July 2023 arXiv papers — page 82

Vladimir V. Mirjanić, Razvan Pascanu, Petar Veličković

Neural Algorithmic Reasoning (NAR) is a research area focused on designing neural architectures that can reliably capture classical computation, usually by learning to execute algorithms. A typical approach is to rely on Graph Neural Network (GNN) architectures, which encode inputs in high-dimensional latent spaces that are repeatedly transformed during the

Yudong Luo, Guiliang Liu, Pascal Poupart, Yangchen Pan

Restricting the variance of a policy's return is a popular choice in risk-averse Reinforcement Learning (RL) due to its clear mathematical definition and easy interpretability. Traditional methods directly restrict the total return variance. Recent methods restrict the per-step reward variance as a proxy. We thoroughly examine the limitations of these varian

Evgeny Polyakov, Nataliya Arefyeva

Quantum chaos, a phenomenon that began to be studied in the last century, still does not have a rigorous understanding. By virtue of the correspondence principle, the properties of the system that lead to chaotic dynamics at the classical level must also be present in the underlying quantum system. In the classical case, the exponential divergence of nearby

Behrooz Mirzaii, Elvis Torres Pérez

There is a natural connection between the third homology of $\textrm{SL}_2(A)$ and the refined Bloch group $\mathcal{RB}(A)$ of a commutative ring $A$. In this article we investigate this connection and as the main result we show that if $A$ is a universal $\textrm{GE}_2$-domain such that $-1 \in A^{\times 2}$, then we have the exact sequence $H_3(\textrm{SM

Tuan-Tu Nguyen, Jiahui Xu, Zeliang Su, Vincent De Andrade

In this study, we present a well-defined methodology for conducting Operando X-ray absorption near-edge structure spectroscopy (XANES) in conjunction with transmission X-ray nano computed tomography (TXM-nanoCT) experiments on the LiNi$_{0.5}$Mn$_{0.3}$Co$_{0.2}$O$_2$ (NMC) cathode electrode. To minimize radiation-induced damage to the sample during charge a

Moamin Abughazala, Henry Muccini

Extracting valuable insights from vast amounts of information is a critical process that involves acquiring, storing, managing, analyzing, and visualizing data. Providing an abstract overview of data analytics applications is crucial to ensure that collected data is transformed into meaningful information. One effective way of achieving this objective is thr

Hector Galindo-Silva, Paula Herrera-Idárraga

This study investigates the impact of integrating gender equality into the Colombian constitution of 1991 on attitudes towards gender equality, experiences of gender-based discrimination, and labor market participation. Using a difference-in-discontinuities framework, we compare individuals exposed to mandatory high school courses on the Constitution with th

Pratibha Verma

The Redner-Ben-Avraham-Kahng (RBK) coagulation model provide a fundamental framework for modeling the aggregation of particles in various physical and biological systems. In this paper, we investigate the global existence of solutions to the discrete version of RBK coagulation equations, encompassing a wide range of coagulation kernels. Furthermore, we demon

Leon Escobar-Diaz, Paula Bran

In this work, we introduce a spectral-infinite element method for solving Einstein's constraint equations in hyperbolic form. As an application of this, we use this method for computing asymptotically flat perturbations of a Kerr black hole with small angular momentum. Our numerical infrastructure is based on the use of a spin-weighted spherical harmonic tra

Henry Ando, David A. Huse

Quantum chaos is a major subject of interest in condensed matter theory, and has recently motivated new questions in the study of classical chaos. In particular, recent studies have uncovered interesting physics in the relationship between chaos and conserved quantities in models of quantum chaos. In this paper, we investigate this relationship in two simple

Jicheng Shi, Yingzhao Lian, Christophe Salzmann, Colin N. Jones

By providing various services, such as Demand Response (DR), buildings can play a crucial role in the energy market due to their significant energy consumption. However, effectively commissioning buildings for such desired functionalities requires significant expert knowledge and design effort, considering the variations in building dynamics and intended use

Federico Re, Pierfrancesco Di Cintio

We investigate the core-cusp problem of the $\Lambda$ cold dark matter ($\Lambda$CDM) scenario in the context of Modified Newtonian Dynamics (MOND) paradigm exploiting the concept of equivalent Newtonian system (ENS). By means of particle-mesh $N-$body simulations in MOND we explore processes of galaxy formation via cold dissipationless collapse or merging o

Samuel Shuman

A major challenge in Causal Set research is that theories need only to match general relativity and quantum field theory in the appropriate limits. This means that there should be many different ways to calculate a scalar field propagator in a causal set that match the known limits, but may give significantly different results on the small scale. In this wor

Tim Cooijmans, Milad Aghajohari, Aaron Courville

Gradient-based learning in multi-agent systems is difficult because the gradient derives from a first-order model which does not account for the interaction between agents' learning processes. LOLA (arXiv:1709.04326) accounts for this by differentiating through one step of optimization. We propose to judge joint policies by their long-term prospects as measu

Sarah Wieghold, Nozomi Shirato, Xinyue Cheng, Kyaw Zin Latt

We investigate the limit of X-ray detection at room temperature on rare-earth molecular films using lanthanum and a pyridine-based dicarboxamide organic linker as a model system. Synchrotron X-ray scanning tunneling microscopy is used to probe the molecules with different coverages on a HOPG substrate. X-ray-induced photocurrent intensities are measured as a

Mikhail V. Sokolov

Many countries impose regulatory restrictions on lending rates known as interest rate caps. In most cases, these restrictions apply to the effective (rather than nominal) interest rate, a measure which incorporates all commissions and fees associated with a loan. Because the effective interest rate is the internal rate of return (IRR) of the loan's cash flow

Gaurav Anand, Samira Safaripour, Craig Snoeyink

The electric field dielectric polarization-based separations mechanism represents a novel method for separating solutions at small length scales. An electric field gradient with a maximum strength of $\mathrm{0.4~MV/m}$ applied across a $\mathrm{10~\mu m}$ deep channel is shown to increase the concentration inside the low electric field region by $\approx \m

Nidhi Vakil, Hadi Amiri

A curriculum is a planned sequence of learning materials and an effective one can make learning efficient and effective for both humans and machines. Recent studies developed effective data-driven curriculum learning approaches for training graph neural networks in language applications. However, existing curriculum learning approaches often employ a single

Nils L. Westhausen, Bernd T. Meyer

Speech enhancement in hearing aids is a challenging task since the hardware limits the number of possible operations and the latency needs to be in the range of only a few milliseconds. We propose a deep-learning model compatible with these limitations, which we refer to as Group-Communication Filter-and-Sum Network (GCFSnet). GCFSnet is a causal multiple-in

Tung Nguyen, Jeffrey Uhlmann

In this paper, we propose a new constraint, called shift-consistency, for solving matrix/tensor completion problems in the context of recommender systems. Our method provably guarantees several key mathematical properties: (1) satisfies a recently established admissibility criterion for recommender systems; (2) satisfies a definition of fairness that elimina

Farmer Schlutzenberg, John Steel

Assume ZF + AD + V=L(R). Let $[\alpha,\beta]$ be a $\Sigma_1$ gap with $J_\alpha(R)$ admissible. We analyze $J_\beta(R)$ as a natural form of "derived model" of a premouse $P$, where $P$ is found in a generic extension of $V$. In particular, we will have $\mathcal{P}(R)\cap J_\beta(R)=\mathcal{P}(R)\cap D$, and if $J_\beta(R)\models$ "$\Theta$ exists", then

James M. Scott, Qiang Du

We present a systematic study on a class of nonlocal integral functionals for functions defined on a bounded domain and the naturally induced function spaces. The function spaces are equipped with a seminorm depending on finite differences weighted by a position-dependent function, which leads to heterogeneous localization on the domain boundary. We show the

Tanmay Inamdar, Lawqueen Kanesh, Madhumita Kundu, Nidhi Purohit

Selection of a group of representatives satisfying certain fairness constraints, is a commonly occurring scenario. Motivated by this, we initiate a systematic algorithmic study of a \emph{fair} version of \textsc{Hitting Set}. In the classical \textsc{Hitting Set} problem, the input is a universe $\mathcal{U}$, a family $\mathcal{F}$ of subsets of $\mathcal{

Apostolos Ampountolas

This study analyzes the transmission of market uncertainty on key European financial markets and the cryptocurrency market over an extended period, encompassing the pre, during, and post-pandemic periods. Daily financial market indices and price observations are used to assess the forecasting models. We compare statistical, machine learning, and deep learnin

M. Parise, D. Passarelli, P. Berrutti, D. Longuevergne

The Proton Improvement Plan-II (PIP-II [1]) linac will include 35 Single Spoke Resonators type 2 (SSR2). A preproduction SSR2 cryomodule will contain 5 jacketed cavities. Several units are already manufactured and prepared for cold testing. In this work, data collected from the fabrication, processing and preparation of the cavities will be presented and the

Shion Fukuzawa, Michael T. Goodrich, Sandy Irani

Using the framework of Tutte embeddings, we begin an exploration of \emph{quantum graph drawing}, which uses quantum computers to visualize graphs. The main contributions of this paper include formulating a model for quantum graph drawing, describing how to create a graph-drawing quantum circuit from a given graph, and showing how a Tutte embedding can be ca

Sambit Mohapatra, Senthil Yogamani, Varun Ravi Kumar, Stefan Milz

LiDAR is crucial for robust 3D scene perception in autonomous driving. LiDAR perception has the largest body of literature after camera perception. However, multi-task learning across tasks like detection, segmentation, and motion estimation using LiDAR remains relatively unexplored, especially on automotive-grade embedded platforms. We present a real-time m

Lingkai Kong, Jiaming Cui, Haotian Sun, Yuchen Zhuang

Diffusion-based graph generative models have recently obtained promising results for graph generation. However, existing diffusion-based graph generative models are mostly one-shot generative models that apply Gaussian diffusion in the dequantized adjacency matrix space. Such a strategy can suffer from difficulty in model training, slow sampling speed, and i

Ahmed Elhussein, Gamze Gursoy

Federated Learning (FL) is a machine learning framework that enables multiple organizations to train a model without sharing their data with a central server. However, it experiences significant performance degradation if the data is non-identically independently distributed (non-IID). This is a problem in medical settings, where variations in the patient po

Ngoc-Ty Nguyen, P. Jonathon Phillips, Larry Tang

Ordinal scores occur commonly in medical imaging studies and in black-box forensic studies \citep{Phillips:2018}. To assess the accuracy of raters in the studies, one needs to estimate the receiver operating characteristic (ROC) curve while accounting for covariates of raters. In this paper, we propose a covariate-adjusted homogeneity test to determine diffe

Yi Xie, Boyu Zhang

We calculate the ring structure of the singular instanton Floer homology of $(S^1\times \Sigma, S^1\times \{p_1,\dots,p_n\})$ with C-coefficients, where $\Sigma$ is a closed oriented surface. As an application, we prove an excision formula for singular instanton homology when n=1. This settles the last unknown case of excision formula for instanton Floer hom

P. A. Kulyavtsev, G. Eremeev, S. Posen, B. Tennis

We present the results of commissioning a dedicated furnace for Nb3Sn coatings of 2.6 GHz single cell cavities. Nb3Sn is a desired coating due to its high critical temperature and smaller surface resistance compared to bulk Nb. Usage of Nb3Sn coated cavities will greatly reduce operating costs due to decreased dependance on cryo cooling. Tin is deposited by

Dennis Peuter, Viorica Sofronie-Stokkermans, Sebastian Thunert

We study the problem of $P$-interpolation, where $P$ is a set of binary predicate symbols, for certain classes of local extensions of a base theory. For computing the $P$-interpolating terms, we use a hierarchic approach: This allows us to compute the interpolating terms using a method for computing interpolating terms in the base theory. We use these result

M. Cadeddu, F. Dordei, C. Giunti

We review the physics of coherent elastic neutrino-nucleus scattering and the results and perspectives for the measurements of the radius of the neutron distribution of the nucleus, of the weak mixing angle, and of new neutrino interactions due to physics beyond the Standard Model.

Caleb Eckhardt

We show that a C*-algebra generated by an irreducible representation of a finitely generated virtually nilpotent group satisfies the universal coefficient theorem and has real rank 0. This combines with previous joint work with Gillaspy and McKenney to show these C*-algebras are classified by their Elliott invariants. When we further assume the group is nilp

Zeyang Jia, Eli Ben-Michael, Kosuke Imai

Algorithmic decisions and recommendations are used in many high-stakes decision-making settings such as criminal justice, medicine, and public policy. We investigate whether it would have been possible to improve a security assessment algorithm employed during the Vietnam War, using outcomes measured immediately after its introduction in late 1969. This empi

Giuseppe Cotardo, Gretchen L. Matthews, Alberto Ravagnani, Julia Shapiro

We investigate adversarial network coding and decoding focusing on the multishot regime. Errors can occur on a proper subset of the network edges and are modeled via an adversarial channel. The paper contains both bounds and capacity-achieving schemes for the Diamond Network and the Mirrored Diamond Network. We also initiate the study of the generalizations

Masoomeh Aslahishahri, Jordan Ubbens, Ian Stavness

We present DARTS, a transformer model for reference-based image super-resolution. DARTS learns joint representations of two image distributions to enhance the content of low-resolution input images through matching correspondences learned from high-resolution reference images. Current state-of-the-art techniques in reference-based image super-resolution are

Scott Stirling

In 2019, Schneidermann and Teicher showed that the Kirk invariant classifies two-component link maps of two-spheres in the four-sphere up to link homotopy. In this paper, we construct a three-component link homotopy invariant. We construct two link maps where each component has the same image, and apply our invariant to prove that nevertheless they are not l

Amit Kumar, Abhijit Majumder, Ismail Soudi, Johannes H. Weber

The leading jet transport coefficients $\hat{q}$ or $\hat{e}_{2}$ encode transverse or longitudinal momentum broadening of a hard parton traversing a hot medium. Understanding their temperature dependence is key to appreciating the observed suppression of high-transverse momentum probes at RHIC or LHC collision energies. We present a first continuum extrapol

Rajat De, Dominik Kempa

Grammar compression is a general compression framework in which a string $T$ of length $N$ is represented as a context-free grammar of size $n$ whose language contains only $T$. In this paper, we focus on studying the limitations of algorithms and data structures operating on strings in grammar-compressed form. Previous work focused on proving lower bounds f

Stephen Arndt, Josh Ascher, Kirk Pruhs

We consider the online transportation problem set in a metric space containing parking garages of various capacities. Cars arrive over time, and must be assigned to an unfull parking garage upon their arrival. The objective is to minimize the aggregate distance that cars have to travel to their assigned parking garage. We show that the natural greedy algorit

Muhsin Abdul Karim, Jiashu Wang, David Graf, Kota Yoshimura

The synthesis of thin films of magnetic topological materials is necessary to achieve novel quantized Hall effects and electrodynamic responses. EuIn2As2 is a recently predicted topological axion insulator that has an antiferromagnetic ground state and an inverted band structure, but that has only been synthesized and studied as a single crystal. We report o

Samir Canning, Hannah Larson, Sam Payne

We study collections of subrings of $H^*(\overline{\mathcal{M}}_{g,n})$ that are closed under the tautological operations that map cohomology classes on moduli spaces of smaller dimension to those on moduli spaces of larger dimension and contain the tautological subrings. Such extensions of tautological rings are well-suited for inductive arguments and flexi

Andreas Irmler, Raghavendra Kanakagiri, Sebastian T. Ohlmann, Edgar Solomonik

We propose an algorithm that aims at minimizing the inter-node communication volume for distributed and memory-efficient tensor contraction schemes on modern multi-core compute nodes. The key idea is to define processor grids that optimize intra-/inter-node communication volume in the employed contraction algorithms. We present an implementation of the propo

Abdullah Alqarni, Wei Wen, Ben C. P. Lam, Nicole Kochan

Objectives: To examine sex differences in the associations between vascular risk factors and 6-year changes in the volume of white matter hyperintensities (WMH), and between changes in WMH volumes and changes in cognitive performance, in a cohort of non-demented older adults. Methods: WMH volumes at 3 time-points (baseline, and 2- and 6-year follow-up) were

Renato Paes Leme, Jon Schneider, Heyang Shang, Shuran Zheng

We initiate the study of Bayesian conversations, which model interactive communication between two strategic agents without a mediator. We compare this to communication through a mediator and investigate the settings in which a mediation can expand the range of implementable outcomes. We look into the eventual outcome of two-player games after interactive co

Yatharth Dubey, Siyue Liu

In this note, we study the size of the support of integer solutions to linear equations $Ax=b, ~x\in\Z^n$ where $A\in\Z^{m\times n}, b\in\Z^n$. We give an upper bound on the smallest support size as a function of $A$, taken as a worst case over all $b$ such that the above system has a solution. This bound is asymptotically tight, and in fact matches the boun

Henrik Stromberg, Valentin Mayer-Eichberger, Armin Lohrengel

This paper describes a novel method of generating hex-dominant meshes using pre-computed optimal subdivisions of the unit cube in a grid-based approach. Our method addresses geometries that are standard in mechanical engineering and often must comply with the restrictions of subtractive manufacturability. A central component of our method is the set of subdi

Naivedya Amarnani, Amaury De Burgos, Wayne Broughton

We use Menger's Theorem and K\"onig's Line Colouring Theorem to show that in any tripartite graph with two complete (bipartite) sides the maximum number of pairwise edge-disjoint triangles equals the minimum number of edges that meet all triangles. This generalizes the corresponding result for complete tripartite graphs given by Lakshmanan, et al.

Leonie Koessler, Jonas Schuett

Companies like OpenAI, Google DeepMind, and Anthropic have the stated goal of building artificial general intelligence (AGI) - AI systems that perform as well as or better than humans on a wide variety of cognitive tasks. However, there are increasing concerns that AGI would pose catastrophic risks. In light of this, AGI companies need to drastically improve

Rafael Cerna Loli, Bruno Clerckx

In this letter, we propose the use of a meta-learning based precoder optimization framework to directly optimize the Rate-Splitting Multiple Access (RSMA) precoders with partial Channel State Information at the Transmitter (CSIT). By exploiting the overfitting of the compact neural network to maximize the explicit Average Sum-Rate (ASR) expression, we effect

G. Eremeev, U. Pudasaini, S. Cheban, J. Fischer

Two CEBAF 5-cell accelerator cavities have been coated with Nb3Sn film using the vapor diffusion technique. One cavity was coated in the Jefferson Lab Nb3Sn cavity coating system, and the other in the Fermilab Nb3Sn coating system. Both cavities were measured at 4 K and 2 K in the vertical dewar test in each lab and then assembled into a cavity pair at Jeffe

Samad Khabbazi-Oskouei, Stefano Mancini, Milajiguli Rexiti

We extend the notion of quantum reading to the case where the information to be retrieved, which is encoded into a set of quantum channels, is of quantum nature. We use two qubit unitaries describing the system environment interaction, with the initial environment state determining the system's input output channel and hence the encoded information. The perf

P. Chris Fragile, Koushik Chatterjee, Adam Ingram, Matthew Middleton

We present a straightforward argument for why the luminous, hard state of black hole X-ray binaries (BHXRBs) cannot always be associated with a magnetically arrested accretion disc (MAD). It relies on three core premises: 1) that the type-C quasi-periodic oscillation (QPO) is best explained by Lense-Thirring (LT) precession of a tilted, inner, hot flow; 2) t

Jakub Podgorný, Michal Dovčiak, René Goosmann, Frédéric Marin

Rebirth of X-ray polarimetric instruments will have a significant impact on our knowledge of compact accreting sources. The properties of inner-accreting regions of active galactic nuclei (AGNs) or X-ray binary systems (XRBs), such as black-hole spin, their disc inclination and orientation, shape and size of their corona, can be polarimetrically studied, par

Charles Naudet, Alan E. Lindsay

This paper is a computational bifurcation analysis of a non-linear partial differential equation (PDE) characterizing equilibrium configurations in Micro electromechanical Systems (MEMS). MEMS are engineering systems that utilize electrostatic forces to actuate elastic surfaces. The potential equilibrium states of MEMS are described by solutions of a singula

Reza Jahanbakhshi, Tamer A. Zaki

The influence of surface roughness on transition to turbulence in a Mach 4.5 boundary layer is studied using direct numerical simulations. Transition is initiated by the nonlinearly most dangerous inflow disturbance, which causes the earliest possible breakdown on a flat plate for the prescribed inflow energy and Mach number. This disturbance is primarily co

Kyle Mana, Fernando Acero, Stephen Mak, Parisa Zehtabi

Discrete optimization belongs to the set of $\mathcal{NP}$-hard problems, spanning fields such as mixed-integer programming and combinatorial optimization. A current standard approach to solving convex discrete optimization problems is the use of cutting-plane algorithms, which reach optimal solutions by iteratively adding inequalities known as \textit{cuts}

Milani M, Phou T, Ligoure C, Cipelletti L

The evaporation of drops of colloidal suspensions plays an important role in numerous contexts, such as the production of powdered dairies, the synthesis of functional supraparticles, and virus and bacteria survival in aerosols or drops on surfaces. The presence of colloidal particles in the evaporating drop eventually leads to the formation of a dense shell

Kazufumi Takahashi

Invertible disformal transformations serve as a useful tool to explore ghost-free scalar-tensor theories. In this paper, we construct a generalization of invertible disformal transformations that involves arbitrary higher-order covariant derivatives of the scalar field. As a result, we obtain a more general class of ghost-free scalar-tensor theories than eve

Gilchan Park, Byung-Jun Yoon, Xihaier Luo, Vanessa López-Marrero

Background: Identification of the interactions and regulatory relations between biomolecules play pivotal roles in understanding complex biological systems and the mechanisms underlying diverse biological functions. However, the collection of such molecular interactions has heavily relied on expert curation in the past, making it labor-intensive and time-con

Zifan Wang, Xinlei Yi, Yi Shen, Michael M. Zavlanos

This paper considers convex games involving multiple agents that aim to minimize their own cost functions using locally available information. A common assumption in the study of such games is that the agents are symmetric, meaning that they have access to the same type of information. Here we lift this assumption, which is often violated in practice, and in

A. N. Akay, B. Dagli, B. Ketenoglu, A. Ozturk

Construction of the ERLC (twin LC) collider tangential to LHC will give opportunity to investigate ep collisions at essentially higher center-of-mass energies than ERL50 and LHC based ep collider. Luminosity estimations show that values well exceeding 10^{34} cm^{-2}s^{-1} can be achieved for ERLC and HL-LHC based ep colliders. Certainly, proposed ep collide

Md Abdullah Al Mamun, Quazi Mishkatul Alam, Erfan Shayegani, Pedram Zaree

Machine learning (ML) models are overparameterized to support generality and avoid overfitting. The state of these parameters is essentially a "don't-care" with respect to the primary model provided that this state does not interfere with the primary model. In both hardware and software systems, don't-care states and undefined behavior have been shown to be

Samuel J. Edwards, Michael Levine

This paper will present a multi-fidelity, data-adaptive approach with a Long Short-Term Memory (LSTM) neural network to estimate ship response statistics in bimodal, bidirectional seas. The study will employ a fast low-fidelity, volume-based tool SimpleCode and a higher-fidelity tool known as the Large Amplitude Motion Program (LAMP). SimpleCode and LAMP dat

Yae Jee Cho, Gauri Joshi, Dimitrios Dimitriadis

Many existing FL methods assume clients with fully-labeled data, while in realistic settings, clients have limited labels due to the expensive and laborious process of labeling. Limited labeled local data of the clients often leads to their local model having poor generalization abilities to their larger unlabeled local data, such as having class-distributio

Canon Sun, Adil Attar, Igor Boettcher

We theoretically investigate the superfluid phase transition of helium-3 under nanoscale confinement of one spatial dimension realized in recent experiments. Instead of the 3x3 complex matrix order parameter found in the three-dimensional system, the quasi two-dimensional superfluid is described by a reduced 3x2 complex matrix. It features a nodal quasiparti

Denis C. Ilie-Ablachim, Bogdan Dumitrescu

In this paper we present new methods of anomaly detection based on Dictionary Learning (DL) and Kernel Dictionary Learning (KDL). The main contribution consists in the adaption of known DL and KDL algorithms in the form of unsupervised methods, used for outlier detection. We propose a reduced kernel version (RKDL), which is useful for problems with large dat

M. S. Shakel, H. E. Elsayed-Ali, G. Eremeev, U. Pudasaini

A DC cylindrical magnetron sputtering system has been commissioned and operated to deposit Nb3Sn onto 2.6 GHz Nb SRF cavities. After optimizing the deposition conditions in a mock-up cavity, Nb-Sn films are deposited first on flat samples by multilayer sequential sputtering of Nb and Sn, and later annealed at 950 {\deg}C for 3 hours. X-ray diffraction of the

Jonas Berx, Alireza Mashaghi

Circuit topology employs fundamental units of entanglement, known as soft contacts, for constructing knots from the bottom up, utilising circuit topology relations, namely parallel, series, cross, and concerted relations. In this article, we further develop this approach to facilitate the analysis of chirality, which is a significant quantity in polymer chem

Olivier Hervet, Caitlin A. Johnson, Adrian Youngquist

Multiwavelength observations are now the norm for studying blazars' various states of activity, classifying them, and determining possible underlying physical processes driving their emission. Broadband emission models became unavoidable tools for testing emission scenarios and setting values to physical quantities such as the magnetic field strength, Dopple

Dayu Yang, Yue Zhang, Hui Fang

In this paper, we report our methods and experiments for the TREC Conversational Assistance Track (CAsT) 2022. In this work, we aim to reproduce multi-stage retrieval pipelines and explore one of the potential benefits of involving mixed-initiative interaction in conversational passage retrieval scenarios: reformulating raw queries. Before the first ranking

Michał Siwak, Lynne A. Hillenbrand, Ágnes Kóspál, Péter Ábrahám

Gaia21bty, a pre-main sequence star that previously had shown aperiodic dips in its light curve, underwent a considerable $\Delta G\approx2.9$ mag brightening that occurred over a few months between 2020 October - 2021 February. The Gaia lightcurve shows that the star remained near maximum brightness for about $4-6$ months, and then started slowly fading ove

Frederic Runge, Jörg K. H. Franke, Frank Hutter

Experimental screening and selection pipelines for the discovery of novel riboswitches are expensive, time-consuming, and inefficient. Using computational methods to reduce the number of candidates for the screen could drastically decrease these costs. However, existing computational approaches do not fully satisfy all requirements for the design of such ini

Sofya Lipnitskaya

The regulAS software package is a bioinformatics tool designed to support computational biology researchers in investigating regulatory mechanisms of splicing alterations through integrative analysis of large-scale RNA-Seq data from cancer and healthy human donors, characterized by TCGA and GTEx projects. This technical report provides a comprehensive overvi

Roman Schubert, Thomas Plastow

We consider an open quantum system described by the GKLS equation and we are interested in the onset of decoherence. We are in particulary interested in situations where only some degrees of freedom of the system are coupled to the environment, and we want to understand if, and how fast, the noise travels through the system and eventually affects all degrees

Denis C. Ilie-Ablachim, Bogdan Dumitrescu

In this paper we present new algorithms for training reduced-size nonlinear representations in the Kernel Dictionary Learning (KDL) problem. Standard KDL has the drawback of a large size of the kernel matrix when the data set is large. There are several ways of reducing the kernel size, notably Nystr\"om sampling. We propose here a method more in the spirit

Shubhayan Sarkar

Quantum networks with multiple sources allow the observation of quantum nonlocality without inputs. Consequently, the incompatibility of measurements is not a necessity for observing quantum nonlocality when one has access to multiple quantum sources. Here we investigate the minimal scenario without inputs where one can observe any form of quantum nonlocalit

Denis C. Ilie-Ablachim, Bogdan Dumitrescu

In this paper we present a new classification method based on Dictionary Learning (DL). The main contribution consists of a kernel version of incoherent DL, derived from its standard linear counterpart. We also propose an improvement of the AK-SVD algorithm concerning the representation update. Our algorithms are tested on several popular databases of classi

Tushar M. Athawale, Bryan Triana, Tanmay Kotha, Dave Pugmire

Color maps are a commonly used visualization technique in which data are mapped to optical properties, e.g., color or opacity. Color maps, however, do not explicitly convey structures (e.g., positions and scale of features) within data. Topology-based visualizations reveal and explicitly communicate structures underlying data. Although we have a good underst

Patrick Emami, Xiangyu Zhang, David Biagioni, Ahmed S. Zamzam

In multi-timescale multi-agent reinforcement learning (MARL), agents interact across different timescales. In general, policies for time-dependent behaviors, such as those induced by multiple timescales, are non-stationary. Learning non-stationary policies is challenging and typically requires sophisticated or inefficient algorithms. Motivated by the prevale

Bryan Brzycki, Andrew P. V. Siemion, Imke de Pater, James M. Cordes

To date, the search for radio technosignatures has focused on sky location as a primary discriminant between technosignature candidates and anthropogenic radio frequency interference (RFI). In this work, we investigate the possibility of searching for technosignatures by identifying the presence and nature of intensity scintillations arising from the turbule

K. Khan, W. F. Magalhaes, Jailson S. Araujo, B. de Lima Bernardo

The principle of microscopic reversibility is a fundamental element in the formulation of fluctuation relations and the Onsager reciprocal relations. As such, a clear description of whether and how this principle is adapted to the quantum mechanical scenario might be essential to a better understanding of nonequilibrium quantum processes. Here, we propose a

Giorgio Cartechini, Marta Missiaggia, Emanuele Scifoni, Chiara La Tessa

We present MONAS (MicrOdosimetry-based modelliNg for relative biological effectiveness (RBE) ASsessment) toolkit. MONAS is a TOPAS Monte Carlo extension, that combines simulations of microdosimetric distributions with radiobiological microdosimetry-based models for predicting cell survival curves and dose-dependent RBE. MONAS expands TOPAS microdosimetric ex

Zikun Li, Jinjun Peng, Yixuan Mei, Sina Lin

Optimizing quantum circuits is challenging due to the very large search space of functionally equivalent circuits and the necessity of applying transformations that temporarily decrease performance to achieve a final performance improvement. This paper presents Quarl, a learning-based quantum circuit optimizer. Applying reinforcement learning (RL) to quantum

Arash Hajisharifi, Michele Girfoglio, Annalisa Quaini, Gianluigi Rozza

The simulation of atmospheric flows by means of traditional discretization methods remains computationally intensive, hindering the achievement of high forecasting accuracy in short time frames. In this paper, we apply three reduced order models that have successfully reduced the computational time for different applications in computational fluid dynamics w

Ranjan Sapkota, Manoj Karkee

The field of agricultural communication is evolving rapidly with the advent of generative artificial intelligence (AI), particularly image generation technologies. As these tools begin to influence how agricultural data is visualized and disseminated, the sector's diversity spanning both technical and non-technical researchers, demands a rigorous foundationa

Maldon Patrice Goodridge, Subhash Lakshminarayana, Alessandro Zocca

Load-altering attacks targetting a large number of IoT-based high-wattage devices (e.g., smart electric vehicle charging stations) can lead to serious disruptions of power grid operations. In this work, we aim to uncover spatiotemporal characteristics of LAAs that can lead to serious impact. The problem is challenging since existing protection measures such

Jesus Berdugo, Pavel Zalesskii

In this paper we prove a pro-p version of the Rips-Sela's Theorems on splittings of a group as an amalgamated free product or HNN-extension over an infinite cyclic subgroup.

Raiyan Rahman, Christopher Indris, Tianxiao Zhang, Kaidong Li

Aphid infestations can cause extensive damage to wheat and sorghum fields and spread plant viruses, resulting in significant yield losses in agriculture. To address this issue, farmers often rely on chemical pesticides, which are inefficiently applied over large areas of fields. As a result, a considerable amount of pesticide is wasted on areas without pests

Ege Erdem, Berke Demiralp, Hadi S Pisheh, Peyman Firoozy

The scanning electron microscope (SEM) recordings of dynamic nano-electromechanical systems (NEMS) are difficult to analyze due to the noise caused by low frame rate, insufficient resolution and blurriness induced by applied electric potentials. Here, we develop an image processing algorithm enhanced by the physics of the underlying system to track the motio

Sarah Healy, Shunsaku Horiuchi, Marta Colomer Molla, Dan Milisavljevic

We compile a catalog of 578 highly probable and 62 likely red supergiants (RSGs) of the Milky Way, which represents the largest list of Galactic RSG candidates designed for continuous follow-up to date. We match distances measured by Gaia DR3, 2MASS photometry, and a 3D Galactic dust map to obtain luminous bright late-type stars. Determining the stars' bolom

Anamari Nakic

We give the very first example of a simple $2-(81,6,2)$ design. Its points are the elements of the elementary abelian group of order 81 and each block is the union of two parallel lines of the 4-dimensional geometry over the field of order 3. Hence it is also additive.

T. B. Petersen, M. P. Kelly, T. Reid, M. Kedzie

A 218 MHz quarter wave niobium cavity has been fabricated for the purpose of demonstrating Nb3Sn technology on a low-beta accelerator cavity. Niobiumtin has been established as a promising next generation SRF material, but development has focused primarily in high-beta elliptical cell cavities. This material has a significantly higher TC than niobium, allowi

Eric Orenstein, Kevin Barnard, Lonny Lundsten, Geneviève Patterson

Ocean scientists have been collecting visual data to study marine organisms for decades. These images and videos are extremely valuable both for basic science and environmental monitoring tasks. There are tools for automatically processing these data, but none that are capable of handling the extreme variability in sample populations, image quality, and habi

Udi Boker, Guy Hefetz

Discounting the influence of future events is a key paradigm in economics and it is widely used in computer-science models, such as games, Markov decision processes (MDPs), reinforcement learning, and automata. While a single game or MDP may allow for several different discount factors, nondeterministic discounted-sum automata (NDAs) were only studied with r

Rundong Luo, Wenjing Wang, Wenhan Yang, Jiaying Liu

Low-light conditions not only hamper human visual experience but also degrade the model's performance on downstream vision tasks. While existing works make remarkable progress on day-night domain adaptation, they rely heavily on domain knowledge derived from the task-specific nighttime dataset. This paper challenges a more complicated scenario with border ap

Hai Duong, ThanhVu Nguyen, Matthew Dwyer

Deep Neural Networks (DNNs) have emerged as an effective approach to tackling real-world problems. However, like human-written software, DNNs can have bugs and can be attacked. To address this, research has explored a wide-range of algorithmic approaches to verify DNN behavior. In this work, we introduce NeuralSAT, a new verification approach that adapts the

Eman Alqahtani, Mustafa A. Mustafa

This paper proposes a zone-based privacy-preserving billing protocol for local energy markets that takes into account energy volume deviations of market participants from their bids. Our protocol incorporates participants' locations on the grid for splitting the deviations cost. The proposed billing model employs multiparty computation so that the accurate c