcroix, Rintaro Ikeshita

It is challenging to improve automatic speech recognition (ASR) performance in noisy conditions with single-channel speech enhancement (SE). In this paper, we investigate the causes of ASR performance degradation by decomposing the SE errors using orthogonal projection-based decomposition (OPD). OPD decomposes the SE errors into noise and artifact components

N. Fang, D. Yamashita, S. Fujii, K. Otsuka

The unique optical properties of two-dimensional layered materials are attractive for achieving increased functionality in integrated photonics. Owing to the van der Waals nature, these materials are ideal for integrating with nanoscale photonic structures. Here we report on carefully designed air-mode silicon photonic crystal nanobeam cavities for efficient

Chikun Ding, Yu Shi, Jun Chen, Yuebing Zhou

In this paper we obtain an exact high dimensional anti-de Sitter (AdS) black hole solution in Einstein-bumblebee gravity theory. This AdS-like black hole can only exist with a linear functional potential of the bumblebee field. We find that the Smarr formula and the first law of black hole thermodynamics can still be constructed in this Lorentz symmetry brea

Gabriel Chandler, Wolfgang Polonik

This work proposes and investigates a novel method for anomaly detection and shows it to be competitive in a variety of Euclidean and non-Euclidean situations. It is based on an extension of the depth quantile functions (DQF) approach. The DQF approach encodes geometric information about a point cloud via functions of a single variable, whereas each observat

Yang Ge, Yashar Komijani

Two-channel Kondo lattice serves as a model for a growing family of heavy-fermion compounds. We employ the dynamical large-N technique and go beyond the independent bath approximation to study this model both numerically and analytically using renormalization group ideas. We show that the Kondo effect induces dynamic magnetic correlations that lead to an eme

Mubark B Jedh, Jian Kai Lee, Lotfi ben Othmane

Attackers demonstrated the use of remote access to the in-vehicle network of connected vehicles to launch cyber-attacks and remotely take control of these vehicles. Machine-learning-based Intrusion Detection Systems (IDSs) techniques have been proposed for the detection of such attacks. The evaluation of some of these IDS demonstrated their efficacy in terms

Will Gilbert, Tuomo Tanttu, Wee Han Lim, MengKe Feng

Once called a "classically non-describable two-valuedness" by Pauli , the electron spin is a natural resource for long-lived quantum information since it is mostly impervious to electric fluctuations and can be replicated in large arrays using silicon quantum dots, which offer high-fidelity control. Paradoxically, one of the most convenient control strategie

Raghavendra Addanki, Andrew McGregor, Alexandra Meliou, Zafeiria Moumoulidou

Given an $n$-point metric space $(\mathcal{X},d)$ where each point belongs to one of $m=O(1)$ different categories or groups and a set of integers $k_1, \ldots, k_m$, the fair Max-Min diversification problem is to select $k_i$ points belonging to category $i\in [m]$, such that the minimum pairwise distance between selected points is maximized. The problem wa

Rajiv R. P. Singh, Jaan Oitmaa

We develop finite temperature strong coupling expansions for the SU(N) Hubbard Model in powers of $\beta t$, $w=\exp{(-\beta U)}$ and ${1\over \beta U}$ for arbitrary filling. The expansions are done in the grand canonical ensemble and are most useful at a density of one particle per site, where for $U$ larger than or of order the Bandwidth, the expansions c

Kenzo Ogure

We investigate how neural networks (NNs) understand physics using 1D quantum mechanics. After training an NN to accurately predict energy eigenvalues from potentials, we used it to confirm the NN's understanding of physics from four different aspects. The trained NN could predict energy eigenvalues of different kinds of potentials than the ones learned, pred

Nima Mobadersany

Acoustic microstreaming has several industrial, therapeutic, and biomedical applications - Acoustic cleaning, micromixing, microfluid transport, hemolysis, sonoporation. The acoustic microstreaming due to the oscillation of ultrasound contrast microbubbles in the middle of the gap between two parallel walls is studied numerically. Axisymmetric Boundary Eleme

Shoichi Naito, Shintaro Sawada, Chihiro Nakagawa, Naoya Inoue

Providing feedback on the argumentation of the learner is essential for developing critical thinking skills, however, it requires a lot of time and effort. To mitigate the overload on teachers, we aim to automate a process of providing feedback, especially giving diagnostic comments which point out the weaknesses inherent in the argumentation. It is recommen

Yuto Yokoyama, Akane Tanaka, Yoshiyuki Tagawa

Previous studies suggest that the behaviour of impacting blood is similar to that of a Newtonian fluid, which has a shear viscosity equivalent to that of blood at high shear rates. To understand this important fact, we conducted comparative experiments of droplet impact on a glass surface using whole blood and three solutions with a shear viscosity similar t

Alejandra Rocha-Solache, Iván Rodríguez-Montoya, David Sánchez-Argüelles, Itziar Aretxaga

The complex physics involved in atmospheric turbulence makes it very difficult for ground-based astronomy to build accurate scintillation models and develop efficient methodologies to remove this highly structured noise from valuable astronomical observations. We argue that a Deep Learning approach can bring a significant advance to treat this problem becaus

Josselin Garnier, Knut Solna

We present a theory for wave scintillation in the situation with a time-dependent partially coherent source and a time-dependent randomly heterogeneous medium. Our objective is to understand how the scintillation index of the measured intensity depends on the source and medium parameters. We deduce from an asymptotic analysis of the random wave equation a ge

Shuzhe Shi, Sangyong Jeon, Charles Gale

We report on the discovery of new analytical solutions of the equations of relativistic ideal hydrodynamics. In this solution, the fluid expands in the longitudinal direction and contains a plateau structure that extends over a finite range in rapidity and can be either symmetric or asymmetric in that variable. We further calculate the corresponding pseudo-r

Hongxiang Qiu, Marco Carone, Alex Luedtke

Estimation and evaluation of individualized treatment rules have been studied extensively, but real-world treatment resource constraints have received limited attention in existing methods. We investigate a setting in which treatment is intervened upon based on covariates to optimize the mean counterfactual outcome under treatment cost constraints when the t

Kirtus G. Leyba, Joshua J. Daymude, Jean-Gabriel Young, M. E. J. Newman

The Border Gateway Protocol (BGP) is a distributed protocol that manages interdomain routing without requiring a centralized record of which autonomous systems (ASes) connect to which others. Many methods have been devised to infer the AS topology from publicly available BGP data, but none provide a general way to handle the fact that the data are notoriousl

Cormac O'Raifeartaigh

Soon after he proposed three classic observational tests for the general theory of relativity, Einstein realised that a consistent description of the universe as a whole provided another important challenge for the theory. In this essay, we recall how general relativity found important application in the nascent field of cosmology, from the static models of

A. Malyeyev, I. Titov, C. D. Dewhurst, K. Suzuki

Based on Brown's static equations of micromagnetics, we compute the uniaxial polarization of the scattered neutron beam of a bulk magnetic material. The theoretical expressions are compared to experimental data on a soft magnetic nanocrystalline alloy. The micromagnetic SANS theory provides a general framework for polarized real-space neutron methods, an

Gonzalo Manzano, Édgar Roldán

We derive universal bounds for the finite-time survival probability of the stochastic work extracted in steady-state heat engines and the stochastic heat dissipated to the environment. We also find estimates for the time-dependent thresholds that these quantities does not surpass with a prescribed probability. At long times, the tightest thresholds are propo

M. E. Villalba, F. A. Gómez Albarracín, D. C. Cabra, H. D. Rosales

Engineering non trivial topological phases in materials, specially skyrmion-like arrangements, has been of great interest in the last decade due to its potential technological applications. In this work, we study a model of electrons coupled to a magnetic texture in the kagome lattice interacting with magnetic moments via Rashba spin orbit coupling in the la

Gregory Berkolaiko, Graham Cox, Bernard Helffer, Mikael Persson Sundqvist

Recent work of the authors and their collaborators has uncovered fundamental connections between the Dirichlet-to-Neumann map, the spectral flow of a certain family of self-adjoint operators, and the nodal deficiency of a Laplacian eigenfunction (or an analogous deficiency associated to a non-bipartite equipartition). Using a refined construction of the Diri

Evan Johnson, Alan Hastings

How do species coexist? A framework known as Modern Coexistence Theory measures mechanisms of coexistence by comparing a species perturbed to low density (the invader) to other species that remain at their typical densities (the residents); this invader-resident comparison measures a rare-species advantage that results from specialization. However, there are

Francesco Danzi, James M. Gibert

The pattern of formation of resonant frequency clusters in idealized sympodial dichasium trees is revealed by numerical modeling and analysis. The larger cluster's cardinality correlates with that of a Small World Network, which share the same adjacency matrix. Topology and inherent symmetry of the structure dictate compartmentalization of the modal characte

Bárbara C. e Souza, Filipi N. Silva, Henrique F. de Arruda, Giovana D. da Silva

Several complex systems are characterized by presenting intricate characteristics taking place at several scales of time and space. These multiscale characterizations are used in various applications, including better understanding diseases, characterizing transportation systems, and comparison between cities, among others. In particular, texts are also char

Yu Hamada, Ryuichiro Kitano, Ryutaro Matsudo, Hiromasa Takaura

The ultra-cold muon technology developed for the muon $g-2$ experiment at J-PARC provides a low emittance $\mu^+$ beam which can be accelerated and used for realistic collider experiments. We consider the possibility of new collider experiments by accelerating the $\mu^+$ beam up to 1 TeV. Allowing the $\mu^+$ beam to collide with a high intensity $e^-$ beam

Christian Bagshaw

Building upon the work of A. Booker and C. Pomerance (2017), we prove that for a prime power $q \geq 7$, every residue class modulo an irreducible polynomial $F \in \mathbb{F}_q[X]$ has a non-constant, square-free representative which has no irreducible factors of degree exceeding $\text{deg}~F -1$. We also give applications to generating sequences of irredu

Edwin Beggs, Shahn Majid

We study geodesics flows on curved quantum Riemannian geometries using a recent formulation in terms of bimodule connections and completely positive maps. We complete this formalism with a canonical $*$ operation on noncommutative vector fields. We show on a classical manifold how the Ricci tensor arises naturally in our approach as a term in the convective

Alessandro Carderi, Matthieu Joseph, François Le Maître, Romain Tessera

Belinskaya's theorem states that given an ergodic measure-preserving transformation, any other transformation with the same orbits and an $\mathrm{L}^1$ cocycle must be flip-conjugate to it. Our main result shows that this theorem is optimal: for all $p<1$ the integrability condition on the cocycle cannot be relaxed to being in $\mathrm{L}^p$. This also allo

Regina S. Burachik, Bethany I. Caldwell, C. Yalçın Kaya, Walaa M. Moursi

The Douglas-Rachford and Peaceman-Rachford algorithms have been successfully employed to solve convex optimization problems, or more generally find zeros of monotone inclusions. Recently, the behaviour of these methods in the inconsistent case, i.e., in the absence of solutions has triggered significant consideration. It has been shown that under mild assump

A. A. Leha, A. P. Zhuravel, A. Karpov, A. V. Lukashenko

Superconducting microcircuits and metamaterials are promising candidates for use in new generation cryogenic electronics. Their functionality is largely justified by the macroscopic distribution of electromagnetic fields in arranged unit cells, rather than by the microscopic properties of composite materials. We present a new method for visualizing the spati

Hao Guo, Behrooz Makki, Magnus Åström, Mohamed-Slim Alouini

Internet-of-vehicle (IoV) is a general concept referring to, e.g., autonomous drive based vehicle-to-everything (V2X) communications or moving relays. Here, high rate and reliability demands call for advanced multi-antenna techniques and millimeter-wave (mmw) based communications. However, the sensitivity of the mmw signals to blockage may limit the system p

Yiling Jia, Hongning Wang

Existing online learning to rank (OL2R) solutions are limited to linear models, which are incompetent to capture possible non-linear relations between queries and documents. In this work, to unleash the power of representation learning in OL2R, we propose to directly learn a neural ranking model from users' implicit feedback (e.g., clicks) collected on the f

Guendalina Caldarini, Sardar Jaf, Kenneth McGarry

Chatbots are intelligent conversational computer systems designed to mimic human conversation to enable automated online guidance and support. The increased benefits of chatbots led to their wide adoption by many industries in order to provide virtual assistance to customers. Chatbots utilise methods and algorithms from two Artificial Intelligence domains: N

Leo Kozachkov, Patrick M. Wensing, Jean-Jacques Slotine

We prove that Riemannian contraction in a supervised learning setting implies generalization. Specifically, we show that if an optimizer is contracting in some Riemannian metric with rate $\lambda > 0$, it is uniformly algorithmically stable with rate $\mathcal{O}(1/\lambda n)$, where $n$ is the number of labelled examples in the training set. The results ho

Tahar Allouche, Jérôme Lang, Florian Yger

Epistemic voting interprets votes as noisy signals about a ground truth. We consider contexts where the truth consists of a set of objective winners, knowing a lower and upper bound on its cardinality. A prototypical problem for this setting is the aggre-gation of multi-label annotations with prior knowledge on the size of the ground truth. We posit noisemod

Mihael Eraković, Marko T. Cvitaš

A combined approach that uses the vibrational self-consistent field (VSCF) and vibrational configuration interaction (VCI) method together with the semiclassical instanton theory was developed to study vibrational tunneling spectra of molecules with multiple wells. The method can be applied to calculate low-lying vibrational states in the systems with arbitr

Hannes Westermann, Jaromir Savelka, Vern R. Walker, Kevin D. Ashley

Machine learning research typically starts with a fixed data set created early in the process. The focus of the experiments is finding a model and training procedure that result in the best possible performance in terms of some selected evaluation metric. This paper explores how changes in a data set influence the measured performance of a model. Using three

Ali Nejat, Laura Solitare, Edward Pettitt, Hamed Mohsenian-Rad

Community resilience in the face of natural hazards relies on a community's potential to bounce back. A failure to integrate equity into resilience considerations results in unequal recovery and disproportionate impacts on vulnerable populations, which has long been a concern in the United States. This research investigated aspects of equity related to commu

Balint Varga, Jairo Inga, Soeren Hohmann

This paper presents a systematic method for the design of a limited information shared control (LISC). LISC is used in applications where not all system states or reference trajectories are measurable by the automation. Typical examples are partially human-controlled systems, in which some subsystems are fully controlled by automation while others are contro

Aziz Burak Gulen, Alexander McCleary

We present a new language for persistent homology in terms of Galois connections. This language has two main advantages over traditional approaches. First, it simplifies and unifies central concepts such as interleavings and matchings. Second, it provides access to Rota's Galois connection theorem -- a powerful tool with many potential applications in applie

Josselin Garnier, Knut Sølna

A theory for the characterization of the fourth moment of electromagnetic wave beams is presented in the case when the source is partially coherent. A Gaussian-Schell model is used for the partially coherent random source. The white-noise paraxial regime is considered, which holds when the wavelength is much smaller than the correlation radius of the source,

Haozhe Sun, Wei-Wei Tu, Isabelle Guyon

We introduce OmniPrint, a synthetic data generator of isolated printed characters, geared toward machine learning research. It draws inspiration from famous datasets such as MNIST, SVHN and Omniglot, but offers the capability of generating a wide variety of printed characters from various languages, fonts and styles, with customized distortions. We include 9

Ron Mittelhammer, George Judge, Miguel Henry

In this paper, we introduce a flexible and widely applicable nonparametric entropy-based testing procedure that can be used to assess the validity of simple hypotheses about a specific parametric population distribution. The testing methodology relies on the characteristic function of the population probability distribution being tested and is attractive in

Patrick Graf

We study the failure of the Lipman-Zariski conjecture in positive characteristic. For rational double points, the conjecture holds true except for a short finite list of exceptions. For log canonical surface singularities, the conjecture continues to hold with the same list of exceptions under an additional tameness hypothesis. In particular, among rational

Gang Chen, Peng Peng, Peihan Zhang, Wei Dong

Obstacle avoidance of quadrotors in dynamic environments is still a very open problem. Current works commonly leverage traditional static maps to represent static obstacles and the detection and tracking of moving objects (DATMO) method to model dynamic obstacles separately. The detection module requires pre-training, and the dynamic obstacles can only be mo

Arnav Vaibhav Malawade, Trier Mortlock, Mohammad Abdullah Al Faruque

Although autonomous vehicles (AVs) are expected to revolutionize transportation, robust perception across a wide range of driving contexts remains a significant challenge. Techniques to fuse sensor data from camera, radar, and lidar sensors have been proposed to improve AV perception. However, existing methods are insufficiently robust in difficult driving c

Andrea Agazzi, Jonathan C. Mattingly, Omar Melikechi

We introduce a family of stochastic models motivated by the study of nonequilibrium steady states of fluid equations. These models decompose the deterministic dynamics of interest into fundamental building blocks, i.e., minimal vector fields preserving some fundamental aspects of the original dynamics. Randomness is injected by sequentially following each ve

Alireza Rezazadeh, Yasamin Jafarian, Ali Kord

Image classification is widely used to build predictive models for breast cancer diagnosis. Most existing approaches overwhelmingly rely on deep convolutional networks to build such diagnosis pipelines. These model architectures, although remarkable in performance, are black-box systems that provide minimal insight into the inner logic behind their predictio

Julien Abadji, Pedro Ortiz Suarez, Laurent Romary, Benoît Sagot

The need for raw large raw corpora has dramatically increased in recent years with the introduction of transfer learning and semi-supervised learning methods to Natural Language Processing. And while there have been some recent attempts to manually curate the amount of data necessary to train large language models, the main way to obtain this data is still t

Santiago F. Caballero-Benítez

This article gives details of the course on "Quantum Matter in optical lattices and high-Q cavities" given at the School of Physics XXVIII at UNAM in 2021. The notes describe useful concepts for analog quantum simulation and details of models in optical lattices and high-Q cavities. The notes are in Spanish. En este art\'iculo se discuten algunos detalles de

Shashwat Goel, Ameya Prabhu, Amartya Sanyal, Ser-Nam Lim

Machine Learning models face increased concerns regarding the storage of personal user data and adverse impacts of corrupted data like backdoors or systematic bias. Machine Unlearning can address these by allowing post-hoc deletion of affected training data from a learned model. Achieving this task exactly is computationally expensive; consequently, recent w

Haedong Park, Wenlong Gao, Xiao Zhang, Sang Soon Oh

Topological insulators constitute one of the most intriguing phenomena in modern condensed matter theory. The unique and exotic properties of topological states of matter allow for unidirectional gapless electron transport and extremely accurate measurements of the Hall conductivity. Recently, new topological effects occurring at Dirac/Weyl points have been

Kirill Solovev, Nicolas Pröllochs

Social media has become an indispensable channel for political communication. However, the political discourse is increasingly characterized by hate speech, which affects not only the reputation of individual politicians but also the functioning of society at large. In this work, we empirically analyze how the amount of hate speech in replies to posts from p

H. Y. Yuan, W. P. Sterk, Akashdeep Kamra, Rembert A. Duine

For a wide range of nonclassical magnonic states that have been proposed and demonstrated recently, a new time scale besides the magnon lifetime - the magnon dephasing time - becomes important, but this time scale is rarely studied. Considering exchange interaction and spin-phonon coupling, we evaluate the pure magnon dephasing time and find it to be smaller

Pierre Mathonet, Michel Rigo, Manon Stipulanti, Naïm Zénaïdi

We consider the sequence of integers whose $n$th term has base-$p$ expansion given by the $n$th row of Pascal's triangle modulo $p$ (where $p$ is a prime number). We first present and generalize well-known relations concerning this sequence. Then, with the great help of Sloane's On-Line Encyclopedia of Integer Sequences, we show that it appears naturally as

Sebastien Valeyre

This paper derives an optimal portfolio that is based on trend-following signal. Building on an earlier related article, it provides a unifying theoretical setting to introduce an autocorrelation model with the covariance matrix of trends and risk premia. We specify practically relevant models for the covariance matrix of trends. The optimal portfolio is dec

Daniel Bossaller, Daniel Herden, Alexandra V. Pasi

In this paper, we address the question of when a non-free $\aleph_1$-free group $H$ can be be free in a transitive cardinality-preserving model extension. Using the $\Gamma$-invariant, denoted $\Gamma(H)$, we present a necessary and sufficient condition resolving this question for $\aleph_1$-free groups of cardinality $\aleph_1$. Specifically, if $\Gamma(H)

Kyu Jung Bae, Howard Baer, Vernon Barger, Robert Wiley Deal

The cosmological moduli problem (CMP) comes in three parts: 1. potential violation of BBN constraints from late decaying moduli fields, 2. the moduli-induced gravitino problem wherein gravitinos are overproduced and 3. the moduli-induced lightest SUSY particle (LSP) overproduction problem. We examine the cosmological moduli problem and its connection to elec

Santiago Badia, Eric Neiva, Francesc Verdugo

In this work, we propose a novel formulation for the solution of partial differential equations using finite element methods on unfitted meshes. The proposed formulation relies on the discrete extension operator proposed in the aggregated finite element method. This formulation is robust with respect to the location of the boundary/interface within the cell.

Björn Liljegren-Sailer

A priori error bounds have been derived for different balancing-related model reduction methods. The most classical result is a bound for balanced truncation and singular perturbation approximation that is applicable for asymptotically stable linear time-invariant systems with homogeneous initial conditions. Recently, there have been a few attempts to genera

Michael Griffin, Ken Ono, Wei-Lun Tsai

Motivated by the many roles that hook lengths play in mathematics, we study the distribution of the number of $t$-hooks in the partitions of $n$. We prove that the limiting distribution is normal with mean $\mu_t(n)\sim \frac{\sqrt{6n}}{\pi}-\frac{t}{2}$ and variance $\sigma_t^2(n)\sim \frac{(\pi^2-6)\sqrt{6n}}{2\pi^3}.$ Furthermore, we prove that the distri

Eung-Joo Lee, Damon M. Conover, Shuvra S. Bhattacharyyaa, Heesung Kwon

Object detection is increasingly used onboard Unmanned Aerial Vehicles (UAV) for various applications; however, the machine learning (ML) models for UAV-based detection are often validated using data curated for tasks unrelated to the UAV application. This is a concern because training neural networks on large-scale benchmarks have shown excellent capability

Indu Kant Deo, Rajeev Jaiman

In this paper, we present a deep learning technique for data-driven predictions of wave propagation in a fluid medium. The technique relies on an attention-based convolutional recurrent autoencoder network (AB-CRAN). To construct a low-dimensional representation of wave propagation data, we employ a denoising-based convolutional autoencoder. The AB-CRAN arch

Elisabeth Remm

We investigate formal deformations of certain classes of nonassociative algebras including classes of K[{\Sigma}3]-associative algebras, Lie-admissible algebras and anti-associative algebras. In a process which is similar to Poisson algebra for the associative case we identify for each type of algebra (A, {\mu}), an algebra (A, {\mu}, {\psi}) such that the f

Stanley Bak, Hoang-Dung Tran

ACAS Xu is an air-to-air collision avoidance system designed for unmanned aircraft that issues horizontal turn advisories to avoid an intruder aircraft. Due the use of a large lookup table in the design, a neural network compression of the policy was proposed. Analysis of this system has spurred a significant body of research in the formal methods community

Suma Murthy, Raffaella Morganti, Nissim Kanekar, Tom Oosterloo

We present a search for associated HI 21 cm absorption in a sample of 29 radio-loud active galactic nuclei (AGNs) at $0.7 < z < 1$, carried out with the upgraded Giant Metrewave Radio Telescope. We detect HI 21 cm absorption against none of our target AGNs, obtaining $3\sigma$ upper limits to the optical depth of $\lesssim$ 1% per 50 km s$^{-1}$ channel. The

Donia Ben Amor, Michael Joham, Wolfgang Utschick

In this work, we present new results for the application of rate splitting multiple access (RSMA) to the downlink (DL) of a massive multiple-input-multiple-output (MaMIMO) system operating in frequency-division-duplex (FDD) mode. Due to the lack of uplink (UL) - DL channel reciprocity in such systems, explicit training in the DL has to be performed in order

Anders Rønn-Nielsen, Mads Stehr

We consider a stationary random field indexed by an increasing sequence of subsets of $\mathbb{Z}^d$ obeying a very broad geometrical assumption on how the sequence expands. Under certain mixing and local conditions, we show how the tail distribution of the individual variables relates to the tail behavior of the maximum of the field over the index sets in t

Maria Jose Pacifico, Fan Yang, Jiagang Yang

In this note, we consider the thermodynamic formalism for Lorenz attractors of flows in any dimension. Under a mild condition on the H\"older continuous potential function $\phi$, we prove that for an open and dense subset of $C^1$ vector fields, every Lorenz attractor supports a unique equilibrium state. In particular, we obtain the uniqueness for the measu

Kathrin Hanauer, Monika Henzinger, Stefan Schmid, Jonathan Trummer

Reconfigurable optical topologies promise to improve the performance in datacenters by dynamically optimizing the physical network in a demand-aware manner. State-of-the-art optical technologies allow to establish and update direct connectivity (in the form of edge-disjoint matchings) between top-of-rack switches within microseconds or less. However, to full

Jacek Krzywinski, Aliaksei Halavanau

This paper describes how to efficiently solve time-dependent x-ray dynamic diffraction problems in distorted crystals with an FFT-based beam propagation method (FFT BPM). We show examples of using the technique to simulate the propagation of x-ray beams in deformed crystals in space and time domains relevant to the cavity-based x-ray Free Electron Lasers (CB

Sergio Sánchez-Ramírez, Javier Conejero, Francesc Lordan, Anna Queralt

With the advent of more powerful Quantum Computers, the need for larger Quantum Simulations has boosted. As the amount of resources grows exponentially with size of the target system Tensor Networks emerge as an optimal framework with which we represent Quantum States in tensor factorizations. As the extent of a tensor network increases, so does the size of

Mustafa O. Karabag, Cyrus Neary, Ufuk Topcu

In a cooperative multiagent system, a collection of agents executes a joint policy in order to achieve some common objective. The successful deployment of such systems hinges on the availability of reliable inter-agent communication. However, many sources of potential disruption to communication exist in practice, such as radio interference, hardware failure

Mengshu Sun, Haoyu Ma, Guoliang Kang, Yifan Jiang

The transformer architectures with attention mechanisms have obtained success in Nature Language Processing (NLP), and Vision Transformers (ViTs) have recently extended the application domains to various vision tasks. While achieving high performance, ViTs suffer from large model size and high computation complexity that hinders the deployment of them on edg

Marina Bertolini, Gilberto Bini, Cristina Turrini

Grassmann tensors arise from classical problems of scene reconstruction in computer vision. In particular, bifocal Grassmann tensors, related to a pair of projections from a projective space onto view-spaces of varying dimensions, generalise the classical notion of fundamental matrices. In this paper we study in full generality the variety of bifocal Grassma

Diogo Faustino, Nuno Gonçalves, Manuel Portela, António Rito Silva

The agility inherent to today's business promotes the definition of software architectures where the business entities are decoupled into modules and/or services. However, there are advantages in having a rich domain model, where domain entities are tightly connected, because it fosters an initial quick development. On the other hand, the split of the busine

Mathieu Chambefort, Raphaël Butez, Emilie Chautru, Stephan Clémençon

In image denoising problems, the increasing density of available images makes an exhaustive visual inspection impossible and therefore automated methods based on machine-learning must be deployed for this purpose. This is particulary the case in seismic signal processing. Engineers/geophysicists have to deal with millions of seismic time series. Finding the

Sugata Chowdhury, Heather M. Hill, Albert F. Rigosi, Patrick M. Vora

Two-dimensional (2D) materials that exhibit charge density waves (CDWs) have generated many research endeavors in the hopes of employing their exotic properties for various quantum-based technologies. Early investigations surrounding CDWs were mostly focused on bulk materials. However, applications for quantum devices have since required devices to be constr

Matteo Ciardi, Tommaso Macrì, Fabio Cinti

In this work, we explore the relevant methodology for the investigation of interacting systems with contact interactions, and we introduce a class of zonal estimators for path-integral Monte Carlo methods, designed to provide physical information about limited regions of inhomogeneous systems.We demonstrate the usefulness of zonal estimators by their applica

William E. Hurst, Kyungyong Lee, Li Li, George D. Nasr

Let $K$ be an algebraically closed field of characteristic 0. When the Jacobian $({\partial f}/{\partial x})({\partial g}/{\partial y}) - ({\partial g}/{\partial x})({\partial f}/{\partial y})$ is a constant for $f,g\in K[x,y]$, Magnus' formula from [A. Magnus, Volume preserving transformations in several complex variables, Proc. Amer. Math. Soc. 5 (1954), 2

R. S. Nascimento, A. Rodríguez-Ardila, L. Dahmer-Hahn, M. A. Fonseca-Faria

In this work, we study the optical properties of compact radio sources selected from the literature in order to determine the impact of the radio-jet in their circumnuclear environment. Our sample includes 58 Compact Steep Spectrum (CSS) and GigaHertz Peaked Spectrum (GPS) and 14 Megahertz-Peaked spectrum (MPS) radio sources located at $z\leq 1$. The radio l

J. D. Franson

Each mode $\small{j}$ of the electromagnetic field is mathematically equivalent to a harmonic oscillator described by a wave function $\small{\psi_j(x_j)}$ in the quadrature representation. An approach was recently introduced in which the wave function $\small{\psi_j(x_j)}$ was further quantized to produce a field operator $\small{{\hat \psi}_j(x_j)}$ [J.D.

Maryam Khalid, Emily Willis

Emotion prediction is a key emerging research area that focuses on identifying and forecasting the emotional state of a human from multiple modalities. Among other data sources, physiological data can serve as an indicator for emotions with an added advantage that it cannot be masked/tampered by the individual and can be easily collected. This paper surveys

Gustavo Kasper Facenda, Elad Domanovitz, Ashish Khisti, Wai-Tian Tan

This paper investigates the performance of streaming codes in low-latency applications over a multi-link three-node relayed network. The source wishes to transmit a sequence of messages to the destination through a relay. Each message must be reconstructed after a fixed decoding delay. The special case with one link connecting each node has been studied by F