December 2023 arXiv papers — page 11

Michael K. Brown, Prashanth Sridhar

A landmark theorem of Orlov relates the singularity category of a graded Gorenstein algebra to the derived category of the associated noncommutative projective scheme. We generalize this theorem to the setting of differential graded algebras. As an application, we obtain new cases of the Lattice Conjecture in noncommutative Hodge theory.

Augusto Damineli, Noel D. Richardson, Felipe Navarete, Theodore. R. Gull

Changes in the flux and spectrum of Eta Carinae since 1900 have been attributed to the evolution of the central binary by some. Others suggest evolution in the occulting ejecta. The brightness jump in the 1940s, which coincided with the appearance of narrow forbidden emission lines, may have been caused by the clearing and ionization of intervening circumste

Nisar Ahmed, Luke Burks, Kailah Cabral, Alyssa Bekai Rose

We consider the problem of evaluating dynamic consistency in discrete time probabilistic filters that approximate stochastic system state densities with Gaussian mixtures. Dynamic consistency means that the estimated probability distributions correctly describe the actual uncertainties. As such, the problem of consistency testing naturally arises in applicat

Xiongfang Liu, Tong Yang, Shanquan Chen, Jing Wu

Researchers pursuing advanced photoelectric devices have discovered near room-temperature metal-insulator transitions (MIT) in non-volatile VO2. Despite theoretical investigations suggesting that polaron dynamics mediate the MIT, direct experimental evidence remains scarce. In this study, we present direct evidence of the polaron state in insulating VO2 thro

David Amaro-Alcalá, Barry C. Sanders, Hubert de Guise

We introduce a characterisation scheme for a universal qutrit gate set. Motivated by the rising interest in qutrit systems, we apply our criteria to establish that our hyperdihedral group underpins a scheme to characterise the performance of a qutrit T gate. Our resulting qutrit scheme is feasible, as it requires resources and data analysis techniques simila

Cameron Zachreson, Ruarai Tobin, Camelia Walker, Eamon Conway

Residential aged-care facilities (RACFs, also called long-term care facilities, aged care homes, or nursing homes) have elevated risks of respiratory infection outbreaks and associated disease burden. During the COVID-19 pandemic, social isolation policies were commonly used in these facilities to prevent and mitigate outbreaks. We refer specifically to gene

Mageshwaran Tamilan, Gargi Shaw, Sudip Bhattacharyya, Kimitake Hayasaki

Tidal disruption event (TDE) iPTF16fnl shows a relatively low optical flare with observationally very weak X-ray emission and the spectroscopic property that the helium emission line from the source dominates over the hydrogen emission line at early times. We explore these observed signatures by calculating spectral emission lines with the publicly available

Haifeng Tang

Krylov complexity, as a novel measure of operator complexity under Heisenberg evolution, exhibits many interesting universal behaviors and also bounds many other complexity measures. In this work, we study Krylov complexity $\mathcal{K}(t)$ in Random Matrix Theory (RMT). In large $N$ limit: (1) For infinite temperature, we analytically show that the Lanczos

Binchao Zhang, Weidong Hu, Fan Yang, Shenheng Xu

Reducing the in-band radar cross section (RCS) of antennas has been a widely concerned problem. However, most of works focus on RCS reduction of antenna arrays, or need to additionally increase the size of a single antenna. Therefore, this work presents a method to control the null of the in-band RCS by changing the load impedance of the antenna without addi

Jude T. Anderson, David M. Williams

This paper provides a comprehensive guide to generating unconstrained, simplicial, four-dimensional (4D), hypervolume meshes for space-time applications. While several universal procedures for constructing unconstrained, d-dimensional, anisotropic Delaunay meshes are already known, many of the explicit implementation details are missing from the relevant lit

Nicholas Yan

Music has always been thought of as a "human" endeavor -- when praising a piece of music, we emphasize the composer's creativity and the emotions the music invokes. Because music also heavily relies on patterns and repetition in the form of recurring melodic themes and chord progressions, artificial intelligence has increasingly been able to replicate music

Tianyi Zhang, Caihua Wan, Xiufeng Han

We propose an in-plane magnon valve (MV), a sandwich structure composed of ferromagnetic insulator/heavy metal/ferromagnetic insulator (MI/HM/MI). When the magnetizations of the two MI layers are parallel, the longitudinal conductance in the HM layer is greater than that in the antiparallel state according to the magnetic proximity effect, termed as the in-p

Noah Cockram, Peter Ashwin, Ana Rodrigues

We establish conditions for the existence of a family of piecewise linear invariant curves in a two-parameter family of piecewise isometries on the upper half-plane known as Translated Cone Exchange Transformations. We show that these curves are embeddings of interval exchange transformations and give rise to layers of invariant regions. We also show the exi

Melrose Roderick, Felix Berkenkamp, Fatemeh Sheikholeslami, Zico Kolter

In many real-world problems, there is a limited set of training data, but an abundance of unlabeled data. We propose a new method, Generative Posterior Networks (GPNs), that uses unlabeled data to estimate epistemic uncertainty in high-dimensional problems. A GPN is a generative model that, given a prior distribution over functions, approximates the posterio

Gonzalo Ibañez-Firnkorn, Emanuel Ramadori

In this article, we introduce the fractional maximal operator on the Hyperbolic space, a non-doubling measure space, and study the weighted boundedness. Motivated in the weighted boundedness of Hardy-Littlewood maximal studied by Antezana and Ombrosi in [1], we give conditions for the weak type and strong type estimate for fractional maximal. Also, we provid

Chia-Min Lin, Rei Tamura, Keiko I. Nagao

We propose a model of uniform rate inflation on the brane. The potential is given by a hyperbolic cosine function plus a negative cosmological constant. The equation of motion is solved analytically without using slow-roll approximation. The result is that the inflaton field is rolling at a constant speed. The prediction for cosmological perturbations depend

Yannis Angelopoulos

We consider a supersonic flow past an airfoil in the context of the steady, isentropic and irrotational compressible Euler equations. We show that for appropriate data, either a shock forms, in which case certain derivatives of the solution blow up, or a sonic line forms, which translates to the fact that the hyperbolic character of the equations degenerates

Lei Fan, Yang Zhao

Terrain surface roughness, often described abstractly, poses challenges in quantitative characterisation with various descriptors found in the literature. This study compares five commonly used roughness descriptors, exploring correlations among their quantified terrain surface roughness maps across three terrains with distinct spatial variations. Additional

Martina Favero, Paul A. Jenkins

Wright-Fisher diffusions and their dual ancestral graphs occupy a central role in the study of allele frequency change and genealogical structure, and they provide expressions, explicit in some special cases but generally implicit, for the sampling probability, a crucial quantity in inference. Under a finite-allele mutation model, with possibly parent-depend

Noah Cockram, Peter Ashwin, Ana Rodrigues

In this paper, we investigate a class of non-invertible piecewise isometries on the upper half-plane known as Translated Cone Exchanges. These maps include a simple interval exchange on a boundary we call the baseline. We provide a geometric construction for the first return map to a neighbourhood of the vertex of the middle cone for a large class of paramet

Joshua Inman, Tanmay Khandait, Giulia Pedrielli, Lalitha Sankar

The performance of modern machine learning algorithms depends upon the selection of a set of hyperparameters. Common examples of hyperparameters are learning rate and the number of layers in a dense neural network. Auto-ML is a branch of optimization that has produced important contributions in this area. Within Auto-ML, hyperband-based approaches, which eli

Deepak Prakash Kumar, Sivakumar Rathinam, Swaroop Darbha, Trevor Bihl

In this article, a heuristic is proposed for a min-max heterogeneous multi-vehicle multi-depot traveling salesman problem (TSP), wherein heterogeneous vehicles start from given depot positions and need to cover a given set of targets. The vehicles should cover given targets such that the maximum tour time is minimized. In the considered problem, vehicles con

Lee-Peng Teo

This is the second volume of a textbook for a two-semester course in mathematical analysis. This second volume is about analysis of multi-variable functions. The topics covered include Euclidean spaces, convergence of sequences, open sets and closed sets, limits and continuity, uniform continuity, connectedness, compactness, intermediate value theorem, extre

Alessandro Barone, Shoji Hashimoto, Andreas Jüttner, Takashi Kaneko

We present a study on the nonperturbative calculation of observables for inclusive semileptonic decays of $B_{(s)}$ mesons using lattice QCD. We focus on the comparison of two different methods to analyse the lattice data of Euclidean correlation functions, specifically Chebyshev and Backus-Gilbert approaches. This type of computation may eventually provide

Bingchen Zhong, Min Shuai, Xi Chen, Vikina Martinez

The current intense study of ferroelectric nematic liquid crystals was initiated by the observation of the same ferroelectric nematic phase in two independently discovered organic rod-shaped mesogenic compounds, RM734 and DIO. We recently reported that the compound RM734 also exhibits a monotropic, low-temperature, antiferroelectric phase having reentrant is

Tetiana Obikhod, Ievgenii Petrenko

The cosmological observations of gravitational lenses, cosmic microwave background, rotation speed of stars in galaxies confirm the existence of about 27% dark matter in the Universe. The nature of these particles is unknown, however, there are theoretical models Beyond the Standard Model (BSM), such as superstrings and D-branes, which predict new particles

D. S. Almeida, R. R. Montenegro-Filho

We use the density matrix renormalization group (DMRG) and a hard-core boson map to investigate the quantum phase transitions present in the phase diagram of the frustrated Heisenberg ladder in a magnetic field. The quantum bicritical point is observed at the end of a first-order transition line, which is at the meeting of the two second-order transition lin

Spandan Choudhury, Jaime E. Pineda, Paola Caselli, Michael Chun-Yuan Chen

Aims. We aim to study the structure and kinematics of the two filaments inside the subsonic core Barnard 5 in Perseus using high-resolution ($\approx$ 2400 au) NH3 data and a multi-component fit analysis. Methods. We used observations of NH3 (1,1) and (2,2) inversion transitions using the Very Large Array (VLA) and the Green Bank Telescope (GBT). We smoothed

Chuan Wen, Xingyu Lin, John So, Kai Chen

Learning from demonstration is a powerful method for teaching robots new skills, and having more demonstration data often improves policy learning. However, the high cost of collecting demonstration data is a significant bottleneck. Videos, as a rich data source, contain knowledge of behaviors, physics, and semantics, but extracting control-specific informat

Matteo Ninniri, Marco Podda, Davide Bacciu

This work focuses on the task of property targeting: that is, generating molecules conditioned on target chemical properties to expedite candidate screening for novel drug and materials development. DiGress is a recent diffusion model for molecular graphs whose distinctive feature is allowing property targeting through classifier-based (CB) guidance. While C

Xiaobo Liu

The Paterson--Stockmeyer method is an evaluation scheme for matrix polynomials with scalar coefficients that arise in many state-of-the-art algorithms based on polynomial or rational approximation, for example, those for computing transcendental matrix functions. We derive a mixed-precision version of the Paterson--Stockmeyer method that is particularly usef

Yixun Xing, Casey Moore, Debabrata Saha, Dan Nguyen

Achieving effective synergy between radiotherapy and immunotherapy is critical for optimizing tumor control and treatment outcomes. To explore the underlying mechanisms of this synergy, we have investigated a novel treatment approach known as personalized ultra-fractionated stereotactic adaptive radiation therapy (PULSAR), which emphasizes the impact of radi

Rupert Klein, Xin Liu

In this paper, we investigate the boundary layer arising from the fast internal waves in the Boussinesq equations with the Brunt-Vais\"al\"a frequency of order $ \mathcal O(1/\varepsilon) $. For the homogeneous-in-height stratification, previous work by \emph{Desjardins, Lannes, Saut, 3(1):153--192, Water Waves, 2021} establishes uniform-in-$\epsilon$ estima

James Kotary, Jacob Christopher, My H Dinh, Ferdinando Fioretto

The integration of constrained optimization models as components in deep networks has led to promising advances on many specialized learning tasks. A central challenge in this setting is backpropagation through the solution of an optimization problem, which often lacks a closed form. One typical strategy is algorithm unrolling, which relies on automatic diff

B. Avila, J. Gamboa, R. B. MacKenzie, F. Mendez

A cosmological model based on two scalar fields is proposed. The first of these, $\varphi$, has mass $\mu$, while the second, $\chi$, is massless. The pair are coupled through a ``Higgs portal''. First, we show how the model reproduces the Friedmann equations if the square of the mass of the $\varphi$ field is proportional to the cosmological constant and $\

Xianyu Hu

Let $M$ denote a specific cubic fourfold that accommodates a group action by $\mathbb{Z}/3\mathbb{Z}$. Through utilization of derived Mckay correspondence, we present a new proof establishing the identification of the equivariant Kuznetsov component in the equivariant derived category of $M$ with the derived category of certain abelian surface. This surface

Cassandra Czobit, Reza Samavi

Image-to-image translation has gained popularity in the medical field to transform images from one domain to another. Medical image synthesis via domain transformation is advantageous in its ability to augment an image dataset where images for a given class is limited. From the learning perspective, this process contributes to data-oriented robustness of the

Clay Adams, Francesca Cantor, Anese Gashi, Semir Mujevic

We reinterpret various properties of Noetherian local rings via the existence of some $n$-ary numerical function satisfying certain uniform bounds. We provide such characterizations for seminormality, weak normality, generalized Cohen-Macaulayness, and $F$-purity, among others. Our proofs that such numerical functions exist are nonconstructive and rely on th

Hongkang Ni, Haoya Li, Lexing Ying

This work proposes a protocol for Fermionic Hamiltonian learning. For the Hubbard model defined on a bounded-degree graph, the Heisenberg-limited scaling is achieved while allowing for state preparation and measurement errors. To achieve $\epsilon$-accurate estimation for all parameters, only $\tilde{\mathcal{O}}(\epsilon^{-1})$ total evolution time is neede

Nick Laskin

A new fractional non-homogeneous counting process has been introduced and developed using the Kilbas and Saigo three-parameter generalization of the Mittag-Leffler function. The probability distribution function of this process reproduces for certain set of the fractality parameters the famous Poisson and fractional Poisson probability distributions as well

Gerardo González Robert, Mumtaz Hussain, Nikita Shulga, Hiroki Takahasi

For an infinite iterated function system $\mathbf{f}$ on $[0,1]$ with an attractor $\Lambda(\mathbf{f})$ and for an infinite subset $D\subseteq \mathbb{N}$, consider the set \[ \mathbb E(\mathbf{f},D)= \{ x \in \Lambda(\mathbf{f}): a_n(x)\in D \text{ for all }n\in\mathbb N \text{ and }\lim_{n\to\infty} a_n=\infty\}. \] For a function $\varphi:\mathbb{N}\to [

Tim Austin, Lewis Bowen, Christopher Shriver

We construct an explicit algebraic example of a subshift of finite type over a group $\Gamma$ with an invariant Markov measure which has completely positive sofic entropy (with respect to `most' sofic approximations) and yet does not have a direct Bernoulli factor, because its model spaces shatter into exponentially many clusters of sub-exponential size. The

Carl M. Bender, Daniel W. Hook

It is generally assumed that a Hamiltonian for a physically acceptable quantum system (one that has a positive-definite spectrum and obeys the requirement of unitarity) must be Hermitian. However, a PT-symmetric Hamiltonian can also define a physically acceptable quantum-mechanical system even if the Hamiltonian is not Hermitian. The study of PT-symmetric qu

Tharnier O. Puel, Tommaso Macrì

Confinement is a pivotal phenomenon in numerous models of high-energy and statistical physics. In this study, we investigate the emergence of confined meson excitations within a one-dimensional system, comprising Rydberg-dressed atoms trapped and coupled to a cavity field. This system can be effectively represented by an Ising-Dicke Hamiltonian model. The ob

Wei Wang, Angela Doufexi, Mark A Beach

This study delves into the radiation pattern synthesis of reconfigurable intelligent surfaces (RIS) / reflection metasurfaces. Through superimposing multiple single-reflection profiles, which comprise the amplitude and/or phase settings of all constituent elements, a single incident wave can be effectively reflected in multiple asymmetric directions. However

Vinicius Lima, Vetria Byrd

Traffic accidents are one of the biggest challenges in a society where commuting is so important. What triggers an accident can be dependent on several subjective parameters and varies within each region, city, or country. In the same way, it is important to understand those parameters in order to provide a knowledge basis to support decisions regarding futu

Kaitlyn Wang, Jian Ge, Kevin Willis, Kevin Wang

Of over 5,000 exoplanets identified so far, only a few hundred possess sub-Earth radii. The formation processes of these sub-Earths remain elusive, and acquiring additional samples is essential for investigating this unique population. In our study, we employ the GPFC method, a novel GPU Phase Folding algorithm combined with a Convolutional Neural Network, o

Léa Feuillet, Marcio Meléndez, Steve Kraemer, Henrique Schmitt

We select a sample of 1,437 active galactic nuclei (AGN) from the catalog of the Sloan Digital Sky Survey (SDSS) galaxy properties from the Portsmouth group by detection of the high-ionization [Ne V] 3426 \r{A} emission line. We compare the fluxes of [Ne III] 3869 \r{A}, [O III] 5007 \r{A}, [O II] 3726, 3728 \r{A}, and [O I] 6300 \r{A} to that of [Ne V]. All

Alexander Demin, Joris van der Hoeven

Consider a sparse polynomial in several variables given explicitly as a sum of non-zero terms with coefficients in an effective field. In this paper, we present several algorithms for factoring such polynomials and related tasks (such as gcd computation, square-free factorization, content-free factorization, and root extraction). Our methods are all based on

G. D. Alexeev, M. G. Alexeev, C. Alice, A. Amoroso

The COMPASS Collaboration performed measurements of the Drell-Yan process in 2015 and 2018 using a 190 GeV/c $\pi^{-}$ beam impinging on a transversely polarised ammonia target. Combining the data of both years, we present final results on the amplitudes of the five azimuthal modulations in the dimuon production cross section. Three of these transverse-spin-

Joanna Perido, Peter K. Day, Andrew D. Beyer, Nicholas F. Cothard

The Balloon Experiment for Galactic INfrared Science (BEGINS) is a concept for a sub-orbital observatory that will operate from $\lambda$ = 25-250 $\mu$m to characterize dust in the vicinity of high-mass stars. The mission's sensitivity requirements will be met by utilizing arrays of 1,840 lens-coupled, lumped-element kinetic inductance detectors (KIDs) oper

Cesar S. Eschenazi, Wanderson J. Lambert, Marlon M. López-Flores, Dan Marchesin

In previous work, we developed a topological framework for solving Riemann initial-value problems for a system of conservation laws. Its core is a differentiable manifold, called the wave manifold, with points representing shock and rarefaction waves. In the present paper, we construct, in detail, the three-dimensional wave manifold for a system of two conse

Taylan Kargin, Joudi Hajar, Vikrant Malik, Babak Hassibi

We investigate the Distributionally Robust Regret-Optimal (DR-RO) control of discrete-time linear dynamical systems with quadratic cost over an infinite horizon. Regret is the difference in cost obtained by a causal controller and a clairvoyant controller with access to future disturbances. We focus on the infinite-horizon framework, which results in stabili

Agathe Sadeghi, Achintya Gopal, Mohammad Fesanghary

This paper introduces a new causal structure learning method for nonstationary time series data, a common data type found in fields such as finance, economics, healthcare, and environmental science. Our work builds upon the constraint-based causal discovery from nonstationary data algorithm (CD-NOD). We introduce a refined version (CD-NOTS) which is designed

Mark Kamper Svendsen, Michael Ruggenthaler, Hannes Hübener, Christian Schäfer

When light and matter interact strongly, the resulting hybrid system inherits properties from both constituents, allowing one to modify material behavior by engineering the surrounding electromagnetic environment. This concept underlies the emerging paradigm of cavity materials engineering, which aims at the control of material properties via tailored vacuum

Stefan Frei, Jan Reichle, Stefan Volkwein

We present a non-intrusive gradient and a non-intrusive BFGS algorithm for parameter estimation problems in non-stationary elasticity. To avoid multiple (and potentially expensive) solutions of the underlying partial differential equation (PDE), we approximate the PDE solver by a neural network within the algorithms. The network is trained offline for a give

Chenwei Xu, Jerry Yao-Chieh Hu, Aakaash Narayanan, Mattson Thieme

We introduce a novel Proximal Policy Optimization (PPO) algorithm aimed at addressing the challenge of maintaining a uniform proton beam intensity delivery in the Muon to Electron Conversion Experiment (Mu2e) at Fermi National Accelerator Laboratory (Fermilab). Our primary objective is to regulate the spill process to ensure a consistent intensity profile, w

Matthew Enlow, Adam Larios, Jiahong Wu

We propose a modification to the nonlinear term of the three-dimensional incompressible Navier-Stokes equations (NSE) in either advective or rotational form which "calms" the system in the sense that the algebraic degree of the nonlinearity is effectively reduced. This system, the calmed Navier-Stokes Equations (calmed NSE), utilizes a "calming function" in

Janus Varmarken, Rahmadi Trimananda, Athina Markopoulou

This paper proposes a general network fingerprinting framework, Seqnature, that uses packet sequences as its basic data unit and that makes it simple to implement any fingerprinting technique that can be formulated as a problem of identifying packet exchanges that consistently occur when the fingerprinted event is triggered. We demonstrate the versatility of

Farshed Abdukhakimov, Chulu Xiang, Dmitry Kamzolov, Robert Gower

Adaptive optimization methods are widely recognized as among the most popular approaches for training Deep Neural Networks (DNNs). Techniques such as Adam, AdaGrad, and AdaHessian utilize a preconditioner that modifies the search direction by incorporating information about the curvature of the objective function. However, despite their adaptive characterist

Antonio González-López

It is well known that the visual information represented in the simple cells of the primary visual cortex V1 is spatially localized, orientation-sensitive and bandpass-filtered. In addition, the visual information represented is subsampled. On the other hand, the methods used to assess image quality of x-ray systems performing detectability tasks are usually

Andrei I. Davydychev, Pablo Navarrete, York Schröder

We derive analytic results for scalar massless bosonic vacuum sum-integrals at two loops. Building upon a recent factorization proof of massive two-loop vacuum integrals, we are able to solve the corresponding Matsubara sums and map the result onto one-loop structures, thereby proving factorization also in the sum-integral setting. Analytic results are provi

Luca Dell'Anna

We calculate the equilibrium Josephson current through a disordered interacting quantum dot described by a Sachdev-Ye-Kitaev model fully contacted by two BCS superconductors, such that all modes of the dot contribute to the coupling, which encodes hopping and spin-flip processes. We show that, at zero temperature and at the conformal limit, i.e. in the stron

Caitlin Lienkaemper

Estimating the linear dimensionality of a data set in the presence of noise is a common problem. However, data may also be corrupted by monotone nonlinear distortion that preserves the ordering of matrix entries but causes linear methods for estimating rank to fail. In light of this, we consider the problem of computing \emph{underlying rank}, which is the l

Edan Orzech, Martin Rinard

In general, Nash equilibria in normal-form games may require players to play (probabilistically) mixed strategies. We define a measure of the complexity of finite probability distributions and study the complexity required to play Nash equilibria in finite two player $n\times n$ games with rational payoffs. Our central results show that there exist games in

Dandan Tang, Xin Tong

Missing data are inevitable in longitudinal studies. Traditional methods, such as the full information maximum likelihood (FIML), are commonly used to handle ignorable missing data. However, they may lead to biased model estimation due to missing not at random data that often appear in longitudinal studies. Recently, machine learning methods, such as random

Jochen Wagner, Alma Anna Ubele, Verena Schenzinger, Axel Kreuter

This study presents an extended analysis of aerosol optical depth at 501 nm (AOD) in the Alpine valley of Innsbruck, Austria, from 2007 to 2023, and offers a comparative analysis with the Alpine station of Davos, Switzerland. AOD is derived from ground-based sunphotometer measurements of direct spectral irradiance during daytime. The Davos Station is part of

Stefano Fiorini, Stefano Coniglio, Michele Ciavotta, Enza Messina

We introduce QuaterGCN, a spectral Graph Convolutional Network (GCN) with quaternion-valued weights at whose core lies the Quaternionic Laplacian, a quaternion-valued Laplacian matrix by whose proposal we generalize two widely-used Laplacian matrices: the classical Laplacian (defined for undirected graphs) and the complex-valued Sign-Magnetic Laplacian (prop

Michael Uzhansky, Abhishek Rakshit, Yoav Kalcheim, Elad Koren

Pyroelectric and photovoltaic effects are vital in cutting-edge thermal imaging, infrared sensors, thermal and solar energy harvesting. Recent advances revealed the great potential of the bulk photovoltaic effect in two-dimensional (2D) semiconductor-ferroelectric materials to enable reconfigurable p-n junction operation with the potential to surpass the Sho

Vladislav Poliakov, Wen-Han Kao, Natalia B. Perkins

The Yao-Lee model is an example of exactly solvable spin-orbital models that are generalizations of the original Kitaev honeycomb model with extra local orbital degrees of freedom. Similar to the Kitaev model, both spin and orbital degrees of freedom are effectively represented using sets of three-flavored Majorana fermions. The Yao-Lee model exhibits a quan

Mehran Alidoost Nia

This paper presents the adaptive software security model, an innovative approach integrating the MAPE-K loop and the Software Development Life Cycle (SDLC). It proactively embeds security policies throughout development, reducing vulnerabilities from different levels of software engineering. Three primary contributions-MAPE-K integration, SDLC embedding, and

Lucas Sourrouille

We propose a mechanism to construct the eigenvalues and eigenfunctions of the massless Dirac-Weyl equation in the presences of magnetic flux $\Phi$ localized in a restricted region of the plane. Using this mechanism we analyze the degeneracy of the existed energy levels. We find that the zero and first energy level has the same $N+1$ degeneracy, where $N$ is

Diego Soi, Davide Maiorca, Giorgio Giacinto, Harel Berger

Android malware still represents the most significant threat to mobile systems. While Machine Learning systems are increasingly used to identify these threats, past studies have revealed that attackers can bypass these detection mechanisms by making subtle changes to Android applications, such as adding specific API calls. These modifications are often refer

Maximilian E. Schüle, Thomas Neumann, Alfons Kemper

Although database systems perform well in data access and manipulation, their relational model hinders data scientists from formulating machine learning algorithms in SQL. Nevertheless, we argue that modern database systems perform well for machine learning algorithms expressed in relational algebra. To overcome the barrier of the relational model, this pape

Min K. Kim, Hafu Takero, Sara Fedovik

We aim to provide an explanation for how the human brain might connect words for sentence formation. A novel approach to modeling syntactic representation is introduced, potentially showing the existence of universal syntactic structures for all natural languages. As the discovery of DNA's double helix structure shed light on the inner workings of genetics,

I. A. Muzalevskii, N. B. Shulgina, A. A. Bezbakh, V. Chudoba

Search for the population of the low-energy continuum of a tetraneutron system was performed for reactions of the $^{8}$He beam on a deuterium target. These studies are based on the data [I.A. Muzalevskii \textit{et al.}, Phys.\ Rev.\ C \textbf{103}, 044313 (2021)], previously used for the studies of $^{7}$H and $^{6}$H in the $^2\text{H}(^8\text{He},{^3\tex

Jingda Yang, Ying Wang

This paper introduces Auto-modeling of Formal Verification with Real-world Prompting for 5G and NextG protocols (AVRE), a novel system designed for the formal verification of Next Generation (NextG) communication protocols, addressing the increasing complexity and scalability challenges in network protocol design and verification. Utilizing Large Language Mo

Ravi Kashikar, D. DeTellem, P. S. Ghosh, Yixuan Xu

Hybrid organic-inorganic perovskites are famous for the diversity of their chemical compositions, phases and phase transitions, and associated physical properties. We use a combination of experimental and computational techniques to reveal strong coupling between structure, magnetism, and spin splitting in a representative of the largest family of hybrid org

Omar Eldaghar, Michael W. Mahoney, David F. Gleich

Network epidemic simulation holds the promise of enabling fine-grained understanding of epidemic behavior, beyond that which is possible with coarse-grained compartmental models. Key inputs to these epidemic simulations are the networks themselves. However, empirical measurements and samples of realistic interaction networks typically display properties that

Arjun Roy, Joseph P. Cusumano

We study the non-linear dynamics and failure statistics of a coupled-field fatigue damage evolution model. We develop a methodology to derive averaged damage evolution rate laws from such models. We show that such rate laws reduce life-cycle simulation times by orders of magnitude and permit dynamical systems analysis of long-time behavior, including failure

Zhihao Zhang, Yuan Zuo, Chenghua Lin, Junjie Wu

Phrase mining is a fundamental text mining task that aims to identify quality phrases from context. Nevertheless, the scarcity of extensive gold labels datasets, demanding substantial annotation efforts from experts, renders this task exceptionally challenging. Furthermore, the emerging, infrequent, and domain-specific nature of quality phrases presents furt

Giacomo Turri, Vladimir Kostic, Pietro Novelli, Massimiliano Pontil

We present and analyze an algorithm designed for addressing vector-valued regression problems involving possibly infinite-dimensional input and output spaces. The algorithm is a randomized adaptation of reduced rank regression, a technique to optimally learn a low-rank vector-valued function (i.e. an operator) between sampled data via regularized empirical r

Rogério Capobianco, Betti Hartmann, Jutta Kunz

We study the geodesic motion in a space-time describing a swirling universe. We show that the geodesic equations can be fully decoupled in the Hamilton-Jacobi formalism leading to an additional constant of motion. The analytical solutions to the geodesic equations can be given in terms of elementary and elliptic functions. We also consider a space-time descr

Dennis Wu, Jerry Yao-Chieh Hu, Weijian Li, Bo-Yu Chen

We present STanHop-Net (Sparse Tandem Hopfield Network) for multivariate time series prediction with memory-enhanced capabilities. At the heart of our approach is STanHop, a novel Hopfield-based neural network block, which sparsely learns and stores both temporal and cross-series representations in a data-dependent fashion. In essence, STanHop sequentially l

Nir Yellinek, Leonid Karlinsky, Raja Giryes

Vision-Language models (VLMs) have proven to be effective at aligning image and text representations, producing superior zero-shot results when transferred to many downstream tasks. However, these representations suffer from some key shortcomings in understanding Compositional Language Concepts (CLC), such as recognizing objects' attributes, states, and rela

Jongrae Kim, Woojeong Lee, Kwang-Hyun Cho

Boolean networks have been widely used in many areas of science and engineering to represent various dynamical behaviour. In systems biology, they became useful tools to study the dynamical characteristics of large-scale biomolecular networks and there have been a number of studies to develop efficient ways of finding steady states or cycles of Boolean netwo

Swarup Ranjan Behera, Krishna Mohan Injeti, Jaya Sai Kiran Patibandla, Praveen Kumar Pokala

Audio Question Answering (AQA) constitutes a pivotal task in which machines analyze both audio signals and natural language questions to produce precise natural language answers. The significance of possessing high-quality, diverse, and extensive AQA datasets cannot be overstated when aiming for the precision of an AQA system. While there has been notable fo

Abhijit Mishra, Mingda Li, Soham Deo

This paper addresses the privacy and security concerns associated with deep neural language models, which serve as crucial components in various modern AI-based applications. These models are often used after being pre-trained and fine-tuned for specific tasks, with deployment on servers accessed through the internet. However, this introduces two fundamental

Sumayya Moshin, Shaheen Nazir, Muhammad Imran Qureshi

We construct polarized Calabi--Yau 3-folds with at worst isolated canonical orbifold points in codimension 4 that can be described in terms of the equations of the Segre embedding of $\mathbb P^2 \times \mathbb P^2$ in $\mathbb P^8$. We investigate the existence of other deformation families in their Hilbert scheme by either studying Tom and Jerry degenerati

Abhay Singh Bhadoriya, Sivakumar Rathinam, Swaroop Darbha, David W. Casbeer

In this article, we consider a multi-agent path planning problem in a stochastic environment. The environment, which can be an urban road network, is represented by a graph where the travel time for selected road segments (impeded edges) is a random variable because of traffic congestion. An unmanned ground vehicle (UGV) wishes to travel from a starting loca

Muhammad Imran Qureshi

We construct two types of wellformed and quasismooth biregular models (infinite series) of rigid orbifold del Pezzo surfaces having their (sub) anti-canonical embeddings in $\mathbb P^6(w_i) $. One type of model contains a family of rigid del Pezzo surfaces with a fixed Fano index and weights of ambient $\mathbb P^6(w_i)$ are parameterized by positive intege

Manon Richard, Lisa Giordani, Cristian Brokate, Jean Liénard

This study proposes a comprehensive methodology for identifying three techniques utilized in foreign-operated information manipulation campaigns: Copy-Pasta, Rewording, and Translation. Our approach, dubbed the ``$3\Delta$-space duplicate methodology'', quantifies the semantic, grapheme, and language aspects of messages. Computing pairwise distances within t

Tobias Schimanski, Chiara Colesanti Senni, Glen Gostlow, Jingwei Ni

Nature is an amorphous concept. Yet, it is essential for the planet's well-being to understand how the economy interacts with it. To address the growing demand for information on corporate nature disclosure, we provide datasets and classifiers to detect nature communication by companies. We ground our approach in the guidelines of the Taskforce on Nature-rel

Malik Hassanaly, Peter J. Weddle, Ryan N. King, Subhayan De

Bayesian parameter inference is useful to improve Li-ion battery diagnostics and can help formulate battery aging models. However, it is computationally intensive and cannot be easily repeated for multiple cycles, multiple operating conditions, or multiple replicate cells. To reduce the computational cost of Bayesian calibration, numerical solvers for physic

Maulik Parikh, Francesco Setti

We consider quantum gravity fluctuations in a pair of nearby gravitational wave detectors. Quantum fluctuations of long-wavelength modes of the gravitational field induce coherent fluctuations in the detectors, leading to correlated noise. We determine the variance and covariance in the lengths of the arms of the detectors, and thereby obtain the graviton no

Paul Lashomb, Ronald B. Morgan, Travis Whyte, Walter Wilcox

In lattice QCD the calculation of disconnected quark loops from the trace of the inverse quark matrix has large noise variance. A multilevel Monte Carlo method is proposed for this problem that uses different degree polynomials on a multilevel system. The polynomials are developed from the GMRES algorithm for solving linear equations. To reduce orthogonaliza

Jingbo Lin, Zhilu Zhang, Yuxiang Wei, Dongwei Ren

In this paper, we introduce a new perspective for improving image restoration by removing degradation in the textual representations of a given degraded image. Intuitively, restoration is much easier on text modality than image one. For example, it can be easily conducted by removing degradation-related words while keeping the content-aware words. Hence, we

Vladimir K. Dubovoy, Bernd Kirstein, Conrad Mädler, Karsten Müller

This paper is dedicated to the introduction in a circle of ideas and methods, which are connected with the notion of characteristic function of a non-selfadjoint operator. We start with the consideration of closed and open systems (Subsections 2.1.1-2.1.2). In Subsections 2.1.2-2.1.3 we introduce the notion of operator colligation and define the characterist

Kainã Diniz, Tanja Schoger, Guilherme T. Moura, Arthur L. Fonseca

We demonstrate a new method for determining the radius of micron-sized particles trapped by a vortex laser beam. The technique is based on measuring the rotation experienced by the center of mass of a microsphere that is laterally displaced by a Stokes drag force to an off-axis equilibrium position. The rotation results from an optical torque pointing along

Yifeng Huang, Duc Duy Nguyen, Lam Nguyen, Cuong Pham

This paper addresses the task of counting human actions of interest using sensor data from wearable devices. We propose a novel exemplar-based framework, allowing users to provide exemplars of the actions they want to count by vocalizing predefined sounds ''one'', ''two'', and ''three''. Our method first localizes temporal positions of these utterances from