April 2024 arXiv papers — page 5

Vinzenz Tütsch, Zhiyu He, Florian Dörfler, Kenan Zhang

This paper develops an adaptive traffic control policy inspired by Maximum Pressure (MP) while imposing coordination across intersections. The proposed Coordinated Maximum Pressure-plus-Penalty (CMPP) control policy features a local objective for each intersection that consists of the total pressure within the neighborhood and a penalty accounting for the qu

Pertti Saariluoma, Juhani Heinilä, Erkki Kuisma, Jaana Leikas

This paper discusses Life-Based Design (LBD) methodology within the context of designing technologies for reaching a state of solitude, the state where a person wishes to minimize her social contacts to get space or freedom.

Vincent Perrier

The aim of this article is to derive discontinuous finite elements vector spaces which can be put in a discrete de-Rham complex for which an harmonic gap property may be proven. First, discontinuous finite element spaces inspired by classical N{\'e}d{\'e}lec or Raviart-Thomas conforming space are considered, and we prove that by relaxing the normal or tangen

L. Barquín-González, S. Mateos, F. J. Carrera, I. Ordovás-Pascual

The optical spectroscopic classification of active galactic nuclei (AGN) into type 1 and type 2 can be understood in the frame of the AGN unification models. However, it remains unclear which physical properties are driving the classification into intermediate sub-types (1.0,1.2,1.5,1.8,1.9). To shed light on this issue, we present an analysis of the effect

Yucheng Hu, Yuxing Lu

Large Language Models (LLMs) have catalyzed significant advancements in Natural Language Processing (NLP), yet they encounter challenges such as hallucination and the need for domain-specific knowledge. To mitigate these, recent methodologies have integrated information retrieved from external resources with LLMs, substantially enhancing their performance ac

Trung Thanh Nguyen, Yasutomo Kawanishi, Takahiro Komamizu, Ichiro Ide

Open-vocabulary Temporal Action Detection (Open-vocab TAD) is an advanced video analysis approach that expands Closed-vocabulary Temporal Action Detection (Closed-vocab TAD) capabilities. Closed-vocab TAD is typically confined to localizing and classifying actions based on a predefined set of categories. In contrast, Open-vocab TAD goes further and is not li

Rayan Armani, Changlin Qian, Jiaxi Jiang, Christian Holz

While camera-based capture systems remain the gold standard for recording human motion, learning-based tracking systems based on sparse wearable sensors are gaining popularity. Most commonly, they use inertial sensors, whose propensity for drift and jitter have so far limited tracking accuracy. In this paper, we propose Ultra Inertial Poser, a novel 3D full

Ihab Alam, Isabelle Chalendar, Fida El Chami, Emmanuel Fricain

In this paper, we revisit the Riemann--Liouville analytic semigroup. In particular, we completely characterize the membership to the Schatten class $S^r$ on $L^2(0,1)$, as well as the membership to the class of nuclear operators on $L^p(0,1)$, $p\geq 1$, and the membership to the ideal of absolutely $r$-summing operators for any $r\geq 1$.

Thomas Nussle, Pascal Thibaudeau, Stam Nicolis

A path integral method, combined with atomistic spin dynamics simulations, has been developed to calculate thermal quantum expectation values using a classical approach. In this study, we show how to treat Hamiltonians with non-linear terms, that are relevant for describing uniaxial anisotropies and mechanical constraints. These interactions can be expressed

Christophe Villien, Anne Frassati, Bruno Flament

Pedestrian Indoor localization based on modalities available in modern smartphones have been widely studied in literature and many of the specific challenges have been addressed. However, very few approaches consider the whole problem and proposed solutions are very often evaluated under very limited scenarios. We propose a fusion engine for localization tha

Anjitha Ashokan, Chithra A

The eccentricity matrix $\epsilon(G)$, of a connected graph $G$ is obtained by retaining the maximum distance from each row and column of the distance matrix of $G$ and the other entries are assigned with 0. In this paper, we discuss the eccentricity spectrum of subdivision vertex (edge) join of regular graphs. Also, we obtain new families of graphs having i

Zesheng Liu, YoungHyun Koo, Maryam Rahnemoonfar

The mass loss of the polar ice sheets contributes considerably to ongoing sea-level rise and changing ocean circulation, leading to coastal flooding and risking the homes and livelihoods of tens of millions of people globally. To address the complex problem of ice behavior, physical models and data-driven models have been proposed in the literature. Although

Daniele Nazzari, Lukas Wind, Masiar Sistani, Dominik Mayr

Artificial neural networks (ANNs) have had an enormous impact on a multitude of sectors, from research to industry, generating an unprecedented demand for tailor-suited hardware platforms. Their training and execution is highly memory-intensive, clearly evidencing the limitations affecting the currently available hardware based on the von Neumann architectur

Yuekun Dai, Dafeng Zhang, Xiaoming Li, Zongsheng Yue

The increasing demand for computational photography and imaging on mobile platforms has led to the widespread development and integration of advanced image sensors with novel algorithms in camera systems. However, the scarcity of high-quality data for research and the rare opportunity for in-depth exchange of views from industry and academia constrain the de

Benjamin Godard, Guillaume Pineau Des Forêts, Shmuel Bialy

Context. Atomic and molecular line emissions from shocks may provide valuable information on the injection of mechanical energy in the interstellar medium (ISM), the generation of turbulence, and the processes of phase transition between the Warm Neutral Medium (WNM) and the Cold Neutral Medium (CNM).Aims. In this series of papers, we investigate the propert

Lukas Rapp, Sisi Miao, Laurent Schmalen

We propose a novel soft-aided hard-decision decoding algorithm for general product-like codes. It achieves error correcting performance similar to that of a soft-decision turbo decoder for staircase and OFEC codes, while maintaining a low complexity.

Norman Mu, Jingwei Ji, Zhenpei Yang, Nate Harada

Many existing motion prediction approaches rely on symbolic perception outputs to generate agent trajectories, such as bounding boxes, road graph information and traffic lights. This symbolic representation is a high-level abstraction of the real world, which may render the motion prediction model vulnerable to perception errors (e.g., failures in detecting

Lu Feng, Tao Han, Jing-Fei Zhang, Xin Zhang

Cosmological observations can be used to weigh neutrinos, but this method is model-dependent, with results relying on the cosmological model considered. If we consider interactions between dark energy and dark matter, the neutrino mass constraints differ from those derived under the standard model. On the contrary, gravitational wave (GW) standard siren obse

Joris P. W. Verbiest, Sarah J. Vigeland, Nataliya K. Porayko, Siyuan Chen

The stability of the spin of pulsars and the precision with which these spins can be determined, allows many unique tests of interest to physics and astrophysics. Perhaps the most challenging and revolutionary of these, is the detection of nanohertz gravitational waves. An increasing number of efforts to detect and study long-period gravitational waves by ti

Samuel Valiquette, Jean Peyhardi, Éric Marchand, Gwladys Toulemonde

In this article, we develop a new class of multivariate distributions adapted for count data, called Tree P\'olya Splitting. This class results from the combination of a univariate distribution and singular multivariate distributions along a fixed partition tree. Known distributions, including the Dirichlet-multinomial, the generalized Dirichlet-multinomial

Georgios Papadopoulos, Edward Witten

By adapting previously known arguments concerning Ricci flow and the c-theorem, we give a direct proof that in a two-dimensional sigma-model with compact target space, scale invariance implies conformal invariance in perturbation theory. This argument, which applies to a general sigma-model constructed with a target space metric and B-field, is in accord wit

Luxi Chen, Zhengyi Wang, Zihan Zhou, Tingting Gao

Optimization-based approaches, such as score distillation sampling (SDS), show promise in zero-shot 3D generation but suffer from low efficiency, primarily due to the high number of function evaluations (NFEs) required for each sample and the limitation of optimization confined to latent space. This paper introduces score-based iterative reconstruction (SIR)

Laura Baudis

The DARWIN/XLZD experiment is a next-generation dark matter detector with a multi-ten-ton liquid xenon time projection chamber at its core. Its principal goal will be to explore the experimentally accessible parameter space for Weakly Interacting Massive Particles (WIMPs) in a wide mass-range, until interactions of astrophysical neutrinos will become an irre

Joao Afonso, Elvis Konjoh Selabi, Maurizio Murgia, Antonio Ravara

We propose TRAC, a tool for the specification and verification of coordinated multiparty distributed systems. Relying on finite-state machines (FSMs) where transition labels look like Hoare triples, \thetool can specify the coordination of the participants of a distributed protocol for instance an execution model akin blockchain smart contracts (SCs). In fac

Daniel Barlet, Jon Ingolfur Magnusson

In this note we show that a weakly geometrically flat map $\pi$ : M $\rightarrow$ N between pure dimensional complex spaces has the local lifting property for cycles. From this result we also deduce that, under these hypotheses, several properties of M are transferred to N.

De-Cheng Zou, Xu Yang, Meng-Yun Lai, Hyat Huang

Nonlinearly scalarized black holes are investigated in Einstein-scalar-Gauss-Bonnet (EsGB) theory with polynomial coupling functions $\zeta(\phi)$ satisfying $\zeta''(0) = 0$, where $\zeta'(\phi) = 0$ features besides $\phi=0$ solutions with constant $\phi_{\rm s} \ne 0$. We determine the threshold amplitudes for Gaussian pulses, above which Schwarzschild bl

Albertus Johannes Malan, Joel Ferguson, Michele Cucuzzella, Jacquelien M. A. Scherpen

In this paper, we consider the problem of voltage stability in DC networks containing uncertain loads with non-monotone incremental impedances and where the steady-state power availability is restricted to a subset of the buses in the network. We propose controllers for powered buses that guarantee voltage regulation and output strictly equilibrium independe

Dazhuo Qiu, Mengying Wang, Arijit Khan, Yinghui Wu

This paper introduces a new class of explanation structures, called robust counterfactual witnesses (RCWs), to provide robust, both counterfactual and factual explanations for graph neural networks. Given a graph neural network M, a robust counterfactual witness refers to the fraction of a graph G that are counterfactual and factual explanation of the result

Mingkai Tang, Yuanhang Li, Hongji Liu, Yingbing Chen

With the expansion of the scale of robotics applications, the multi-goal multi-agent pathfinding (MG-MAPF) problem began to gain widespread attention. This problem requires each agent to visit pre-assigned multiple goal points at least once without conflict. Some previous methods have been proposed to solve the MG-MAPF problem based on Decoupling the goal Ve

Jérôme Bolte, Tam Le, Éric Moulines, Edouard Pauwels

Motivated by the extensive application of approximate gradients in machine learning and optimization, we investigate inexact subgradient methods subject to persistent additive errors. Within a nonconvex semialgebraic framework, assuming boundedness or coercivity, we establish that the method yields iterates that eventually fluctuate near the critical set at

Ismael S. S. Carrasco, Tiago J. Oliveira

Two-dimensional (2D) KPZ growth is usually investigated on substrates of lateral sizes $L_x=L_y$, so that $L_x$ and the correlation length ($\xi$) are the only relevant lengths determining the scaling behavior. However, in cylindrical geometry, as well as in flat rectangular substrates $L_x \neq L_y$ and, thus, the surfaces can become correlated in a single

Yi Huang, Ken'ichi Ohshika, Huiping Pan, Athanase Papadopoulos

This is the first paper to systematically study the earthquake metric, an asymmetric Finsler metric on Teichm{\"u}ller space introduced by Thurston. We provide proofs for several assertions of Thurston and establish new properties of this metric, among which are incompleteness, asymptotic distance to the boundary and comparisons with the Thurston metric and

S. J. Kole, Gareth P. Alexander, Ananyo Maitra, Sriram Ramaswamy

Chiral active materials display odd dynamical effects in both their elastic and viscous responses. We show that the most symmetric mesophase with two-dimensional odd elasticity in three dimensions is chiral, polar and columnar, with two-dimensional translational order in the plane perpendicular to the columns and no elastic restoring force for their relative

Sho Ueda, Xujun Ye

Early detection of fertilizer-induced stress in tomato plants is crucial for optimizing crop yield through timely management interventions. While conventional optical methods struggle to detect fertilizer stress in young leaves, these leaves contain valuable diagnostic information through their microscopic hair-like structures, particularly trichomes, which

Yixiao Wang, Xing Ji, Gang Chen, Kun Xu

The Runge--Kutta discontinuous Galerkin (RKDG) method is a high-order technique for addressing hyperbolic conservation laws, which has been refined over recent decades and is effective in handling shock discontinuities. Despite its advancements, the RKDG method faces challenges, such as stringent constraints on the explicit time-step size and reduced robustn

Jukka P. Pekola, Bayan Karimi

We discuss thermalization in a multimode quantum cavity under unitary evolution. According to general principles, an isolated system with quadratic couplings does not exhibit thermalization. However, we find that three-wave perturbation, typical for instance in superconducting Josephson systems, may lead to thermalization into a Bose-Einstein distribution of

LHCb collaboration, R. Aaij, A. S. W. Abdelmotteleb, C. Abellan Beteta

The four decays, $\Lambda_{b}^{0} \rightarrow \Sigma_c^{(*)++} D^{(*)-} K^{-}$, are observed for the first time using proton-proton collision data collected with the LHCb detector at a centre-of-mass energy of $13\,\rm{TeV}$, corresponding to an integrated luminosity of $6\,\rm{fb}^{-1}$. By considering the $\Lambda_b^0 \rightarrow \Lambda_c^{+} \overline{D}

Shisen Yue, Siyuan Song, Xinyuan Cheng, Hai Hu

Understanding the non-literal meaning of an utterance is critical for large language models (LLMs) to become human-like social communicators. In this work, we introduce SwordsmanImp, the first Chinese multi-turn-dialogue-based dataset aimed at conversational implicature, sourced from dialogues in the Chinese sitcom $\textit{My Own Swordsman}$. It includes 20

Alessio Gravina, Daniele Zambon, Davide Bacciu, Cesare Alippi

Modern graph representation learning works mostly under the assumption of dealing with regularly sampled temporal graph snapshots, which is far from realistic, e.g., social networks and physical systems are characterized by continuous dynamics and sporadic observations. To address this limitation, we introduce the Temporal Graph Ordinary Differential Equatio

Yuval Cornfeld, Ehud Lehrer, Eilon Solan

Consider a dynamic decision-making scenario where at every stage the investor has to choose between investing in one of two projects or gathering more information. At each stage, the investor may seek counsel from one of several consultants, who, for a fixed cost, provide partial information about the realized state. We explore the optimal strategy and its d

Bianka Csanaková, Ondřej Novák, Lukáš Roškot, Jiří Mužík

In this paper, we present a single crystal, KTA (potassium titanyl-arsenate, KTiOAsO$_4$) based picosecond optical parametric amplifier pumped by an in-house built 1030 nm Yb:YAG thin-disk laser, capable of tunability from 1.46 to 3.5 $\mu$m, operating at 90 kHz, with high average power in the signal and idler beams. The highest output power of 8.9 W was rea

Huy Hien Vu, Hidetaka Kamigaito, Taro Watanabe

Despite significant improvements in enhancing the quality of translation, context-aware machine translation (MT) models underperform in many cases. One of the main reasons is that they fail to utilize the correct features from context when the context is too long or their models are overly complex. This can lead to the explain-away effect, wherein the models

C. Tschudi, H. M. Schmid, M. Nowak, H. Le Coroller

We carried out very deep VLT/SPHERE imaging polarimetry of the nearby system Eps Eri based on 38.5 hours of integration time with a 600 - 900 nm broadband filter to search for polarized scattered light from a planet or from circumstellar dust using AO, coronagraphy, high precision differential polarimetry, and angular differential imaging. We have improved s

Thomas Traversié

Kuroda's translation embeds first-order classical logic into intuitionistic logic, such that a formula and its translation are equivalent in classical logic. Recently, Brown and Rizkallah extended this translation to higher-order logic. However, they showed that the translation fails in the presence of functional extensionality, and they did not prove the cl

Nicola Cavallucci, Andrea Sambusetti

We study the theory of convergence for CAT$(0)$-lattices (that is groups $\Gamma$ acting geometrically on proper, geodesically complete CAT$(0)$-spaces) and their quotients (CAT$(0)$-orbispaces). We describe some splitting and collapsing phenomena, explaining precisely how these action can degenerate to a possibly non-discrete limit action. Finally, we prove

Shuyang Han, Zhaofeng Kang, Jiang Zhu

The non-vanishing neutrino mass strongly hints the existence of right-handed neutrinos (RHNs), singlets of the standard model (SM). However, they are highly decoupled from the SM and difficult to probe. In this work, we consider the Majorana RHNs from the type-I seesaw mechanism may well mix with the heavy neutral lepton dwelling in certain vector-like lepto

Sacha Sokoloski

Bayes' rule describes how to infer posterior beliefs about latent variables given observations, and inference is a critical step in learning algorithms for latent variable models (LVMs). Although there are exact algorithms for inference and learning for certain LVMs such as linear Gaussian models and mixture models, researchers must typically develop approxi

Ziyan Chen, Jingwen He, Xinqi Lin, Yu Qiao

Blind face restoration (BFR) on images has significantly progressed over the last several years, while real-world video face restoration (VFR), which is more challenging for more complex face motions such as moving gaze directions and facial orientations involved, remains unsolved. Typical BFR methods are evaluated on privately synthesized datasets or self-c

Anh-Dung Le, Stéphane Villeneuve

In this paper, we study well-posedness of McKean-Vlasov stochastic differential equations (SDE) whose drift depends pointwisely on marginal density and satisfies a local integrability condition in time-space variables. The drift and noise coefficients are assumed to be Lipschitz continuous in distribution variable with respect to Wasserstein metric $W_p$. Ou

Luis Gerhorst, Henriette Herzog, Peter Wägemann, Maximilian Ott

High-performance IO demands low-overhead communication between user- and kernel space. This demand can no longer be fulfilled by traditional system calls. Linux's extended Berkeley Packet Filter (BPF) avoids user-/kernel transitions by just-in-time compiling user-provided bytecode and executing it in kernel mode with near-native speed. To still isolate BPF p

Damianos Iosifidis, Konstantinos Pallikaris

We study the cosmology of the complete quadratic (in torsion and nonmetricity) metric-affine gravity. Namely, we add to the scalar-curvature gravitational Lagrangian, the 17 independent quadratic (parity-even and parity-odd) torsion and nonmetricity invariants. Sticking to a homogeneous and isotropic Friedmann-Robertson-Walker spacetime and assuming a perfec

Xinwei Lee, Xinjian Yan, Ningyi Xie, Yoshiyuki Saito

Variational Quantum Eigensolver (VQE) is a quantum-classical hybrid algorithm used to estimate the ground energy of a given Hamiltonian. It consists of a parameterized quantum circuit, which the parameters are optimized using a classical optimizer. With the increasing need in solving large-scale problems in real-world applications, solving those large proble

Antoine Godichon-Baggioni, Stephane S. Robin, Laure Sansonnet

We consider the robust estimation of the parameters of multivariate Gaussian linear regression models. To this aim we consider robust version of the usual (Mahalanobis) least-square criterion, with or without Ridge regularization. We introduce two methods each considered contrast: (i) online stochastic gradient descent algorithms and their averaged versions

Xinshu Zhao, Dianshi Moses Li, Ze Zack Lai, Piper Liping Liu

Percentage coefficient (bp) has emerged in recent publications as an additional and alternative estimator of effect size for regression analysis. This paper retraces the theory behind the estimator. It's posited that an estimator must first serve the fundamental function of enabling researchers and readers to comprehend an estimand, the target of estimation.

Alex Carriero, Kim Luijken, Anne de Hond, Karel GM Moons

Risk prediction models are increasingly used in healthcare to aid in clinical decision making. In most clinical contexts, model calibration (i.e., assessing the reliability of risk estimates) is critical. Data available for model development are often not perfectly balanced with respect to the modeled outcome (i.e., individuals with vs. without the event of

Chuxiao Liu, Xiao Zhang

We show that the spherically symmetric Einstein-scalar-field equations for small slowly particle-like decaying initial data at null infinity have unique global solutions.

Dora Kreković, Petar Krivić, Ivana Podnar Žarko, Mario Kušek

The adoption of the Internet of Things (IoT) deployments has led to a sharp increase in network traffic as a vast number of IoT devices communicate with each other and IoT services through the IoT-edge-cloud continuum. This network traffic increase poses a major challenge to the global communications infrastructure since it hinders communication performance

Domingo Barrera, Salah Eddargani, María José Ibáñez, Sara Remogna

In this paper, the construction of $C^{1}$ cubic quasi-interpolants on a three-direction mesh of $\RR^{2}$ is addressed. The quasi-interpolating splines are defined by directly setting their Bernstein-B\'{e}zier coefficients relative to each triangle from point and gradient values in order to reproduce the polynomials of the highest possible degree. Moreover

Nacira Agram, Bernt Oksendal, Frank Proske, Olena Tymoshenko

In this paper, we consider a McKean-Vlasov (mean-field) stochastic partial differential equations (SPDEs) driven by a Brownian sheet. We study the propagation of chaos for a space-time Ornstein-Uhlenbeck SPDE type. Subsequently, we prove the existence and uniqueness of a nonlinear McKean-Vlasov SPDE. Finally, we establish a Fokker-Planck equation for the law

Yufeng Yang, Adrian Kneip, Charlotte Frenkel

Edge vision systems combining sensing and embedded processing promise low-latency, decentralized, and energy-efficient solutions that forgo reliance on the cloud. As opposed to conventional frame-based vision sensors, event-based cameras deliver a microsecond-scale temporal resolution with sparse information encoding, thereby outlining new opportunities for

Xiao-Feng Song, Shuang Liu, Xi-Hao Chen, Yusuf Turek

This paper delves into the crucial aspects of pointer-induced quantum decoherence and the transition between von Neumann's projective strong measurement and Aharonov's weak measurement. Both phenomena significantly impact the dynamical understanding of quantum measurement processes. Specifically, we focus on the interplay between quantum decoherence and the

Tizian Wenzel, Armin Iske

Kernel based approximation offers versatile tools for high-dimensional approximation, which can especially be leveraged for surrogate modeling. For this purpose, both "knot insertion" and "knot removal" approaches aim at choosing a suitable subset of the data, in order to obtain a sparse but nevertheless accurate kernel model. In the present work, focussing

Mariia Ignashina, Julia Ive

Current text generation models are trained using real data which can potentially contain sensitive information, such as confidential patient information and the like. Under certain conditions output of the training data which they have memorised can be triggered, exposing sensitive data. To mitigate against this risk we propose a safer alternative which sees

Maarten C. Stol, Alessandra Mileo

Neurosymbolic background knowledge and the expressivity required of its logic can break Machine Learning assumptions about data Independence and Identical Distribution. In this position paper we propose to analyze IID relaxation in a hierarchy of logics that fit different use case requirements. We discuss the benefits of exploiting known data dependencies an

Zhen Guo

Large language model pre-training has become increasingly expensive, with most practitioners relying on scaling laws to allocate compute budgets for model size and training tokens, commonly referred to as Compute-Optimal or Chinchilla Optimal. In this paper, we hypothesize a new scaling law that suggests model performance depends mostly on the amount of comp

Yifeng Huang

Evidences have suggested that counting representations are sometimes tractable even when the corresponding classification problem is almost impossible, or "wild" in a precise sense. Such counting problems are directly related to matrix counting problems, many of which are under active research. Using a general framework we formulate for such counting problem

Vinay Setty

We introduce 'FactCheck Editor', an advanced text editor designed to automate fact-checking and correct factual inaccuracies. Given the widespread issue of misinformation, often a result of unintentional mistakes by content creators, our tool aims to address this challenge. It supports over 90 languages and utilizes transformer models to assist humans in the

Kristina Mach, Hessam Roodaki, Michael Sommersperger, Nassir Navab

This paper presents an innovative approach to intraoperative Optical Coherence Tomography (iOCT) image segmentation in ophthalmic surgery, leveraging statistical analysis of speckle patterns to incorporate statistical pathology-specific prior knowledge. Our findings indicate statistically different speckle patterns within the retina and between retinal layer

Zainab Alwaisi, Simone Soderi, Rocco De Nicola

Internet of Everything (IoE) is a newly emerging trend, especially in homes. Marketing forces toward smart homes are also accelerating the spread of IoE devices in households. An obvious risk of the rapid adoption of these smart devices is that many lack controls for protecting the privacy and security of end users from attacks designed to disrupt lives and

Dhruv Shah, R. K. Shishir, Manjaree, Shreya Pithva

Perturbing the arrangements of pegs on a static Galton board can result in non-trivial stationary distributions, which in the continuum limit correspond to departure from regular gaussian behavior. Two such distributions are obtained. Further, the distributions generated for a dynamic galton board under external forcing in a general direction are obtained by

Mark B. Richardson, Stefan Loesch

The scope of this article includes the three preeminent descriptions of concentrated liquidity from Bancor (2020 and 2022), and Uniswap (2021), as well as three additional descriptions informed by trigonometric analysis of the same. The purpose of this contribution is to organize the seminal and derivative forms of this cornerstone DeFi technology, and algeb

Aleksandrs Belovs

Up to now, relatively few exponential quantum speed-ups have been achieved. Out of them, the welded tree problem (Childs, Cleve, Deotto, Farhi, Gutmann, and Spielman'2003) is one of the unusual examples, as the exponential speed-up is attained by a quantum walk. In this paper, we give a very short proof of the optimal linear hitting time for this problem by

Teng Zhou, Yongchuan Tang

Diffusion models have emerged as effective tools for generating diverse and high-quality content. However, their capability in high-resolution image generation, particularly for panoramic images, still faces challenges such as visible seams and incoherent transitions. In this paper, we propose TwinDiffusion, an optimized framework designed to address these c

Monit Sharma, Yan Jin, Hoong Chuin Lau, Rudy Raymond

Combinatorial problems are a common challenge in business, requiring finding optimal solutions under specified constraints. While significant progress has been made with variational approaches such as QAOA, most problems addressed are unconstrained (such as Max-Cut). In this study, we investigate a hybrid quantum-classical method for constrained optimization

Maria Lomaeva, Amélie Saintonge, Ilse De Looze

Star formation histories (SFHs) of galaxies are affected by a variety of factors, both external (field vs. cluster/group) and internal (presence of a bar and AGN, morphological type). In this work, we extend our previous study and apply the <SFR5>/<SFR200> metric to a sample of eleven nearby galaxies with MUSE observations. Based on a combination of H$\alpha

Chhavi Tyagi, Wenge Guo

Multi-label classification is a common challenge in various machine learning applications, where a single data instance can be associated with multiple classes simultaneously. The current paper proposes a novel tree-based method for multi-label classification using conformal prediction and multiple hypothesis testing. The proposed method employs hierarchical

James M. Cline

The IceCube collaboration has identified neutrinos of energy $\sim 10-100$ TeV from the blazar TXS 0506+056 and the active galaxy NGC 1068, which must have traveled through a dense dark matter spike surrounding the supermassive black holes that power the galactic nuclei. We use this to set new constraints on dark matter-neutrino scattering, and interpret the

Julien Houle, Valerio Faraoni

The phase space of Bianchi I universes in vacuum Brans-Dicke gravity is analyzed in terms of physical variables. The behaviour of the solutions of the field equations near the fixed points (which are solutions of Einstein gravity) is compared with basic ideas of the recent first-order thermodynamics of scalar-tensor gravity, elucidating new phenomenology.

Yan-Qing Zhu, Zhen Zheng, Giandomenico Palumbo, Z. D. Wang

We report the discovery of several classes of novel topological insulators (TIs) with hybrid-order boundary states generated from the first-order TIs with additional crystalline symmetries. Unlike the current studies on hybrid-order TIs where different-order topology arises from merging different-order TIs in various energy, {\color{red} these novel TIs exhi

Lanwei Zhang, Jamie Evans, Jingge Zhu

Compute-forward multiple access (CFMA) is a transmission strategy which allows the receiver in a multiple access channel (MAC) to first decode linear combinations of the transmitted signals and then solve for individual messages. Compared to existing MAC strategies such as joint decoding or successive interference cancellation (SIC), CFMA was shown to achiev

Harshini Gangapuram, Vidya Manian

Brain responses related to working memory originate from distinct brain areas and oscillate at different frequencies. EEG signals with high temporal correlation can effectively capture these responses. Therefore, estimating the functional connectivity of EEG for working memory protocols in different frequency bands plays a significant role in analyzing the b

Y. Estaremi, Z. Huang

In this paper we characterize quasi-contraction, stable and convergent weighted conditional type (WCT) operators on $L^p(\mu)$. Indeed we provide equivalent conditions for quasi-contraction WCT operators. Also, we prove that convergence, uniformly stability, strongly stability and weakly stability of WCT operators are equivalent. Finally we provided some con

Peter Grünwald, Tyron Lardy, Yunda Hao, Shaul K. Bar-Lev

We provide a general condition under which e-variables in the form of a simple-vs.-simple likelihood ratio exist when the null hypothesis is a composite, multivariate exponential family. Such `simple' e-variables are easy to compute and expected-log-optimal with respect to any stopping time. Simple e-variables were previously only known to exist in quite spe

Fabio Federici, Bruce Lipschultz, Gijs R. A. Akkermans, Kevin Verhaegh

Conditions similar to those at the end of the divertor leg in a tokamak were replicated in the linear plasma machine Magnum-PSI. The neutral pressure in the target chamber is then increased to cause the target to transition from an attached to a detached state. Superimposed to this steady state regime, ELM-like pulses are reproduced, resulting in a sudden in

Abdullahi Mohammad, Mahmoud Tukur Kabir, Mikko Valkama, Bo Tan

This paper presents a novel approach to achieving secure wireless communication by leveraging the inherent characteristics of wireless channels through end-to-end learning using a single-input-multiple-output (SIMO) autoencoder (AE). To ensure a more realistic signal transmission, we derive the signal model that captures all radio frequency (RF) hardware imp

Cengis Hasan, Alexandros Agapitos, David Lynch, Alberto Castagna

We present a method that addresses the pain point of long lead-time required to deploy cell-level parameter optimisation policies to new wireless network sites. Given a sequence of action spaces represented by overlapping subsets of cell-level configuration parameters provided by domain experts, we formulate throughput optimisation as Continual Reinforcement

Kota Saito

Let $ \lfloor x \rfloor $ denote the integer part of $ x $. In 1947, Mills constructed a real number $ \xi > 1 $ such that $\lfloor \xi^{3^k} \rfloor$ is always a prime number for every positive integer $k$. We define Mills' constant as the smallest real number $\xi$ satisfying this property. Determining whether this number is irrational has been a long-stan

Antonio Emanuele Cinà, Jérôme Rony, Maura Pintor, Luca Demetrio

Adversarial examples are typically optimized with gradient-based attacks. While novel attacks are continuously proposed, each is shown to outperform its predecessors using different experimental setups, hyperparameter settings, and number of forward and backward calls to the target models. This provides overly-optimistic and even biased evaluations that may

Paolo Villani, Jörg Unger, Martin Weiser

We introduce a novel adaptive Gaussian Process Regression (GPR) methodology for efficient construction of surrogate models for Bayesian inverse problems with expensive forward model evaluations. An adaptive design strategy focuses on optimizing both the positioning and simulation accuracy of training data in order to reduce the computational cost of simulati

Hikaru Shimizu, Wojciech Roga, David Elkouss, Masahiro Takeoka

Distributed quantum entanglement plays a crucial role in realizing networks that connect quantum devices. However, sharing entanglement between distant nodes by means of photons is a challenging process primary due to unavoidable losses in the linking channels. In this paper, we propose a simple loss-tolerant protocol for the Greenberger-Horne-Zeilinger stat

Ginés López-Pérez, Esteban Martínez Vañó, Abraham Rueda Zoca

We compute the Borel complexity of some classes of Banach spaces such as different versions of diameter two properties, spaces satisfying the Daugavet equation or spaces with an octahedral norm. In most of the above cases our computation is even optimal, which completes the research done during the last years around this topic for isomorphism classes of Bana

Nathan Gavenski, Felipe Meneguzzi, Michael Luck, Odinaldo Rodrigues

Imitation learning is an approach in which an agent learns how to execute a task by trying to mimic how one or more teachers perform it. This learning approach offers a compromise between the time it takes to learn a new task and the effort needed to collect teacher samples for the agent. It achieves this by balancing learning from the teacher, who has some

Zhihao Fang, Xingwu Chen

For piecewise-smooth differential systems, in this paper we focus on crossing limit cycles and sliding loops bifurcating from a grazing loop connecting one high multiplicity tangent point. For the low multiplicity cases considered in previous publications, the method is to define and analyze return maps following the classic idea of Poincar\'e. However, high

Adam D. Kypriadis, Isaac E. Lagaris, Aristidis Likas, Konstantinos E. Parsopoulos

Approximating solutions of ordinary and partial differential equations constitutes a significant challenge. Based on functional expressions that inherently depend on neural networks, neural forms are specifically designed to precisely satisfy the prescribed initial or boundary conditions of the problem, while providing the approximate solutions in closed for

Jessica Enright, Samuel D. Hand, Laura Larios-Jones, Kitty Meeks

Temporal graphs provide a useful model for many real-world networks. Unfortunately the majority of algorithmic problems we might consider on such graphs are intractable. There has been recent progress in defining structural parameters which describe tractable cases by simultaneously restricting the underlying structure and the times at which edges appear in

Rafiullah Omar, Justus Bogner, Joran Leest, Vincenzo Stoico

ML-enabled systems that are deployed in a production environment typically suffer from decaying model prediction quality through concept drift, i.e., a gradual change in the statistical characteristics of a certain real-world domain. To combat this, a simple solution is to periodically retrain ML models, which unfortunately can consume a lot of energy. One r

Eartha Kruft Welton, Sharif Khudairi, James Tuite

A subset $S$ of vertices of a graph $G$ is in \emph{general position} if no shortest path in $G$ contains three vertices of $S$. The \emph{general position problem} consists of finding the number of vertices in a largest general position set of $G$, whilst the \emph{lower general position problem} asks for a smallest maximal general position set. In this pap

Zhihao Fang, Xingwu Chen

Tangent points, especial dynamics existing only in piecewise-smooth systems, usually have dynamical properties like equilibria of smooth systems. Loops connecting tangent points own partly properties of limit cycles and homoclinic loops of smooth systems. In this paper we give classifications for tangent points by tangency degree and for loops connecting the

Yusi Long, Songhan Zhao, Shimin Gong, Bo Gu

This paper considers multiple unmanned aerial vehicles (UAVs) to assist sensing data transmissions from the ground users (GUs) to a remote base station (BS). Each UAV collects sensing data from the GUs and then forwards the sensing data to the remote BS. The GUs first backscatter their data to the UAVs and then all UAVs forward data to the BS by the nonortho

Jana Egli, Benedek Forrai, Thomas Buchner, Jiangtao Su

Conventional industrial robots often use two-fingered grippers or suction cups to manipulate objects or interact with the world. Because of their simplified design, they are unable to reproduce the dexterity of human hands when manipulating a wide range of objects. While the control of humanoid hands evolved greatly, hardware platforms still lack capabilitie