April 2023 arXiv papers — page 18

T. V. Ricci, J. E. Steiner, R. B. Menezes, K. Slodkowski Clerici

We analysed the nuclear region of all 56 early-type galaxies from the DIVING$^\mathrm{3D}$ Project, which is a statistically complete sample of objects that contains all 170 galaxies of the Southern Hemisphere with B < 12.0 mag and galactic latitude |b| < 15$^{\circ}$. Observations were performed with the Integral Field Unit of the Gemini Multi-Object Spectr

Roshan Sharma, Shengyi Wang, Alexander Oey, Anastasiia Evdokimova

Logical atomicity has been widely accepted as a specification format for data structures in concurrent separation logic. While both lock-free and lock-based data structures have been verified against logically atomic specifications, most of the latter start with atomic specifications for the locks as well. In this paper, we compare this approach with one bas

Johannes K. Fichte, Robert Ganian, Markus Hecher, Friedrich Slivovsky

The QSAT problem, which asks to evaluate a quantified Boolean formula (QBF), is of fundamental interest in approximation, counting, decision, and probabilistic complexity and is also considered the prototypical PSPACEcomplete problem. As such, it has previously been studied under various structural restrictions (parameters), most notably parameterizations of

Qi Zhang, Yayi Yang, Chongyang Shi, An Lao

The rapid growth of social media has caused tremendous effects on information propagation, raising extreme challenges in detecting rumors. Existing rumor detection methods typically exploit the reposting propagation of a rumor candidate for detection by regarding all reposts to a rumor candidate as a temporal sequence and learning semantics representations o

Kahraman Kostas

The proliferation of the Internet of Things (IoT) has introduced a massive influx of devices into the market, bringing with them significant security vulnerabilities. In this diverse ecosystem, robust IoT device identification is a critical preventive measure for network security and vulnerability management. This study proposes a deep learning-based method

Rui Xue, Shao-Teng Huang, Hu-Bing Xiao, Ze-Rui Wang

The proton synchrotron radiation is considered as the origin of high-energy emission of blazars at times. However, extreme physical parameters are often required. In this work, we propose an analytical method to study the parameter space when applying the proton synchrotron radiation to fit the keV, GeV, and very-high-energy emission of blazar jets. We find

Somjit Nath, Gopeshh Raaj Subbaraj, Khimya Khetarpal, Samira Ebrahimi Kahou

Deep Reinforcement Learning has shown significant progress in extracting useful representations from high-dimensional inputs albeit using hand-crafted auxiliary tasks and pseudo rewards. Automatically learning such representations in an object-centric manner geared towards control and fast adaptation remains an open research problem. In this paper, we introd

José Edson Sampaio, Euripedes Carvalho da Silva

In this article, we present a complete classification, with normal forms, of the real algebraic curves under blow-spherical homeomorphisms at infinity.

Yangyao Chen, H. J. Mo, Kai Wang

The presence of massive galaxies at high $z$ as recently observed by JWST appears to contradict the current $\Lambda$CDM cosmology. Here we aim to alleviate this tension by incorporating uncertainties from three sources in counting galaxies: cosmic variance, error in stellar mass estimation, and backsplash enhancement. Each of these factors significantly inc

Anatoli S. Kheifets, Zhongtao Xu

The mutual angle formed by the non-collinear polarization axes of two laser pulses is used to control two-photon XUV+IR ionization of noble gas atoms in the process of reconstruction of attosecond bursts by beating of two-photon transitions (RABBITT). The magnitude and the phase of this beating can be controlled very efficiently by the mutual polarization an

Eduardo O. Pinho, Celso C. Barros

In this work we study the effects of rotating stars on the behavior of bosons close to their surfaces. For this task, metrics determined by the rotation of these stars will be taken into account. We will consider the Klein-Gordon equation in the Hartle-Thorne metric and in the one proposed by Berti et al. by considering some kinds of stars. Pions and Higgs b

Iris Ma, Cristina V. Lopes

Commit messages play a crucial role in collaborative software development. They provide a clear and concise description of the changes made to the source code. However, many commit messages among students' projects lack useful information. This is a concern, as low-quality commit messages can negatively impact communication of software development and future

Junyoung Byun, Yujin Choi, Jaewook Lee

This study aims to alleviate the trade-off between utility and privacy of differentially private clustering. Existing works focus on simple methods, which show poor performance for non-convex clusters. To fit complex cluster distributions, we propose sophisticated dynamical processing inspired by Morse theory, with which we hierarchically connect the Gaussia

Xiaosheng Lin, Dachun Yang, Sibei Yang, Wen Yuan

Let $(\mathcal{X},d,\mu)$ be a doubling metric measure space in the sense of R. R. Coifman and G. Weiss, $L$ a non-negative self-adjoint operator on $L^2(\mathcal{X})$ satisfying the Davies--Gaffney estimate, and $X(\mathcal{X})$ a ball quasi-Banach function space on $\mathcal{X}$ satisfying some mild assumptions. In this article, the authors introduce the H

Shuyang Cao, Wenjie Huang, Daniel Boyanovsky

Axions mix with neutral pions after the QCD phase transition through their common coupling to the radiation bath via a Chern-Simons term, as a consequence of the $U(1)$ anomaly. The non-equilibrium effective action that describes this mixing phenomenon is obtained to second order in the coupling of neutral pions and axions to photons. We show that a misalign

Tuhin Kundu, Jishnu Ray Chowdhury, Cornelia Caragea

Keyphrase generation aims at generating topical phrases from a given text either by copying from the original text (present keyphrases) or by producing new keyphrases (absent keyphrases) that capture the semantic meaning of the text. Encoder-decoder models are most widely used for this task because of their capabilities for absent keyphrase generation. Howev

David Fitzek, Robert S. Jonsson, Werner Dobrautz, Christian Schäfer

Variational quantum algorithms (VQAs) represent a promising approach to utilizing current quantum computing infrastructures. VQAs are based on a parameterized quantum circuit optimized in a closed loop via a classical algorithm. This hybrid approach reduces the quantum processing unit load but comes at the cost of a classical optimization that can feature a

Yusuke Fujita, Makoto Iima

The wing structure of several insects, including dragonflies, is not smooth, but corrugated; its vertical cross-section consists of a connected series of line segments. Some previous studies have reported that corrugated wings exhibit better aerodynamic performance than flat wings at low Reynolds numbers (ten to the third). However, the mechanism remains unc

Kshitiz Upadhyay, Jan N. Fuhg, Nikolaos Bouklas, K. T. Ramesh

A novel data-driven constitutive modeling approach is proposed, which combines the physics-informed nature of modeling based on continuum thermodynamics with the benefits of machine learning. This approach is demonstrated on strain-rate-sensitive soft materials. This model is based on the viscous dissipation-based visco-hyperelasticity framework where the to

Roberto Andreani, Gabriel Haeser, Leonardo M. Mito, Héctor Ramírez

In a previous paper [R. Andreani, G. Haeser, L. M. Mito, H. Ram\'irez, T. P. Silveira. First- and second-order optimality conditions for second-order cone and semidefinite programming under a constant rank condition. Mathematical Programming, 2023. DOI: 10.1007/s10107-023-01942-8] we introduced a constant rank constraint qualification for nonlinear semidefin

Mohamed Fadhlallah Guerri, Cosimo Distante, Paolo Spagnolo, Fares Bougourzi

In the recent years, hyperspectral imaging (HSI) has gained considerably popularity among computer vision researchers for its potential in solving remote sensing problems, especially in agriculture field. However, HSI classification is a complex task due to the high redundancy of spectral bands, limited training samples, and non-linear relationship between s

X. Mi, A. A. Michailidis, S. Shabani, K. C. Miao

Engineered dissipative reservoirs have the potential to steer many-body quantum systems toward correlated steady states useful for quantum simulation of high-temperature superconductivity or quantum magnetism. Using up to 49 superconducting qubits, we prepared low-energy states of the transverse-field Ising model through coupling to dissipative auxiliary qub

Hiroyuki Hirashita

We model the effect of grain size distribution in a galaxy on the evolution of CO and H$_2$ abundances. The formation and dissociation of CO and H$_2$ in typical dense clouds are modelled in a manner consistent with the grain size distribution. The evolution of grain size distribution is calculated based on our previous model, which treats the galaxy as a on

Giridhar Kaushik Ramachandran, Haritha Gangavarapu, Kevin Lybarger, Ozlem Uzuner

In online forums like Reddit, users share their experiences with medical conditions and treatments, including making claims, asking questions, and discussing the effects of treatments on their health. Building systems to understand this information can effectively monitor the spread of misinformation and verify user claims. The Task-8 of the 2023 Internation

Paul Owoicho, Ivan Sekulić, Mohammad Aliannejadi, Jeffrey Dalton

This research aims to explore various methods for assessing user feedback in mixed-initiative conversational search (CS) systems. While CS systems enjoy profuse advancements across multiple aspects, recent research fails to successfully incorporate feedback from the users. One of the main reasons for that is the lack of system-user conversational interaction

Kotomi Taniguchi, Liton Majumdar, Paola Caselli, Shigehisa Takakuwa

We present Atacama Large Millimeter/submillimeter Array Band 3 data toward five massive young stellar objects (MYSOs), and investigate relationships between unsaturated carbon-chain species and saturated complex organic molecules (COMs). An HC$_{5}$N ($J=35-34$) line has been detected from three MYSOs, where nitrogen(N)-bearing COMs (CH$_{2}$CHCN and CH$_{3}

Fisseha Admasu Ferede, Madhusudhanan Balasubramanian

Inaccurate optical flow estimates in and near occluded regions, and out-of-boundary regions are two of the current significant limitations of optical flow estimation algorithms. Recent state-of-the-art optical flow estimation algorithms are two-frame based methods where optical flow is estimated sequentially for each consecutive image pair in a sequence. Whi

Dmitry Gayfulin

Given an irrational number $\alpha$ consider its irrationality measure function $\psi_{\alpha}(t)=\min\limits_{1\le q\le t, q\in\mathbb{Z}}\|q\alpha\|$. The set of all values of $\lambda(\alpha)=(\limsup\limits_{t\to\infty} t\psi_{\alpha}(t))^{-1}$ where $\alpha $ runs through the set $\mathbb{R}\setminus\mathbb{Q}$ is called the Lagrange spectrum $\mathbb{L

Carlo Baldassi, Enrico M. Malatesta, Gabriele Perugini, Riccardo Zecchina

We study the binary and continuous negative-margin perceptrons as simple non-convex neural network models learning random rules and associations. We analyze the geometry of the landscape of solutions in both models and find important similarities and differences. Both models exhibit subdominant minimizers which are extremely flat and wide. These minimizers c

Hao Yuan, Weixuan Zhang, Zilong Zhou, Wenlong Wang

Electronic sensors play important roles in various applications, such as industry and environmental monitoring, biomedical sample ingredient analysis, wireless networks and so on. However, the sensitivity and robustness of current schemes are often limited by the low quality-factors of resonators and fabrication disorders. Hence, exploring new mechanisms of

Zhuoran Jiang, Siqi Wang, Yifei Xu, Leshan Sun

Radiation-induced acoustic (RA) imaging is a promising technique for visualizing radiation energy deposition in tissues, enabling new imaging modalities and real-time therapy monitoring. However, it requires measuring hundreds or even thousands of averages to achieve satisfactory signal-to-noise ratios (SNRs). This repetitive measurement increases ionizing r

Yifan Jiang, Filip Ilievski, Kaixin Ma

Stories about everyday situations are an essential part of human communication, motivating the need to develop AI agents that can reliably understand these stories. Despite the long list of supervised methods for story completion and procedural understanding, current AI has no mechanisms to automatically track and explain procedures in unseen stories. To bri

Sumit Goel, Amit Goyal

We consider two-player contests with the possibility of ties and study the effect of different tie-breaking rules on effort. For ratio-form and difference-form contests that admit pure-strategy Nash equilibrium, we find that the effort of both players is monotone decreasing in the probability that ties are broken in favor of the stronger player. Thus, the ef

Kacper Leśniara, Piotr Szymański

Recent years brought advancements in using neural networks for representation learning of various language or visual phenomena. New methods freed data scientists from hand-crafting features for common tasks. Similarly, problems that require considering the spatial variable can benefit from pretrained map region representations instead of manually creating fe

Ryosuke Hirai

We present an analytical model that describes the response of companion stars after being impacted by a supernova in a close binary system. This model captures key properties of the luminosity evolution obtained from 1D stellar evolution calculations fairly well: a high-luminosity plateau phase and a decaying tail phase. It can be used to constrain the pre-s

Ty Roachford

Ensoul is a framework proposed for the purpose of creating technologies that create more technologies through the combined use of networks, and nests, of energy homeostatic (enerstatic) loops and open-ended evolutionary techniques. Generative technologies developed by such an approach serve as both simple, yet insightful models of thermodynamically driven co

Pawan Sigdel, Ananth Kandadai, Kalimuthu Jawaharraj, Bharat Jasthi

Microbiologically influenced corrosion (MIC) compromises the integrity of many technologically relevant metals. Protective coatings based on synthetic materials pose potential environmental impacts. Here, we report a MIC resistant coating based on a biofilm matrix of Citrobacter sp. strain MIC21 on underlying copper (Cu) surfaces. Three identical corrosion c

Anders Giovanni Møller, Jacob Aarup Dalsgaard, Arianna Pera, Luca Maria Aiello

In the realm of Computational Social Science (CSS), practitioners often navigate complex, low-resource domains and face the costly and time-intensive challenges of acquiring and annotating data. We aim to establish a set of guidelines to address such challenges, comparing the use of human-labeled data with synthetically generated data from GPT-4 and Llama-2

Akihiro Fujii, Hideki Tsunashima, Yoshihiro Fukuhara, Koji Shimizu

Deep-learning inverse techniques have attracted significant attention in recent years. Among them, the neural adjoint (NA) method, which employs a neural network surrogate simulator, has demonstrated impressive performance in the design tasks of artificial electromagnetic materials (AEM). However, the impact of the surrogate simulators' accuracy on the solut

Hao Chen, Lorenz J. Falling, Heath Kersell, George Yan

Using CoOx thin films supported on Au(111) single crystal surfaces as model catalysts for the CO oxidation reaction we show that three reaction regimes exist in response to chemical and topographic restructuring of the CoOx catalyst as a function of reactant gas phase CO/O2 stoichiometry a finding that highlights the versatility of catalysts and their evolut

Elijah Schiltz-Rouse, Hyeongjoo Row, Stewart A. Mallory

Using computer simulation and analytical theory, we study an active analog of the well-known Tonks gas, where active Brownian particles are confined to a one-dimensional (1D) channel. By introducing the notion of a kinetic temperature, we derive an accurate analytical expression for the pressure and clarify the paradoxical behavior where active Brownian part

L. L. Sales, F. C. Carvalho, H. T. C. M. Souza

In this paper, we revisit the hydrogen recombination history from a novel perspective: the evolution of chemical potentials. We derive expressions for the chemical potentials, which depend on the thermal bath temperature and the ionization degree of the universe. Our main finding reveals a constraint between the chemical potentials of hydrogen and proton at

Zhiyuan Yang

We compute the conjugate system of twisted Araki-Woods von Neumann algebras $ \mathcal{L}_T(H) $ for a compatible braided crossing symmetric twist $T$ on a finite dimensional Hilbert space $ \mathcal{H} $ with norm $ \|T\| <1$. This implies that those algebras have finite non-microstates free Fisher information and therefore are always factors of type $\text

Abhishek Mandal, Susan Leavy, Suzanne Little

Generative multimodal models based on diffusion models have seen tremendous growth and advances in recent years. Models such as DALL-E and Stable Diffusion have become increasingly popular and successful at creating images from texts, often combining abstract ideas. However, like other deep learning models, they also reflect social biases they inherit from t

Mingchen Li, Lifu Huang

Open domain entity state tracking aims to predict reasonable state changes of entities (i.e., [attribute] of [entity] was [before_state] and [after_state] afterwards) given the action descriptions. It's important to many reasoning tasks to support human everyday activities. However, it's challenging as the model needs to predict an arbitrary number of entity

Cyrille Kenne, Gisèle Mophou, Mahamadi Warma

In this paper, a class of semilinear fractional elliptic equations associated to the spectral fractional Dirichlet Laplace operator is considered. We establish the existence of optimal solutions as well as a minimum principle of Pontryagin type and the first order necessary optimality conditions of associated optimal control problems. Second order conditions

Kieron Drumm

In recent years, product categorisation has been a common issue for E-commerce companies who have utilised machine learning to categorise their products automatically. In this study, we propose an ensemble approach, using a combination of different models to separately predict each product's category, subcategory, and colour before ultimately combining the r

Jason Schweinsberg, Yubo Shuai

Consider a birth and death process started from one individual in which each individual gives birth at rate $\lambda$ and dies at rate $\mu$, so that the population size grows at rate $r = \lambda - \mu$. Lambert and Harris, Johnston, and Roberts came up with methods for constructing the exact genealogy of a sample of size $n$ taken from this population at t

Casey Meehan, Florian Bordes, Pascal Vincent, Kamalika Chaudhuri

Self-supervised learning (SSL) algorithms can produce useful image representations by learning to associate different parts of natural images with one another. However, when taken to the extreme, SSL models can unintendedly memorize specific parts in individual training samples rather than learning semantically meaningful associations. In this work, we perfo

Nathan O. Adeyemi, Kayse Lee Maass, Amanda M. Graham, Kalyan S. Pasupathy

For a large portion of mental health patients, the Emergency Department is the first point of contact when in crisis and in need of urgent acute care. Unfortunately, those who have already received an admission disposition may wait hours or days after before being placed in a psychiatric inpatient (IP) care unit. Known as ED boarding, one primary contributor

Trambak Banerjee, Bhaswar B. Bhattacharya, Gourab Mukherjee

Nonparametric two-sample testing is a classical problem in inferential statistics. While modern two-sample tests, such as the edge count test and its variants, can handle multivariate and non-Euclidean data, contemporary gargantuan datasets often exhibit heterogeneity due to the presence of latent subpopulations. Direct application of these tests, without re

Daniel J Kane, Andrei B. Vakhtin

The measurement of optical ultrafast laser pulses is done indirectly because the required bandwidth to measure these pulses exceeds the bandwidth of current electronics. As a result, this measurement problem is often posed as a 1-D phase retrieval problem, which is fraught with ambiguities. The phase retrieval method known as ptychography solves this problem

Nicholas Walker, John Dagdelen, Kevin Cruse, Sanghoon Lee

Although gold nanorods have been the subject of much research, the pathways for controlling their shape and thereby their optical properties remain largely heuristically understood. Although it is apparent that the simultaneous presence of and interaction between various reagents during synthesis control these properties, computational and experimental appro

Ragavendran Gopalakrishnan, Yueyang Zhong

This paper presents asymptotic properties of the Erlang-C formula in a spectrum of many-server limiting regimes. Specifically, we address an important gap in the literature regarding its limiting value in critically loaded regimes by studying extensions of the well-known square-root safety staffing rule used in the Quality-and-Efficiency-Driven (QED) regime.

Bin Wang, Armstrong Aboah, Zheyuan Zhang, Ulas Bagci

This study investigates the potential of eye-tracking technology and the Segment Anything Model (SAM) to design a collaborative human-computer interaction system that automates medical image segmentation. We present the \textbf{GazeSAM} system to enable radiologists to collect segmentation masks by simply looking at the region of interest during image diagno

Daniel Kramer, Michael Gowanlock, David Trilling, Andrew McNeill

Ground-based, all-sky astronomical surveys are imposed with an inevitable day-night cadence that can introduce aliases in period-finding methods. We examined four different methods -- three from the literature and a new one that we developed -- that remove aliases to improve the accuracy of period-finding algorithms. We investigate the effectiveness of these

David R. Nicholus

After summarizing characteristics of antidiagonal operators, we derive three direct sum decompositions characterizing antidiagonalizable linear operators - the first up to permutation-similarity, the second up to similarity, and the third up to unitary similarity. Each corresponds to a unique quasidiagonalization. We prove the permutation-similarity direct s

Ishan Shivansh Bangroo

In response to the global need for sustainable energy, green technology may help fight climate change. Before green infrastructure to be easily integrated into the world's energy system, it needs upgrading. By improving energy infrastructure and decision-making, artificial intelligence (AI) may help solve this challenge. EHVs have grown in popularity because

Enrique Dehaerne, Bappaditya Dey, Sandip Halder, Stefan De Gendt

Innovative Electronic Design Automation (EDA) solutions are important to meet the design requirements for increasingly complex electronic devices. Verilog, a hardware description language, is widely used for the design and verification of digital circuits and is synthesized using specific EDA tools. However, writing code is a repetitive and time-intensive ta

Dmitriy Leykekhman, Boris Vexler

In this paper we establish best approximation type estimates for the fully discrete Galerkin solutions of transient Stokes problem in $L^2(I;L^2(\Omega)^d)$ and $L^2(I;H^1(\Omega)^d)$ norms. These estimates fill the gap in the error analysis of the transient Stokes problems and have a number of applications. The analysis naturally extends to inhomogeneous pa

Stefano Fregonese, Zhiyuan Tong, Sibo Wang, Mattia Bacca

Accurate prediction of the force required to puncture a soft material is critical in many fields like medical technology, food processing, and manufacturing. However, such a prediction strongly depends on our understanding of the complex nonlinear behavior of the material subject to deep indentation and complex failure mechanisms. Only recently we developed

Marcelo G. L. Nogueira-Santos, Celso C. Barros

The $\eta$-Baryon interactions at low energies are studied in a model based in effective chiral Lagragians that take into account baryons of spin 1/2 and spin 3/2 in the intermediate states. The interacting baryons to be considered in this work are $B= N, \Lambda, \Sigma, \Xi$. We calculate the expected total and differential cross sections, phase-shifts and

Jimmy Wei, Kurt Shuster, Arthur Szlam, Jason Weston

Current dialogue research primarily studies pairwise (two-party) conversations, and does not address the everyday setting where more than two speakers converse together. In this work, we both collect and evaluate multi-party conversations to study this more general case. We use the LIGHT environment to construct grounded conversations, where each participant

Jessica C. Jones, Nazar Delegan, F. Joseph Heremans, Alex B. F. Martinson

Surface termination and interfacial interactions are critical for advanced solid-state quantum applications. In this paper, we demonstrate that atomic layer deposition (ALD) can both provide valuable insight on the chemical environment of the surface, having sufficient sensitivity to distinguish between the common diamond (001) surface termination types and

Yuji Saikai, Khue-Dung Dang

Mixtures of Gaussian process experts is a class of models that can simultaneously address two of the key limitations inherent in standard Gaussian processes: scalability and predictive performance. In particular, models that use Dirichlet processes as gating functions permit straightforward interpretation and automatic selection of the number of experts in a

André Rossi Kuroswiski, Humberto Baldessarini Pires, Angelo Passaro, Lamartine Nogueira Frutuoso

The increasing use of drones to perform various tasks has motivated an exponential growth of research aimed at optimizing the use of these means, benefiting both military and civilian applications, including logistics delivery. In this sense, the combined use of trucks and drones has been explored with great interest by Operations Research. This work present

Manh Hong Duong, The Anh Han

In this paper, we discover that the class of random polynomials arising from the equilibrium analysis of random asymmetric evolutionary games is \textit{exactly} the Kostlan-Shub-Smale system of random polynomials, revealing an intriguing connection between evolutionary game theory and the theory of random polynomials. Through this connection, we analyticall

Yusha Liu, Aarti Singh

In continuum-armed bandit problems where the underlying function resides in a reproducing kernel Hilbert space (RKHS), namely, the kernelised bandit problems, an important open problem remains of how well learning algorithms can adapt if the regularity of the associated kernel function is unknown. In this work, we study adaptivity to the regularity of transl

Jake Buzhardt, Phanindra Tallapragada

We consider the problem of the transport of a density of states from an initial state distribution to a desired final state distribution through a dynamical system with actuation. In particular, we consider the case where the control signal is a function of time, but not space; that is, the same actuation is applied at every point in the state space. This is

Jing Wang, Brian J. Rollick, Bernardo A. Huberman

A successful commercial deployment of quantum key distribution (QKD) technologies requires integrating QKD links into existing fibers and sharing the same fiber networks with classical data traffic. To mitigate the spontaneous Raman scattering (SpRS) noise from classical data channels, several quantum/classical coexistence strategies have been developed. O-b

Mohammad NaseriTehrani, MohammadJavad Salehi, Antti Tölli

Integrating coded caching (CC) into multi-input multi-output (MIMO) setups significantly enhances the achievable degrees of freedom (DoF). We consider a cache-aided MIMO configuration with a CC gain $t$, where a server with $L$ Tx-antennas communicates with $K$ users, each equipped with $G$ Rx-antennas. Similar to existing works, we also extend a core CC app

Renhao Wang, Jiayuan Mao, Joy Hsu, Hang Zhao

Robots operating in the real world require both rich manipulation skills as well as the ability to semantically reason about when to apply those skills. Towards this goal, recent works have integrated semantic representations from large-scale pretrained vision-language (VL) models into manipulation models, imparting them with more general reasoning capabilit

Nils Prigge

The tautological ring $R^*(M)$ of a smooth manifold $M$ is the ring of characteristic classes generated by the Miller-Morita-Mumford classes, and is often more accessible than the ring of all characteristic classes of smooth $M$-bundles. In this paper, we show that the Krull dimension of the tautological ring vanishes for almost all manifolds homotopy equiva

Bin Han

Standard interpolatory subdivision schemes and their underlying interpolating refinable functions are of interest in CAGD, numerical PDEs, and approximation theory. Generalizing these notions, we introduce and study $n_s$-step interpolatory $M$-subdivision schemes and their interpolating $M$-refinable functions with $n_s\in \mathbb{N} \cup\{\infty\}$ and a d

Louis Esser

For certain quasismooth Calabi-Yau hypersurfaces in weighted projective space, the Berglund-H\"{u}bsch-Krawitz (BHK) mirror symmetry construction gives a concrete description of the mirror. We prove that the minimal log discrepancy of the quotient of such a hypersurface by its toric automorphism group is closely related to the weights and degree of the BHK m

Hichem Hajaiej, Tianhao Liu, Linjie Song, Wenming Zou

In this paper, we study the existence and nonexistence of positive solutions for a coupled elliptic system with critical exponent and logarithmic terms. The presence of the the logarithmic terms brings major challenges and makes it difficult to use the previous results established in the work of Chen and Zou without new ideas and innovative techniques.

Dan Coman, George Marinescu, Huan Wang

We study asymptotic estimates of the dimension of cohomology on possibly non-compact complex manifolds for line bundles endowed with Hermitian metrics with algebraic singularities. We give a unified approach to establishing singular holomorphic Morse inequalities for hyperconcave manifolds, pseudoconvex domains, $q$-convex manifolds and $q$-concave manifolds

Jiaze Sun, Zhixiang Chen, Tae-Kyun Kim

3D pose transfer is a challenging generation task that aims to transfer the pose of a source geometry onto a target geometry with the target identity preserved. Many prior methods require keypoint annotations to find correspondence between the source and target. Current pose transfer methods allow end-to-end correspondence learning but require the desired fi

Moran Baruch, Nir Drucker, Gilad Ezov, Yoav Goldberg

Training large-scale CNNs that during inference can be run under Homomorphic Encryption (HE) is challenging due to the need to use only polynomial operations. This limits HE-based solutions adoption. We address this challenge and pioneer in providing a novel training method for large polynomial CNNs such as ResNet-152 and ConvNeXt models, and achieve promisi

Mohsen Mortazavi

Choosing the right stock portfolio with the highest efficiencies has always concerned accurate and legal investors. Investors have always been concerned about the accuracy and legitimacy of choosing the right stock portfolio with high efficiency. Therefore, this paper aims to determine the criteria for selecting an optimal stock portfolio with a high-efficie

Yuiki Takahashi, Chi Zhang, Arian Jadbabaie, Nicholas R. Hutzler

Molecules are a powerful platform to probe fundamental symmetry violations beyond the Standard Model, as they offer both large amplification factors and robustness against systematic errors. As experimental sensitivities improve, it is important to develop new methods to suppress sensitivity to external electromagnetic fields, as limits on the ability to con

Michael Blondin, Philip Offtermatt, Alex Sansfaçon-Buchanan

Constant-rate multi-mode systems (MMS) are hybrid systems with finitely many modes and real-valued variables that evolve over continuous time according to mode-specific constant rates. We introduce a variant of linear temporal logic (LTL) for MMS, and we investigate the complexity of the model-checking problem for syntactic fragments of LTL. We obtain a comp

Eric R. Beyerle, Ziyue Zou, Pratyush Tiwary

With the advent of faster computer processors and especially graphics processing units (GPUs) over the last few decades, the use of data-intensive machine learning (ML) and artificial intelligence (AI) has increased greatly, and the study of crystal nucleation has been one of the beneficiaries. In this review, we outline how ML and AI have been applied to ad

Long Chen

Through the calculation of the matrix element of the singlet axial-current operator between the vacuum and a pair of gluons in dimensional regularization with an anticommuting $\gamma_5$ defined in a Kreimer-scheme variant, we find that additional renormalization counter-terms proportional to the Chern-Simons current operator are needed starting from $\mathc

Pragati Gupta, Arjen Vaartjes, Xi Yu, Andrea Morello

We propose a scheme to generate spin cat states, i.e., superpositions of maximally separated quasiclassical states on a single high-dimensional nuclear spin in a solid-state device. We exploit a strong quadrupolar nonlinearity to drive the nucleus significantly faster than usual gate sequences, achieving collapses and revivals two orders of magnitude faster

Wesley Cooke, Zihao Mo, Weiming Xiang

Neural network model compression techniques can address the computation issue of deep neural networks on embedded devices in industrial systems. The guaranteed output error computation problem for neural network compression with quantization is addressed in this paper. A merged neural network is built from a feedforward neural network and its quantized versi

Yejiang Yang, Zihao Mo, Weiming Xiang

In this paper, a computationally efficient data-driven hybrid automaton model is proposed to capture unknown complex dynamical system behaviors using multiple neural networks. The sampled data of the system is divided by valid partitions into groups corresponding to their topologies and based on which, transition guards are defined. Then, a collection of sma

Matheus S. Palmero, Iberê L. Caldas

In magnetically confined plasma, it is possible to qualitatively describe the magnetic field configuration via phase spaces of suitable symplectic maps. These phase spaces are of mixed type, where chaos coexists with regular motion, and the complete understanding of the chaotic transport is a challenge that, when overcome, may provide further knowledge into

Lorena Mezini, Catherine E. Fielder, Andrew R. Zentner, Yao-Yuan Mao

Within the $\Lambda$CDM cosmology, dark matter haloes are comprised of both a smooth component and a population of smaller, gravitationally bound subhaloes. These components are often treated as a single halo when halo properties, such as density profiles, are extracted from simulations. Recent work has shown that density profiles change substantially when s

Madhava Sarma Vemuri, Umamaheswara Rao Tida

Metal inter-layer via (MIV) in Monolithic three-dimensional integrated circuits (M3D-IC) is used to connect inter-layer devices and provide power and clock signals across multiple layers. The size of MIV is comparable to logic gates because of the significant reduction in substrate layers due to sequential integration. Despite MIV's small size, the impact of

Hyeonjung, Jung, Jayant Gupta, Bharat Jayaprakash

Ordinary and partial differential equations (DE) are used extensively in scientific and mathematical domains to model physical systems. Current literature has focused primarily on deep neural network (DNN) based methods for solving a specific DE or a family of DEs. Research communities with a history of using DE models may view DNN-based differential equatio

Michael Neunteufel, Joachim Schöberl

In this paper we extend the recently introduced mixed Hellan-Herrmann-Johnson (HHJ) method for nonlinear Koiter shells to nonlinear Naghdi shells by means of a hierarchical approach. The additional shearing degrees of freedom are discretized by H(curl)-conforming N\'ed\'elec finite elements entailing a shear locking free method. By linearizing the models we

Boning Yu, Ghilles Ainouche, Manoj Singh, Bishnu Sharma

We use scanning tunneling microscopy to study the temperature evolution of the atomic-scale properties of the nearly-commensurate charge density wave (NC-CDW) state of the low-dimensional material, 1T-TaS$_2$. Our measurements at 203 K, 300 K, and 354 K, roughly spanning the temperature range of the NC-CDW state, show that while the average CDW periodicity i

Oksana Koltachykhina

For the first time in detail the influence of Orthodox Christianity on the development of cosmological ideas in Ukraine. The evolution of existing models of the birth and structure of the universe at that time was investigated. The connection between Orthodox ideas and cosmological notions in Ukraine is shown. The little-known works of the first teachers of

Haoqiang Kang, Terra Blevins, Luke Zettlemoyer

Pretrained Language Models (PLMs) learn rich cross-lingual knowledge and can be finetuned to perform well on diverse tasks such as translation and multilingual word sense disambiguation (WSD). However, they often struggle at disambiguating word sense in a zero-shot setting. To better understand this contrast, we present a new study investigating how well PLM

Muhammad Ali Jamshed, Ferheen Ayaz, Aryan Kaushik, Carlo Fischione

Unmanned aerial vehicle (UAV)-assisted communication is becoming a streamlined technology in providing improved coverage to the internet-of-things (IoT) based devices. Rapid deployment, portability, and flexibility are some of the fundamental characteristics of UAVs, which make them ideal for effectively managing emergency-based IoT applications. This paper

Chi Hoi Yip

We show that a large multiplicative subgroup of a finite field $\mathbb{F}_q$ cannot be decomposed into $A+A$ or $A+B+C$ nontrivially. We also find new families of multiplicative subgroups that cannot be decomposed as the sum of two sets nontrivially. In particular, our results extensively generalize the results of S\'{a}rk\"{o}zy and Shkredov on the additiv

Akhil Anil Rajput, Yuqin Jiang, Sanjay Nayak, Ali Mostafavi

Effective climate mitigation strategies in cities rely on understanding and mapping urban carbon footprints. One significant source of carbon is a product of lifestyle choices and travel behaviors of urban residents. Although previous research addressed consumption- and home-related footprints, activity-based footprints of urban dwellers have garnered less a

Steven A. Grosz, Anil K. Jain

One of the most challenging problems in fingerprint recognition continues to be establishing the identity of a suspect associated with partial and smudgy fingerprints left at a crime scene (i.e., latent prints or fingermarks). Despite the success of fixed-length embeddings for rolled and slap fingerprint recognition, the features learned for latent fingerpri

Kamaljyoti Nath, Xuhui Meng, Daniel J Smith, George Em Karniadakis

This paper presents a physics-informed neural network (PINN) approach for monitoring the health of diesel engines. The aim is to evaluate the engine dynamics, identify unknown parameters in a "mean value" model, and anticipate maintenance requirements. The PINN model is applied to diesel engines with a variable-geometry turbocharger and exhaust gas recircula