March 2023 arXiv papers — page 21

Shun Muroga, Yasuaki Miki, Kenji Hata

We present a multimodal deep learning (MDL) framework for predicting physical properties of a 10-dimensional acrylic polymer composite material by merging physical attributes and chemical data. Our MDL model comprises four modules, including three generative deep learning models for material structure characterization and a fourth model for property predicti

Sotetsu Koyamada, Shinri Okano, Soichiro Nishimori, Yu Murata

We propose Pgx, a suite of board game reinforcement learning (RL) environments written in JAX and optimized for GPU/TPU accelerators. By leveraging JAX's auto-vectorization and parallelization over accelerators, Pgx can efficiently scale to thousands of simultaneous simulations over accelerators. In our experiments on a DGX-A100 workstation, we discovered th

Man Zhou, Naishan Zheng, Jie Huang, Chunle Guo

Image and video restoration has achieved a remarkable leap with the advent of deep learning. The success of deep learning paradigm lies in three key components: data, model, and loss. Currently, many efforts have been devoted to the first two while seldom study focuses on loss function. With the question ``are the de facto optimization functions e.g., $L_1$,

Haodi Liang, Jiahua Chen

This paper develops several interesting, significant, and interconnected approaches to nonparametric or semi-parametric statistical inferences. The overwhelmingly favoured maximum likelihood estimator (MLE) under parametric model is renowned for its strong consistency and optimality generally credited to Cramer. These properties, however, falter when the mod

Esteban González, Genly Leon, Guillermo Fernandez-Anaya

This paper investigates exact solutions of cosmological interest in fractional cosmology. Given $\mu$, the order of Caputo's fractional derivative, and $w$, the matter equation of state, we present specific exact power-law solutions. We discuss the exact general solution of the Riccati Equation, where the solution for the scale factor is a combination of pow

Adam K. Taras, Niko Suenderhauf, Peter Corke, Donald G. Dansereau

Vision is a popular and effective sensor for robotics from which we can derive rich information about the environment: the geometry and semantics of the scene, as well as the age, gender, identity, activity and even emotional state of humans within that scene. This raises important questions about the reach, lifespan, and potential misuse of this information

Zhengqing Miao, Xin Zhang, Meirong Zhao, Dong Ming

EEG-based recognition of activities and states involves the use of prior neuroscience knowledge to generate quantitative EEG features, which may limit BCI performance. Although neural network-based methods can effectively extract features, they often encounter issues such as poor generalization across datasets, high predicting volatility, and low model inter

Abhay Zala, Jaemin Cho, Satwik Kottur, Xilun Chen

There is growing interest in searching for information from large video corpora. Prior works have studied relevant tasks, such as text-based video retrieval, moment retrieval, video summarization, and video captioning in isolation, without an end-to-end setup that can jointly search from video corpora and generate summaries. Such an end-to-end setup would al

Andreas Bauer

We propose a unifying paradigm for analyzing and constructing topological quantum error correcting codes as dynamical circuits of geometrically local channels and measurements. To this end, we relate such circuits to discrete fixed-point path integrals in Euclidean spacetime, which describe the underlying topological order: If we fix a history of measurement

Lu Lu, Yi Yu, Zongsheng Zheng, Guangya Zhu

The Andrew's sine function is a robust estimator, which has been used in outlier rejection and robust statistics. However, the performance of such estimator does not receive attention in the field of adaptive filtering techniques. Two Andrew's sine estimator (ASE)-based robust adaptive filtering algorithms are proposed in this brief. Specifically, to achieve

Zidu Li, Mason A. Porter, Bhaskar Choubey

The computational investigation of Fermi, Pasta, Ulam, and Tsingou of arrays of nonlinearly coupled oscillators has led to a wealth of studies in nonlinear dynamics. Most studies of oscillator arrays have considered homogeneous oscillators, even though there are inherent heterogeneities between {individual} oscillators in real-world arrays. Well-known FPUT p

Mohamed Shouman, Ahmed Atallah, Mohammad S. Ramadan

The paper provides a new approach to utilizing space environmental forces in time- and energy-optimal, propellant-less spacecraft rendezvous missions. Considering the nonlinear form of the relative dynamic equations, rendezvous missions are posed as optimal control problems subject to input saturation. We conduct a direct optimal control approach to obtain o

Davesh Maulik, Salim Tayou

Given a Brauer class on a K3 surface defined over a number field, we prove that there exists infinitely many reductions where the Brauer class vanishes, under certain technical hypotheses, answering a question of Frei--Hassett--V\'arilly-Alvarado.

Yong Du

The type-II seesaw model can explain neutrino masses and address the baryon asymmetry problem of the Universe simultaneously. In this letter, we explore its phase transition and the resulting gravitational wave signals. We find a strong first-order electroweak phase transition generically prefers a relatively light triplet in the $300\sim500$GeV range, which

Rui Peng, Guanghui Zhang

Consider the eigenvalue problem of a linear second order elliptic operator: \begin{equation} \nonumber -D\Delta \varphi -2\alpha\nabla m(x)\cdot \nabla\varphi+V(x)\varphi=\lambda\varphi\ \ \hbox{ in }\Omega, \end{equation} complemented by the Dirichlet boundary condition or the following general Robin boundary condition: $$ \frac{\partial\varphi}{\partial n}

Hailong Dao, Kyle Maddox, Vaibhav Pandey

We give an explicit formula to count the number of geometric branches of a curve in positive characteristic using the theory of tight closure. This formula readily shows that the property of having a single geometric branch characterizes $F$-nilpotent curves. Further, we show that a reduced, local $F$-nilpotent ring has a single geometric branch; in particul

Risheng Liu, Yaohua Liu, Shangzhi Zeng, Jin Zhang

In recent years, there has been a surge of machine learning applications developed with hierarchical structure, which can be approached from Bi-Level Optimization (BLO) perspective. However, most existing gradient-based methods overlook the interdependence between hyper-gradient calculation and Lower-Level (LL) iterative trajectory, focusing solely on the fo

Jorge Ugan, Mohamed Abdel-Aty, Zubayer Islam

Speeding has been and continues to be a major contributing factor to traffic fatalities. Various transportation agencies have proposed speed management strategies to reduce the amount of speeding on arterials. While there have been various studies done on the analysis of speeding proportions above the speed limit, few studies have considered the effect on th

T. H. Chang, T. N. Wang, H. H. Jen, Y. -C. Chen

High-fidelity control-$Z$ ($C_Z$) gates are essential and mandatory to build a large-scale quantum computer. In neutral atoms, the strong dipole-dipole interactions between their Rydberg states make them one of the pioneering platforms to implement $C_Z$ gates. Here we numerically investigate the time-optimal pulses to generate a high-fidelity Rydberg $C_{Z}

Felipe Atenas

We analyze the Douglas-Rachford splitting method for weakly convex optimization problems, by the token of the Douglas-Rachford envelope, a merit function akin to the Moreau envelope. First, we use epi-convergence techniques to show that this artifact approximates the original objective function via epigraphs. Secondly, we present how global convergence and l

Jeffrey Fairbanks, Akshharaa Tharigonda, Nasir U. Eisty

Numerous articles emphasize the benefits of implementing Continuous Integration and Delivery (CI/CD) pipelines in software development. These pipelines are expected to improve the reputation of a project and decrease the number of commits and issues in the repository. Although CI/CD adoption may be slow initially, it is believed to accelerate service deliver

Yuuki Hayashi, Go Mishima, Yukinari Sumino, Hiromasa Takaura

It is becoming more important to subtract renormalons efficiently from perturbative calculations, in order to achieve high precision QCD calculations. We propose a new framework ``Dual Space Approach" for renormalon separation, which enables subtraction of multiple renormalons simultaneously. Using a dual transform which suppresses infrared renormalons, we d

Dongfang Yang, Yu Zeng, Silvio Dolfi

The function $\mathrm{P}_{\mathbf{v}}(G)$, measuring the proportion of the elements of a finite group $G$ that are zeros of irreducible characters of $G$, takes (as proved in [12]) only values $\frac{m-1}{m}$, for $1 \leq m \leq 6$, in the interval $[0, \mathrm{P}_{\mathbf{v}}(A_7))$.In this paper, we give a complete classification of the finite groups $G$ s

Tang Li, Fengchun Qiao, Mengmeng Ma, Xi Peng

As black-box models increasingly power high-stakes applications, a variety of data-driven explanation methods have been introduced. Meanwhile, machine learning models are constantly challenged by distributional shifts. A question naturally arises: Are data-driven explanations robust against out-of-distribution data? Our empirical results show that even thoug

Kazuyuki Arikawa, Shoichi Koyama, Hiroshi Saruwatari

A spatial active noise control (ANC) method based on kernel interpolation of a sound field with exterior radiation suppression is proposed. The aim of spatial ANC is to reduce incoming noise over a target region by using multiple secondary sources and microphones. The method based on kernel interpolation of a sound field allows noise attenuation in a regiona

Xi Chen, Binghui Peng

We study the complexity of finding an approximate (pure) Bayesian Nash equilibrium in a first-price auction with common priors when the tie-breaking rule is part of the input. We show that the problem is PPAD-complete even when the tie-breaking rule is trilateral (i.e., it specifies item allocations when no more than three bidders are in tie, and adopts the

Vesko Valov

We prove that any region $\Gamma$ in a homogeneous $n$-dimensional and locally compact separable metric space $X$, where $n\geq 2$, cannot be irreducibly separated by a closed $(n-1)$-dimensional subset $C$ with the following property: $C$ is acyclic in dimension $n-1$ and there is a point $b\in C\cap\Gamma$ having a special local base $\mathcal B_C^b$ in $C

Stephanie Tsuei, Stefano Soatto

We compute the uncertainty of XIVO, a monocular visual-inertial odometry system based on the Extended Kalman Filter, in the presence of Gaussian noise, drift, and attribution errors in the feature tracks in addition to Gaussian noise and drift in the IMU. Uncertainty is computed using Monte-Carlo simulations of a sufficiently exciting trajectory in the midst

Duong Thuy Anh Nguyen, Duong Tung Nguyen, Angelia Nedich

This paper presents a new distributed algorithm that leverages heavy-ball momentum and a consensus-based gradient method to find a Nash equilibrium (NE) in a class of non-cooperative convex games with unconstrained action sets. In this approach, each agent in the game has access to its own smooth local cost function and can exchange information with its neig

Weiliang Yao, Qing Huang, Tao Xie, Andrey Podlesnyak

Continuous spin excitations are widely recognized as one of the hallmarks of novel spin states in quantum magnets, such as quantum spin liquids (QSLs). Here, we report the observation of such kind of excitations in K2Ni2(SO4)3, which consists of two sets of intersected spin-1 Ni2+ trillium lattices. Our inelastic neutron scattering measurement on single crys

H. B. Xiao, J. T. Zhu, J. H. Fan, Z. Y. Pei

The study of blazar jet has been performed for several decades via the VLBI technique, while its generation and propagation stay unclear. In the present work, we compiled a sample of 407 VLBI detected \textit{Fermi} blazars (VFBs) and studied the correlations between apparent velocity (${\rm log}\,\beta_{\rm app}$) and jet/accretion disk properties. We found

Chaitanya Mitash, Fan Wang, Shiyang Lu, Vikedo Terhuja

This paper introduces Amazon Robotic Manipulation Benchmark (ARMBench), a large-scale, object-centric benchmark dataset for robotic manipulation in the context of a warehouse. Automation of operations in modern warehouses requires a robotic manipulator to deal with a wide variety of objects, unstructured storage, and dynamically changing inventory. Such sett

Mitsuaki Kimura, Erika Kuno

The fine curve graph of a surface was introduced by Bowden, Hensel, and Webb as a graph consisting of essential simple closed curves on the surface. Long, Margalit, Pham, Verberne, and Yao proved that the automorphism group of the fine curve graph of a closed orientable surface is isomorphic to the homeomorphism group of the surface. In this paper, based on

Alexander Strohmaier, Edward Witten

The timelike tube theorem asserts that in quantum field theory without gravity, the algebra of observables in an open set U is the same as the corresponding algebra of observables in its ``timelike envelope'' E(U), which is an open set that is in general larger. The theorem was originally proved in the 1960's by Borchers and Araki for quantum fields in Minko

Heyu Zhu, Jiantao Wang, Yun Chen, Mingfeng Liu

Excellent high-temperature mechanical properties of Ni-based single crystal superalloys (NSCSs) are attributed to the yield strength anomaly of Ni$_{3}$Al that is intimately related to generalized stacking fault energies (GSFEs). Therefore, clarifying the effects of alloying elements on the GSFEs is of great significance for alloys design. Here, by means of

Haomin Zhuang, Yihua Zhang, Sijia Liu

Despite the record-breaking performance in Text-to-Image (T2I) generation by Stable Diffusion, less research attention is paid to its adversarial robustness. In this work, we study the problem of adversarial attack generation for Stable Diffusion and ask if an adversarial text prompt can be obtained even in the absence of end-to-end model queries. We call th

Nikolay V. Emelyanov, Mikhail Kovalev, Maxim I. Varfolomeev

Launch of the Gaia space observatory started a new era in astrometry when the accuracy of star coordinates increased by thousands of times. Significant improvement of accuracy was also expected for the coordinates of the Solar system bodies. Gaia DR3 provided us with the data which could be used to test our expectations. In this work, we refine the orbits of

Tianyuan Yao, Nancy Newlin, Praitayini Kanakaraj, Vishwesh nath

Diffusion-weighted (DW) MRI measures the direction and scale of the local diffusion process in every voxel through its spectrum in q-space, typically acquired in one or more shells. Recent developments in micro-structure imaging and multi-tissue decomposition have sparked renewed attention to the radial b-value dependence of the signal. Applications in tissu

Maria Luisa Buzzo, Duncan A. Forbes, Jean P. Brodie, Steven R. Janssens

Prompted by the many controversial claims involving the NGC 1052 group, including that it hosts two dark matter-free galaxies with overluminous and monochromatic globular cluster (GC) systems, here we map out the large-scale structure (LSS) of GCs over the entire group. To recover the LSS, we use archival optical CFHT imaging data. We recover two GC density

Cheng Cheng, Lin Fu

Very recently, a defect model which depicts the growth tendency of the near-wall peak of the streamwise turbulence intensity has been developed (Chen $\&$ Sreenivasan, J. Fluid Mech. (2021), vol.908, R3). Based on the finiteness of the near-wall turbulence production, this model predicts that the magnitude of the peak will approach a finite limit as the Reyn

A. Karassev, P. Krupski, V. Todorov, V. Valov

The notion of a $V^n$-continuum was introduced by Alexandroff \cite{ps} as a generalization of the concept of $n$-manifold. In this note we consider the cohomological analogue of $V^n$-continuum and prove that any strongly locally homogeneous generalized continuum $X$ with cohomological dimension $\dim_G X=n$ is a generalized $V^n$-space with respect to the

Prateeti Mukherjee, Satya Lokam

We analyze the number of queries that a whitebox adversary needs to make to a private learner in order to reconstruct its training data. For $(\epsilon, \delta)$ DP learners with training data drawn from any arbitrary compact metric space, we provide the \emph{first known lower bounds on the adversary's query complexity} as a function of the learner's privac

Gurdip Bakshi, John Crosby, Xiaohui Gao

Emphasizing the statistics of jumps crossing the strike and local time, we develop a decomposition of equity option risk premiums. Operationalizing this theoretical treatment, we equip the pricing kernel process with unspanned risks, embed (unspanned) jump risks, and allow equity return volatility to contain unspanned risks. Unspanned risks are consistent wi

Liuxian Zhao

This paper proposes an acoustic beam splitter based on acoustic Luneburg lens. A two-dimensional acoustic Luneburg lens with gradient refractive index is achieved to provide a practical realization for the acoustic beam splitter. The acoustic wave propagation through the beam splitter was explored theoretically, numerically and experimentally. Results show t

Jie Min, Yili Hong, William Q. Meeker, George Ostrouchov

Graphics processing units (GPUs) are widely used in many high-performance computing (HPC) applications such as imaging/video processing and training deep-learning models in artificial intelligence. GPUs installed in HPC systems are often heavily used, and GPU failures occur during HPC system operations. Thus, the reliability of GPUs is of interest for the ov

Shuting Ai, Jinlu Li

In this paper, we study some optimization problems in uniformly convex and uniformly smooth Bochner spaces. We consider four cases of the underlying subsets: closed and convex subsets, closed and convex cones, closed subspaces and closed balls. In each case, we study the existence problems and the inverse image properties. We think that the results and the a

Roberto A. Machado, Gretchen L. Matthews, Welington Santos

We consider the problem of secure distributed matrix multiplication (SDMM), where a user has two matrices and wishes to compute their product with the help of $N$ honest but curious servers under the security constraint that any information about either $A$ or $B$ is not leaked to any server. This paper presents a \emph{new scheme} that considers the inner p

Joseph A. Wolf

Consider a connected homogeneous Riemannian manifold $(M,ds^2)$ and a Riemannian covering $(M,ds^2) \to \Gamma \backslash (M,ds^2)$. If $\Gamma \backslash (M,ds^2)$ is homogeneous then every $\gamma \in \Gamma$ is an isometry of constant displacement. The Homogeneity Conjecture suggests the converse: if every $\gamma \in \Gamma$ is an isometry of constant di

Orazio Pinti, Assad A. Oberai

Low-fidelity data is typically inexpensive to generate but inaccurate. On the other hand, high-fidelity data is accurate but expensive to obtain. Multi-fidelity methods use a small set of high-fidelity data to enhance the accuracy of a large set of low-fidelity data. In the approach described in this paper, this is accomplished by constructing a graph Laplac

Budhi Arta Surya

This paper revisits classical works of Rauch (1963, et al. 1965) and develops a novel method for maximum likelihood (ML) smoothing estimation from incomplete information/data of stochastic state-space systems. Score function and conditional observed information matrices of incomplete data are introduced and their distributional identities are established. Us

Randall Clark, Henry Abarbanel, Luke C. Fairbanks, Ramon E Sanchez

Using data alone, without knowledge of underlying physical models, nonlinear discrete time regional forecasting dynamical rules are constructed employing well tested methods from applied mathematics and nonlinear dynamics. Observations of environmental variables such as wind velocity, temperature, pressure, etc allow the development of forecasting rules that

Yingzhou Bi, Jiangtao Huang, Penghui Liu, Lianmei Wang

Software vulnerabilities can have serious consequences, which is why many techniques have been proposed to defend against them. Among these, vulnerability detection techniques are a major area of focus. However, there is a lack of a comprehensive approach for benchmarking these proposed techniques. In this paper, we present the first survey that comprehensiv

Thomas Parmer, Luis M. Rocha

Given the large size and complexity of most biochemical regulation and signaling networks, there is a non-trivial relationship between the micro-level logic of component interactions and the observed macro-dynamics. Here we address this issue by formalizing the existing concept of pathway modules, which are sequences of state updates that are guaranteed to o

Nancy Abdallah, Nasrin Altafi, Pietro De Poi, Luca Fiorindo

We study Hilbert functions, Lefschetz properties, and Jordan type of Artinian Gorenstein algebras associated to Perazzo hypersurfaces in projective space. The main focus lies on Perazzo threefolds, for which we prove that the Hilbert functions are always unimodal. Further we prove that the Hilbert function determines whether the algebra is weak Lefschetz, an

Constantin Rein, Martin Kolář, Klaus Kroy, Viktor Holubec

Autonomous active Brownian ratchets rectify active Brownian particle motion solely by means of a spatially modulated but stationary activity, without external forces. We argue that such ratcheting requires at least a two-dimensional geometry. The underlying principle is similar to the ratcheting induced by steric obstacles in microswimmer baths: suitably pol

Reto Buzano, Louis Yudowitz

We prove bubble-tree convergence of sequences of gradient Ricci shrinkers with uniformly bounded entropy and uniform local energy bounds, refining the compactness theory of Haslhofer-Mueller. In particular, we show that no energy concentrates in neck regions, a result which implies a local energy identity for the sequence. Direct consequences of these result

Vladimir Dotsenko, Ualbai Umirbaev

All algebras of a certain type are said to form a Nielsen-Schreier variety if every subalgebra of a free algebra is free. This property has been perceived as extremely rare; in particular, only six Nielsen-Schreier varieties of algebras with one binary operation have been discovered in prior work on this topic. We propose an effective combinatorial criterion

Xin-Zhe Zhang, Li-Ting Wu, Ru-Zhi Luo, Jing Chen

Negative-index materials (NIMs) are shown to support optical anti-parity-time (anti-PT) symmetry even when they are lossless. Here we prove the feasibility in achieving higher-order exceptional points (EPs) in loss-free waveguide arrays by utilizing the anti-$\mathcal{PT}$ symmetry induced by NIM. Numerical simulation about a third-order EP fits well with th

Keiichi Wada, Yuki Kudoh, Tohru Nagao

Multi-wavelength observations of active galactic nuclei (AGNs) often reveal various time scales of variability. Among these phenomena, "changing-look AGNs" are extreme cases where broad emission lines become faint/bright or even disappear/emerge between multi-epoch observations, providing crucial information about AGN internal structures. We here focus on "c

Ahana Ghosh, Sebastian Tschiatschek, Sam Devlin, Adish Singla

Block-based programming environments are increasingly used to introduce computing concepts to beginners. However, novice students often struggle in these environments, given the conceptual and open-ended nature of programming tasks. To effectively support a student struggling to solve a given task, it is important to provide adaptive scaffolding that guides

Francesco Bernardini, Abhijit Chakraborty, Carlos Ordóñez

This pedagogical article elucidates the fundamentals of trapped-ion quantum computing, which is one of the potential platforms for constructing a scalable quantum computer. The evaluation of a trapped-ion system's viability for quantum computing is conducted in accordance with DiVincenzo's criteria.

Henrique Reggiani, Kevin C. Schlaufman, Andrew R. Casey

The progenitor systems and explosion mechanisms responsible for the thermonuclear events observationally classified as Type Ia supernovae are uncertain and difficult to uniquely constrain using traditional observations of Type Ia supernova host galaxies, progenitors, light curves, and remnants. For the subset of thermonuclear events that are prolific produce

Gabriel Nowaskie

Since the groundwork published by Torres-Vega and Frederick, the Quantum Phase Space Representation (QPSR) has been explored as a method for solving a multitude of physical systems and describing phenomena. Most recently, Valentino A. Simpao has developed a method, the Heaviside Operational Ansatz, to solve the Time Dependent Schrodinger Equation (TDSE) in t

Melvyn Tyloo

For many coupled dynamical systems, the interaction is the outcome of the measurement that each unit has of the others as e.g. in modern inverter-based power grids, autonomous vehicular platoons or swarms of drones, or it is the results of physical flows. Synchronization among all the components of these systems is of primal importance to avoid failures. The

G. R. Fonseca, F. R. Prudêncio, M. G. Silveirinha, P. A. Huidobro

In recent years there has been a great interest in topological photonics and protected edge states. Here, we present a first principles method to compute topological invariants of three-dimensional gapless phases. Our approach allows to calculate the topological charges of Weyl points through the efficient numerical computation of gap Chern numbers, which re

Alexander J. Gaidis, Joao Moreira, Ke Sun, Alyssa Milburn

We present the design, implementation, and evaluation of FineIBT: a CFI enforcement mechanism that improves the precision of hardware-assisted CFI solutions, like Intel IBT, by instrumenting program code to reduce the valid/allowed targets of indirect forward-edge transfers. We study the design of FineIBT on the x86-64 architecture, and implement and evaluat

Heather Desaire, Aleesa E. Chua, Madeline Isom, Romana Jarosova

ChatGPT has enabled access to AI-generated writing for the masses, and within just a few months, this product has disrupted the knowledge economy, initiating a culture shift in the way people work, learn, and write. The need to discriminate human writing from AI is now both critical and urgent, particularly in domains like higher education and academic writi

Stacey Sheldon, Yatish Kumar, Michael Goodrich, Graham Heyes

To increase the science rate for high data rates/volumes, Thomas Jefferson National Accelerator Facility (JLab) has partnered with Energy Sciences Network (ESnet) to define an edge to data center traffic shaping / steering transport capability featuring data event-aware network shaping and forwarding. The keystone of this ESnet JLab FPGA Accelerated Transpor

Brandi Ransom, Akash Ramdas, Eder Lomeli, Jad Fidawi

We introduce an adhesion parameter that enables rapid screening for materials interfaces with high adhesion. This parameter is obtained by density functional theory calculations of individual single-material slabs rather than slabs consisting of combinations of two materials, eliminating the need to calculate all configurations of a prohibitively vast space

Tsuyoshi Miezaki, Akihiro Munemasa

In the present paper, we give harmonic weight enumerators and Jacobi polynomials for the first-order Reed--Muller codes and the extended Hamming codes. As a corollary, we show the nonexistence of combinatorial $4$-designs in these codes.

Ilya D. Shkredov

We obtain a generalization of the recent Kelley--Meka result on sets avoiding arithmetic progressions of length three. In our proof we develop the theory of the higher energies. Also, we discuss the case of longer arithmetic progressions, as well as a general family of norms, which includes the higher energies norms and Gowers norms.

Xiaoyu Wang, Oskar Vafek

We revisit the Hofstadter butterfly for a subset of topologically trivial Bloch bands arising from a continuum free electron Hamiltonian in a periodic lattice potential. We employ the recently developed procedure -- which was previously used to analyze the case of topologically non-trivial bands [\href{https://journals.aps.org/prb/abstract/10.1103/PhysRevB.1

Ru Wang, Linxiu Zeng, Xinyong Zhang, Sanbrita Mondal

While being able to read with screen magnifiers, low vision people have slow and unpleasant reading experiences. Eye tracking has the potential to improve their experience by recognizing fine-grained gaze behaviors and providing more targeted enhancements. To inspire gaze-based low vision technology, we investigate the suitable method to collect low vision u

Matheus M. Castro, Giuseppe Tenaglia

In this paper, we study the random dynamical system $f_\omega^n$ generated by a family of maps $\{f_{\omega_0}: \mathbb{S}^1 \to \mathbb{S}^1\}_{\omega_0 \in [-\varepsilon,\varepsilon]},$ $f_{\omega_0}(x) = \alpha \xi (x+\omega_0) +a\ (\mathrm{mod }\ 1),$ where $\xi: \mathbb S^1 \to \mathbb R$ is a non-degenerated map, $a\in [0,1)$, and $\alpha,\varepsilon>0

Zixuan Feng, Mariam Guizani, Marco A. Gerosa, Anita Sarma

Diversity and inclusion in open source software (OSS) is a multifaceted concept that arises from differences in contributors' gender, seniority, language, region, and other characteristics. D&I has received growing attention in OSS ecosystems and projects, and various programs have been implemented to foster contributor diversity. However, we do not yet know

Michal Kosinski, Poruz Khambatta, Yilun Wang

Carefully standardized facial images of 591 participants were taken in the laboratory, while controlling for self-presentation, facial expression, head orientation, and image properties. They were presented to human raters and a facial recognition algorithm: both humans (r=.21) and the algorithm (r=.22) could predict participants' scores on a political orien

Reuben Tan, Arijit Ray, Andrea Burns, Bryan A. Plummer

We propose a self-supervised approach for learning to perform audio source separation in videos based on natural language queries, using only unlabeled video and audio pairs as training data. A key challenge in this task is learning to associate the linguistic description of a sound-emitting object to its visual features and the corresponding components of t

Yuanhao Xiong, Long Zhao, Boqing Gong, Ming-Hsuan Yang

Existing video-language pre-training methods primarily focus on instance-level alignment between video clips and captions via global contrastive learning but neglect rich fine-grained local information in both videos and text, which is of importance to downstream tasks requiring temporal localization and semantic reasoning. A powerful model is expected to be

Heqiang Wang, Jieming Bian, Jie Xu

In this study, we address the emerging field of Streaming Federated Learning (SFL) and propose local cache update rules to manage dynamic data distributions and limited cache capacity. Traditional federated learning relies on fixed data sets, whereas in SFL, data is streamed, and its distribution changes over time, leading to discrepancies between the local

Adrian Dumitru, Heikki Mäntysaari, Risto Paatelainen

The forward scattering amplitude of a small dipole at high energies is given in the mean field approximation by the Balitsky-Kovchegov (BK) evolution equation. It requires an initial condition $N(r; x_0)$ describing the scattering of a dipole with size $r$ off the target that is probed at momentum fraction $x_0$. Rather than using ad hoc parameterizations tu

Daniel J. Reardon, William A. Coles

Density fluctuations in the ionised interstellar medium have a profound effect on radio pulsar observations, through angular scattering, intensity scintillations, and small changes in time delays from dispersion. Here we show that it is possible to recover the variations in dispersive delays that originate from a dominant scattering region using measurements

Pierre Nazé

When a thermally isolated system performs a driving process in the quasistatic regime, its variation of average energy is equal to its quasistatic work. Even though presenting this simple definition, few attempts have been made to describe such quantity from the fluctuation theorem point of view. In this work, based on Jarzynski's equality, four forms of suc

Eric Mayotte, Thomas Fitoussi

We test for an anisotropy in the mass of arriving cosmic-ray primaries associated with the galactic plane. The sensitivity to primary mass is obtained through the depth of shower maximum, $X_{\rm max}$, extracted from hybrid events measured over a 14-year period at the Pierre Auger Observatory. The sky is split into distinct on- and off-plane regions using t

Jimmy He

We study fluctuations of the current at the boundary for the half space asymmetric simple exclusion process (ASEP) and the height function of the half space six vertex model at the boundary at large times. We establish a phase transition depending on the asymptotic density of particles at the boundary, with GSE and GOE limits as well as the Baik--Rains cross

Himanshu Dave, M. Houssem Kasbaoui

We investigate the mechanisms by which inertial particles dispersed at semi-dilute conditions cause significant drag-reduction in a turbulent channel flow at $\mathrm{Re}_\tau = 180$. We consider a series of four-way coupled Euler-Lagrange simulations where particles having friction Stokes number $\mathrm{St}^+ = 6$ or 30 are introduced at progressively incr

Chaoyang Wang, Lachlan Ewen MacDonald, Laszlo A. Jeni, Simon Lucey

In this paper we present a new method for deformable NeRF that can directly use optical flow as supervision. We overcome the major challenge with respect to the computationally inefficiency of enforcing the flow constraints to the backward deformation field, used by deformable NeRFs. Specifically, we show that inverting the backward deformation function is a

Will Dana, David E Speyer, Hugh Thomas

Motivated by the goal of studying cluster algebras in infinite type, we study the stability domains of modules for the preprojective algebra in the corresponding infinite types. Specifically, we study real bricks: those modules whose endomorphism algebra is a division ring and which have no self-extensions. We define "shard modules" to be those real bricks w

Zhimeng Yang, Ariah Klages-Mundt, Lewis Gudgeon

We investigate the theoretical and empirical relationships between activity in on-chain markets and pricing in off-chain cryptocurrency markets (e.g., ETH/USD prices). The motivation is to develop methods for proxying off-chain market data using data and computation that is in principle verifiable on-chain and could provide an alternative approach to blockch

Dylan Owens, Siyi Xu, Elena Manjavacas, S. K. Leggett

Excess infrared flux from white dwarf stars is likely to arise from a dusty debris disk or a cool companion. In this work, we present near-infrared spectroscopic observations with Keck/MOSFIRE, Gemini/GNIRS, and Gemini/Flamingos-2 of seven white dwarfs with infrared excesses identified in previous studies. We confirmed the presence of dust disks around four

E. Medina-Guerra, Parveen Kumar, I. V. Gornyi, Yuval Gefen

Quantum state engineering plays a vital role in various applications in the field of quantum information. Different strategies, including drive-and-dissipation, adiabatic cooling, and measurement-based steering, have been proposed in the past for state generation and manipulation, each with its upsides and downsides. Here, we address a class of measurement-b

Leszek Plaskota, Paweł Siedlecki

We study the worst case tractability of multivariate linear problems defined on separable Hilbert spaces. Information about a problem instance consists of noisy evaluations of arbitrary bounded linear functionals, where the noise is either deterministic or random. The cost of a single evaluation depends on its precision and is controlled by a cost function.

M. Selch, M. Suleymanov, C. X. Zhang, M. A. Zubkov

Hall conductivity for the intrinsic anomalous quantum Hall effect in homogeneous systems is given by the topological invariant composed of the Green function depending on momentum of quasiparticle. This expression reveals correspondence with the mathematical notion of the degree of mapping. A more involved situation takes place for the quantum Hall effect in

Erickson Tjoa

In this Essay we construct a concrete, non-perturbative realization of metric reconstruction using quantum-optical model of particle detectors in relativistic quantum information. The non-perturbative approach allows us to realize a version of "short-distance physics corresponds to poor statistics" idea by Kempf which occurs way above the Planck scale before

Clément Caillaud, Mathieu Lugrin, Sébastien Esquieu, Cédric Content

Characterizing the boundary layer transition to turbulence around realistic hypersonic vehicles is a challenging task due to the numerous parameters that affect the process. To address this challenge, the cone-cylinder-flare (CCF) geometry has been designed to provide a flow topology that captures various transition mechanisms observed on reentry objects, su

Silas Alben

We study steady flows that are optimal for heat transfer in a two-dimensional periodic domain. The flows maximize heat transfer under the constraints of incompressibility and a given energy budget (i.e. mean viscous power dissipation). Using an unconstrained optimization approach, we compute optima starting from 30--50 random initializations across several d

Michele Mancarella, Francesco Iacovelli, Davide Gerosa

The detection of black-hole binaries at high redshifts is a cornerstone of the science case of third-generation gravitational-wave interferometers. The star-formation rate peaks at z~2 and decreases by orders of magnitude by z~10. Any confident detection of gravitational waves from such high redshifts would imply either the presence of stars formed from pris

Zhuoran Xiong, Marihan Amein, Olivier Therrien, Warren J. Gross

We present FMAS, a fast multi-objective neural architecture search framework for semantic segmentation. FMAS subsamples the structure and pre-trained parameters of DeepLabV3+, without fine-tuning, dramatically reducing training time during search. To further reduce candidate evaluation time, we use a subset of the validation dataset during the search. Only t

Aditya Dave, Ioannis Faros, Nishanth Venkatesh, Andreas A. Malikopoulos

Safety-critical cyber-physical systems require control strategies whose worst-case performance is robust against adversarial disturbances and modeling uncertainties. In this paper, we present a framework for approximate control and learning in partially observed systems to minimize the worst-case discounted cost over an infinite time horizon. We model distur

Adrian Thummerer, Erik van der Bijl, Arthur Jr Galapon, Joost JC Verhoeff

Purpose: Medical imaging has become increasingly important in diagnosing and treating oncological patients, particularly in radiotherapy. Recent advances in synthetic computed tomography (sCT) generation have increased interest in public challenges to provide data and evaluation metrics for comparing different approaches openly. This paper describes a datase

Cunzhi Zhang, Francois Gygi, Giulia Galli

The full realization of spin qubits for quantum technologies relies on the ability to control and design the formation processes of spin defects in semiconductors and insulators. We present a computational protocol to investigate the synthesis of point-defects at the atomistic level, and we apply it to the study of a promising spin-qubit in silicon carbide,