March 2023 arXiv papers — page 14

M. M. Ettefaghi, R. Moazzemi, M. Yazdani Najafabadi

We consider the indirect detection of dark matter within an extension of the standard model (SM) including a singlet fermion as cold dark matter (CDM) and a singlet pseudo-scalar as a mediator between dark matter and the SM particles. The annihilation cross section of the CDM into two monochromatic photons is calculated and compared with the latest H.E.S.S.

Alexander Ororbia

Brain-inspired machine intelligence research seeks to develop computational models that emulate the information processing and adaptability that distinguishes biological systems of neurons. This has led to the development of spiking neural networks, a class of models that promisingly addresses the biological implausibility and {the lack of energy efficiency}

Yan Xu, Bin Diao, Yi-Bo Wang, Xiu-Lin Huang

The range of the U bosonic coupling constants in neutron star matter is a very interesting but still unsolved problem which has multifaceted influences in nuclear physics, particle physics, astrophysics and cosmology. The combination of the theoretical numerical simulation and the recent observations provides a very good opportunity to solve this problem. In

Ramesh Adhikari, Costas Busch

Sharding is used to address the performance and scalability issues of the blockchain protocols, which divides the overall transaction processing costs among multiple clusters of nodes. Shards require less storage capacity and communication and computation cost per node than the existing whole blockchain networks, and they operate in parallel to maximize perf

Ling An, Liming Ling, Xiaoen Zhang

In this paper, we explore the integrable fractional derivative nonlinear Schr\"odinger (fDNLS) equation by using the inverse scattering transform. Firstly, we start from the recursion operator and obtain a formal fDNLS equation. Then the inverse scattering problem is formulated and solved through the matrix Riemann-Hilbert problem. Subsequently, we give the

Jiaju Miao, Pawel Polak

We propose a gradient-free online ensemble learning algorithm that dynamically combines forecasts from a heterogeneous set of machine learning models based on their recent predictive performance, measured by out-of-sample R-squared. The ensemble is model-agnostic, requires no gradient access, and is designed for sequential forecasting under nonstationarity.

Michael B. Lund

For much of February 2023, the world was in panic as repeated balloon-like unidentified flying objects (UFOs) were reported over numerous countries by governments that often responded with military action. As a result, most of these craft either escaped or were destroyed, making any further observation of them nearly impossible. These were not the first time

Fangzhou Su, Wenlong Mou, Peng Ding, Martin J. Wainwright

Anecdotally, using an estimated propensity score is superior to the true propensity score in estimating the average treatment effect based on observational data. However, this claim comes with several qualifications: it holds only if propensity score model is correctly specified and the number of covariates $d$ is small relative to the sample size $n$. We re

Garima Goyal, Dheeraj Kumar Singh

We examine the possible existence of Dirac semimetal with magnetic order in a two-dimensional system with a nonsymmorphic symmetry by using the Hartree-Fock mean-field theory within the Hubbard model. We locate the region in the second-neighbor spin-orbit coupling vs Hubbard interaction phase diagram, where such a state is stabilized. The edge states for the

Zequn Cao, Xiaoheng Deng

Task offloading is a widely used technology in Mobile Edge Computing (MEC), which declines the completion time of user task with the help of resourceful edge servers. Existing works mainly focus on the case that the computation density of a user task is homogenous so that it can be offloaded in full or by percentage. However, various user tasks in real life

Hongxiang Cai, Zeyuan Zhang, Zhenyu Zhou, Ziyin Li

Integrating LiDAR and Camera information into Bird's-Eye-View (BEV) has become an essential topic for 3D object detection in autonomous driving. Existing methods mostly adopt an independent dual-branch framework to generate LiDAR and camera BEV, then perform an adaptive modality fusion. Since point clouds provide more accurate localization and geometry infor

Gildas Diguet, Madoka Nakayama, Sohei Tasaki, Fumitake Kato

We numerically study the anisotropic Turing patterns (TPs) of an activator-inhibitor system, focusing on anisotropic diffusion by using the Finsler geometry (FG) modeling technique. In the FG modeling prescription, the diffusion coefficients are dynamically generated to be direction dependent owing to an internal degree of freedom (IDOF) and its interaction

Yi-Xian Chen, Douglas N. C. Lin

Accretion discs around super-massive black holes (SMBH) not only power active galactic nuclei (AGNs), but also host single and binary embedded stellar-mass black holes (EBHs) that grow rapidly from gas accretion. The merger of these EBHs provides a promising mechanism for the excitation of some gravitational wave events observed by LIGO-Virgo, especially tho

Xiaodan Li, Yuefeng Chen, Yao Zhu, Shuhui Wang

Recent studies have shown that higher accuracy on ImageNet usually leads to better robustness against different corruptions. Therefore, in this paper, instead of following the traditional research paradigm that investigates new out-of-distribution corruptions or perturbations deep models may encounter, we conduct model debugging in in-distribution data to ex

Zhongxu Zhai, Will J. Percival, Hong Guo

We measure and analyze galaxy clustering and the dependence on luminosity, color, age, stellar mass and specific star formation rate using Baryon Oscillation Spectroscopic Survey (BOSS) galaxies at $0.48<z<0.62$. We fit the monopole and quadrupole moments of the two-point correlation function (2PCF) and its projection on scales of $0.1$ -- $60.2h^{-1}$Mpc, a

Nozomi Sugiura

Principal Geodesic Analysis (PGA) is applied to a climate time series. First, we transform each multidimensional sequence into the path signature. Since the signature lives in a curved space, usual principal component analysis (PCA) is not applicable. Instead, we treat the signature space as a geodesic manifold. By replacing the notion of straight lines with

Nishant Jain, Suryansh Kumar, Luc Van Gool

We introduce an approach to enhance the novel view synthesis from images taken from a freely moving camera. The introduced approach focuses on outdoor scenes where recovering accurate geometric scaffold and camera pose is challenging, leading to inferior results using the state-of-the-art stable view synthesis (SVS) method. SVS and related methods fail for o

Fei Zhu, Zhen Cheng, Xu-Yao Zhang, Cheng-Lin Liu

Reliable confidence estimation for deep neural classifiers is a challenging yet fundamental requirement in high-stakes applications. Unfortunately, modern deep neural networks are often overconfident for their erroneous predictions. In this work, we exploit the easily available outlier samples, i.e., unlabeled samples coming from non-target classes, for help

Hasna Chnafa, Miloud Mekkaoui, Ahmed Jellal, Abdelhadi Bahaoui

We study the effect of the energy gap on the transmission of fermions in graphene exposed to linearly polarized light as a laser barrier. We determine the energy spectrum, apply boundary conditions at interfaces, and use the transfer matrix approach to obtain transmissions for all energy modes. We show that when the energy gap increases, the oscillations of

Daniel Campos, Alexandre Marques, Mark Kurtz, ChengXiang Zhai

In this paper, we introduce the range of oBERTa language models, an easy-to-use set of language models which allows Natural Language Processing (NLP) practitioners to obtain between 3.8 and 24.3 times faster models without expertise in model compression. Specifically, oBERTa extends existing work on pruning, knowledge distillation, and quantization and lever

Tasuku Inao, Isao Yokota

Due to ethical and economical reasons, sequential single-arm trial designs are used for assessing the therapeutic efficacy of new treatments in phase II trials. Simon's 2-stage design and Lan-DeMets' $\alpha$-spending function method with O'Brien-Fleming type are widely recognized as the traditional methods for futility stopping and efficacy stopping, respec

Sirui Ding, Qiaoyu Tan, Chia-yuan Chang, Na Zou

Organ transplant is the essential treatment method for some end-stage diseases, such as liver failure. Analyzing the post-transplant cause of death (CoD) after organ transplant provides a powerful tool for clinical decision making, including personalized treatment and organ allocation. However, traditional methods like Model for End-stage Liver Disease (MELD

Le Bin Ho

We present a no-go result for postselection measurements where the conditional expectation value of a joint system-device observable under postselection is nothing else than the conventional expectation value. Such a no-go result relies on the rank-m degenerate of the joint observable, where m is the dimension of the device subspace. Remarkable, we show that

Fanchen Meng, Benedikt Maurer, Fabian Peschel, Sencer Selcuk

X-ray absorption spectroscopy (XAS) is an element-specific materials characterization technique that is sensitive to structural and electronic properties. First-principles simulated XAS has been widely used as a powerful tool to interpret experimental spectra and draw physical insights. Recently, there has also been growing interest in building computational

Hanqi Jiang, Cheng Zeng, Runnan Chen, Shuai Liang

Recently, methods for neural surface representation and rendering, for example NeuS, have shown that learning neural implicit surfaces through volume rendering is becoming increasingly popular and making good progress. However, these methods still face some challenges. Existing methods lack a direct representation of depth information, which makes object rec

S. H. Chiu, T. K. Kuo

A hermitian matrix can be parametrized by a set consisting of its determinant and the eigenvalues of its submatrices. We established a group of equations which connect these variables with the mixing parameters of diagonalization. These equations are simple in structure and manifestly invariant in form under the symmetry operations of dilatation, translation

Zengjie Zhang, Sofie Haesaert

The control synthesis of a dynamic system subject to a signal temporal logic (STL) specification is commonly formulated as a mixed-integer linear/convex programming (MILP/MICP) problem. Solving such a problem is computationally expensive when the specification is long and complex. In this paper, we propose a framework to transform a long and complex specific

Hitoshi Seo, Yasuhiro Tanaka

We numerically investigate photo-responses of the charge ordered state upon stimuli of pulsed laser light, especially paying attention to the differences in the pulse width, whose shortness has been a key to experimentally realize large photo-induced effects. As a model for charge ordering, we consider an interacting spinless fermion model on a one-dimension

Hardik Sharma, Rajat Garg, Harshini Sewani, Rasha Kashef

Globalization has introduced many new challenges making Supply chain management (SCM) complex and huge, for which improvement is needed in many industries. The Internet of Things (IoT) has solved many problems by providing security and traceability with a promising solution for supply chain management. SCM is segregated into different processes, each requiri

Chihiro Matsui, Naoto Tsuji

We give an exact matrix product steady state and matrix product forms of local observables for the bulk impurity-doped XXZ spin model coupled to dissipators at both ends, whose dynamics is described by the Lindblad quantum master equation. We find that local magnetization is induced at the impurity site when the spin current flows, which is contrary to the u

Tadashi Wadayama, Ayano Nakai-Kasai

A continuous-time average consensus system is a linear dynamical system defined over a graph, where each node has its own state value that evolves according to a simultaneous linear differential equation. A node is allowed to interact with neighboring nodes. Average consensus is a phenomenon that the all the state values converge to the average of the initia

C. A. Fonseca-Mora

Let $\Phi'$ denote the strong dual of a nuclear space $\Phi$. In this paper we introduce sufficient conditions for the convergence uniform on compacts in probability for a sequence of $\Phi'$-valued processes with continuous or c\`{a}dl\`{a}g paths. We illustrate the usefulness of our results by considering two applications to stochastic analysis. First, we

Jie Zhou, Leong-Chuan Kwek, Jing-Ling Chen

Quantum entanglement serves as an important resource for quantum processing. In the original thought experiment of the Quantum Cheshire Cat, the physical properties of the cat (state) can be decoupled from its quantum entities. How do quantum entanglement and weak values affect such thought experiment? Here, we conceive a new thought experiment that exploits

Ethan Wisdom, Tejas Gokhale, Chaowei Xiao, Yezhou Yang

In this work, we present a data poisoning attack that confounds machine learning models without any manipulation of the image or label. This is achieved by simply leveraging the most confounding natural samples found within the training data itself, in a new form of a targeted attack coined "Mole Recruitment." We define moles as the training samples of a cla

Joshua Yang, Melissa A. Guidry, Daniil M. Lukin, Kiyoul Yang

Inverse design has revolutionized the field of photonics, enabling automated development of complex structures and geometries with unique functionalities unmatched by classical design. However, the use of inverse design in nonlinear photonics has been limited. In this work, we demonstrate quantum and classical nonlinear light generation in silicon carbide na

Steven L. Brunton, J. Nathan Kutz

Partial differential equations (PDEs) are among the most universal and parsimonious descriptions of natural physical laws, capturing a rich variety of phenomenology and multi-scale physics in a compact and symbolic representation. This review will examine several promising avenues of PDE research that are being advanced by machine learning, including: 1) the

Michael Zingale, Kiran Eiden, Max Katz

We explore the early evolution of flame ignition and spreading on the surface of a neutron star in three-dimensions, in the context of X-ray bursts. We look at the nucleosynthesis and morphology of the burning front and compare to two-dimensional axisymmetric simulations to gauge how important a full three-dimensional treatment of the flame is for the early

Qinsheng Zhang, Jiaming Song, Xun Huang, Yongxin Chen

We present DiffCollage, a compositional diffusion model that can generate large content by leveraging diffusion models trained on generating pieces of the large content. Our approach is based on a factor graph representation where each factor node represents a portion of the content and a variable node represents their overlap. This representation allows us

Stefano Campese, Ivano Lauriola, Alessandro Moschitti

An effective paradigm for building Automated Question Answering systems is the re-use of previously answered questions, e.g., for FAQs or forum applications. Given a database (DB) of question/answer (q/a) pairs, it is possible to answer a target question by scanning the DB for similar questions. In this paper, we scale this approach to open domain, making it

Lenore Blum, Manuel Blum

We have defined the Conscious Turing Machine (CTM) for the purpose of investigating a Theoretical Computer Science (TCS) approach to consciousness. For this, we have hewn to the TCS demand for simplicity and understandability. The CTM is consequently and intentionally a simple machine. It is not a model of the brain, though its design has greatly benefited -

Gustavo Henrique dos Santos, Raphael César Souza Pimenta, Rafael de Morais Gomes, Stephen Patrick Walborn

In parametric down conversion, a nonlinear crystal is pumped by a laser and spontaneous emission takes place in signal and idler modes according to the phase matching conditions. A seed laser can stimulate the emission in the signal beam if there is mode overlap between them. This also enhances the emission in the idler beam, affecting its coherence properti

W. G. Jiang, C. S. Barquist, K. Gunther, Y. Lee

A microelectromechanical oscillator with a 0.73 $\mu$m gap structure is employed to probe the surface Andreev bound states in superfluid $^3$He-B. The surface specularity of the oscillator is increased by preplating it with 1.6 monolayers of $^4$He. In the linear regime, the temperature dependence of the damping coefficient is measured at various pressures,

A. Emran, C. M. Dalle Ore, D. P. Cruikshank, J. C. Cook

A link between exposures of water (H${}_{2}$O) ice with traces of an ammoniated compound (e.g., a salt) and the probable effusion of a water-rich cryolava onto the surface of Pluto has been established in previous investigations (Dalle Ore et al. 2019). Here we present the results from the application of a machine learning technique and a radiative transfer

Varun Nair, Elliot Schumacher, Geoffrey Tso, Anitha Kannan

Large language models (LLMs) have emerged as valuable tools for many natural language understanding tasks. In safety-critical applications such as healthcare, the utility of these models is governed by their ability to generate outputs that are factually accurate and complete. In this work, we present dialog-enabled resolving agents (DERA). DERA is a paradig

Dallin J. Barton, Dan-Thien Nguyen, Daniel E. Perea, Kelsey A. Stoerzinger

Hydrogen embrittlement mechanisms of steels have been studied for several decades. Understanding hydrogen diffusion behavior in steels is crucial towards both developing predictive models for hydrogen embrittlement and identifying mitigation strategies. However, because hydrogen has a low atomic mass, it is extremely challenging to detect by most analytical

Anthony O'Dea

The Arnold Cat Map (ACM) is a popular chaotic map used in image encryption. Chaotic maps are known for their sensitivity to initial conditions and their ability to mix, or rearrange, pixels. However, ACM is periodic, and the period is relatively short. This periodicity decreases the effective key space for a cryptosystem. Further, ACM can only be performed o

Dhruv C. Desai, Jinsoo Park, Jin-Jian Zhou, Marco Bernardi

Bulk Dirac semimetals (DSMs) exhibit unconventional transport properties and phase transitions due to their peculiar low-energy band structure. Yet the electronic interactions governing nonequilibrium phenomena in DSMs are not fully understood. Here we show that electron-phonon (e-ph) interactions in a prototypical bulk DSM, Na3Bi, are predominantly two-dime

Christophe Morisset, Romano L. M. Corradi, Jorge García-Rojas, Antonio Mampaso

Ueta & Otsuka (2021) proposed a method, named as the "Proper Plasma Analysis Practice", to analyze spectroscopic data of ionized nebulae. The method is based on a coherent and simultaneous determination of the reddening correction and physical conditions in the nebulae. The same authors (Ueta & Otsuka 2022, UO22) reanalyzed the results of Galera-Rosillo et a

Ricardo Oliveira, Miguel Gonçalves, Pedro Ribeiro, Eduardo V. Castro

We show that incommensurability can enhance superconductivity in one dimensional quasiperiodic systems with s-wave pairing. As a parent model, we use a generalized Aubry-André model that includes quasiperiodic modulations both in the potential and in the hoppings. In the absence of interactions, the model contains extended, critical and localized phases for

Veronica Pasquarella, Fernando Quevedo

We calculate amplitudes for 2D vacuum transitions by means of the Euclidean methods of Coleman-De Luccia (CDL) and Brown-Teitelboim (BT), as well as the Hamiltonian formalism of Fischler, Morgan and Polchinski (FMP). The resulting similarities and differences in between the three approaches are compared with their respective 4D realisations. For CDL, the tot

Mark Whitmeyer

A sender with state-independent preferences (i.e., transparent motives) privately observes a signal about the state of the world before sending a message to a receiver, who subsequently takes an action. Regardless of whether the receiver can mediate--and commit to a garbling of the sender's message--or delegate--commit to a stochastic decision rule as a func

Kun-Ting Chen, Quynh Quang Ngo, Kuno Kurzhals, Kim Marriott

We investigate reading strategies for node-link diagrams that wrap around the boundaries in a flattened torus topology by examining eye tracking data recorded in a previous controlled study. Prior work showed that torus drawing affords greater flexibility in clutter reduction than traditional node-link representations, but impedes link-and-path exploration t

Kathryn Beck, Mahya Ghandehari, Jeannette Janssen, Nauzer Kalyaniwalla

Current methods of graph signal processing rely heavily on the specific structure of the underlying network: the shift operator and the graph Fourier transform are both derived directly from a specific graph. In many cases, the network is subject to error or natural changes over time. This motivated a new perspective on GSP, where the signal processing frame

Liran Peng, Peter N. Blossey, Walter M. Hannah, Christopher S. Bretherton

High-Resolution Multi-scale Modeling Frameworks (HR) -- global climate models that embed separate, convection-resolving models with high enough resolution to resolve boundary layer eddies -- have exciting potential for investigating low cloud feedback dynamics due to reduced parameterization and ability for multidecadal throughput on modern computing hardwar

Davide Villa, Miead Tehrani-Moayyed, Clifton Paul Robinson, Leonardo Bonati

Wireless network emulators are being increasingly used for developing and evaluating new solutions for Next Generation (NextG) wireless networks. However, the reliability of the solutions tested on emulation platforms heavily depends on the precision of the emulation process, model design, and parameter settings. To address, obviate, or minimize the impact o

Michael Poli, Stefano Massaroli, Stefano Ermon, Bryan Wilder

We present a methodology for formulating simplifying abstractions in machine learning systems by identifying and harnessing the utility structure of decisions. Machine learning tasks commonly involve high-dimensional output spaces (e.g., predictions for every pixel in an image or node in a graph), even though a coarser output would often suffice for downstre

Zhenhua Chen, David Crandall

Inspired by the ConvNets with structured hidden representations, we propose a Tensor-based Neural Network, TCNN. Different from ConvNets, TCNNs are composed of structured neurons rather than scalar neurons, and the basic operation is neuron tensor transformation. Unlike other structured ConvNets, where the part-whole relationships are modeled explicitly, the

Yixuan Lin, Ji Liu

The paper proposes a heterogeneous push-sum based subgradient algorithm for multi-agent distributed convex optimization in which each agent can arbitrarily switch between subgradient-push and push-subgradient at each time. It is shown that the heterogeneous algorithm converges to an optimal point at an optimal rate over time-varying directed graphs.

Joanne Tan, Tie Sien Suk

What's in a name, a poet once asked. To which we present this work, where we investigate the importance of a paper title in ensuring its best outcome. We queried astronomy papers using NASA ADS and ranked 6000 of them in terms of cheekiness level. We investigate the correlation between citation counts and (i) the presence of a colon, and (ii) cheekiness rank

Son Tu, Jianlu Zhang

For a continuous Hamiltonian $H : (x, p, u) \in T^*\mathbb{R}^n \times \mathbb{R}\rightarrow \mathbb{R}$, we consider the asymptotic behavior of associated Hamilton--Jacobi equations with state-constraint $H(x, Du, \lambda u) \leq C_\lambda$ in $\Omega_\lambda\subset \mathbb{R}^n$ and $H(x, Du, \lambda u) \geq C_\lambda$ on $\overline{\Omega}_\lambda\subset

Mohammad Askari, Won Dong Shin, Damian Lenherr, William Stewart

Multimodal UAVs (Unmanned Aerial Vehicles) are rarely capable of more than two modalities, i.e., flying and walking or flying and perching. However, being able to fly, perch, and walk could further improve their usefulness by expanding their operating envelope. For instance, an aerial robot could fly a long distance, perch in a high place to survey the surro

Megan Stickler, William Ott, Zachary P. Kilpatrick, Krešimir Josić

Normative models are often used to describe how humans and animals make decisions. These models treat deliberation as the accumulation of uncertain evidence that terminates with a commitment to a choice. When extended to social groups, such models often assume that individuals make independent observations. However, individuals typically gather evidence from

Sebastien Brisard, Michael Bertin, Frederic Legoll

Using the equivalent inclusion method (a method strongly related to the Hashin-Shtrikman variational principle) as a surrogate model, we propose a variance reduction strategy for the numerical homogenization of random composites made of inclusions (or rather inhomogeneities) embedded in a homogeneous matrix. The efficiency of this strategy is demonstrated wi

Shentong Mo, Yapeng Tian

Sound source localization is a typical and challenging task that predicts the location of sound sources in a video. Previous single-source methods mainly used the audio-visual association as clues to localize sounding objects in each image. Due to the mixed property of multiple sound sources in the original space, there exist rare multi-source approaches to

F. Esteban Contreras Mendoza, César Hernández Cruz

Given nonnegative integers, $s$ and $k$, an $(s,k)$-polar partition of a graph $G$ is a partition $(A,B)$ of $V_G$ such that $G[A]$ and $\overline{G[B]}$ are complete multipartite graphs with at most $s$ and $k$ parts, respectively. If $s$ or $k$ is replaced by $\infty$, it means that there is no restriction on the number of parts of $G[A]$ or $\overline{G[B

David P. Blecher, Arianna Cecco, Mehrdad Kalantar

We present some more foundations for a theory of real structure in operator spaces and algebras, in particular concerning the real case of the theory of injectivity, and the injective, ternary, and $C^*$-envelope. We consider the interaction between these topics and the complexification. We also generalize many of these results to the setting of operator spa

Alastair N. Fletcher, Julie M. Steranka

We show that the set of Julia limiting directions of a transcendental-type $K$-quasiregular mapping $f:\mathbb{R}^n\to \mathbb{R}^n$ must contain a component of a certain size, depending on the dimension $n$, the maximal dilatation $K$, and the order of growth of $f$. In particular, we show that if the order of growth is small enough, then every direction is

Jinbing Chen, Dmitry E. Pelinovsky

We study the standing periodic waves in the semi-discrete integrable system modelled by the Ablowitz-Ladik equation. We have related the stability spectrum to the Lax spectrum by separating the variables and by finding the characteristic polynomial for the standing periodic waves. We have also obtained rogue waves on the background of the modulationally unst

Julio Silva-Rodríguez, Jose Dolz, Ismail Ben Ayed

The recent popularity of foundation models and the pre-train-and-adapt paradigm, where a large-scale model is transferred to downstream tasks, is gaining attention for volumetric medical image segmentation. However, current transfer learning strategies devoted to full fine-tuning for transfer learning may require significant resources and yield sub-optimal r

David P. Blecher

We verify that a large portion of the theory of complex operator spaces and operator algebras (as represented by the 2004 book by the author and Le Merdy for specificity) transfers to the real case. We point out some of the results that do not work in the real case. We also discuss how the theory and standard constructions interact with the complexification.

Henry Navarro, Ali C. Basaran, Fernando Ajejas, Lorenzo Fratino

The strongly correlated material La0.7Sr0.3MnO3 (LSMO) exhibits metal-to-insulator and magnetic transition near room temperature. Although the physical properties of LSMO can be manipulated by strain, chemical doping, temperature, or magnetic field, they often require large external stimuli. To include additional flexibility and tunability, we developed a hy

Zhining Gu, Wenwen Li, Michael Hanemann, Yushiou Tsai

This paper explores the application of machine learning to enhance our understanding of water accessibility issues in underserved communities called Colonias located along the northern part of the United States - Mexico border. We analyzed more than 2000 such communities using data from the Rural Community Assistance Partnership (RCAP) and applied hierarchic

Nikhilesh Alatur, Olov Andersson, Roland Siegwart, Lionel Ott

From construction materials, such as sand or asphalt, to kitchen ingredients, like rice, sugar, or salt; the world is full of granular materials. Despite impressive progress in robotic manipulation, manipulating and interacting with granular material remains a challenge due to difficulties in perceiving, representing, modelling, and planning for these variab

Franziska Boenisch, Christopher Mühl, Adam Dziedzic, Roy Rinberg

When training a machine learning model with differential privacy, one sets a privacy budget. This budget represents a maximal privacy violation that any user is willing to face by contributing their data to the training set. We argue that this approach is limited because different users may have different privacy expectations. Thus, setting a uniform privacy

Vincent Froese, Christoph Hertrich

We study the parameterized complexity of training two-layer neural networks with respect to the dimension of the input data and the number of hidden neurons, considering ReLU and linear threshold activation functions. Albeit the computational complexity of these problems has been studied numerous times in recent years, several questions are still open. We an

Brijesh Kumar

We present the idea of emergent qubits by an exact model construction on a trestle, also generalized to arbitrary graphs. The corresponding eigenstates are quantum paramagnetic, with free multipolar moments. We rigorously transform the toric code model on a torus, cylinder and sheet into emergent qubits, writing all the eigenstates exactly. We devise exact q

Jiabin Lin, Shana Moothedath

We study the problem of federated stochastic multi-arm contextual bandits with unknown contexts, in which M agents are faced with different bandits and collaborate to learn. The communication model consists of a central server and the agents share their estimates with the central server periodically to learn to choose optimal actions in order to minimize the

Zhimei Ren, Emil Y. Sidky, Rina Foygel Barber, Chien-Min Kao

An alternating direction method of multipliers (ADMM) framework is developed for nonsmooth biconvex optimization for inverse problems in imaging. In particular, the simultaneous estimation of activity and attenuation (SAA) problem in time-of-flight positron emission tomography (TOF-PET) has such a structure when maximum likelihood estimation (MLE) is employe

Xinyi Wu, Haohong Wang, Aggelos K. Katsaggelos

User-generated cinematic creations are gaining popularity as our daily entertainment, yet it is a challenge to master cinematography for producing immersive contents. Many existing automatic methods focus on roughly controlling predefined shot types or movement patterns, which struggle to engage viewers with the circumstances of the actor. Real-world cinemat

R. Bernabei, P. Belli, A. Bussolotti, V. Caracciolo

Proceedings for our meeting ``What comes beyond the Standard Models'', which covered a broad series of subjects.

Mayte Cano, Andrés Perillo, Juan Antonio López, Faustino Tello

This White Paper sets out to explain the value that metamodelling can bring to air traffic management (ATM) research. It will define metamodelling and explore what it can, and cannot, do. The reader is assumed to have basic knowledge of SESAR: the Single European Sky ATM Research project. An important element of SESAR, as the technological pillar of the Sing

Idris Cinemre, Gokce Hacioglu

Orthogonal frequency division multiplexing (OFDM) is critical for high-speed visible light communication (VLC) transmission; however, it suffers from a high peak-to-average power ratio (PAPR) problem. Among PAPR reduction techniques, pre-coding methods have shown promising advantages such as signal independence and no requirement for signaling overhead. In t

Mehmet Parlak

In case of an accident between two autonomous vehicles equipped with emerging technologies, how do we apportion liability among the various players? A special liability regime has not even yet been established for damages that may arise due to the accidents of autonomous vehicles. Would the immutable, time-stamped sensor records of vehicles on distributed le

Eric Anderson, Feng-Ren Fan, Jiaqi Cai, William Holtzmann

Understanding quantum many-body systems is at the heart of condensed matter physics. The ability to control the underlying lattice geometry of a system, and thus its many-body interactions, would enable the realization of and transition between emergent quantum ground states. Here, we report in-situ gate switching between honeycomb and triangular lattice geo

Ahmad B. Barhoumi, Maxim L. Yattselev

We investigate asymptotic behavior of polynomials $ Q_n(z) $ satisfying non-Hermitian orthogonality relations $$ \int_\Delta s^kQ_n(s)\rho(s)ds =0, \quad k\in\{0,\ldots,n-1\}, $$ where $ \Delta $ is a Chebotar\"ev (minimal capacity) contour connecting three non-collinear points and $ \rho(s) $ is a Jacobi-type weight including a possible power-type singulari

Mouhamed Moustapha Fall, Ignace Aristide Minlend, Tobias Weth

We prove the existence of a family of compact subdomains $\Omega$ of the flat cylinder $\mathbb{R}^N\times \mathbb{R}/2\pi\mathbb{Z}$ for which the Neumann eigenvalue problem for the Laplacian on $\Omega$ admits eigenfunctions with constant Dirichlet values on $\partial \Omega$. These domains $\Omega$ have the property that their boundaries $\partial \Omega$

J. J. Charfman, M. M. M., J. Dietrich, N. T. Schragal

Here, we present a simple solution to problems that have plagued (extra)"galactic" astronomers and cosmologists over the last century. We show that "galaxy" formation, dark matter, and the tension in the expansion of the universe can all be explained by the natural behaviors of an overwhelmingly large population of exoplanets throughout the universe. Some of

Todd Gamblin, Daniel S. Katz

Continuous integration (CI) has become a ubiquitous practice in modern software development, with major code hosting services offering free automation on popular platforms. CI offers major benefits, as it enables detecting bugs in code prior to committing changes. While high-performance computing (HPC) research relies heavily on software, HPC machines are no

Martin Cerny, Michel Grabisch

The computation of a solution concept of a cooperative game usually employs values of all coalitions. However, in some applications, the values of some of the coalitions might be unknown due to high costs associated with their determination or simply because it is not possible to determine them exactly. We introduce a method to approximate standard solution

Philipp C. Böttcher, Leonardo Rydin Gorjão, Dirk Witthaut

The energy mix of future power systems will include high shares of wind power and solar PV. These generation facilities are generally connected via power-electronic inverters. While conventional generation responds dynamically to the state of the electric power system, inverters are power electronic hardware and need to be programmed to react to the state of

Lucio La Cava, Davide Costa, Andrea Tagarelli

The fervor for Non-Fungible Tokens (NFTs) attracted countless creators, leading to a Big Bang of digital assets driven by latent or explicit forms of inspiration, as in many creative processes. This work exploits Vision Transformers and graph-based modeling to delve into visual inspiration phenomena between NFTs over the years. Our goals include unveiling th

Jacopo Borga, William Da Silva, Ewain Gwynne

The Brownian separable permutons are a one-parameter family -- indexed by $p\in(0,1)$ -- of universal limits of random constrained permutations. We show that for each $p\in (0,1)$, there are explicit constants $1/2 < \alpha_*(p) \leq \beta^*(p) < 1$ such that the length of the longest increasing subsequence in a random permutation of size $n$ sampled from th

Hsuan-Hua Huang, Hsing-Wen Han, Kuang-Ta Lo, Tzu-Ting Yang

Using administrative data on Taiwanese lottery winners, this paper examines the effects of cash windfalls on entrepreneurship. We compare the start-up decisions of households winning more than 1.5 million NTD (50,000 USD) in the lottery in a particular year with those of households winning less than 15,000 NTD (500 USD). Our results suggest that a substantia

Therese Biedl, David Eppstein, Torsten Ueckerdt

Graph embedding, especially as a subgraph of a grid, is an old topic in VLSI design and graph drawing. In this paper, we investigate related questions concerning the complexity of embedding a graph $G$ in a host graph that is the strong product of a path $P$ with a graph $H$ that satisfies some properties, such as having small treewidth, pathwidth or tree de

Zihao Sheng, Zilin Huang, Sikai Chen

To drive safely in complex traffic environments, autonomous vehicles need to make an accurate prediction of the future trajectories of nearby heterogeneous traffic agents (i.e., vehicles, pedestrians, bicyclists, etc). Due to the interactive nature, human drivers are accustomed to infer what the future situations will become if they are going to execute diff

CMS Collaboration

The production of $\Upsilon$(2S) and $\Upsilon$(3S) mesons in lead-lead (PbPb) and proton-proton (pp) collisions is studied in their dimuon decay channel using the CMS detector at the LHC. The $\Upsilon$(3S) meson is observed for the first time in PbPb collisions, with a significance above five standard deviations. The ratios of yields measured in PbPb and p

I. Lobato, T. Friedrich, S. Van Aert

State-of-the-art electron microscopes such as scanning electron microscopes (SEM), scanning transmission electron microscopes (STEM) and transmission electron microscopes (TEM) have become increasingly sophisticated. However, the quality of experimental images is often hampered by stochastic and deterministic distortions arising from the instrument or its en

Majid Gazor, Nasrin Sadri

We provide a complete symmetry-breaking bifurcation control for equivariant smooth differential systems with Bogdanov-Takens singularities. Controller coefficient space is partitioned by critical controller sets into different connected regions. The connected regions provide a classification for all qualitatively different dynamics of the controlled system.

Shalosh B. Ekhad, Doron Zeilberger

Using Symbolic Computation with Maple, we can discover lots of (rigorously-proved!) facts about Standard Young Tableaux, in particular the distribution of the entries in any specific cell, and the sorting probabilities.

Fergus J. Moore, John Russo Tanniemola B. Liverpool, C. Patrick Royall

The transport of active particles may occur in complex environments, in which it emerges from the interplay between the mobility of the active components and the quenched disorder of the environment. Here we explore structural and dynamical properties of Active Brownian Particles (ABPs) in random environments composed of fixed obstacles in three dimensions.