March 2023 arXiv papers — page 29

Mao Zeng

We explore inequality constraints as a new tool for numerically evaluating Feynman integrals. A convergent Feynman integral is non-negative if the integrand is non-negative in either loop momentum space or Feynman parameter space. Applying various identities, all such integrals can be reduced to linear sums of a small set of master integrals, leading to infi

Anthony Medellin, Anant Bhamri, Reza Langari, Swaminathan Gopalswamy

Autonomous navigation in unstructured off-road environments is greatly improved by semantic scene understanding. Conventional image processing algorithms are difficult to implement and lack robustness due to a lack of structure and high variability across off-road environments. The use of neural networks and machine learning can overcome the previous challen

Katerina P. Hilleke, Xiaoyu Wang, Dongbao Luo, Nisha Geng

The structure of the material responsible for the room temperature and near ambient pressure superconductivity reported in an N-doped lutetium hydride [Nature, 615, 244 (2023)] has not been conclusively determined. Herein, density functional theory calculations are performed in an attempt to uncover what it might be. Guided by a range of strategies including

Zheheng Luo, Qianqian Xie, Sophia Ananiadou

The performance of text summarization has been greatly boosted by pre-trained language models. A main concern of existing methods is that most generated summaries are not factually inconsistent with their source documents. To alleviate the problem, many efforts have focused on developing effective factuality evaluation metrics based on natural language infer

M. Eva Mungai, Jessy Grizzle

For legged robots to operate in complex terrains, they must be robust to the disturbances and uncertainties they encounter. This paper contributes to enhancing robustness through the design of fall detection/prediction algorithms that will provide sufficient lead time for corrective motions to be taken. Falls can be caused by abrupt (fast-acting), incipient

Gabriel Asher, Phil Bohlman, Karsten Kleyensteuber

COVID-19 misinformation on social media platforms such as twitter is a threat to effective pandemic management. Prior works on tweet COVID-19 misinformation negates the role of semantic features common to twitter such as charged emotions. Thus, we present a novel COVID-19 misinformation model, which uses both a tweet emotion encoder and COVID-19 misinformati

Viraja C. Khatu, Sarah C. Gallagher, Keith Horne, Edward M. Cackett

Measuring broad emission-line widths in active galactic nuclei (AGN) is not straightforward owing to the complex nature of flux variability in these systems. Line-width measurements become especially challenging when signal-to-noise is low, profiles are narrower, or spectral resolution is low. We conducted an extensive correlation analysis between emission-l

Deepan Muthirayan, Pramod P. Khargonekar

In this paper, we consider the problem of learning online to manage Demand Response (DR) resources. A typical DR mechanism requires the DR manager to assign a baseline to the participating consumer, where the baseline is an estimate of the counterfactual consumption of the consumer had it not been called to provide the DR service. A challenge in estimating b

Xuyang Shen, Dong Li, Jinxing Zhou, Zhen Qin

We explore a new task for audio-visual-language modeling called fine-grained audible video description (FAVD). It aims to provide detailed textual descriptions for the given audible videos, including the appearance and spatial locations of each object, the actions of moving objects, and the sounds in videos. Existing visual-language modeling tasks often conc

Mark A. Webster, Armanda O. Quintavalle, Stephen D. Bartlett

Storing quantum information in a quantum error correction code can protect it from errors, but the ability to transform the stored quantum information in a fault tolerant way is equally important. Logical Pauli group operators can be implemented on Calderbank-Shor-Steane (CSS) codes, a commonly-studied category of codes, by applying a series of physical Paul

Arturo de Nieves Gutierrez de Rubalcava, Oscar Sanchez Piñeiro, Rebeca Moreno Jiménez, Joseph Aylett-Bullock

Humanitarian agencies must be prepared to mobilize quickly in response to complex emergencies, and their effectiveness depends on their ability to identify, anticipate, and prepare for future needs. These are typically highly uncertain situations in which predictive modeling tools can be useful but challenging to build. To better understand the need for huma

Sneha Pandit, Sven Wedemeyer, Mats Carlsson, Mikołaj Szydlarski

The Ha line, one of the most studied chromospheric diagnostics, is a tracer for magnetic field structures, while its line core intensity provides an estimate of the mass density. The brightness temperatures from Atacama Large Millimetre-submm Array (ALMA) observations provide a complementary view of the activity and the thermal structure of stellar atmospher

Fabian R. Lux, Emil Prodan

Tessellations of the hyperbolic spaces by regular polygons are becoming popular because they support discrete quantum and classical models displaying unique spectral and topological characteristics. Resolving the true bulk spectra and the thermodynamic response functions of these models requires converging periodic boundary conditions and our work delivers a

Oswin Aichholzer, Joachim Orthaber, Birgit Vogtenhuber

It is a longstanding conjecture that every simple drawing of a complete graph on $n \geq 3$ vertices contains a crossing-free Hamiltonian cycle. We strengthen this conjecture to "there exists a crossing-free Hamiltonian path between each pair of vertices" and show that this stronger conjecture holds for several classes of simple drawings, including strongly

Pierre Nazé

For systems performing a weakly isothermal process, the decorrelation time dictates how fast the relaxation function decorrelates. However, like many other thermally isolated systems, the transverse-field quantum Ising chain presents an ill-defined decorrelation time. On the other hand, the Kibble-Zurek mechanism uses a heuristic relaxation time to achieve i

Konstantinos Georgiou, Nikos Giachoudis, Evangelos Kranakis

We consider search by mobile agents for a hidden, idle target, placed on the infinite line. Feasible solutions are agent trajectories in which all agents reach the target sooner or later. A special feature of our problem is that the agents are $p$-faulty, meaning that every attempt to change direction is an independent Bernoulli trial with known probability

Walid Hariri

Large language models, pivotal in artificial intelligence, find diverse applications. ChatGPT (Chat Generative Pre-trained Transformer), an OpenAI creation, stands out as a widely adopted, powerful tool. It excels in chatbots, content generation, language translation, recommendations, and medical applications, due to its ability to generate human-like respon

Ryosuke T. Tominaga, Shu-ichiro Inutsuka, Sanemichi Z. Takahashi

Secular gravitational instability (GI) is one promising mechanism for explaining planetesimal formation. The previous studies on secular GI utilized a razor-thin disk model and derived the growth condition in terms of the vertically integrated physical values such as dust-to-gas surface density ratio. However, in weakly turbulent disks where secular GI can o

Srinath Tankasala, Mitch Pryor

In this work, we address the problem of computation time for trajectory generation in quadrotors. Most trajectory generation methods for waypoint navigation of quadrotors, for example minimum snap/jerk and minimum-time, are structured as bi-level optimizations. The first level involves allocating time across all input waypoints and the second step is to mini

Derek Jones, Jonathan E. Allen, Xiaohua Zhang, Behnam Khaleghi

Publicly available collections of drug-like molecules have grown to comprise 10s of billions of possibilities in recent history due to advances in chemical synthesis. Traditional methods for identifying "hit" molecules from a large collection of potential drug-like candidates have relied on biophysical theory to compute approximations to the Gibbs free energ

Noëlle Harte, Dominik Obrist, Marco Caversaccio, Guillaume P. R. Lajoinie

The cochlea is our fluid-filled organ of hearing with a unique spiral shape. The physiological role of this shape remains unclear. Previous research has paid only little attention to the occurrence of transverse flow in the cochlea, in particular in relation to the cochlea's shape. To better understand its influence on fluid dynamics, this study aims to char

Petr Beneš, Filip Blaschke

We present a systematic exploration of a general family of effective $SU(2)$ models with an adjoint scalar. First, we discuss a redundancy in this class of models and use it to identify seemingly different, yet physically equivalent models. Next, we construct the Bogomol'nyi-Prasad-Sommerfield (BPS) limit and derive analytic monopole solutions. In contrast t

Andrea Ottolini, Raghavendra Tripathi

Consider a well-shuffled deck of cards of $n$ different types where each type occurs $m$ times. In a complete feedback game, a player is asked to guess the top card from the deck. After each guess, the top card is revealed to the player and is removed from the deck. The total number of correct guesses in a complete feedback game has attracted significant int

Andreas Löhne, Benjamin Weißing

Empirical quantiles for finitely distributed univariate random variables can be obtained by solving a certain linear program. It is shown in this short note that multivariate empirical quantiles can be obtained in a very similar way by solving a vector linear program. This connection provides a new approach for computing Tukey depth regions and more general

Stuart Raby, Junichiro Kawamura

In this talk, given at Corfu 2022 Workshop on the Standard Model and Beyond, I present work in collaboration with Junichiro Kawamura,Ref.~[arXiv:2212.00840]. The talk is also based on a number of papers on a Global $SU(5)$ F-theory GUT in collaboration with Herb Clemens. In the model $SU(5)$ is broken to the MSSM via a Wilson line. This is accomplished (with

Dipankar Maity

We consider a class of pursuit-evasion differential games in which the evader has continuous access to the pursuer's location, but not vice-versa. There is a remote sensor (e.g., a radar station) that can sense the evader's location upon a request from the pursuer and communicate that sensed location to the pursuer. The pursuer has a budget on the total numb

Felix Dobslaw, Kristian Angelin, Lena-Maria Öberg, Awais Ahmad

We see an explosive global labour demand in the Software Industry, and higher education institutions play a crucial role in supplying the industry with professionals with relevant education. Existing literature identifies a gap between what software engineering education teaches students and what the software industry demands. Using our open-sourced Job Mark

János Kollár, Pham Huu Tiep

Given a faithful finite-dimensional representation $V$ of a finite group $G$ over any field $\mathbb{F}$, we show that any irreducible ${\mathbb{F}}G$-module $W$ appears, as a submodule or a quotient, in $\mathrm{Sym}^m(V)$ for some integer $1 \leq m \leq |G|$ (that may depend on $W$).

Robert Hönig, Jan Ackermann, Mingyuan Chi

Modern neural encoders offer unprecedented text-image retrieval (TIR) accuracy, but their high computational cost impedes an adoption to large-scale image searches. To lower this cost, model cascades use an expensive encoder to refine the ranking of a cheap encoder. However, existing cascading algorithms focus on cross-encoders, which jointly process text-im

Xiang Li, Mingfu Shao

The high-throughput short-reads RNA-seq protocols often produce paired-end reads, with the middle portion of the fragments being unsequenced. We explore if the full-length fragments can be computationally reconstructed from the sequenced two ends in the absence of the reference genome - a problem here we refer to as de novo bridging. Solving this problem pro

Aniket Shah

We consider limits of certain measures supported on lattice points in lattice polyhedra defined as the intersection of half-spaces $\{m\in\mathbb{R}^n|\langle v_i,x\rangle+a_i \geq 0\}$, where $\sum_i v_i = 0$. The measures are densities associated to lattice random variables obtained by restriction of multinomial random variables. We find the limiting Gauss

Sofia Yfantidou, Pavlos Sermpezis, Athena Vakali, Ricardo Baeza-Yates

Personal informatics (PI) systems, powered by smartphones and wearables, enable people to lead healthier lifestyles by providing meaningful and actionable insights that break down barriers between users and their health information. Today, such systems are used by billions of users for monitoring not only physical activity and sleep but also vital signs and

Rajshekhar Das, Yonatan Dukler, Avinash Ravichandran, Ashwin Swaminathan

Prompt learning is an efficient approach to adapt transformers by inserting learnable set of parameters into the input and intermediate representations of a pre-trained model. In this work, we present Expressive Prompts with Residuals (EXPRES) which modifies the prompt learning paradigm specifically for effective adaptation of vision transformers (ViT). Out

Saba Asif Baig, Jacques Distler, Andreas Karch, Amir Raz

One characteristic feature of many fractonic lattice models, and a defining property of the exotic field theories developed to describe them, are subsystem symmetries including a conservation of not just net electric charge but also electric dipole moments or charges living on submanifolds. So far all such theories were based on internal subsystem symmetries

Owen Chase, Felicia McBride, Andrea Gokus, Matteo Lucchini

PKS 2005-489 is a well-known, bright southern BL Lac object that has been detected up to TeV energies. In a low-flux state it exhibits the expected multiwavelength double-peaked spectrum in the radio -- $\gamma$-ray band. The high-flux state shows extreme flux variations in the X-ray band with a hardening as well as a peculiar curved feature in the spectrum.

Aaron Berk, Simone Brugiapaglia, Tim Hoheisel

This paper studies well-posedness and parameter sensitivity of the Square Root LASSO (SR-LASSO), an optimization model for recovering sparse solutions to linear inverse problems in finite dimension. An advantage of the SR-LASSO (e.g., over the standard LASSO) is that the optimal tuning of the regularization parameter is robust with respect to measurement noi

Wenshi Gu

In the field of Japanese-Chinese translation linguistics, the issue of correctly translating attributive clauses has persistently proven to be challenging. Present-day machine translation tools often fail to accurately translate attributive clauses from Japanese to Chinese. In light of this, this paper investigates the linguistic problem underlying such diff

Zahra Shamsi, Diwakar Shukla

The molecular origins of proteins' functions are a combinatorial search problem in the proteins' sequence space, which requires enormous resources to solve. However, evolution has already solved this optimization problem for us, leaving behind suboptimal solutions along the way. Comparing suboptimal proteins along the evolutionary pathway, or ancestors, with

Sofia Yfantidou, Marios Constantinides, Dimitris Spathis, Athena Vakali

Personal devices are omnipresent in our lives, seamlessly monitoring our activities, from smart rings tracking sleep patterns to smartwatches keeping an eye on missed heartbeats. The rich data streams from such devices fuel advanced Artificial Intelligence (AI) applications. Instead of solely relying on direct sensor measurements, these applications are incr

Timothy R. Bedding, Hans Kjeldsen

With long data sets available for asteroseismology from space missions, it is sometimes necessary to deal with time series that have large gaps. This is becoming particularly relevant for TESS, which is revisiting many fields on the sky every two years. Because solar-like oscillators have finite mode lifetimes, it has become tempting to close large gaps by s

Chin Tseng, Ghulam Jilani Quadri, Zeyu Wang, Danielle Albers Szafir

Scatterplots commonly use color to encode categorical data. However, as datasets increase in size and complexity, the efficacy of these channels may vary. Designers lack insight into how robust different design choices are to variations in category numbers. This paper presents a crowdsourced experiment measuring how the number of categories and choice of col

Thomas Siegert

The Positron Puzzle is a half-century old conundrum about the origin of the Galactic $\gamma$-ray emission line at photon energies of 511 keV, and the shape of its morphology, showing a bulge-to-disk luminosity ratio of $\sim 1$ - unlike any astrophysical source distribution. Positrons that have been cooled to the eV scale capture electrons and form the inte

Nina Marhamati, Sena Clara Creston

This work proposes an interactive art installation "Mood spRing" designed to reflect the mood of the environment through interpretation of language and tone. Mood spRing consists of an AI program that controls an immersive 3D animation of the seasons. If the AI program perceives the language and tone of the users as pleasant, the animation progresses through

Manasi Mandal, Nathan C. Drucker, Phum Siriviboon, Thanh Nguyen

Topological superconductors (TSCs) have garnered significant research and industry attention in the past two decades. By hosting Majorana bound states which can be used as qubits that are robust against local perturbations, TSCs offer a promising platform toward (non-universal) topological quantum computation. However, there has been a scarcity of TSC candid

Harley Quinn, Wenlu Wang, Jörg G. Werner, Keith A. Brown

Multifunctional thin films in energy-related devices often must be electrically insulating where a single nanoscale defect can result in complete device-scale failure. Locating and characterizing such defects presents a fundamental problem where high-resolution imaging methods are needed to find defects, but imaging with high spatial resolution limits the fi

Yiling Xie, Xiaoming Huo

We propose an adjusted Wasserstein distributionally robust estimator -- based on a nonlinear transformation of the Wasserstein distributionally robust (WDRO) estimator in statistical learning. The classic WDRO estimator is asymptotically biased, while our adjusted WDRO estimator is asymptotically unbiased, resulting in a smaller asymptotic mean squared error

Yanyan Xu, Serdar Colak, Emre C. Kara, Scott J. Moura

The rising adoption of plug-in electric vehicles (PEVs) leads to the alignment of their electricity and their mobility demands. Therefore, transportation and power infrastructures are becoming increasingly interdependent. In this work, we uncover patterns of PEV mobility by integrating for the first time two unique data sets: (i) mobile phone activity of 1.3

Grant T. Barkley, Christian Gaetz

We adapt the hypercube decompositions introduced by Blundell-Buesing-Davies-Veli\v{c}kovi\'{c}-Williamson to prove the Combinatorial Invariance Conjecture for Kazhdan-Lusztig $R$-polynomials in the case of elementary intervals in $S_n$. This significantly generalizes the main previously-known case of the conjecture, that of lower intervals.

Fares Bougourzi, Cosimo Distante, Fadi Dornaika, Abdelmalik Taleb-Ahmed

In the last three years, the world has been facing a global crisis caused by Covid-19 pandemic. Medical imaging has been playing a crucial role in the fighting against this disease and saving the human lives. Indeed, CT-scans has proved their efficiency in diagnosing, detecting, and following-up the Covid-19 infection. In this paper, we propose a new Transfo

M. Stoilov, A. Adamczak, D. Bakalov, P. Danev

We report the first experimental determination of the collision-energy dependence of the muon transfer rate from the ground state of muonic hydrogen to oxygen at near-thermal energies. A sharp increase by nearly an order of magnitude in the energy range 0 - 70 meV was found that is not observed in other gases. The results set a reliable reference for quantum

Edoardo Maria Centamori, Michele Campisi, Vittorio Giovannetti

We study the performance of quantum thermal machines in which the working fluid of the model is represented by a many-body quantum system that is periodically connected with external baths via local couplings. A formal characterization of the limit cycles of the set-up is presented in terms of the mixing properties of the quantum channel that describes the e

François Lamothe, Alain Haït, Emmanuel Rachelson, Claudio Contardo

The strengthening of linear relaxations and bounds of mixed integer linear programs has been an active research topic for decades. Enumeration-based methods for integer programming like linear programming-based branch-and-bound exploit strong dual bounds to fathom unpromising regions of the feasible space. In this paper, we consider the strengthening of line

Felix Dobslaw, Peter Bergh

Sudden access to the rapidly improving large language model GPT by open-ai forces educational institutions worldwide to revisit their exam procedures. In the pre-GPT era, we successfully applied oral and open-book home exams for two courses in the third year of our predominantly remote Software Engineering BSc program. We ask in this paper whether our curren

Jean-Christophe Pain

In the present work, we provide the general expression of the normalized centered moments of the Fr\'echet extreme-value distribution. In order to try to represent a set of data corresponding to rare events by a Fr\'echet distribution, it is important to be able to determine its characteristic parameter $\alpha$. Such a parameter can be deduced from the vari

Valentin Macé, Raphaël Boige, Felix Chalumeau, Thomas Pierrot

In the context of neuroevolution, Quality-Diversity algorithms have proven effective in generating repertoires of diverse and efficient policies by relying on the definition of a behavior space. A natural goal induced by the creation of such a repertoire is trying to achieve behaviors on demand, which can be done by running the corresponding policy from the

Ruyi Ding, Cheng Gongye, Siyue Wang, Aidong Ding

Deep Neural Networks (DNN) are vulnerable to adversarial perturbations-small changes crafted deliberately on the input to mislead the model for wrong predictions. Adversarial attacks have disastrous consequences for deep learning-empowered critical applications. Existing defense and detection techniques both require extensive knowledge of the model, testing

Christian Remi Wewer, Alexandros Iosifidis

Moisture content (MC) estimation is important in the manufacturing process of drying bulky filter media products as it is the prerequisite for drying optimization. In this study, a dataset collected by performing 161 drying industrial experiments is described and a methodology for MC estimation in an non-destructive and online manner during industrial drying

Xiaowei Yu, Lu Zhang, Haixing Dai, Yanjun Lyu

Designing more efficient, reliable, and explainable neural network architectures is critical to studies that are based on artificial intelligence (AI) techniques. Previous studies, by post-hoc analysis, have found that the best-performing ANNs surprisingly resemble biological neural networks (BNN), which indicates that ANNs and BNNs may share some common pri

Jonathan Rowanhill, Ashlie B. Hocking, Aditya Zutshi, Kerianne L. Hobbs

Recent advances in artificial intelligence and machine learning may soon yield paradigm-shifting benefits for aerospace systems. However, complexity and possible continued on-line learning makes neural network control systems (NNCS) difficult or impossible to certify under the United States Military Airworthiness Certification Criteria defined in MIL-HDBK-51

Nicholas S. Manton, Maciej Dunajski

A quantum mechanical model for the Neon-20 nucleus is developed that allows for the splitting of a bipyramidal structure of five alpha-partices into an alpha-particle and an Oxygen-16 nucleus. The geometry of the configuration space is assumed to be a 3-dimensional spatial wormhole, and on the wormhole background there is an attractive short-range potential.

S. Pallikkara Chandrasekharan, I. Lucci, D. Gupta, C. Cornet

Here, we quantitatively determine the impact of III-V/Si interface atomic configuration on the wetting properties of the system. Based on a description at the atomic scale using density functional theory, we first show that it is possible to determine the absolute interface energies in heterogeneous materials systems. A large variety of absolute GaP surface

Thomas Bakx, Toshiki Kurita, Nora Elisa Chisari, Zvonimir Vlah

We test the regime of validity of the effective field theory (EFT) of intrinsic alignments (IA) at the one-loop level by comparing with 3D halo shape statistics in N-body simulations. This model is based on the effective field theory of large-scale structure (EFT of LSS) and thus a theoretically well-motivated extension of the familiar non-linear alignment (

Tao Sun, Lu Pang, Weimin Lyu, Chao Chen

Deep neural networks are vulnerable to backdoor attacks, where an adversary manipulates the model behavior through overlaying images with special triggers. Existing backdoor defense methods often require accessing a few validation data and model parameters, which is impractical in many real-world applications, e.g., when the model is provided as a cloud serv

Alejandro Guerra-Manzanares, L. Julian Lechuga Lopez, Michail Maniatakos, Farah E. Shamout

Machine Learning (ML) has recently shown tremendous success in modeling various healthcare prediction tasks, ranging from disease diagnosis and prognosis to patient treatment. Due to the sensitive nature of medical data, privacy must be considered along the entire ML pipeline, from model training to inference. In this paper, we conduct a review of recent lit

Kuo K. Liao, Glennys R. Farrar

We simulate the evolution of the helicity of relic neutrinos as they propagate to Earth through a realistic model of the Galactic magnetic field, improving upon the rough estimates in the literature. For magnetic moments consistent with experimental bounds and several orders of magnitude smaller, we confirm that the helicity of relic neutrinos and anti-neutr

Jonathan Ulises Alvarez MArtinez, Castro-Beltrán R, Polo-Parada Luis, Gerardo Gutierres-Juarez

The combination of microfluidic technology and optical fluids characterization techniques has been recently applied to produce lab-on-a-chip systems. In the present work, bringing together the imaging technique called photoacoustic imaging (PAI) and microfluidic technology were implemented to obtain micro-scale imaging. Laser-induced ultrasound signals were

Leonardo Patimo, Jacinta Torres

We construct atomic decompositions for crystals of type $C_{2}$ and define a charge statistic on them, thus providing positive combinatorial formulas for Kostka-Foulkes polynomials associated to them together with a natural geometric interpretation.

Xiangyu Chen, Varsha Kishore, Kilian Q Weinberger

Image steganography is the process of concealing secret information in images through imperceptible changes. Recent work has formulated this task as a classic constrained optimization problem. In this paper, we argue that image steganography is inherently performed on the (elusive) manifold of natural images, and propose an iterative neural network trained t

Beniamin Bogosel

The first main result presented in the paper shows that the perimeters of inner parallel sets of planar shapes having a given constant width are minimal for the Reuleaux triangles. This implies that the areas of inner parallel sets and, consequently, the inverse of the Cheeger constant are also minimal for the Reuleaux triangles. Proofs use elementary geomet

François Lamothe, Emmanuel Rachelson, Alain Haït, Cédric Baudoin

In this work, we consider the dynamic unsplittable flow problem. This variation of the unsplittable flow problem has received little attention so far. The unsplittable flow problem is an NP-hard extension of the multi-commodity flow problem where each commodity sends its flow on only one path. In its dynamic version, this problem features several time steps

Leo Y. Alcorn, H. K. C Yee, Laurent Drissen, Carter Rhea

We report CFHT/SITELLE imaging Fourier Transform Spectrograph observations of the Brightest Cluster Galaxy (BCG) of galaxy cluster Abell 2390 at z=0.228. The BCG displays a prominent cone of emission in H$\alpha$, H$\beta$, [NII], and [OII] to the North-West with PA = 42$^o$, 4.4 arcsec in length (15.9 kpc), which is associated with elongated and asymmetric

Robert M. Alaniz, Josh Brunner, Michael Coulombe, Erik D. Demaine

We analyze the computational complexity of basic reconfiguration problems for the recently introduced surface Chemical Reaction Networks (sCRNs), where ordered pairs of adjacent species nondeterministically transform into a different ordered pair of species according to a predefined set of allowed transition rules (chemical reactions). In particular, two que

Zhipeng Bao, Pavel Tokmakov, Yu-Xiong Wang, Adrien Gaidon

Object discovery -- separating objects from the background without manual labels -- is a fundamental open challenge in computer vision. Previous methods struggle to go beyond clustering of low-level cues, whether handcrafted (e.g., color, texture) or learned (e.g., from auto-encoders). In this work, we augment the auto-encoder representation learning framewo

François Brunault, Wadim Zudilin

We compute explicitly the Goncharov regulator integral associated to $K_4$ classes on modular curves in terms of $L$-values of modular forms. We use this expression to connect it with the Beilinson regulator integral.

Yiqing Shen, Pengfei Guo, Jingpu Wu, Qianqi Huang

The synergy of long-range dependencies from transformers and local representations of image content from convolutional neural networks (CNNs) has led to advanced architectures and increased performance for various medical image analysis tasks due to their complementary benefits. However, compared with CNNs, transformers require considerably more training dat

Forrest Hurley, Christine Heitsch

Understanding the base pairing of an RNA sequence provides insight into its molecular structure.By mining suboptimal sampling data, RNAprofiling 1.0 identifies the dominant helices in low-energy secondary structures as features, organizes them into profiles which partition the Boltzmann sample, and highlights key similarities/differences among the most infor

Chao-Xing Liu, Yulin Chen, Ali Yazdani, B. Andrei Bernevig

We develop an analytic theory to describe the interaction between electrons and K-phonons and study its influence on superconductivity in the bare bands of twisted bilayer graphene (TBG). We find that, due to symmetry and the two-center approximation, only one optical K-phonon (~ 160meV) of graphene is responsible for inter-valley electron-phonon interaction

François Lamothe, Emmanuel Rachelson, Alain Haït, Cedric Baudoin

Unsplittable flow problems cover a wide range of telecommunication and transportation problems and their efficient resolution is key to a number of applications. In this work, we study algorithms that can scale up to large graphs and important numbers of commodities. We present and analyze in detail a heuristic based on the linear relaxation of the problem a

Julián Morales, M. Guadalupe Aparicio, Carlos F. Longo, Cristian L. Arrieta

We introduce an electro-optical arrangement that is able to produce time-bin encoded symbols with the decoy state method over a standard optical fiber in the C-band telecom window. The device consists of a specifically designed pulse pattern generator for pulse production, a field-programmable gate array that controls timing and synchronization. The electric

Laura T. Knoll, Gustavo M. Bosyk

With the rapid development of quantum technologies in recent years, the need for high sensitivity measuring techniques has become a key issue. In particular, optical sensors based on quantum states of light have proven to be optimal resources for high precision interferometry. Nevertheless, their performance may be severely affected by the presence of noise

Olivier Ezratty

There is a common wisdom according to which many technologies can progress according to some exponential law like the empirical Moore's law that was validated for over half a century with the growth of transistors number in chipsets. As a still in the making technology with a lot of potential promises, quantum computing is supposed to follow the pack and gro

Lee Smolin

I study several aspects of the path(st) integral we formulated in previous papers on energetic causal sets with Cortes and others. The focus here is on quantum field theories, including the standard model of particle physics. I show that the the theory can be extended to a quantum field theory, cut off in momentum space. Fields of spin 0, 1/2 and 1 may be na

Yingying Zhang, William M. Postiglione, Rui Xie, Chi Zhang

Solid-state control of the thermal conductivity of materials is of exceptional interest for novel devices such as thermal diodes and switches. Here, we demonstrate the ability to continuously tune the thermal conductivity of nanoscale films of $\rm La_{0.5}Sr_{0.5}CoO_{3-\delta}$ (LSCO) by a factor of over 5, via a room-temperature electrolyte-gate-induced n

Raz Paul, Kobi Cohen, Gil Kedar

We consider the problem of of multi-flow transmission in wireless networks, where data signals from different flows can interfere with each other due to mutual interference between links along their routes, resulting in reduced link capacities. The objective is to develop a multi-flow transmission strategy that routes flows across the wireless interference n

Arthur Guijt, Dirk Thierens, Tanja Alderliesten, Peter A. N. Bosman

In a parallel EA one can strictly adhere to the generational clock, and wait for all evaluations in a generation to be done. However, this idle time limits the throughput of the algorithm and wastes computational resources. Alternatively, an EA can be made asynchronous parallel. However, EAs using classic recombination and selection operators (GAs) are known

Christopher Kang, Micheline B. Soley, Eleanor Crane, S. M. Girvin

Circuit QED enables the combined use of qubits and oscillator modes. Despite a variety of available gate sets, many hybrid qubit-boson (i.e., oscillator) operations are realizable only through optimal control theory (OCT) which is oftentimes intractable and uninterpretable. We introduce an analytic approach with rigorously proven error bounds for realizing s

Yi-Fan Jiang, Thomas P. Devereaux, Hong-Chen Jiang

We have studied the ground state properties of Hubbard model on long six-leg square cylinders with doped hole concentration per site $5.55\% \leq \delta\leq 12.5\%$ using density-matrix renormalization group. By keeping a large number of states for long system sizes, we find that the nature of the ground state is remarkably sensitive to the presence of next-

Pau-Chen Cheng, Wojciech Ozga, Enriquillo Valdez, Salman Ahmed

Intel Trust Domain Extensions (TDX) is a new architectural extension in the 4th Generation Intel Xeon Scalable Processor that supports confidential computing. TDX allows the deployment of virtual machines in the Secure-Arbitration Mode (SEAM) with encrypted CPU state and memory, integrity protection, and remote attestation. TDX aims to enforce hardware-assis

Hongyi Xu, Guoxian Song, Zihang Jiang, Jianfeng Zhang

We present OmniAvatar, a novel geometry-guided 3D head synthesis model trained from in-the-wild unstructured images that is capable of synthesizing diverse identity-preserved 3D heads with compelling dynamic details under full disentangled control over camera poses, facial expressions, head shapes, articulated neck and jaw poses. To achieve such high level o

Daniel R. Cassar

A multitask deep neural network model was trained on more than 218k different glass compositions. This model, called GlassNet, can predict 85 different properties (such as optical, electrical, dielectric, mechanical, and thermal properties, as well as density, viscosity/relaxation, crystallization, surface tension, and liquidus temperature) of glasses and gl

Mariia Dospolova

Let $K$ be a convex compact $GB$-subset of a separable Hilbert space $H$. Denote by $\mathrm{Spec}_k K$ the set $\{(\xi_1(h), \ldots, \xi_k(h))\colon h\in K\}\subset \mathbb{R}^k,$ where $\xi_1, \ldots, \xi_k$ are independent copies of the isonormal Gaussian process on $H$. Tsirelson showed that in this case the intrinsic volumes of $K$ satisfy the relation

Konstantinos Kontras, Christos Chatzichristos, Huy Phan, Johan Suykens

Sleep abnormalities can have severe health consequences. Automated sleep staging, i.e. labelling the sequence of sleep stages from the patient's physiological recordings, could simplify the diagnostic process. Previous work on automated sleep staging has achieved great results, mainly relying on the EEG signal. However, often multiple sources of information

Kimberly Do, Rock Yuren Pang, Jiachen Jiang, Katharina Reinecke

Computer science research has led to many breakthrough innovations but has also been scrutinized for enabling technology that has negative, unintended consequences for society. Given the increasing discussions of ethics in the news and among researchers, we interviewed 20 researchers in various CS sub-disciplines to identify whether and how they consider pot

Jake Welde, Matthew D. Kvalheim, Vijay Kumar

In this work, we give sufficient conditions for the almost global asymptotic stability of a cascade in which the subsystems are only almost globally asymptotically stable. The result is extended to upper triangular systems of arbitrary size. In particular, if the unforced subsystems are almost globally asymptotically stable and their only chain recurrent poi

Nicolas Sanchis-Gual, Adrian del Rio

We show that binary black hole mergers with precessing evolution can potentially excite photons from the quantum vacuum in such a way that total helicity is not preserved in the process. Helicity violation is allowed by quantum fluctuations that spoil the electric-magnetic duality symmetry of the classical Maxwell theory without charges. We show here that pr

Arkanath Pathak, Nicholas Dufour

Modern Generative Adversarial Networks (GANs) generate realistic images remarkably well. Previous work has demonstrated the feasibility of "GAN-classifiers" that are distinct from the co-trained discriminator, and operate on images generated from a frozen GAN. That such classifiers work at all affirms the existence of "knowledge gaps" (out-of-distribution ar

Zhiwei Zhou, Erick Elejalde

Social Media (SM) has become a stage for people to share thoughts, emotions, opinions, and almost every other aspect of their daily lives. This abundance of human interaction makes SM particularly attractive for social sensing. Especially during polarizing events such as political elections or referendums, users post information and encourage others to suppo

Shaunak Modak, Chris Hamilton

A major puzzle concerning the wide stellar binaries (semimajor axes $a\gtrsim 10^3$\,AU) in the Solar neighborhood is the origin of their observed superthermal eccentricity distribution function (DF), which is well-approximated by $P(e)\propto e^\alpha$ with $\alpha\approx 1.3$. This DF evolves under the combined influence of (i) tidal torques from the Galac

Hamzeh Davarikia, Faycal Znidi, Masoud Barati, Heena Rathore

In the event of large disturbances, the practice of controlled islanding is used as a last resort to prevent cascading outages. The application of the strategy at the right time is crucial to maintaining system security. A controlled islanding strategy may be deployed efficiently at the right time by predicting the time of uncontrolled system splitting. The

K. Ram Prabhakar, Vishal Vinod, Nihar Ranjan Sahoo, R. Venkatesh Babu

Enhancing practical low light raw images is a difficult task due to severe noise and color distortions from short exposure time and limited illumination. Despite the success of existing Convolutional Neural Network (CNN) based methods, their performance is not adaptable to different camera domains. In addition, such methods also require large datasets with s