April 2023 arXiv papers — page 134

Zhi-Qi Cheng, Qi Dai, Siyao Li, Jingdong Sun

Charts are a powerful tool for visually conveying complex data, but their comprehension poses a challenge due to the diverse chart types and intricate components. Existing chart comprehension methods suffer from either heuristic rules or an over-reliance on OCR systems, resulting in suboptimal performance. To address these issues, we present ChartReader, a u

Yue Guan, Daigo Shishika, Jason R. Marden, Michael Dorothy

This work introduces the dynamic Defender-Attacker Blotto (dDAB) game, extending the classical static Blotto game to a dynamic resource allocation setting over graphs. In the dDAB game, a defender is required to maintain numerical superiority against attacker resources across a set of key nodes in a connected graph. The engagement unfolds as a discrete-time

Jackson Bunting, Takuya Ura

Many estimators of dynamic discrete choice models with persistent unobserved heterogeneity have desirable statistical properties but are computationally intensive. In this paper we propose a method to quicken estimation for a broad class of dynamic discrete choice problems by exploiting semiparametric index restrictions. Specifically, we propose an estimator

Thomas A. Trainor

Nuclear modification factors (NMFs) are spectrum ratios rescaled by an estimate of the number of binary N-N collisions $N_{bin}$ within an A-B collision. NMFs from more-central A-A collisions have been interpreted to indicate formation of a quark-gluon plasma (QGP) when compared with results from control $p$-A or $d$-A collisions. However, subsequent analyse

Joerg Jaeckel, Valentina Montoya, Cedric de Jonge

In this note we look at the time evolution of signals in axion dark matter experiments from a quantum perspective. Our aim is not to contribute new results to the general discussion of the quantum/classical connection (which we do not) but rather to slightly illuminate the specific case of axion experiments. From the classical perspective one expects a signa

Bertin Many Manda, Vassos Achilleos, Olivier Richoux, Charalampos Skokos

We numerically investigate the characteristics of the long-time dynamics of a single-site wave-packet excitation in a disordered and nonlinear Su-Schrieffer-Heeger model. In the linear regime, as the parameters controlling the topology of the system are varied, we show that the transition between two different topological phases is preceded by an anomalous d

Tsz On Mario Chan

The "qualitative" extension theorem of Demailly guarantees existence of holomorphic extensions of holomorphic sections on some subvariety under certain positive-curvature assumption, but that comes without any estimate of the extensions, especially when the singular locus of the subvariety is non-empty and the holomorphic section to be extended does

Brandon Theodorou, Cao Xiao, Jimeng Sun

Synthetic electronic health records (EHRs) that are both realistic and preserve privacy can serve as an alternative to real EHRs for machine learning (ML) modeling and statistical analysis. However, generating high-fidelity and granular electronic health record (EHR) data in its original, highly-dimensional form poses challenges for existing methods due to t

Tejas Srinivasan, Furong Jia, Mohammad Rostami, Jesse Thomason

Adapters present a promising solution to the catastrophic forgetting problem in continual learning. However, training independent Adapter modules for every new task misses an opportunity for cross-task knowledge transfer. We propose Improvise to Initialize (I2I), a continual learning algorithm that initializes Adapters for incoming tasks by distilling knowle

Matteo Luca Ruggiero, Davide Astesiano

Gravitoelectromagnetic analogies are somewhat ubiquitous in General Relativity, and they are often used to explain peculiar effects of Einstein's theory of gravity in terms of familiar results from classical electromagnetism. Perhaps, the best known of these analogy pertains to the similarity between the equations of electromagnetism and those of the lineari

Richard G. Forbes

This work concerns studies of field electron emission (FE) from large area emitters. It discusses--and where possible corrects--several literature weaknesses related to the analysis of experimental current-voltage data and related emitter characterization, using a recent paper in Applied Surface Science to exemplify these weaknesses. One weakness, not detect

Marco Barone, Nicolás Caro-Montoya, Eudes Naziazeno

We prove that arithmetic is interpretable in any indecomposable polynomial ring (in any set of variables), and in addition we provide an alternative uniform proof of undecidability for all members in this class of rings.

John Byrne, Michael Tait

We study the function $H_n(C_{2k})$, the maximum number of Hamilton paths such that the union of any pair of them contains $C_{2k}$ as a subgraph. We give upper bounds on this quantity for $k\ge 3$, improving results of Harcos and Solt\'esz, and we show that if a conjecture of Ustimenko is true then one additionally obtains improved upper bounds for all $k\g

Bokui Shen, Xinchen Yan, Charles R. Qi, Mahyar Najibi

Modeling the 3D world from sensor data for simulation is a scalable way of developing testing and validation environments for robotic learning problems such as autonomous driving. However, manually creating or re-creating real-world-like environments is difficult, expensive, and not scalable. Recent generative model techniques have shown promising progress t

Dong Huo, Jian Wang, Yiming Qian, Yee-Hong Yang

This paper tackles spectral reflectance recovery (SRR) from RGB images. Since capturing ground-truth spectral reflectance and camera spectral sensitivity are challenging and costly, most existing approaches are trained on synthetic images and utilize the same parameters for all unseen testing images, which are suboptimal especially when the trained models ar

William A. Callahan, Edwin Supple, David Ginley, Michael Sanders

Beta gallium oxide ($\beta$-Ga$_2$O$_3$) shows significant promise in the high-temperature, high-power, and sensing electronics applications. However, long-term stable metallization layers for Ohmic contacts at high temperature present unique thermodynamic challenges. The current most common Ohmic contact design based on 20 nm of Ti has been repeatedly demon

Ke Chen, Gordon Wichern, François G. Germain, Jonathan Le Roux

In spite of the progress in music source separation research, the small amount of publicly-available clean source data remains a constant limiting factor for performance. Thus, recent advances in self-supervised learning present a largely-unexplored opportunity for improving separation models by leveraging unlabelled music data. In this paper, we propose a s

B. N. J. Persson

When a body is exposed to external forces large local stresses may occur at the surface because of surface roughness. Surface stress concentration is important for many applications and in particular for fatigue due to pulsating external forces. For randomly rough surfaces I calculate the probability distribution of surface stress in response to a uniform ex

Sushant S. Mahajan, Xudong Sun, Junwei Zhao

Using time-distance local helioseismology flow maps within 1 Mm of the solar photosphere, we detect inflows toward activity belts that contribute to solar cycle scale variations in near-surface meridional flow. These inflows stretch out as far as 30 degrees away from active region centroids. If active region neighborhoods are excluded, the solar cycle scale

Addi Ait-Mlouk, Sadi Alawadi, Salman Toor, Andreas Hellander

Chatbots are mainly data-driven and usually based on utterances that might be sensitive. However, training deep learning models on shared data can violate user privacy. Such issues have commonly existed in chatbots since their inception. In the literature, there have been many approaches to deal with privacy, such as differential privacy and secure multi-par

Michela Mancini, Timothy Duff, Anton Leykin, John A. Christian

Initial orbit determination (IOD) from line-of-sight (i.e., bearing) measurements is a classical problem in astrodynamics. Indeed, there are many well-established methods for performing the IOD task when given three line-of-sight observations at known times. Interestingly, and in contrast to these existing methods, concepts from algebraic geometry may be use

Xiao Li, Mohsen Lesani

In contrast to proof-of-work replication, Byzantine quorum systems maintain consistency across replicas with higher throughput modest energy consumption, and deterministic liveness guarantees. If complemented with heterogeneous trust and open membership, they have the potential to serve as blockchains backbone. This paper presents a general model of heteroge

Catherine Leroux, Alexandre Blais

For $\cos(2\theta)$ qubits based on voltage-controlled semiconductor nanowire Josephson junctions we introduce a single-qubit $Z$ gate inspired by the noise-bias preserving gate of the Kerr-cat qubit. This scheme relies on a $\pi$ rotation in phase space via a beamsplitter-like transformation between a qubit and ancilla qubit. The rotation is implemented by

Parag Khanna, Mårten Björkman, Christian Smith

Handovers are basic yet sophisticated motor tasks performed seamlessly by humans. They are among the most common activities in our daily lives and social environments. This makes mastering the art of handovers critical for a social and collaborative robot. In this work, we present an experimental study that involved human-human handovers by 13 pairs, i.e., 2

Melanija Mitrovic, Mahouton Norbert Hounkonnou, Paula Catarino

This chapter aims to provide a clear and understandable picture of constructive semigroups with apartness in Bishop's style of constructive mathematics, BISH. Our theory is partly inspired by the classical case, but it is distinguished from it in two significant aspects: we use intuitionistic logic rather than classical throughout; our work is based on the n

Fan Ge

We prove asymptotics for real moments of the logarithmic derivative of characteristic polynomials evaluated at $1-\frac{a}{N}$ in unitary, even orthogonal, and symplectic ensembles, where $a>0$ and $a=o(1)$ as the size $N$ of the matrix goes to infinity. Previously, such asymptotics were known only for integer moments (in the unitary ensemble by the work of

Vanshali Sharma, M. K. Bhuyan, Pradip K. Das

Various artifacts, such as ghost colors, interlacing, and motion blur, hinder diagnosing colorectal cancer (CRC) from videos acquired during colonoscopy. The frames containing these artifacts are called uninformative frames and are present in large proportions in colonoscopy videos. To alleviate the impact of artifacts, we propose an adversarial network base

Stéphane Launois, Samuel A. Lopes, Alexandra Rogers

This paper extends an algorithm and canonical embedding by Cauchon to a large class of quantum algebras. It applies to iterated Ore extensions over a field satisfying some suitable assumptions which cover those of Cauchon's original setting but also allows for roots of unity. The extended algorithm constructs a quantum affine space $A'$ from the original qua

Nathaniel Chodosh, Deva Ramanan, Simon Lucey

Popular benchmarks for self-supervised LiDAR scene flow (stereoKITTI, and FlyingThings3D) have unrealistic rates of dynamic motion, unrealistic correspondences, and unrealistic sampling patterns. As a result, progress on these benchmarks is misleading and may cause researchers to focus on the wrong problems. We evaluate a suite of top methods on a suite of r

Anita Verma, Denis Golež, Oleg Yu. Gorobtsov, Kelson Kaj

Technology moves towards ever faster switching between different electronic and magnetic states of matter. Manipulating properties at terahertz rates requires accessing the intrinsic timescales of electrons (femtoseconds) and associated phonons (10s of femtoseconds to few picoseconds), which is possible with short-pulse photoexcitation. Yet, in many Mott ins

Lei Jin

We introduce a conservational and constitutive framework for a closed and isothermal two-phase material system consisting of a deformable porous solid matrix and a fully saturating, single-phase, and compressible pore fluid without inter-phase mass exchange. We re-derive a generalized fluid mass balance law using fundamental transport rules. We also summariz

Alec Diaz-Arias, Dmitriy Shin

Recently, fully-transformer architectures have replaced the defacto convolutional architecture for the 3D human pose estimation task. In this paper we propose \textbf{\textit{ConvFormer}}, a novel convolutional transformer that leverages a new \textbf{\textit{dynamic multi-headed convolutional self-attention}} mechanism for monocular 3D human pose estimation

Ignavier Ng, Biwei Huang, Kun Zhang

This paper investigates in which cases continuous optimization for directed acyclic graph (DAG) structure learning can and cannot perform well and why this happens, and suggests possible directions to make the search procedure more reliable. Reisach et al. (2021) suggested that the remarkable performance of several continuous structure learning approaches is

Max S. New, Eric Giovannini, Daniel R. Licata

We present a gradually typed language, GrEff, with effects and handlers that supports migration from unchecked to checked effect typing. This serves as a simple model of the integration of an effect typing discipline with an existing effectful typed language that does not track fine-grained effect information. Our language supports a simple module system to

Siyi Guo, Negar Mokhberian, Kristina Lerman

Language models can be trained to recognize the moral sentiment of text, creating new opportunities to study the role of morality in human life. As interest in language and morality has grown, several ground truth datasets with moral annotations have been released. However, these datasets vary in the method of data collection, domain, topics, instructions fo

Cooper Dix, Brandon Matthews, Ohad Shemmer, Michael S. Brotherton

The most reliable single-epoch supermassive black hole mass ($M_{\rm BH}$) estimates in quasars are obtained by using the velocity widths of low-ionization emission lines, typically the H$\beta$ $\lambda4861$ line. Unfortunately, this line is redshifted out of the optical band at $z\approx1$, leaving $M_{\rm BH}$ estimates to rely on proxy rest-frame ultravi

Kaan Gokcesu, Hakan Gokcesu

This paper focuses on optimal unimodal transformation of the score outputs of a univariate learning model under linear loss functions. We demonstrate that the optimal mapping between score values and the target region is a rectangular function. To produce this optimal rectangular fit for the observed samples, we propose a sequential approach that can its est

Ehsan Zabardast, Javier Gonzalez-Huerta, Francis Palma, Panagiota Chatzipetrou

Software development organisations aim to stay effective and efficient amid growing system complexity. To address this, they often form small teams focused on separate components that can be independently developed, tested, and deployed. Aligning architecture with organisational structures is crucial for effective communication and collaboration, reducing co

Rafael Brahm, Solène Ulmer-Moll, Melissa J. Hobson, Andrés Jordán

We report the discovery and orbital characterization of three new transiting warm giant planets. These systems were initially identified as presenting single transit events in the light curves generated from the full frame images of the Transiting Exoplanet Survey Satellite (TESS). Follow-up radial velocity measurements and additional light curves were used

Neelesh Mungoli

In this paper, we present an Adaptive Ensemble Learning framework that aims to boost the performance of deep neural networks by intelligently fusing features through ensemble learning techniques. The proposed framework integrates ensemble learning strategies with deep learning architectures to create a more robust and adaptable model capable of handling comp

Akkamahadevi Hanni, Andrew Boateng, Yu Zhang

Human expectations arise from their understanding of others and the world. In the context of human-AI interaction, this understanding may not align with reality, leading to the AI agent failing to meet expectations and compromising team performance. Explicable planning, introduced as a method to bridge this gap, aims to reconcile human expectations with the

Krishna Kumar

The widespread adoption of large language models (LLMs), such as OpenAI's ChatGPT, could revolutionize various industries, including geotechnical engineering. However, GPT models can sometimes generate plausible-sounding but false outputs, leading to hallucinations. In this article, we discuss the importance of prompt engineering in mitigating these risks an

Neelesh Mungoli

In recent years, deep learning models have demonstrated remarkable success in various domains, such as computer vision, natural language processing, and speech recognition. However, the generalization capabilities of these models can be negatively impacted by the limitations of their feature fusion techniques. This paper introduces an innovative approach, Ad

Samidh Pal

This study delves into the origins of excess capacity by examining the reactions of capital, labor, and capital intensity. To achieve this, we have employed a novel three-layered production function model, estimating the elasticity of substitution between capital and labor as a nested layer, alongside capital intensity, for all industry groups. We have then

Harel Yadid, Almog Algranti, Mark Levin, Ayal Taitler

The drum kit, which has only been around for around 100 years, is a popular instrument in many music genres such as pop, rock, and jazz. However, the road to owning a kit is expensive, both financially and space-wise. Also, drums are more difficult to move around compared to other instruments, as they do not fit into a single bag. We propose a no-drums appro

Xiaoliang Li, Kongyan Chen, Wei Niu, Bo Huang

Since Kopel's duopoly model was proposed about three decades ago, there are almost no analytical results on the equilibria and their stability in the asymmetric case. The first objective of our study is to fill this gap. This paper analyzes the asymmetric duopoly model of Kopel analytically by using several tools based on symbolic computations. We discuss th

Thanh-Dat Truong, Ngan Le, Bhiksha Raj, Jackson Cothren

Although Domain Adaptation in Semantic Scene Segmentation has shown impressive improvement in recent years, the fairness concerns in the domain adaptation have yet to be well defined and addressed. In addition, fairness is one of the most critical aspects when deploying the segmentation models into human-related real-world applications, e.g., autonomous driv

Rena Li, Sara Kingsley, Chelsea Fan, Proteeti Sinha

Recent years have witnessed an interesting phenomenon in which users come together to interrogate potentially harmful algorithmic behaviors they encounter in their everyday lives. Researchers have started to develop theoretical and empirical understandings of these user driven audits, with a hope to harness the power of users in detecting harmful machine beh

Valter Moretti

I rigorously analyze a proposal, introduced by D.R.Terno, about a spatial localization observable for a Klein-Gordon massive real particle in terms of a Poincar\'e-covariant family of POVMs. I prove that these POVMs are actually a kinematic deformation of the Newton-Wigner PVMs. The first moment of one of these POVMs however exactly coincides with a restrict

Chris Lambie-Hanson

Motivated by two open questions about two-cardinal tree properties, we introduce and study generalized narrow system properties. The first of these questions asks whether the strong tree property at a regular cardinal $\kappa \geq \omega_2$ implies the Singular Cardinals Hypothesis ($\mathsf{SCH}$) above $\kappa$. We show here that a certain narrow system pr

Ke Wang, Han Fu, K. Levin

In cosmological evolution, it is the homogeneous scalar field (inflaton) that drives the universe to expand isotropically and to generate standard model particles. However, to simulate cosmology, atomic gas research has focused on the dynamics of Bose-Einstein condensates (BEC) with continuously applied forces. In this paper we argue a complementary approach

Razvan C. Fetecau, Hui Huang, Jinniao Qiu

We investigate a general class of models for swarming/self-collective behaviour in domains with boundaries. The model is expressed as a stochastic system of interacting particles subject to both reflecting boundary condition and common environmental noise. We rigorously derive its corresponding macroscopic mean-field equation, which is a new type of stochast

Justin K. Yim, Jiming Ren, David Ologan, Selvin Garcia Gonzalez

Entanglements like vines and branches in natural settings or cords and pipes in human spaces prevent mobile robots from accessing many environments. Legged robots should be effective in these settings, and more so than wheeled or tracked platforms, but naive controllers quickly become entangled and stuck. In this paper we present a method for proprioception

Alonso S. Castellanos, Erik A. R. Mendoza, Luciane Quoos

We determine the Weierstrass semigroup at one and two totally ramified places in a Kummer extension defined by the affine equation $y^{m}=\prod_{i=1}^{r} (x-\alpha_i)^{\lambda_i}$ over $K$, the algebraic closure of $\mathbb{F}_q$, where $\alpha_1, \dots, \alpha_r\in K$ are pairwise distinct elements, and $\gcd(m, \sum_{i=1}^{r}\lambda_i)=1$. For an arbitrary

Mingwei Xu, Samuel W. K. Wong, Peijun Sang

Inferring the parameters of ordinary differential equations (ODEs) from noisy observations is an important problem in many scientific fields. Currently, most parameter estimation methods that bypass numerical integration tend to rely on basis functions or Gaussian processes to approximate the ODE solution and its derivatives. Due to the sensitivity of the OD

Mohamed Behery, Gerhard Lakemeyer

The World Wide Lab (WWL) connects the Digital Shadows (DSs) of processes, products, companies, and other entities allowing the exchange of information across company boundaries. Since DSs are context- and purpose-specific representations of a process, as opposed to Digital Twins (DTs) which offer a full simulation, the integration of a process into the WWL r

Erika M. Holmbeck, Jennifer Barnes, Kelsey A. Lund, Trevor M. Sprouse

As LIGO-Virgo-KAGRA enters its fourth observing run, a new opportunity to search for electromagnetic counterparts of compact object mergers will also begin. The light curves and spectra from the first "kilonova" associated with a binary neutron star binary (NSM) suggests that these sites are hosts of the rapid neutron capture ("$r$") process. However, it is

Mehrdad Ghadiri, Richard Peng, Santosh S. Vempala

We analyze the bit complexity of efficient algorithms for fundamental optimization problems, such as linear regression, $p$-norm regression, and linear programming (LP). State-of-the-art algorithms are iterative, and in terms of the number of arithmetic operations, they match the current time complexity of multiplying two $n$-by-$n$ matrices (up to polylogar

Eske M. Pedersen, Christopher W. Stubbs

Various models of modified gravity invoke ``screening'' mechanisms that are sensitive to the value of the local gravitational potential. This could have observable consequences for galaxies. These consequences might be seen by comparing two proxies for galaxy mass -- their luminosity and their internal kinematics -- as a function of local galaxy density. Mot

Joe Yue-Hei Ng, Kevin McCloskey, Jian Cui, Vincent R. Meijer

Contrails (condensation trails) are line-shaped ice clouds caused by aircraft and are likely the largest contributor of aviation-induced climate change. Contrail avoidance is potentially an inexpensive way to significantly reduce the climate impact of aviation. An automated contrail detection system is an essential tool to develop and evaluate contrail avoid

S. I. Kruglov

The process of the Joule-Thomson adiabatic expansion within RNED-AdS spacetime is investigated. The isenthalpic P-T diagrams and the inversion temperature were depicted. The inversion temperature depends on the magnetic charge and RNED coupling constant of black holes. When the Joule-Thomson coefficient vanishes, cooling-heating phase transition occurs. We c

Satoru Hayami, Hiroaki Kusunose

We propose a chiral charge (electric toroidal monopole) as the hidden order parameter in URu$_{2}$Si$_{2}$, which satisfies all the symmetry conditions accumulated by many experimental and theoretical efforts since its discovery. By using the minimal effective $d$-$f$ hybridized model in the itinerant picture, we demonstrate expected cross-correlated phenome

Rishi Ramkannan, Gerben I. Beintema, Roland Tóth, Maarten Schoukens

The SUBNET neural network architecture has been developed to identify nonlinear state-space models from input-output data. To achieve this, it combines the rolled-out nonlinear state-space equations and a state encoder function, both parameterised as neural networks The encoder function is introduced to reconstruct the current state from past input-output da

Mykhailo Tataryn, Mykola Stetsko

Static black hole with the Power Maxwell invariant (PMI), Born-Infeld (BI), logarithmic (LN), exponential (EN) electromagnetic fields in three-dimensional spacetime with cosmological constant was studied. It was shown that the LN and EN fields represent the Born-Infeld type of nonlinear electrodynamics. It the framework of General Relativity the exact soluti

Alexis-Tzianni Charalampopoulos, Shixuan Zhang, Bryce Harrop, Lai-yung Ruby Leung

This work presents a systematic framework for improving the predictions of statistical quantities for turbulent systems, with a focus on correcting climate simulations obtained by coarse-scale models. While high resolution simulations or reanalysis data are available, they cannot be directly used as training datasets to machine learn a correction for the coa

Esra Kendir Tekgül, Bülend Ortaç

A rapid and efficient photo-bleaching process was demonstrated with a high-energy nanosecond pulse to recover existing and/or revealed color centers on 10 kGy Gamma-irradiated Yb-doped optical fiber. Multi-mJ pulsed laser based on an optical parametric amplifier system operating at wavelengths of 532 nm, 680 nm and 793 nm was used. The photo-bleaching perfor

Leonardo Martinelli, Krzysztof Wohlfeld, Jonathan Pelliciari, Riccardo Arpaia

We have investigated the 3d orbital excitations in CaCuO2 (CCO), Nd2CuO4 (NCO), and La2CuO4 (LCO) using high-resolution resonant inelastic x-ray scattering. In LCO they behave as well-localized excitations, similarly to several other cuprates. On the contrary, in CCO and NCO the dxy orbital clearly disperse, pointing to a collective character of this excitat

A. J. Macleod, J. P. Edwards, T. Heinzl, B. King

When photons propagate in vacuum they may fluctuate into matter pairs thus allowing the vacuum to be polarised. This linear effect leads to charge screening and renormalisation. When exposed to an intense background field a nonlinear effect can arise when the vacuum is polarised by higher powers of the background. This nonlinearity breaks the superposition p

Pablo Valverde, Jaime Fernandez, Edwin Buenaño, Juan Carlos González-Avella

We investigate an agent-based model for the emergence of corruption in public contracts. There are two types of agents: business people and public servants. Both business people and public servants can adopt two strategies: corrupt or honest behavior. Interactions between business people and public servants take place through defined payoff rules. Either typ

Sayantan Dutta, Reza Farhadifar, Wen Lu, Gokberk kabacaoglu

Life in complex systems, such as cities and organisms, comes to a standstill when global coordination of mass, energy, and information flows is disrupted. Global coordination is no less important in single cells, especially in large oocytes and newly formed embryos, which commonly use fast fluid flows for dynamic reorganization of their cytoplasm. Here, we c

Amine Bouali, Himanshu Chaudhary, Amritansh Mehrotra, S. K. J. Pacif

In this paper, a well-motivated parametrization of the Hubble parameter ($H$% ) is revisited that renders two models of dark energy showing some intriguing features of the late-time accelerating Universe. A general quintessence field is considered as a source of dark energy. We have obtained tighter constraints using recently updated cosmic observational dat

Mohsen Fathi, Norman Cruz

In this study, we focus on a static spherically symmetric $f(R)$ black hole spacetime characterized by a linear dark matter-related parameter. Our investigation delves into understanding the influence of different assumed values of this parameter on the observable characteristics of the black hole. To fulfill this task, we investigate the light deflection an

Peiyao Wang, Haibin Ling

Fully supervised action segmentation works on frame-wise action recognition with dense annotations and often suffers from the over-segmentation issue. Existing works have proposed a variety of solutions such as boundary-aware networks, multi-stage refinement, and temporal smoothness losses. However, most of them take advantage of frame-wise supervision, whic

Iwona Chlebicka, Krzysztof Łatuszyński, Błażej Miasojedow

Gibbs samplers are preeminent Markov chain Monte Carlo algorithms used in computational physics and statistical computing. Yet, their most fundamental properties, such as relations between convergence characteristics of their various versions, are not well understood. In this paper we prove the solidarity of their spectral gaps: if any of the random scan or

David M. Berry

In order to legitimate and defend democratic politics under conditions of computational capital, my aim is to contribute a notion of what I am calling explanatory publics. I will explore what is at stake when we question the social and political effects of the disruptive technologies, networks and values that are hidden within the "black boxes" of computatio

Joerg Drechsler, Anna-Carolina Haensch

The idea to generate synthetic data as a tool for broadening access to sensitive microdata has been proposed for the first time three decades ago. While first applications of the idea emerged around the turn of the century, the approach really gained momentum over the last ten years, stimulated at least in parts by some recent developments in computer scienc

Leo Pasquazzi

In this work I test two calibration algorithms for the eSSVI volatility surface. The two algorithms are (i) the robust calibration algorithm proposed in Corbetta et al. (2019) and (ii) the calibration algorithm in Mingone (2022). For the latter I considered two types of weights in the objective function. I fitted 108 end-of-month SPXW options chains from the

Eder M. Correa

In this paper, we show that the deformed Hermitian Yang-Mills (dHYM) equation on a rational homogeneous variety, equipped with any invariant K\"{a}hler metric, always admits a solution. In particular, we describe the Lagrangian phase, with respect to any invariant K\"{a}hler metric, of every closed invariant $(1,1)$-form in terms of Lie theory. Building on t

Krzysztof M. Graczyk, Dawid Strzelczyk, Maciej Matyka

We adopt convolutional neural networks (CNN) to predict the basic properties of the porous media. Two different media types are considered: one mimics the sand packings, and the other mimics the systems derived from the extracellular space of biological tissues. The Lattice Boltzmann Method is used to obtain the labeled data necessary for performing supervis

Christopher Salls, Chani Jindal, Jake Corina, Christopher Kruegel

Fuzzing has become a commonly used approach to identifying bugs in complex, real-world programs. However, interpreters are notoriously difficult to fuzz effectively, as they expect highly structured inputs, which are rarely produced by most fuzzing mutations. For this class of programs, grammar-based fuzzing has been shown to be effective. Tools based on thi

Ferhat Erata, Ruzica Piskac, Victor Mateu, Jakub Szefer

Although cryptographic algorithms may be mathematically secure, it is often possible to leak secret information from the implementation of the algorithms. Timing and power side-channel vulnerabilities are some of the most widely considered threats to cryptographic algorithm implementations. Timing vulnerabilities may be easier to detect and exploit, and all

Mike Wong, Murali Ramanujam, Guha Balakrishnan, Ravi Netravali

Camera orientations (i.e., rotation and zoom) govern the content that a camera captures in a given scene, which in turn heavily influences the accuracy of live video analytics pipelines. However, existing analytics approaches leave this crucial adaptation knob untouched, instead opting to only alter the way that captured images from fixed orientations are en

David E. Ruiz-Guirola, Onel L. A. Lopez, Samuel Montejo-Sanchez, Richard Demo Souza

Prolonging the lifetime of massive machine-type communication (MTC) networks is key to realizing a sustainable digitized society. Great energy savings can be achieved by accurately predicting MTC traffic followed by properly designed resource allocation mechanisms. However, selecting the proper MTC traffic predictor is not straightforward and depends on accu

Hossam O. Ahmed

Many overall safety factors need to be considered in the next generation of Urban Air Mobility (UAM) systems and addressing these can become the anchor point for such technology to reach consent for worldwide application. On the other hand, fulfilling the safety requirements from an exponential increase of prolific UAM systems, is extremely complicated, and

Michael Smith, Frank Ferrie

As deep learning-based computer vision algorithms continue to advance the state of the art, their robustness to real-world data continues to be an issue, making it difficult to bring an algorithm from the lab to the real world. Ensemble-based uncertainty estimation approaches such as Monte Carlo Dropout have been successfully used in many applications in an

Wojciech Broniowski, Vanamali Shastry, Enrique Ruiz Arriola

We analyze off-shell effects in the generalized parton distributions (GPDs) of the pion in the context of the Sullivan electroproduction process, as well as the corresponding half-off-shell electromagnetic and gravitational form factors. We illustrate our general results within a chiral quark model, where the off-shell effects show up at a significant level,

Yueying Ni, Shy Genel, Daniel Anglés-Alcázar, Francisco Villaescusa-Navarro

We present CAMELS-ASTRID, the third suite of hydrodynamical simulations in the Cosmology and Astrophysics with MachinE Learning (CAMELS) project, along with new simulation sets that extend the model parameter space based on the previous frameworks of CAMELS-TNG and CAMELS-SIMBA, to provide broader training sets and testing grounds for machine-learning algori

Poonam Choudhary, Bheemsehan Gurjar, Dipankar Chakrabarti, Asmita Mukherjee

The energy-momentum tensor (EMT) and corresponding gravitational form factors (GFFs) provide us information about the internal structure like spin, mass and spatial densities of the proton. The Druck gravitational (D-term) form factor is related to the mechanical stability of the proton and gives information about the spatial distributions of the forces insi

Zhongwei Yang

In this paper, we study the emptiness/nonemptiness and the dimension formulas of affine Deligne-Lusztig varieties for $Sp_4(L)$. We mainly calculate the degree of class polynomials for the Iwahori-Hecke algebra of type $\widetilde{C}_2$. Then, give an explicit description on the emptiness/nonemptiness and dimension formulas of affine Deligne-Lusztig varietie

Arvin Ravanpak, Golnaz Farpour Fadakar

The main properties of the logamediate inflation driven by a non-canonical scalar field in the framework of DGP braneworld gravity are investigated. Considering high energy conditions we calculate the slow-roll parameters, analytically. Then, we deal with the perturbation theory and calculate the most important respective parameters such as the scalar spectr

Eduard Eiben, Tomohiro Koana, Magnus Wahlström

We introduce determinantal sieving, a new, remarkably powerful tool in the toolbox of algebraic FPT algorithms. Given a polynomial $P(X)$ on a set of variables $X=\{x_1,\ldots,x_n\}$ and a linear matroid $M=(X,\mathcal{I})$ of rank $k$, both over a field $\mathbb{F}$ of characteristic 2, in $2^k$ evaluations we can sieve for those terms in the monomial expan

Yuanyuan Luan, Roger S. Zoh, Sneha Jadhav, Lan Xue

While extensive work has been done to correct for biases due to measurement error in scalar-valued covariates prone to errors in generalized linear regression models, limited work has been done to address biases associated with functional covariates prone to errors or the combination of scalar and functional covariates prone to errors in these models. We pro

Maria Kuznetsova

In the paper, we study the problem of recovering the Sturm--Liouville operator with frozen argument from its spectrum and additional data. For this inverse problem, we establish a substantial property of the uniform stability, which consists in that the potential depends Lipschitz continuously on the input data.

Qijie Shen, Hong Wen, Jing Zhang, Qi Rao

Estimating Click-Through Rate (CTR) is a vital yet challenging task in personalized product search. However, existing CTR methods still struggle in the product search settings due to the following three challenges including how to more effectively extract users' short-term interests with respect to multiple aspects, how to extract and fuse users' long-term i

Jacob P. Covey, Harald Weinfurter, Hannes Bernien

Quantum networks providing shared entanglement over a mesh of quantum nodes will revolutionize the field of quantum information science by offering novel applications in quantum computation, enhanced precision in networks of sensors and clocks, and efficient quantum communication over large distances. Recent experimental progress with individual neutral atom

Mehdi Haghshenas, Parisa Ramezani, Maurizio Magarini, Emil Björnson

A reconfigurable intelligent surface (RIS) is a holographic MIMO surface composed of a large number of passive elements that can induce adjustable phase shifts to the impinging waves. By creating virtual line-of-sight (LOS) paths between the transmitter and the receiver, RIS can be a game changer for millimeter-wave (mmWave) communication systems that typica

Styliani I. Kampezidou, Justin Romberg, Kyriakos G. Vamvoudakis, Dimitri N. Mavris

In this work, a novel Stackelberg game theoretic framework is proposed for trading energy bidirectionally between the demand-response (DR) aggregator and the prosumers. This formulation allows for flexible energy arbitrage and additional monetary rewards while ensuring that the prosumers' desired daily energy demand is met. Then, a scalable (linear with the

Yuzo Ishikawa, Ben Wang, Nadia L. Zakamska, Gordon T. Richards

The census of obscured quasar populations is incomplete, and remains a major unsolved problem, especially at higher redshifts, where we expect a greater density of galaxy formation and quasar activity. We present Gemini GNIRS near-infrared spectroscopy of 24 luminous obscured quasar candidates from the Sloan Digital Sky Survey's Stripe 82 region. The targets

Stephen Parsons, C. Seth Parker, Christy Chapman, Mami Hayashida

We present a complete software pipeline for revealing the hidden texts of the Herculaneum papyri using X-ray CT images. This enhanced virtual unwrapping pipeline combines machine learning with a novel geometric framework linking 3D and 2D images. We also present EduceLab-Scrolls, a comprehensive open dataset representing two decades of research effort on thi

Jan Bartsch, Patrik Knopf, Stefania Scheurer, Jörg Weber

The Vlasov-Poisson system describes the time evolution of a plasma in the so-called collisionless regime. The investigation of a high-temperature plasma that is influenced by an exterior magnetic field is one of the most significant aspects of thermonuclear fusion research. In this paper, we formulate and analyze a kinetic optimal control problem for the Vla