April 2023 arXiv papers — page 106

Ghayoor Shah, Danyang Tian, Ehsan Moradi-Pari, Yaser P. Fallah

Research in Cooperative Intersection Management (CIM), utilizing Vehicle-to-Everything (V2X) communication among Connected and/or Autonomous Vehicles (CAVs), is crucial for enhancing intersection safety and driving experience. CAVs can transceive basic and/or advanced safety information, thereby improving situational awareness at intersections. The focus of

Yiannis Loizides

We study a natural family of non-local elliptic boundary problems on a compact oriented surface $\Sigma$ parametrized by the moduli space $\mathcal{M}_\Sigma$ of flat $G$-connections with framing along $\partial \Sigma$. This family generalizes one introduced by Atiyah and Bott for closed surfaces. In earlier work we constructed an analytic index morphism ou

Hongwei Ren, Yuhong Shi, Kewei Liang

Recently, there has been a growing interest in predicting human motion, which involves forecasting future body poses based on observed pose sequences. This task is complex due to modeling spatial and temporal relationships. The most commonly used models for this task are autoregressive models, such as recurrent neural networks (RNNs) or variants, and Transfo

Changfeng Gui, Tuoxin Li, Juncheng Wei, Zikai Ye

We prove that axially symmetric solutions to the $Q$-curvature type problem $$ \alpha P_6 u + 120(1-\frac{e^{6u}}{\int_{\mathbb{S}^6} e^{6u}})=0 \ \ \ \ \ \mbox{on} \ \mathbb{S}^6 $$ must be constants, provided that $ \frac{1}{2}\leq \alpha <1$. In view of the existence of non-constant solutions obtained by Gui-Hu-Xie \cite{GHW2022} for $\frac{1}{7}<\alpha<\

Michael A. Bender, Rathish Das, Martín Farach-Colton, Guido Tagliavini

In an $\alpha$-way set-associative cache, the cache is partitioned into disjoint sets of size $\alpha$, and each item can only be cached in one set, typically selected via a hash function. Set-associative caches are widely used and have many benefits, e.g., in terms of latency or concurrency, over fully associative caches, but they often incur more cache mis

Caitlyn Booms-Peot

Building off of work of Harada, Nowroozi, and Van Tuyl which provided particular length two virtual resolutions for finite sets of points in $\mathbb{P}^1\times\mathbb{P}^1$, we prove that the vast majority of virtual resolutions of a pair for minimal elements of the multigraded regularity in this setting are of Hilbert-Burch type. We give explicit descripti

Guanyi Qin, Runze Hu, Yutao Liu, Xiawu Zheng

Blind Image Quality Assessment (BIQA) is a fundamental task in computer vision, which however remains unresolved due to the complex distortion conditions and diversified image contents. To confront this challenge, we in this paper propose a novel BIQA pipeline based on the Transformer architecture, which achieves an efficient quality-aware feature representa

Thomas Trogdon, Yiting Zhang

We compute the Tracy-Widom distribution describing the asymptotic distribution of the largest eigenvalue of a large random matrix by solving a boundary-value problem posed by Bloemendal in his Ph.D. Thesis (2011). The distribution is computed in two ways. The first method is a second-order finite-difference method and the second is a highly accurate Fourier

Jingjie Ni, Yang Tang, Fangfei Li

This paper proposes model-free reinforcement learning methods for minimum-cost state-flipped control in Boolean control networks (BCNs). We tackle two questions: 1) finding the flipping kernel, namely the flip set with the smallest cardinality ensuring reachability, and 2) deriving optimal policies to minimize the number of flipping actions for reachability

Ali Ahmad Malik, Tariq Masood, Alexander Brem

Technological evolution in the field of robotics is emerging with major breakthroughs in recent years. This was especially fostered by revolutionary new software applications leading to humanoid robots. Humanoids are being envisioned for manufacturing applications to form human-robot teams. But their implication in manufacturing practices especially for indu

Zewen Jiang, Wei Wang, Gang Zhao, Meng Zhai

Ultra-hot Jupiters (UHJs) possess the most extreme environments among various types of exoplanets, making them ideal laboratories to study the chemical composition and kinetics properties of exoplanet atmosphere with high-resolution spectroscopy (HRS). It has the advantage of resolving the tiny Doppler shift and weak signal from exoplanet atmosphere and has

Tao Lei, Junwen Bai, Siddhartha Brahma, Joshua Ainslie

We propose Conditional Adapter (CoDA), a parameter-efficient transfer learning method that also improves inference efficiency. CoDA generalizes beyond standard adapter approaches to enable a new way of balancing speed and accuracy using conditional computation. Starting with an existing dense pretrained model, CoDA adds sparse activation together with a smal

Ranchao Wu, Lingling Yang

Bifurcation of the local Gierer-Meinhardt model is analyzed in this paper. It is found that the degenerate Bogdanov-Takens bifurcation of codimension 3 happens in the model, except that teh saddle-node bifurcation and the Hopf bifurcation. That was not reported in the existing results about this model. The existence of equilibria, their stability, the bifurc

F. Barzi, H. El Moumni, K. Masmar

Motivated by the nonextensive nature of entropy in gravitational context and the Gauge/Gravity duality, black hole thermodynamics has been attracting intense emphasis in the literature. Along the present work, we investigate some features of the phase structure and critical phenomena of the 4-dimensional charged black holes in asymptotically flat spacetime w

Alexander Schied, Zhenyuan Zhang

We introduce a new class of stochastic processes called fractional Wiener-Weierstrass bridges. They arise by applying the convolution from the construction of the classical, fractal Weierstrass functions to an underlying fractional Brownian bridge. By analyzing the $p$-th variation of the fractional Wiener-Weierstrass bridge along the sequence of $b$-adic pa

Yifei Dong, Shuhui Bu, Kun Li, Lin Chen

As robotics technology advances, dense point cloud maps are increasingly in demand. However, dense reconstruction using a single unmanned aerial vehicle (UAV) suffers from limitations in flight speed and battery power, resulting in slow reconstruction and low coverage. Cluster UAV systems offer greater flexibility and wider coverage for map building. Existin

Long Huang, Xiaofeng Wang, Zhicheng Zeng

In this work, we provide a complete characterization of the boundedness of two classes of multiparameter Forelli-Rudin type operators from one mixed-norm Lebesgue space $L^{\vec p}$ to another space $L^{\vec q}$, when $1\leq \vec{p}\leq \vec q<\infty$, equipped with possibly different weights. Using these characterizations, we establish the necessary and suf

Alvin Chen, N. Sukumar

In this paper, we propose a robust low-order stabilization-free virtual element method on quadrilateral meshes for linear elasticity that is based on the stress-hybrid principle. We refer to this approach as the Stress-Hybrid Virtual Element Method (SH-VEM). In this method, the Hellinger$-$Reissner variational principle is adopted, wherein both the equilibri

Bahman Kalantari

We introduce innovative algorithms for computing exact or approximate (minimum-norm) solutions to $Ax=b$ or the {\it normal equation} $A^TAx=A^Tb$, where $A$ is an $m \times n$ real matrix of arbitrary rank. We present more efficient algorithms when $A$ is symmetric PSD. First, we introduce the {\it Triangle Algorithm} (TA), a {\it convex-hull membership} al

Tongxue Zhou, Alexandra Noeuveglise, Romain Modzelewski, Fethi Ghazouani

Brain tumor is one of the leading causes of cancer death. The high-grade brain tumors are easier to recurrent even after standard treatment. Therefore, developing a method to predict brain tumor recurrence location plays an important role in the treatment planning and it can potentially prolong patient's survival time. There is still little work to deal with

Irina Subotić, and Dominic Groß

We analyze a dual-port grid-forming (GFM) control for power systems containing ac and dc transmission, converter-interfaced generation and energy storage, and legacy generation. To operate such a system and provide standard services, state-of-the-art control architectures i) require assigning grid-following (GFL) and GFM controls to different converters, and

Ji Zhou, Jinyang Yang, Haide Wang, Jianrui Zeng

We propose a timing recovery for point-to-multi-point coherent passive optical networks. The results show that the proposed algorithm has low complexity and better robustness against the residual chromatic dispersion.

Darius Foo, Wei-Ngan Chin

This presentation will cover a framework for application-level tracing of OCaml programs. We outline a solution to the main technical challenge, which is being able to log typed values with lower overhead and maintenance burden than existing approaches. We then demonstrate the tools we have built around this for visualizing and exploring executions.

Meng-Jun Hu, Yong-Sheng ZHang

Wavefunction is a fundamental concept of quantum theory. Recent studies have shown surprisingly that wavefunction can be directly reconstructed via the measurement of weak value. The weak value based direct wavefunction reconstruction not only gives the operational meaning of wavefunction, but also provides the possibility of realizing holographic imaging wi

Jiewen Zheng, Ze Chen

Sentence-level relation extraction aims to identify the relation between two entities for a given sentence. The existing works mostly focus on obtaining a better entity representation and adopting a multi-label classifier for relation extraction. A major limitation of these works is that they ignore background relational knowledge and the interrelation betwe

Jinghan Jia, Jiancheng Liu, Parikshit Ram, Yuguang Yao

In response to recent data regulation requirements, machine unlearning (MU) has emerged as a critical process to remove the influence of specific examples from a given model. Although exact unlearning can be achieved through complete model retraining using the remaining dataset, the associated computational costs have driven the development of efficient, app

Sherry Ruan, Allen Nie, William Steenbergen, Jiayu He

Resource limitations make it hard to provide all students with one of the most effective educational interventions: personalized instruction. Reinforcement learning could be a key tool to reduce the development cost and improve the effectiveness of intelligent tutoring software that aims to provide the right support, at the right time, to a student. Here we

François Le Gall

Several quantum algorithms for linear algebra problems, and in particular quantum machine learning problems, have been "dequantized" in the past few years. These dequantization results typically hold when classical algorithms can access the data via length-squared sampling. In this work we investigate how robust these dequantization results are. We introduce

Bui Thi Ha Giang, Dang Van Soa, Le Mai Dung

The influence of the scalar unparticle and anomalous couplings at muon colliders in final states with multiple photons in the Randall-Sundrum model is evaluated in detail. The results indicate that with fixed collision energies, the total cross-sections for the production of multiple photons depend strongly on the polarization of the muon beams, the paramete

Ryan E. G. Bushling

We prove that the integral of a certain Riesz-type kernel over $(n-1)$-rectifiable sets in $\mathbb{R}^n$ is constant, from which a formula for surface measure immediately follows. Geometric interpretations are given, and the solution to a geometric variational problem characterizing convex domains follows as a corollary, strengthening a recent inequality of

Zhangchi Chen, Dinh Tuan Huynh, Song-Yan Xie

We construct explicit universal entire curves in projective spaces whose Nevanlinna characteristic functions grow slower than any preassigned transcendental growth rate. Moreover, we can make such curves to be hypercyclic for translation operations along any given countable directions.

Subhasis Samanta, Hwiwoo Park, Chanhyeon Lee, Sungmin Jeon

Kagome lattice has been actively studied for the possible realization of frustration-induced two-dimensional flat bands and a number of correlation-induced phases. Currently, the search for kagome systems with a nearly dispersionless flat band close to the Fermi level is ongoing. Here, by combining theoretical and experimental tools, we present Sc$_3$Mn$_3$A

Etinosa Ekomwenrenren, John W. Simpson-Porco, Evangelos Farantatos, Mahendra Patel

To address the control challenges associated with the increasing share of inverter-connected renewable energy resources, this paper proposes a direct data-driven approach for fast frequency control in the bulk power system. The proposed control scheme partitions the power system into control areas, and leverages local dispatchable inverter-based resources to

Ali Shirazi, Fereshteh Sadeghi Naieni Fard

Finding the hedge ratios for a portfolio and risk compression is the same mathematical problem. Traditionally, regression is used for this purpose. However, regression has its own limitations. For example, in a regression model, we can't use highly correlated independent variables due to multicollinearity issue and instability in the results. A regression mo

Jiawei Chen, Lin Chen, Jiang Yang, Tianqi Shi

Vision transformers have achieved remarkable success in computer vision tasks by using multi-head self-attention modules to capture long-range dependencies within images. However, the high inference computation cost poses a new challenge. Several methods have been proposed to address this problem, mainly by slimming patches. In the inference stage, these met

Mathieu Oléron, Laurent Limat, Julien Dervaux, Matthieu Roché

We show that energy dissipation partition between a liquid and a solid controls the shape and stability of droplets sliding on viscoelastic gels. When both phases dissipate energy equally, droplet dynamics is similar to that on rigid solids. When only the solid dissipate, we observe an apparent contact angle hysteresis, of viscoelastic origin. We find excell

Igor Strakovsky, William J. Briscoe, Eugene Chudakov, Ilya Larin

New high-statistics total cross section data for $\gamma p\to J/\psi p$ from the GLUonic EXcitation (GlueX) experiment are fitted in a search for the exotic $P_c(4312)^+$ state observed by the Large Hadron Collider beauty (LHCb) collaboration. The integrated luminosity of this GlueX experiment was about $320~\mathrm{pb^{-1}}$. The fits show that destructive

Michael R. Turski, Joseph Norby, Aaron M. Johnson

Trajectory optimization problems for legged robots are commonly formulated with fixed contact schedules. These multi-phase Hybrid Trajectory Optimization (HTO) methods result in locally optimal trajectories, but the result depends heavily upon the predefined contact mode sequence. Contact-Implicit Optimization (CIO) offers a potential solution to this issue

Ysun Choi, Heejun Yang, Jaena Park, Je-Geun Park

Two-dimensional (2D) Heisenberg honeycomb ferromagnets are expected to have interesting topological magnon effects as their magnon dispersion can have Dirac points. The Dirac points are gapped with finite second nearest neighbor Dzyaloshinskii-Moriya interaction, providing nontrivial Berry curvature with finite magnon Hall effect. Yet, it is unknown how the

Gabriel Nowaskie

The Half-Transform Ansatz (HTA) is a proposed method to solve hyper-geometric equations in Quantum Phase Space by transforming a differential operator to an algebraic variable and including a specific exponential factor in the wave function, but the mechanism which provides this solution scheme is not known. Analysis of the HTA's application to the Hydrogen

Mingzhe Hu, Shaoyan Pan, Yuheng Li, Xiaofeng Yang

In this paper, we aimed to provide a review and tutorial for researchers in the field of medical imaging using language models to improve their tasks at hand. We began by providing an overview of the history and concepts of language models, with a special focus on large language models. We then reviewed the current literature on how language models are being

Uddhav Bhattarai, Qin Zhang, Manoj Karkee

The US apple industry relies heavily on semi-skilled manual labor force for essential field operations such as training, pruning, blossom and green fruit thinning, and harvesting. Blossom thinning is one of the crucial crop load management practices to achieve desired crop load, fruit quality, and return bloom. While several techniques such as chemical, and

Xiaofeng Zhu, Thomas Lin, Vishal Anand, Matthew Calderwood

The core challenge in numerous real-world applications is to match an inquiry to the best document from a mutable and finite set of candidates. Existing industry solutions, especially latency-constrained services, often rely on similarity algorithms that sacrifice quality for speed. In this paper we introduce a generic semantic learning-to-rank framework, Se

Xianrui Luo, Juewen Peng, Weiyue Zhao, Ke Xian

All-in-Focus (AIF) photography is expected to be a commercial selling point for modern smartphones. Standard AIF synthesis requires manual, time-consuming operations such as focal stack compositing, which is unfriendly to ordinary people. To achieve point-and-shoot AIF photography with a smartphone, we expect that an AIF photo can be generated from one shot

Sinong Geng, Houssam Nassif, Carlos A. Manzanares

We study dynamic discrete choice models, where a commonly studied problem involves estimating parameters of agent reward functions (also known as "structural" parameters), using agent behavioral data. Maximum likelihood estimation for such models requires dynamic programming, which is limited by the curse of dimensionality. In this work, we present a novel a

Kat R. Agres, Adyasha Dash, Phoebe Chua

This work introduces a new music generation system, called AffectMachine-Classical, that is capable of generating affective Classic music in real-time. AffectMachine was designed to be incorporated into biofeedback systems (such as brain-computer-interfaces) to help users become aware of, and ultimately mediate, their own dynamic affective states. That is, t

Gillian K. Hadfield, Jack Clark

Appropriately regulating artificial intelligence is an increasingly urgent and widespread policy challenge. We identify two primary, competing problem. First is a technical deficit: Legislatures and regulatory face significant challenges in rapidly translating conventional command-and-control legal requirements into technical requirements. Second is a democr

Jian-Ping Dai, Xu Cao, Horst Lenske

Inspired by the recent precise data, we perform model-independently an isospin decomposition of the timelike octet baryons electromagnetic form factors. As noted in our previous work, the relative magnitude of isoscalar and isovector component is determined with the input of data on various isospin channels. Herein we further assert that {their relative phas

Zhen Zeng, Rachneet Kaur, Suchetha Siddagangappa, Saba Rahimi

Time series forecasting is important across various domains for decision-making. In particular, financial time series such as stock prices can be hard to predict as it is difficult to model short-term and long-term temporal dependencies between data points. Convolutional Neural Networks (CNN) are good at capturing local patterns for modeling short-term depen

Ruturaj Sambhus, Aydin Gokce, Stephen Welch, Connor W. Herron

Many state-of-the art robotic applications utilize series elastic actuators (SEAs) with closed-loop force control to achieve complex tasks such as walking, lifting, and manipulation. Model-free PID control methods are more prone to instability due to nonlinearities in the SEA where cascaded model-based robust controllers can remove these effects to achieve s

M. L. Kerr, K. V. Kheruntsyan

This article reviews the recent developments in the theory of generalised hydrodynamics (GHD) with emphasis on the repulsive one-dimensional Bose gas. We discuss the implications of GHD on the mechanisms of thermalisation in integrable quantum many-body systems as well as its ability to describe far-from-equilibrium behaviour of integrable and near integrabl

Ahmed Abdelreheem, Ivan Skorokhodov, Maks Ovsjanikov, Peter Wonka

We explore the task of zero-shot semantic segmentation of 3D shapes by using large-scale off-the-shelf 2D image recognition models. Surprisingly, we find that modern zero-shot 2D object detectors are better suited for this task than contemporary text/image similarity predictors or even zero-shot 2D segmentation networks. Our key finding is that it is possibl

Hua Sun, Hui-Xiang Chen

In this article, we investigate the representations of the Drinfeld doubles $D(R_{mn}(q))$ of the Radford Hopf algebras $R_{mn}(q)$ over an algebraically closed field $\Bbbk$, where $m>1$ and $n>1$ are integers and $q\in\Bbbk$ is a root of unity of order $n$. Under the assumption ${\rm char}(\Bbbk)\nmid mn$, all the finite dimensional indecomposable modules

Jialu Li, Mohit Bansal

Vision-and-Language Navigation (VLN) is the task that requires an agent to navigate through the environment based on natural language instructions. At each step, the agent takes the next action by selecting from a set of navigable locations. In this paper, we aim to take one step further and explore whether the agent can benefit from generating the potential

Mehedi Hasan, Moloud Abdar, Abbas Khosravi, Uwe Aickelin

Although neural networks (especially deep neural networks) have achieved \textit{better-than-human} performance in many fields, their real-world deployment is still questionable due to the lack of awareness about the limitation in their knowledge. To incorporate such awareness in the machine learning model, prediction with reject option (also known as select

Angus Alexander, Adam Rennie

We build on work of Kellendonk, Richard, Tiedra de Aldecoa and others to show that the wave operators for Schr\"{o}dinger scattering theory on $\mathbb{R}^n$ generically have a particular form. As a consequence, Levinson's theorem can be interpreted as the pairing of the $K$-theory class of the unitary scattering operator and the $K$-homology class of the ge

Zeyi Wang, Lars van der Laan, Maya Petersen, Thomas Gerds

Causal mediation analysis with random interventions has become an area of significant interest for understanding time-varying effects with longitudinal and survival outcomes. To tackle causal and statistical challenges due to the complex longitudinal data structure with time-varying confounders, competing risks, and informative censoring, there exists a gene

Akihito Maruya, Qasim Zaidi

Why do moving objects appear rigid when projected retinal images are deformed nonrigidly? We used rotating rigid objects that can appear rigid or non-rigid to test whether shape features contribute to rigidity perception. When two circular rings were rigidly linked at an angle and jointly rotated at moderate speeds, observers reported that the rings wobbled

Amirhossein Rasoulian, Soorena Salari, Yiming Xiao

Intracranial hemorrhage (ICH) is a life-threatening medical emergency that requires timely and accurate diagnosis for effective treatment and improved patient survival rates. While deep learning techniques have emerged as the leading approach for medical image analysis and processing, the most commonly employed supervised learning often requires large, high-

Takuya Kiyokawa, Naoki Shirakura, Hiroki Katayama, Keita Tomochika

Training deep-learning-based vision systems require the manual annotation of a significant number of images. Such manual annotation is highly time-consuming and labor-intensive. Although previous studies have attempted to eliminate the effort required for annotation, the effort required for image collection was retained. To address this, we propose a human-i

Gabriel Currier

In this note, we describe an infinite family of sharp Szemer\'{e}di-Trotter constructions. These constructions are cartesian products of arbitrarily high dimensional generalized arithmetic progressions (GAPs), where the bases for these GAPs come from arbitrary number fields over $\mathbb{Q}$. This can be seen as an extension of a recent result of Guth and Si

Ryota Fujii, Sota Hanazawa, Hiraki Kanehisa, Makoto Sakaguchi

The BRST invariance of the open pure spinor superstring is examined in the presence of background superfields on a Dp-brane. We note that the background superfields introduced in this paper depend on boundary fermions. The BRST invariance leads to supersymmetric Dirac-Born-Infeld (DBI) equations for background superfields depending on boundary fermions as we

Kaki Ryan, Cynthia Sturton

Symbolic execution is a powerful verification tool for hardware designs, but suffers from the path explosion problem. We introduce a new approach, piecewise composition, which leverages the modular structure of hardware to transfer the work of path exploration to SMT solvers. We present a symbolic execution engine implementing the technique. The engine opera

Giorgio Angelotti, Nicolas Drougard, Caroline Ponzoni Carvalho Chanel

In Offline Model Learning for Planning and in Offline Reinforcement Learning, the limited data set hinders the estimate of the Value function of the relative Markov Decision Process (MDP). Consequently, the performance of the obtained policy in the real world is bounded and possibly risky, especially when the deployment of a wrong policy can lead to catastro

Delio Jaramillo-Velez, Lisa Seccia

The v-number of a graded ideal is an algebraic invariant introduced by Cooper et al., and originally motivated by problems in algebraic coding theory. In this paper we study the case of binomial edge ideals and we establish a significant connection between their v-numbers and the concept of connected domination in graphs. More specifically, we prove that the

Youngjoong Kwon, Dahun Kim, Duygu Ceylan, Henry Fuchs

We present a method that enables synthesizing novel views and novel poses of arbitrary human performers from sparse multi-view images. A key ingredient of our method is a hybrid appearance blending module that combines the advantages of the implicit body NeRF representation and image-based rendering. Existing generalizable human NeRF methods that are conditi

Zhonglin Cao, Yuyang Wang, Cooper Lorsung, Amir Barati Farimani

Modeling the ion concentration profile in nanochannel plays an important role in understanding the electrical double layer and electroosmotic flow. Due to the non-negligible surface interaction and the effect of discrete solvent molecules, molecular dynamics (MD) simulation is often used as an essential tool to study the behavior of ions under nanoconfinemen

Chaitanya Joshi, Zahra Zarei, Michael M. Norton, Seth Fraden

Confinement can be used to systematically tame turbulent dynamics occurring in active fluids. Although periodic channels are the simplest geometries to study confinement numerically, the corresponding experimental realizations require closed racetracks. Here, we computationally study 2D active nematics confined to such a geometry -- an annulus. By systematic

Benedykt R. Jany

The color is the primal property of the objects around us and is direct manifestation of light-matter interactions. The color information is used in many different fields of science, technology and industry to investigate material properties or for identification of concentrations of substances. Usually the color information is used as a global parameter in

Alexandre B. Tacla, Nina Machado O'Neill, Gabriel G. Carlo, Fernando de Melo

Here we investigate the use of the majorization-based indicator introduced in [R. O. Vallejos, F. de Melo, and G. G. Carlo, Phys. Rev. A 104, 012602 (2021)] as a way to benchmark the complexity within reach of quantum processors. By considering specific architectures and native gate sets of currently available technologies, we numerically simulate and charac

Yanlin Qi, Gengchen Mai, Rui Zhu, Michael Zhang

Over the past decade, the electric vehicle industry has experienced unprecedented growth and diversification, resulting in a complex ecosystem. To effectively manage this multifaceted field, we present an EV-centric knowledge graph (EVKG) as a comprehensive, cross-domain, extensible, and open geospatial knowledge management system. The EVKG encapsulates esse

Aditya Konale, Zahra Ahmed, Piyush Wanchoo, Vikas Srivastava

Polyborosiloxane (PBS) is an important rate-stiffening soft polymer with dynamic, reversible crosslinks used in applications ranging from self-healing sensing and actuation to body and structural protection. Its highly rate-dependent response, especially for impact-mitigating structures, is important. However, the large strain response of PBS has not been ch

Racin Nygaard, Hein Meling

Data synchronization in decentralized storage systems is essential to guarantee sufficient redundancy to prevent data loss. We present SNIPS, the first succinct proof of storage algorithm for synchronizing storage peers. A peer constructs a proof for its stored chunks and sends it to verifier peers. A verifier queries the proof to identify and subsequently r

Jarred C Novak

Historically, materials such as lead, tungsten, and iron have been used in spacecraft to shield scientific detectors from Cosmic Rays. These materials work well when reentry to Earth is not an issue. The typical strategy is to have a controlled descent of the spacecraft or to have extremely limited shielding, if any, due to the NASA requirement that all impa

L. Palma Torres, M. A. Solís-Prosser, O. Jiménez, E. S. Gómez

Considering pure quantum states, entanglement concentration is the procedure where from $N$ copies of a partially entangled state, a single state with higher entanglement can be obtained. Getting a maximally entangled state is possible for $N=1$. However, the associated success probability can be extremely low while increasing the system's dimensionality. In

Lorenzo Vangelista, Bruno Jechoux, Jean-Xavier Canonici, Michele Zorzi

This paper considers massive Internet of Things systems, especially for LoW Power Wide Area Networks, that aim at connecting billions of low-cost devices with multi-year battery life requirements. Current systems for massive Internet of Things exhibit severe problems when trying to pursue the target of serving a very large number of users. In this paper, a n

Uwe Schäfer

We extend the Weierstrass-Kerner method by applying the Chebychev method to the function F that Kerner has used to show that the formula of Weierstrass actually is the Newton method applied to that F. The resulting method is already known but we want to present the process in one go and in a detailed way.

Roland Meyer, Thomas Wies, Sebastian Wolff

We present a new flow framework for separation logic reasoning about programs that manipulate general graphs. The framework overcomes problems in earlier developments: it is based on standard fixed point theory, guarantees least flows, rules out vanishing flows, and has an easy to understand notion of footprint as needed for soundness of the frame rule. In a

Shady E. Ahmed, Omer San

Model reduction by projection-based approaches is often associated with losing some of the important features that contribute towards the dynamics of the retained scales. As a result, a mismatch occurs between the predicted trajectories of the original system and the truncated one. We put forth a framework to apply a continuous time control signal in the lat

Jie Zhang, Minghui Nie, Changqing Zou, Jian Liu

Although supervised deep normal estimators have recently shown impressive results on synthetic benchmarks, their performance deteriorates significantly in real-world scenarios due to the domain gap between synthetic and real data. Building high-quality real training data to boost those supervised methods is not trivial because point-wise annotation of normal

Joshua Pickard, Amit Surana, Anthony Bloch, Indika Rajapakse

In this paper we develop a framework to study observability for uniform hypergraphs. Hypergraphs, being extensions of graphs, allow edges to connect multiple nodes and unambiguously represent multi-way relationships which are ubiquitous in many real-world networks. We extend the canonical homogeneous polynomial or multilinear dynamical system on uniform hype

Nicolai Jork

This paper is concerned with error estimates for the numerical approximation for affine optimal control problems subject to semilinear elliptic PDEs. To investigate the error estimates, we focus on local minimizers that satisfy certain local growth conditions. The local growth conditions we consider in this paper appeared recently in the context of solution

Bilal Ghanem, Alona Fyshe

Multiple choice questions (MCQs) are an efficient and common way to assess reading comprehension (RC). Every MCQ needs a set of distractor answers that are incorrect, but plausible enough to test student knowledge. Distractor generation (DG) models have been proposed, and their performance is typically evaluated using machine translation (MT) metrics. Howeve

A. Camacho-Guardian

Universality is a fundamental concept in physics that allows for the description of properties of systems that are independent of microscopic details. In this work, we show that polaritons in a Bose-Einstein condensate (BEC) are a suitable platform to probe in a non-demolition way the universal high-energy spectrum of an impurity strongly coupled to a BEC. B

Jing Qin, Biyun Xie

Motion detection has been widely used in many applications, such as surveillance and robotics. Due to the presence of the static background, a motion video can be decomposed into a low-rank background and a sparse foreground. Many regularization techniques that preserve low-rankness of matrices can therefore be imposed on the background. In the meanwhile, ge

Kazuhiro Sakai

We study the E-string theory on $\mathbb{R}^4\times T^2$ with Wilson lines. We consider two examples where interesting automorphisms arise. In the first example, the spectrum is invariant under the $F_4$ Weyl group acting on the Wilson line parameters. We obtain the Seiberg-Witten curve expressed in terms of Weyl invariant $F_4$ Jacobi forms. We also clarify

Pietro Antonio Grassi

We develop the theory of Free Integro-Differential Algebras (FIDA) extending the powerful technique of Free Differential Algebras constructed by D. Sullivan. We extend the analysis beyond the superforms to integral- and pseudo-forms used in supergeometry. It is shown that there are novel structures that might open the road to a deeper understanding of the ge

Ichitaro Yamazaki, Alexander Heinlein, Sivasankaran Rajamanickam

The generalized Dryja--Smith--Widlund (GDSW) preconditioner is a two-level overlapping Schwarz domain decomposition (DD) preconditioner that couples a classical one-level overlapping Schwarz preconditioner with an energy-minimizing coarse space. When used to accelerate the convergence rate of Krylov subspace iterative methods, the GDSW preconditioner provide

Gyeongsik Moon, Hongsuk Choi, Sanghyuk Chun, Jiyoung Lee

Recovering 3D human mesh in the wild is greatly challenging as in-the-wild (ITW) datasets provide only 2D pose ground truths (GTs). Recently, 3D pseudo-GTs have been widely used to train 3D human mesh estimation networks as the 3D pseudo-GTs enable 3D mesh supervision when training the networks on ITW datasets. However, despite the great potential of the 3D

Eslam Mohamed Bakr, Pengzhan Sun, Li Erran Li, Mohamed Elhoseiny

Most pre-trained learning systems are known to suffer from bias, which typically emerges from the data, the model, or both. Measuring and quantifying bias and its sources is a challenging task and has been extensively studied in image captioning. Despite the significant effort in this direction, we observed that existing metrics lack consistency in the inclu

Puja Agarwal, Divya Prem, Christopher Bogart, Abrar Fallatah

Emerging research shows that individual differences in how people use technology sometimes cluster by socioeconomic status (SES) and that when technology is not socioeconomically inclusive, low-SES individuals may abandon it. To understand how to improve technology's SES-inclusivity, we present a multi-phase case study on SocioEconomicMag (SESMag), an emergi

Félix Baril Boudreau, Cristhian Garay

In this article, we introduce the idempotentization process, which bears some philosophical and mathematical similarities with modern analytification and tropicalization. Idempotentization associates to any affine scheme an idempotent version of itself with respect to a fixed covering by distinguished affine open subschemes. Once this cover is fixed, we can

Julian Ransford

In 2018, Krishnan and Quastel showed that the fluctuations of Sepp\"al\"ainen's log-gamma polymer converge in law to the Tracy--Widom GUE distribution in the intermediate disorder regime, which corresponds to taking the inverse temperature $\beta$ to depend on the length of the polymer $2n$, with $\beta=n^{-\alpha}$ for some $\alpha<1/4$. They also conjectur

Andrew Wentzel, Carla Floricel, Guadalupe Canahuate, Mohamed A. Naser

Developing applicable clinical machine learning models is a difficult task when the data includes spatial information, for example, radiation dose distributions across adjacent organs at risk. We describe the co-design of a modeling system, DASS, to support the hybrid human-machine development and validation of predictive models for estimating long-term toxi

Jonathan P. Gardner, John C. Mather, Randy Abbott, James S. Abell

Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least $4m$. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the $6.5m$ James Webb

Chao Cheng, Donna Spiegelman, Fan Li

Mediation analysis is widely used in health science research to evaluate the extent to which an intermediate variable explains an observed exposure-outcome relationship. However, the validity of analysis can be compromised when the exposure is measured with error. Motivated by the Health Professionals Follow-up Study (HPFS), we investigate the impact of expo

Anastasia Potapova, Ian Pilé, Tian-Cheng Yi, Rubem Mondaini

We study the ground state properties of a polarized two-component Fermi gas on multileg attractive-$U$ Hubbard ladders. Using exact diagonalization and density matrix renormalization group method simulations, we construct grand canonical phase diagrams for ladder widths of up to $W=5$ and varying perpendicular geometries, characterizing the quasi-one-dimensi

Jun Korenaga

The early evolution of the Earth-Moon system prescribes the tidal environment of the Hadean Earth and holds the key to the formation mechanism of the Moon and its thermal evolution. Estimating its early state by backtracking from the present, however, suffers from substantial uncertainties associated with ocean tides. Tidal evolution during the solidificatio

K. Park, J. Kim, S. Choi, S. Fan

In order to explore the consequences of spin-orbit coupling on spin-phonon interactions in a set of chemically-similar mixed metal oxides, we measured the infrared vibrational properties of Co$_4B_2$O$_9$ ($B$ = Nb, Ta) as a function of temperature and compared our findings with lattice dynamics calculations and several different models of spin-phonon coupli

Jesús M. Jáquez-Domínguez, Roberto Galván-Madrid, Jacopo Fritz, Manuel Zamora-Avilés

The direct comparison between hydrodynamical simulations and observations is needed to improve the physics included in the former and test biases in the latter. Post-processing radiative transfer and synthetic observations are now the standard way to do this. We report on the first application of the \texttt{SKIRT} radiative transfer code to simulations of a