December 2024 arXiv papers — page 151

Shiqi Jia, Tong Fu, Shubo Wang

Optical polarization singularities (PSs) in real space carry rich topological properties and can enable highly precise manipulations of light fields. Conventional studies focus on the PSs in the open space of optical systems. The properties of PSs inside optical cavities remain largely unexplored. By using full-wave finite-element simulations, we investigate

Anastasia A. Golubtsova, Eric Gourgoulhon, Mikhail A. Podoinitsyn

We continue our studies of holographic renormalization group (RG) flows for a 3d truncated supergravity model, the scalar potential of which can have either one or three extrema depending on the radius of the target manifold. We construct numerically and analytically thermal holographic RG flows, which are described by asymptotically AdS$_3$ black holes (non

A. E. Bondar, E. K. Karkaryan, A. A. Simovonian, M. I. Vysotsky

Semileptonic decays of the $B \overline{B}$ pairs produced in the $\mathit{\Upsilon}(5S)$ can be used to find the relative probability of $\mathit{\Upsilon}(5S) \rightarrow B_s \overline{B}_s$ decays. This could be achieved by the study of time dependence of $B$-meson decays to the leptons of equal and opposite signs.

Jan Rathjens, Shirin Reyhanian, David Kappel, Laurenz Wiskott

Understanding the mechanisms underlying deep neural networks remains a fundamental challenge in machine learning and computer vision. One promising, yet only preliminarily explored approach, is feature inversion, which attempts to reconstruct images from intermediate representations using trained inverse neural networks. In this study, we revisit feature inv

Matthias Baur

We present numerical minimizers for the first seven eigenvalues of the magnetic Dirichlet Laplacian with constant magnetic field in a wide range of field strengths. Adapting an approach by Antunes and Freitas, we use gradient descent for the minimization procedure together with the Method of Fundamental solutions for eigenvalue computation. Remarkably, we ob

Nobuki Takeda

We give the pullback formula for vector-valued Hermitian modular forms on CM field. We also give the equivalent condition for a differential operator on Hermitian modular forms to preserve the automorphic properties.

Egor Cherepanov, Nikita Kachaev, Artem Zholus, Alexey K. Kovalev

The incorporation of memory into agents is essential for numerous tasks within the domain of Reinforcement Learning (RL). In particular, memory is paramount for tasks that require the use of past information, adaptation to novel environments, and improved sample efficiency. However, the term "memory" encompasses a wide range of concepts, which, coupled with

Jiayan Chen, Kai Li, Zhanjin Wang, Zhan Wang

Hepatic echinococcosis (HE) is a prevalent disease in economically underdeveloped pastoral areas, where adequate medical resources are usually lacking. Existing methods often ignore multi-scale feature fusion or focus only on feature fusion between adjacent levels, which may lead to insufficient feature fusion. To address these issues, we propose HES-UNet, a

Hans Triebel

This paper deals with continuous and compact mappings of the Fourier transform in function spaces with dominating mixed smoothness.

Patrick Lei

We prove the Feynman rule conjectured by Bershadsky-Cecotti-Ooguri-Vafa arXiv:hep-th/9309140 and the anomaly equations conjectured by Yamaguchi-Yau arXiv:hep-th/0406078 for the Gromov-Witten theory of the Calabi-Yau threefolds $Z_6 \subset \mathbb{P}(1,1,1,1,2)$, $Z_8 \subset \mathbb{P}(1,1,1,1,4)$, and $Z_{10} \subset \mathbb{P}(1,1,1,2,5)$. These determine

Alexander Zimmermann

We define and characterise completely dg-separable dg-extensions $\varphi:(A,d_A)\rightarrow (B,d_B)$. We completely characterise the case of graded commutative dg-division algebras in characteristic different from $2$. We prove that for a dg-separable extension a short exact sequence of dg-modules over $(B,d_B)$ splits if and only if the restriction to $(A,

Lukas Hensel, Gudrun Grünwald, Katharina Kormann, Rainer Grauer

Active Flux is a modified Finite Volume method that evolves additional Degrees of Freedom for each cell that are located on the interface by a non-conservative method to compute high-order approximations to the numerical fluxes through the respective interface to evolve the cell-average in a conservative way. In this paper, we apply the method to the Vlasov-

Oliver Clarke, Max Kölbl

We study the hypersimplex under the action of the symmetric group $S_n$ by coordinate permutation. We prove that the evaluation of its equivariant $H^*$-polynomial at $1$ is the permutation character of decorated ordered set partitions under the natural action of $S_n$. This verifies a conjecture of Stapledon for the hypersimplex. To prove this result, we gi

Goratamang Gaedie, Shambel Sahlu, Amare Abebe

In this paper, we propose a modified scale factor (MSF) that allows us to explore the accelerating expansion of the universe without invoking the traditional dark-energy model, as described in the Lambda cold dark matter ($\Lambda$CDM) model. Instead, the MSF model introduces parameters that encapsulate the effects traditionally attributed to dark energy. To

Alexander Kolesnikov, Svetlana Popova

We consider the problem of optimal exchange which can be formulated as a kind of optimal transportation problem. The existence of an optimal solution and a duality theorem for the optimal exchange problem are proved in case of completely regular topological spaces. We show the connection between the problem of optimal exchange and the optimal transportation

Wan-Qian Zhao, Zhan-Yong Guo, Zeng-Yuan Tian, Tong-Fu Su

High quality ancient DNA (aDNA) is essential for molecular paleontology. Due to DNA degradation and contamination by environmental DNA (eDNA), current research is limited to fossils less than 1 million years old. The study successfully extracted DNA from Lycoptera davidi fossils from the Early Cretaceous period, dating 120 million years ago. Using high-throu

Luis A. Peña Ardila, Arturo Camacho-Guardian

Polarons have emerged as a powerful concept across many-fields in physics to study an impurity coupled to a quantum bath. The interplay between impurity physics and the formation of composite objects remains a relevant problem to understand how few- and many-body states are robust towards complex environments and polaron physics. In most cases, impurities ar

Simon Badger, Heribertus Bayu Hartanto, Rene Poncelet, Zihao Wu

We present the double-virtual amplitudes contributing to the production of a Higgs boson in association with a $b\bar{b}$ pair at the Large Hadron Collider. We perform the computation within the five-flavour scheme, which employs massless bottom quarks and finite bottom-Yukawa coupling, taking into account all the colour structures. We derive the analytic fo

Jarosław Byrka, Fabrizio Grandoni, Vera Traub

The Steiner Forest problem is an important generalization of the Steiner Tree problem. We are given an undirected graph with nonnegative edge costs and a collection of pairs of vertices. The task is to compute a cheapest forest with the property that the elements of each pair belong to the same connected component of the forest. The current best approximatio

Massimo Stiavelli, Takahiro Morishita, Marco Chiaberge, Nicha Leethochawalit

We present measurements of the gas-phase Oxygen and Nitrogen abundances obtained by applying the direct method to JWST NIRspec $R\sim1000$ spectroscopy for 6 galaxies at redshift greater than 3. Our measurements are based on rest-frame optical Nitrogen [N II]$_{\lambda\lambda6548,6583}$ lines and are complemented by 6 additional objects from the literature a

Maria Camisassa

White dwarf stars are the most common endpoint of stellar evolution. Therefore, these old, numerous and compact objects provide valuable information on the late stages of stellar evolution, the physics of dense plasma and the structure and evolution of our Galaxy. The ESA Gaia space mission has revolutionized this research field, providing parallaxes and mul

Ke-Sheng Huang, Hua-Yu Jiang, Fu-Sheng Yu

In this work, we investigate the transition form factors for $\Lambda_b\rightarrow{\Lambda(1520)}$ within the framework of light-cone sum rules (LCSR), using the light-cone distribution amplitudes (LCDAs) of the $\Lambda_b$-baryon. In the hadronic representation of the correlation function, we carefully select the appropriate Lorentz structures and isolate t

Umang Bhaskar, Yeshwant Pandit

The existence of EFX allocations is one of the most significant open questions in fair division. Recent work by Christodolou, Fiat, Koutsoupias, and Sgouritsa ("Fair allocation in graphs", EC 2023) establishes the existence of EFX allocations for graphical valuations, when agents are vertices in a graph, items are edges, and each item has zero value for all

Yedi Zhang, Yufan Cai, Xinyue Zuo, Xiaokun Luan

Large Language Models (LLMs) have emerged as a transformative AI paradigm, profoundly influencing daily life through their exceptional language understanding and contextual generation capabilities. Despite their remarkable performance, LLMs face a critical challenge: the propensity to produce unreliable outputs due to the inherent limitations of their learni

Pascal Clausen, Li Ma, Mingming He, Ahmet Levent Tasel

We present a technique for fitting high dynamic range illumination (HDRI) sequences using anisotropic spherical Gaussians (ASGs) while preserving temporal consistency in the compressed HDRI maps. Our approach begins with an optimization network that iteratively minimizes a composite loss function, which includes both reconstruction and diffuse losses. This a

Shidan He, Lei Liu, Xiujun Shu, Bo Wang

Anomaly synthesis is a crucial approach to augment abnormal data for advancing anomaly inspection. Based on the knowledge from the large-scale pre-training, existing text-to-image anomaly synthesis methods predominantly focus on textual information or coarse-aligned visual features to guide the entire generation process. However, these methods often lack suf

Yedi Zhang, Fu Song, Taolue Chen, Xuzhi Wu

Reasoning about strategic abilities is key to AI systems comprising multiple agents, which provide a unified framework for formalizing various problems in game theory, social choice theory, etc. In this work, we propose a probabilistic extension of the alternating-time $\mu$-calculus (AMC), named PAMC, for reasoning about the strategic abilities of agents in

Tao Han, Ze Li, Jing-Fei Zhang, Xin Zhang

The advent of third-generation (3G) gravitational-wave (GW) detectors opens new opportunities for multi-messenger observations of binary neutron star merger events, holding significant potential for probing the history of cosmic expansion. In this paper, we investigate the holographic dark energy (HDE) model by using the future GW standard siren data observe

Hongkang Song, Zihui Zhang, Yanpeng Zhou, Jie Hu

Spinal cord tumors significantly contribute to neurological morbidity and mortality. Precise morphometric quantification, encompassing the size, location, and type of such tumors, holds promise for optimizing treatment planning strategies. Although recent methods have demonstrated excellent performance in medical image segmentation, they primarily focus on d

Anh Vu Phan

Measurements of the top quark by the ATLAS and CMS experiments go beyond testing the Standard Model (SM) with high precision. Axion-like particles (ALPs), a potential SM extension involving new pseudoscalar particles, exhibit strong interactions with heavy SM fermions. Consequently, they can significantly affect the kinematic distributions of top quarks in t

Emeric Bouin, Jérôme Coville, Xi Zhang

This paper is devoted to studying propagation phenomena in integro-differential equations with a weakly degenerate non-linearity. The reaction term can be seen as an intermediate between the classical logistic (or Fisher-KPP) non-linearity and the standard weak Allee effect one. We study the effect of the tails of the dispersal kernel on the rate of expansio

Ivan Rosario, Francisco Campanario, Simon Plätzer

We present the implementation of a new interface in VBFNLO 3.0 supporting all di-boson and tri-boson processes with fully leptonic final states, enabling NLO+PS matched calculations. To demonstrate its capabilities, we study parton shower effects in the tri-boson production process $p p \rightarrow e^{+} \nu_e \mu^{-} \bar{\nu}_{\mu} \gamma + X$ using Herwig

Zachary Nasipak

The Teukolsky equation describes perturbations of Kerr spacetime and is central to the study of rotating black holes and gravitational waves. In the frequency domain, the Teukolsky equation separates into radial and angular ordinary differential equations. Mano, Suzuki, and Takasugi (MST) found semi-analytic solutions to the homogeneous radial Teukolsky equa

Somdeb Lahiri

In this paper we assemble some results about the upper-semicontinuity and lower-semicontinuity of the feasible correspondence and the solution correspondence of linear programming problems allowing variability of all parameters of such problems. We also prove continuity properties of optimal value functions, once again allowing all parameters to vary. We dis

Andronikos Paliathanasis, Amlan Halder, Genly Leon

The cosmological history and evolution are examined for gravitational models with interaction in the dark sector of the universe. In particular, we consider the dark energy to be described by a phantom scalar field and the dark matter $\rho _{m}$ as a pressureless ideal gas. We introduce the interacting function $Q=\beta \left( t\right) \rho_{m}$, where the

Alessio Corti, Paul Hacking, Andrea Petracci

We introduce admissible Minkowski decomposition data (amd) for a 3-dimensional reflexive polytope P. This notion is defined purely in terms of the combinatorics of P. Denoting by X the Gorenstein toric Fano 3-fold whose fan is the spanning fan (a.k.a. face fan) of P, our first result states that amd for P determine a smoothing of X. Our second result amounts

Xiaoqian Zhou, Zhen Huang, Heqin Zhu, Qingsong Yao

Anatomical landmark detection (ALD) from a medical image is crucial for a wide array of clinical applications. While existing methods achieve quite some success in ALD, they often struggle to balance global context with computational efficiency, particularly with high-resolution images, thereby leading to the rise of a natural question: where is the performa

Jinsung Park

We introduce maximal discs of Weil-Petersson class in the 3-dimensional Anti-de Sitter space $\mathbb{A}\mathrm{d}\mathbb{S}^{2,1}$, whose parametrization space can be identified with the cotangent bundle $T^*T_0(1)$ of Weil-Petersson universal Teichm\"uller space $T_0(1)$. We prove that the Mess map defines a symplectic diffeomorphism from $T^*T_0(1)$ to $T

Lugaoze Feng, Xunan Li, Guocheng Lv, Ye jin

Motivated by the application of point-to-point communication networks and biological storage, we investigate new achievability bounds for noisy permutation channels with strictly positive and full-rank square matrices. Our new bounds use $\epsilon$-packing with Kullback-Leibler divergence as a metric to bound the distance between distributions and are tighte

Syed Shazaib Shah, Tan Daoliang, Sah Chandan Kumar

Predictive maintenance (PdM) is increasingly pursued to reduce wind farm operation and maintenance costs by accurately predicting the remaining useful life (RUL) and strategically scheduling maintenance. However, the remoteness of wind farms often renders current methodologies ineffective, as they fail to provide a sufficiently reliable advance time window f

Philipp Sürig

We consider on Riemannian manifolds the non-linear evolution equation $$\rho \partial _{t}u=\Delta _{p}u^{q}.$$ Assuming that the manifold satisfies a \textit{(weighted) Sobolev inequality} and under certain assumptions on $p, q$ and function $\rho$, we prove that weak subsolutions to this equation have a finite extinction time. In particular, our main resul

Da Bi, Dominik R. G. Schleicher, Andres Escala

This study investigates the influence of intermediate-mass black holes (IMBHs) on galactic morphology, focusing on their evolution within dwarf galaxies at high redshift (z~2). Using high-resolution zoom-in cosmological simulations, we explore how IMBH properties, including seed masses, formation times, and feedback mechanisms, shape the morphology and prope

Francesco Cremonesi, Lucia Innocenti, Sebastien Ourselin, Vicky Goh

Federated learning (FL) has gained wide popularity as a collaborative learning paradigm allowing collaborative Artificial Intelligence (AI) in sensitive healthcare applications. Nevertheless, the practical implementation of FL presents technical and organizational challenges, as it generally requires complex communication infrastructures. In this context, co

Sören Bieler, Kerstin Weinberg

Lattice-like cellular materials, with their unique combination of lightweight, high strength, and good deformability, are promising for engineering applications. This paper investigates the energy-absorbing properties of four truss-lattice structures with two defined volume fractions of material in static compression experiments. The mass-specific energy abs

M. Moscibrodzka

We revisit the radiative properties of 3D general relativistic magnetohydrodynamics (GRMHD) two-temperature magnetically arrested disk (MAD) models in which electrons are heated by a magnetic turbulent cascade. We focus on studying the model emission, whose characteristics include variability in both total intensity and linear/circular polarizations as well

Yihong Xu, Yuan Yin, Éloi Zablocki, Tuan-Hung Vu

Accurately predicting how agents move in dynamic scenes is essential for safe autonomous driving. State-of-the-art motion forecasting models rely on datasets with manually annotated or post-processed trajectories. However, building these datasets is costly, generally manual, hard to scale, and lacks reproducibility. They also introduce domain gaps that limit

Timothy M. Chan, Chaya Keller, Shakhar Smorodinsky

The hypergraph Zarankiewicz's problem, introduced by Erd\H{o}s in 1964, asks for the maximum number of hyperedges in an $r$-partite hypergraph with $n$ vertices in each part that does not contain a copy of $K_{t,t,\ldots,t}$. Erd\H{o}s obtained a near optimal bound of $O(n^{r-1/t^{r-1}})$ for general hypergraphs. In recent years, several works obtained impro

Masahito Hayashi, Kazuyasu Shigemoto, Takuya Tsukioka

On the Kummer surface, we have obtained two different Gauss metrices by parametrizing it in two ways. We have found that these Gauss metrices are not Ricci flat. The double sphere, which is the special case of the Kummer surface, has the K\"{a}hler metric and the first Chern class of it does not vanish. Its metric is the Einstein metric which is not Ricci fl

Kuan Xu, Zeyu Jiang, Haozhi Cao, Shenghai Yuan

Scene Coordinate Regression (SCR) is a visual localization technique that utilizes deep neural networks (DNN) to directly regress 2D-3D correspondences for camera pose estimation. However, current SCR methods often face challenges in handling repetitive textures and meaningless areas due to their reliance on implicit triangulation. In this paper, we propose

Aakash Madhav Rao, Debayan Gupta

The development of generative models in the past decade has allowed for hyperrealistic data synthesis. While potentially beneficial, this synthetic data generation process has been relatively underexplored in cancer histopathology. One algorithm for synthesising a realistic image is diffusion; it iteratively converts an image to noise and learns the recovery

Mikhail Bugaev, Igor Novikov, Serge Repin, Polina Samorodskaya

The numerical investigation conducted in this paper addresses the problem of CMB radiation imaging as seen through the throat of the Ellis-Bronnikov-Morris-Thorne wormhole. It is assumed that both throats of the wormhole are relatively close to our stellar neighborhood, so close that the view of the ambient background radiation by an observer at the other th

Catalin E. Brita, Stephan Bongers, Frans A. Oliehoek

In offline reinforcement learning, deriving an effective policy from a pre-collected set of experiences is challenging due to the distribution mismatch between the target policy and the behavioral policy used to collect the data, as well as the limited sample size. Model-based reinforcement learning improves sample efficiency by generating simulated experien

Aylar Partovizadeh, Sebastian Schöps, Dimitrios Loukrezis

This work proposes a data-driven surrogate modeling framework for cost-effectively inferring the torque of a permanent magnet synchronous machine under geometric design variations. The framework is separated into a reduced-order modeling and an inference part. Given a dataset of torque signals, each corresponding to a different set of design parameters, torq

David Samuel, Vladislav Mikhailov, Erik Velldal, Lilja Øvrelid

Training large language models requires vast amounts of data, posing a challenge for less widely spoken languages like Norwegian and even more so for truly low-resource languages like Northern S\'ami. To address this issue, we present a novel three-stage continual training approach that substantially improves the downstream performance together with the infe

Da Yin, Haoyi Qiu, Kung-Hsiang Huang, Kai-Wei Chang

In the rapidly evolving field of Large Language Models (LLMs), ensuring safety is a crucial and widely discussed topic. However, existing works often overlook the geo-diversity of cultural and legal standards across the world. To demonstrate the challenges posed by geo-diverse safety standards, we introduce SafeWorld, a novel benchmark specifically designed

Lei Guo, Jiayang Li, Yu Marco Nie, Jun Xie

Combinatorial bilevel congestion pricing (CBCP), a variant of the mixed (continuous/discrete) network design problems, seeks to minimize the total travel time experienced by all travelers in a road network, by strategically selecting toll locations and determining toll charges. Conventional wisdom suggests that these problems are intractable since they have

Michael Cummins, Alberto Padoan, Keith Moffat, Florian Dorfler

This paper introduces Data-enabled Predictive Control Hyperparameter Tuning via Differentiable Optimization (DeePC-Hunt), a backpropagation-based method for automatic hyperparameter tuning of the DeePC algorithm. The necessity for such a method arises from the importance of hyperparameter selection to achieve satisfactory closed-loop DeePC performance. The s

Thierry Gallouët, Etienne Pardoux, Ténan Yeo

A stochastic SIR epidemic model taking into account the heterogeneity of the spatial environment is constructed. The deterministic model is given by a partial differential equation and the stochastic one by a space-time jump Markov process. The consistency of the two models is given by a law of large numbers. In this paper, we study the deviation of the spat

Karl Kunisch, John Sebastian H. Simon

A shape optimization problem subject to an elliptic equation in the presence of missing data on the Dirichlet boundary condition is considered. It is formulated by optimizing the deformation field that varies the spatial domain where the Poisson equation is posed. To take into consideration the missing boundary data the problem is formulated as a no-regret p

Guillaume Marrelec, Alain Giron

We propose to quantify dependence between two systems $X$ and $Y$ in a dataset $D$ based on the Bayesian comparison of two models: one, $H_0$, of statistical independence and another one, $H_1$, of dependence. In this framework, dependence between $X$ and $Y$ in $D$, denoted $B(X,Y|D)$, is quantified as $P(H_1|D)$, the posterior probability for the model of

D. E. Morosan, N. Dresing, C. Palmroos, J. Gieseler

Solar energetic particles in the heliosphere are produced by flaring processes on the Sun or shocks driven by coronal mass ejections. These particles are regularly detected remotely as electromagnetic radiation (X-rays or radio emission), which they generate through various processes, or in situ by spacecraft monitoring the Sun and the heliosphere. We aim to

Surajit Chakraborty, Roshan Maharana, Smarajit Karmakar, Kabir Ramola

Amorphous solids exhibit an excess of low-frequency vibrational modes beyond the Debye prediction, contributing to their anomalous mechanical and thermal properties. Although a $\omega^4$ power-law scaling is often proposed for the distribution of these modes, the precise exponent remains a subject of debate. In this study, we demonstrate that boundary-condi

Yixiong Fang, Ziran Yang, Zhaorun Chen, Zhuokai Zhao

Large vision-language models (LVLMs) excel at multimodal tasks but are prone to misinterpreting visual inputs, often resulting in hallucinations and unreliable outputs. We present DROPOUT DECODING, a novel inference-time approach that quantifies the uncertainty of visual tokens and selectively masks uncertain tokens to improve decoding. Our method measures t

Tatsumi Aoyama, Masashi Hayakawa, Akira Hirayama, Makiko Nio

A discrepancy of approximately 5$\sigma$ exists between the two known results for the tenth-order QED contribution to the anomalous magnetic moment of the electron, calculated from Feynman vertex diagrams without fermion loops. To investigate this, we decomposed this contribution into 389 parts based on a self-energy diagram representation, enabling a diagra

Kristina L. Kupferschmidt, James Requiema, Mya Simpson, Zohrah Varsallay

In this work, we address a lack of systematic understanding of fluctuations in food affordability in Canada. Canada's Food Price Report (CPFR) is an annual publication that predicts food inflation over the next calendar year. The published predictions are a collaborative effort between forecasting teams that each employ their own approach at Canadian Univers

Laurence Sebastian Bowes, Vincent Drach, Patrick Fritzsch, Sofie Martins

The SU(2) gauge group with two fundamental flavors is a candidate for a composite Higgs extension of the Standard Model. Central to Higgs phenomenology is a non-perturbative determination of observables of the theory, such as the decay constant of the pseudo-Nambu-Goldstone Bosons. We present preliminary results for the continuum limit of the pseudoscalar de

Fei Wu, Pablo Marquez-Neila, Hedyeh Rafi-Tarii, Raphael Sznitman

Multi-class semantic segmentation remains a cornerstone challenge in computer vision. Yet, dataset creation remains excessively demanding in time and effort, especially for specialized domains. Active Learning (AL) mitigates this challenge by selecting data points for annotation strategically. However, existing patch-based AL methods often overlook boundary

Craig Vear, Johann Benerradi

In this paper, we discuss the conceptualisation and design of embodied AI within an inclusive music-making project. The central case study is Jess+ an intelligent digital score system for shared creativity with a mixed ensemble of non-disabled and disabled musicians. The overarching aim is that the digital score enables disabled musicians to thrive in a live

David Krieg, Erich Novak, Mario Ullrich

One can recover vectors from $\mathbb{R}^m$ with arbitrary precision, using only $\lceil \log_2(m+1)\rceil +1$ continuous measurements that are chosen adaptively. This surprising result is explained and discussed, and we present applications to infinite-dimensional approximation problems.

Yuan Fa, Agata Piacentini, Bart Macco, Holger Kalisch

Two-dimensional material (2DM)-based field-effect transistors (FETs), such as molybdenum disulfide (MoS${_2}$)-FETs, have gained significant attention for their potential for ultra-short channels, thereby extending Moore's law. However, MoS${_2}$-FETs are prone to the formation of Schottky barriers at the metal-MoS${_2}$ interface, resulting in high contact

Nursel Erey, Sara Faridi, Tài Huy Hà, Takayuki Hibi

Let $I(G)$ be the edge ideal of a gapfree graph $G$. An open conjecture of Nevo and Peeva states that $I(G)^q$ has linear resolution for $q\gg 0$. We present a promising approach to this challenging conjecture by investigating the stronger property of linear quotients. Specifically, we make the conjecture that if $I(G)^q$ has linear quotients for some intege

Ran Li, Yi-Lun Du, Shanshan Cao

We apply a Dense Neural Network (DNN) approach to reconstruct jet momentum within a quark-gluon plasma (QGP) background, using simulated data from PYTHIA and Linear Boltzmann Transport (LBT) Models for comparative analysis. We find that medium response particles from the LBT simulation, scattered out of the QGP background but belonging to medium-modified jet

Xuesong Zhang, Yunbo Xu, Jia Li, Ruonan Liu

Navigating unseen environments from natural language instructions remains challenging for egocentric agents in Vision-and-Language Navigation (VLN). Humans naturally ground concrete semantic knowledge within spatial layouts during indoor navigation. Although prior work has introduced diverse environment representations to improve reasoning, auxiliary modalit

Songlin Yang, Jan Kautz, Ali Hatamizadeh

Linear Transformers have gained attention as efficient alternatives to standard Transformers, but their performance in retrieval and long-context tasks has been limited. To address these limitations, recent work has explored two distinct mechanisms: gating for adaptive memory control and the delta update rule for precise memory modifications. We observe that

N. A. Emelyanov, Vl. V. Kocharovsky

A self-similar solution of the linearised magnetohydrodynamic equations describing the propagation of the Alfv\'en pulse in an axially symmetric magnetic tube of variable diameter is obtained. The electric field component induced by the non-linear Alfv\'en wave and directed along the tube surface, i.e., accelerating particles along the magnetic field, is det

Muhammad Kashif, Muhammad Shafique

This paper presents an easy-to-implement approach to mitigate the challenges posed by barren plateaus (BPs) in randomly initialized parameterized quantum circuits (PQCs) within variational quantum algorithms (VQAs). Recent state-of-the-art research is flooded with a plethora of specialized strategies to overcome BPs, however, our rigorous analysis reveals th

Weijie Tu, Weijian Deng, Dylan Campbell, Yu Yao

Can the relative performance of a pre-trained large multimodal model (LMM) be predicted without access to labels? As LMMs proliferate, it becomes increasingly important to develop efficient ways to choose between them when faced with new data or tasks. The usual approach does the equivalent of giving the models an exam and marking them. We opt to avoid marki

A. I. Frank, G. V. Kulin, M. A. Zakharov, S. V. Mironov

The paper is devoted to the discussion of the possibility of creating UCN sources based on the principle of pulse accumulation (PA) in traps. The implementation of the PA principle would make it possible to create a source with a flux of UCN in a trap significantly exceeding the time average. The paper provides a comparative analysis of various approaches to

Hao Wang, Qiang Luo, Ji Chen

Charge density wave (CDW) is a widely concerned emergent phenomenon in condensed matter physics. To establish a systematic understanding of CDW, we develop a diagrammatic self-consistent-field approach for cubic Holstein model employing fluctuation exchange approximation, and explore the emergence and transition of three-dimensional CDWs. Commensurate CDW (c

Wei Suo, Ji Ma, Mengyang Sun, Lin Yuanbo Wu

Although Large Vision-Language Models (LVLMs) have achieved impressive results, their high computational costs pose a significant barrier to wide application. To enhance inference efficiency, most existing approaches can be categorized as parameter-dependent or token-dependent strategies to reduce computational demands. However, parameter-dependent methods r

D. Di Filippantonio, P. Reig, J. Fabregat

The main goal of this work is to investigate the fast photometric variability of the optical counterparts to supergiant X-ray binaries and to compare the general patterns of such variability with the Galactic population of other early-type stars. We analyzed a sample of 14 high-mass X-ray binaries with supergiant companions observed by the Transiting Exoplan

Hongjuan Li, Hui Kang, Geng Sun, Jiahui Li

Unmanned aerial vehicles (UAVs) have gained considerable attention as a platform for establishing aerial wireless networks and communications. However, the line-of-sight dominance in air-to-ground communications often leads to significant interference with terrestrial networks, reducing communication efficiency among terrestrial terminals. This paper explore

V. E. Kuzmichev, V. V. Kuzmichev

The impact of a fast decaying component of mass-energy, that decreases faster than radiation with the increase of the scale factor, on the evolution of the universe is studied using a hydrodynamic approach. Proceeding from the Hamiltonian formalism, the hydrodynamic-like equations for the velocity and acceleration of the expansion of the universe as a functi

Francis Xiatian Zhang, Jingjing Deng, Robert Lieck, Hubert P. H. Shum

Surgical workflow anticipation is the task of predicting the timing of relevant surgical events from live video data, which is critical in Robotic-Assisted Surgery (RAS). Accurate predictions require the use of spatial information to model surgical interactions. However, current methods focus solely on surgical instruments, assume static interactions between

Dragi Karevski

We present an introduction to the theory of open extended quantum systems. We begin with a microscopic derivation of the so-called Lindblad equation followed by a more abstract approach. Next, we introduce collision models, a versatile framework that offers a possible unraveling of the non-unitary dynamics of open quantum systems. We finally discuss concrete

Yuanyuan Wang, Qian Song, Dawood Wasif, Muhammad Shahzad

Uncertainty quantification (UQ) is essential for assessing the reliability of Earth observation (EO) products. However, the extensive use of machine learning models in EO introduces an additional layer of complexity, as those models themselves are inherently uncertain. While various UQ methods do exist for machine learning models, their performance on EO dat

Vito Iacovino

We define the not abelian Open Gromov-Witten potential.

Shubham Vishnoi, Geetu Kumari, Robert Guest, Pierre-André Cazade

Organic molecular crystals are ideally placed to become next-generation piezoelectric materials due to their diverse chemistries that can be used to engineer tailor-made solid-state assemblies. Using crystal engineering principles, and techniques such as co-crystallisation, these materials can be engineered to have a wide range of electromechanical propertie

Andrey Kudryashov, Sergey Gusev, Anastasiya Orlova, Andrey Afanasiev

Multi-pulse femtosecond laser irradiation of a monolayer of polystyrene microspheres deposited on a polystyrene substrate leads to the formation of carbon nanomaterial exhibiting broadband excitation-dependent luminescence both within the microspheres and in the substrate. Initial polystyrene substrate and microspheres are transparent at the laser wavelength

U. Özdem

Accessing a full picture of the internal structure of hadrons would be a key topic of hadron physics, with the main motivation to study the strong interaction binding the visible matter. Furthermore, the underlying structure of known exotic states remains an unresolved fundamental issue in hadron physics, which is currently being addressed by hadron physics

Zhong-Yu Wang, Yu-Shuai Li, Si-Qiang Luo

Inspired by the newly observed $T_{c\bar{s}}$ state in the $D_{s1}(2460)^{+} \rightarrow D_{s}^{+}\pi^{+}\pi^{-}$ reaction by the LHCb Collaboration, we investigate the amplitude of this decay to explore the origins and properties of the open-charm tetraquark state based on the final state interaction. The invariant mass distributions of $D_{s}^{+}\pi^{+}$ a

Ilke Adalioglu, Serkan Kiranyaz, Mete Ahishali, Aysen Degerli

Echocardiography is the most widely used imaging to monitor cardiac functions, serving as the first line in early detection of myocardial ischemia and infarction. However, echocardiography often suffers from several artifacts including sensor noise, lack of contrast, severe saturation, and missing myocardial segments which severely limit its usage in clinica

Yu He, Fan Yao, Yang Yu, Xiaoyun Qiu

Despite the extensive literature on Tullock contests, computational results for the general model with heterogeneous contestants remain scarce. This paper studies the algorithmic complexity of computing a pure Nash Equilibrium (PNE) in such general Tullock contests. We find that the elasticity parameters {r_i}, which govern the returns to scale of contestant

Olimov Umrbek

We consider an infinite-dimensional non-linear operator related to a hard core (HC) model with a countable set $\mathbb{N}$ of spin values. It is known that finding the fixed points of an infinite-dimensional operator is generally impossible. But we have fully analyzed the fixed points of an infinite-dimensional operator by applying a technique of reducing a

Dominic Magirr, Craig Wang, Xinlei Deng, Tim Morris

Background: For RCTs with time-to-event endpoints, proportional hazard (PH) models are typically used to estimate treatment effects and logrank tests are commonly used for hypothesis testing. There is growing support for replacing this approach with a model-free estimand and assumption-lean analysis method. One alternative is to base the analysis on the diff

Qiushi Wang, Yuchen Fan, Junwei Bao, Hongfei Jiang

In recent years, Parameter-Efficient Fine-Tuning (PEFT) methods like Low-Rank Adaptation (LoRA) have significantly enhanced the adaptability of large-scale pre-trained models. Weight-Decomposed Low-Rank Adaptation (DoRA) improves upon LoRA by separating the magnitude and direction components of the weight matrix, leading to superior performance. However, DoR

Xiannan Huang, Shuhan Qiu, Quan Yuan, Chao Yang

In the context of rail transit operations, real-time passenger flow prediction is essential; however, most models primarily focus on normal conditions, with limited research addressing incident situations. There are several intrinsic challenges associated with prediction during incidents, such as a lack of interpretability and data scarcity. To address these

Dragi Karevski, Michele Coppola, Emanuele Tirrito, Mario Collura

Dynamical phase transitions induced by local projective measurements have attracted a lot of attention in the past few years. It has been in particular argued that measurements may induce an abrupt change in the scaling law of the bipartite entanglement entropy. In this work we show that local projective measurements on a one-dimensional quadratic fermionic

Alexander Gielisse, Nergis Tömen, Jan van Gemert

Most recent works on optical flow use convex upsampling as the last step to obtain high-resolution flow. In this work, we show and discuss several issues and limitations of this currently widely adopted convex upsampling approach. We propose a series of changes, in an attempt to resolve current issues. First, we propose to decouple the weights for the final

Charles Dupont, Debraj Roy

Eradicating extreme poverty and inequality are the key leverage points to achieve the seventeen Sustainable Development goals. Yet, the reduction in extreme poverty and inequality are vulnerable to shocks such as the pandemic and climate change. We find that that these vulnerabilities emerge from the interaction between individual and institutional mechanism