October 2023 arXiv papers — page 75

Umberto Morellini

In the study of the electronic structure of heavy atoms, relativistic effects cannot be neglected and the Dirac operator naturally appears in place of the Schr\"odinger operator, raising a number of additional difficulties. The complexity of these systems has been addressed by various approximations. We consider a model consisting of differential equations c

Stergos Afantenos, Henri Prade, Leonardo Cortez Bernardes

Analogical proportions are statements of the form "$a$ is to $b$ as $c$ is to $d$", which expresses that the comparisons of the elements in pair $(a, b)$ and in pair $(c, d)$ yield similar results. Analogical proportions are creative in the sense that given 3 distinct items, the representation of a 4th item $d$, distinct from the previous items, which forms

Jiahao Xu, Wei Shao, Lihui Chen, Lemao Liu

This paper proposes the DistillCSE framework, which performs contrastive learning under the self-training paradigm with knowledge distillation. The potential advantage of DistillCSE is its self-enhancing feature: using a base model to provide additional supervision signals, a stronger model may be learned through knowledge distillation. However, the vanilla

Simão Correia

We prove that the quartic Korteweg-de Vries equation is globally well-posed for real-valued initial data in $H^s(\mathbb{R})$, $s>-1/24$.

Ryan Cloutier, Michael Greklek-McKeon, Serena Wurmser, Collin Cherubim

Is the population of close-in planets orbiting M dwarfs sculpted by thermally driven escape or is it a direct outcome of the planet formation process? A number of recent empirical results strongly suggest the latter. However, the unique architecture of the TOI-1266 system presents a challenge to models of planet formation and atmospheric escape given its see

Daniel Kalmanovich, Eran Nevo, Gangotryi Sorcar

Which $4$-manifolds admit a flag-no-square (fns) triangulation? We introduce the "star-connected-sum" operation on such triangulations, which preserves the fns property, from which we derive new constructions of fns $4$-manifolds. In particular, we show the following: (i) there exist non-aspherical fns $4$-manifolds, answering in the negative a question by P

Ahmed El Kerim, Pierre Gosselet, Frédéric Magoulès

A novel approach is being developed to introduce a parallel asynchronous implementation of non-intrusive global-local coupling. This study examines scenarios involving numerous patches, including those covering the entire structure. By leveraging asynchronous, the method aims to minimize reliance on communication, handle failures effectively, and address loa

Moriah Aberle, Sarah Gold, Rivkah Moshe, David Offner

We say a graph $H$ decomposes a graph $G$ if there exists a partition of the edges of $G$ into subgraphs isomorphic to $H$. We seek to characterize necessary and sufficient conditions for a cycle of length $k$, denoted $C_k$, to decompose the Cartesian product of two cycles $C_m ~\square~ C_n$. We prove that if $m$ is a multiple of 3, then the Cartesian prod

Shao-Ping Li, Bingrong Yu

A singlet majoron can arise from the seesaw framework as a pseudo-Goldstone boson when the heavy Majorana neutrinos acquire masses via the spontaneous breaking of global ${\rm U}(1)_L$ symmetry. The resulting cosmological impacts are usually derived from the effective majoron-neutrino interaction, and the majoron abundance is accumulated through the freeze-i

Vladimir Sokolovsky, Leonid Prigozhin

HTS dynamo magnetic flux pumps are perspective devices for contactless charging the superconductor magnets and coils. In this work, we investigate the influence of a ferromagnetic substrate of a coated conductor used as the pump stator. We use the thin shell model of a coated conductor with a ferromagnetic substrate and show that such a conductor increases t

Mateus Roder, Leandro Aparecido Passos, João Paulo Papa, André Luis Debiaso Rossi

Quality classification of wood boards is an essential task in the sawmill industry, which is still usually performed by human operators in small to median companies in developing countries. Machine learning algorithms have been successfully employed to investigate the problem, offering a more affordable alternative compared to other solutions. However, such

Wenjin Yang, Yuanwei Wu, Yan Gong, Nicolas Mauron

Studying stars that are located off the Galactic plane is important for understanding the formation history of the Milky Way. We searched for SiO masers toward off-plane O-rich asymptotic giant branch (AGB) stars from the catalog presented by Mauron et al. (2019) in order to shed light on the origin of these objects. A total of 102 stars were observed in the

Laura Guislain, Eric Bertin

We study a nonequilibrium ferromagnetic mean-field spin model exhibiting a phase with spontaneous temporal oscillations of the magnetization, on top of the usual paramagnetic and ferromagnetic phases. This behavior is obtained by introducing dynamic field variables coupled to the spins through non-reciprocal couplings. We determine a nonequilibrium generaliz

Mirko Armillotta

A novel estimation approach for a general class of semi-parametric multivariate time series models is introduced where the conditional mean is modeled through parametric functions. The focus of the estimation is the conditional mean parameter vector for non-negative time series. Quasi-Maximum Likelihood Estimators (QMLEs) based on the linear exponential fami

Lucas Weber, Elia Bruni, Dieuwke Hupkes

Finding the best way of adapting pre-trained language models to a task is a big challenge in current NLP. Just like the previous generation of task-tuned models (TT), models that are adapted to tasks via in-context-learning (ICL) are robust in some setups but not in others. Here, we present a detailed analysis of which design choices cause instabilities and

Claire M. Cisowski, Madeline C. Waller, Robert Bennett

In this work we generalise the adjoint method of inverse design to nonreciprocal media. As a test case, we use three-dimensional topology optimization via the level-set method to optimise one-way energy transfer for point-like source and observation points. To achieve this we introduce a suite of tools, chiefly what we term the `Faraday-adjoint' method which

Betony Adams, Ilya Sinayskiy, Shivang Agarwal, Francesco Petruccione

The potential role of spin in biological systems is a primary topic in quantum biology. However, much of this research focuses on electron spin. A recent hypothesis suggests that nuclear spin may be better suited to biological processes, being less sensitive to decoherence. The hypothesis details how phosphorus nuclei might be prepared in a spin-entangled st

Ali Rohan, Muhammad Saad Rafaq, Md. Junayed Hasan, Furqan Asghar

Livestock health and welfare monitoring has traditionally been a labor-intensive task performed manually. Recent advances have led to the adoption of AI and computer vision techniques, particularly deep learning models, as decision-making tools within the livestock industry. These models have been employed for tasks like animal identification, tracking, body

Chengyan Yu, Shihuan Wang, Dong zhang, Yingying Zhang

Numerous children diagnosed with Autism Spectrum Disorder (ASD) exhibit abnormal eye gaze pattern in communication and social interaction. Due to the high cost of ASD interventions and a shortage of professional therapists, researchers have explored the use of virtual reality (VR) systems as a supplementary intervention for autistic children. This paper pres

Juepeng Zheng, Shuai Yuan, Weijia Li, Haohuan Fu

Powered by the advances of optical remote sensing sensors, the production of very high spatial resolution multispectral images provides great potential for achieving cost-efficient and high-accuracy forest inventory and analysis in an automated way. Lots of studies that aim at providing an inventory to the level of each individual tree have generated a varie

Tena Dubcek, Debora Ledergerber, Jana Thomann, Giovanna Aiello

Neural oscillations are considered to be brain-specific signatures of information processing and communication in the brain. They also reflect pathological brain activity in neurological disorders, thus offering a basis for diagnoses and forecasting. Epilepsy is one of the most common neurological disorders, characterized by abnormal synchronization and desy

Francisco Eiras, Kemal Oksuz, Adel Bibi, Philip H. S. Torr

Referring Image Segmentation (RIS) - the problem of identifying objects in images through natural language sentences - is a challenging task currently mostly solved through supervised learning. However, while collecting referred annotation masks is a time-consuming process, the few existing weakly-supervised and zero-shot approaches fall significantly short

Luis González-De La Fuente, Alicia Nieto-Reyes, Pedro Terán

Statistical depth functions order the elements of a space with respect to their centrality in a probability distribution or dataset. Since many depth functions are maximized in the real line by the median, they provide a natural approach to defining median-like location estimators for more general types of data (in our case, fuzzy data). We analyze the relat

Mathieu Bajodek, Hugo Lhachemi, Giorgio Valmorbida

This article presents proposals for the design of reduced-order controllers for high-dimensional dynamical systems. The objective is to develop efficient control strategies that ensure stability and robustness with reduced computational complexity. By leveraging the concept of partial pole placement, which involves placing a subset of the closed-loop system'

Dibyendu Bala, Olaf Kaczmarek, Peter Lowdon, Owe Philipsen

Determining the type of excitations that can exist in a thermal medium is key to understanding how hadronic matter behaves at extreme temperatures. In this work we study this question for pseudo-scalar mesons comprised of light-strange and strange-strange quarks, analysing how their low-energy spectral properties are modified as one passes through the high-t

Leonid Prigozhin, Vladimir Sokolovsky

Ferromagnetic substrate influences the electromagnetic response of a type-II superconducting film to the applied magnetic field. We present a two-dimensional integrodifferential model for the magnetization of a flat superconductor/ferromagnet bilayer of an arbitrary shape using a thin shell quasistatic model for the ferromagnetic substrate and an infinitely

Etienne Bamas, Sai Ganesh Nagarajan, Ola Svensson

One of the most popular clustering algorithms is the celebrated $D^\alpha$ seeding algorithm (also know as $k$-means++ when $\alpha=2$) by Arthur and Vassilvitskii (2007), who showed that it guarantees in expectation an $O(2^{2\alpha}\cdot \log k)$-approximate solution to the ($k$,$\alpha$)-means cost (where euclidean distances are raised to the power $\alph

Mingwei Zhu, Leigang Sha, Yu Shu, Kangjia Zhao

Multimodal large language models (MLLMs) have shown great potential in perception and interpretation tasks, but their capabilities in predictive reasoning remain under-explored. To address this gap, we introduce a novel benchmark that assesses the predictive reasoning capabilities of MLLMs across diverse scenarios. Our benchmark targets three important domai

Uri Bader, Alex Furman, Jean Lécureux

Let $\Gamma$ be a group acting on with finite stabilizers and finite fundamental domain on a building of type $\tilde A_2$. We prove that any non-trivial normal subgroup of $\Gamma$ is of finite index in $\Gamma$.

Xugang Lu, Peng Shen, Yu Tsao, Hisashi Kawai

Domain shift poses a significant challenge in cross-domain spoken language recognition (SLR) by reducing its effectiveness. Unsupervised domain adaptation (UDA) algorithms have been explored to address domain shifts in SLR without relying on class labels in the target domain. One successful UDA approach focuses on learning domain-invariant representations to

Maria Gordina, Liangbing Luo

We consider sub-Riemannian manifolds which are homogeneous spaces equipped with a natural sub-Riemannian structure induced by a transitive action by a Lie group. In such a setting, the corresponding sub-Laplacian is not an elliptic but a hypoelliptic operator. We study logarithmic Sobolev inequalities with respect to the hypoelliptic heat kernel measure on s

Nathan Szwarcberg, Tom Colinot, Christophe Vergez, Michaël Jousserand

This article develops the design of a sound synthesis model of a woodwind instrument by modal decomposition of the input impedance, taking into account viscothermal losses as well as localized nonlinear losses at the end of the resonator. This formalism has already been applied by Diab et al. (2022) to the study of forced systems. It is now implemented for s

Quinten Bolding, Baohao Liao, Brandon James Denis, Jun Luo

Transformer models have demonstrated remarkable performance in neural machine translation (NMT). However, their vulnerability to noisy input poses a significant challenge in practical implementation, where generating clean output from noisy input is crucial. The MTNT dataset is widely used as a benchmark for evaluating the robustness of NMT models against no

Lara Herriott, Henriette L. Capel, Isaac Ellmen, Nathan Schofield

Mathematical models play a crucial role in understanding the spread of infectious disease outbreaks and influencing policy decisions. These models aid pandemic preparedness by predicting outcomes under hypothetical scenarios and identifying weaknesses in existing frameworks. However, their accuracy, utility, and comparability are being scrutinized. Agent-bas

Nicolas Forcadel, Cyril Imbert, Regis Monneau

In this note, we consider an evolution coercive Hamilton-Jacobi equation posed in a domain and supplemented with a boundary condition. We are interested in proving a comparison principle in the case where the time and the (normal) gradient variables are strongly coupled at the boundary. We elaborate on a method introduced by P.-L. Lions and P. Souganidis (At

Tingqin Lai, Xiaolin Liang, Yi Zhu, Xinyi Wu

Recently, there has been increased attention towards 3D imaging using single-pixel single-photon detection (also known as temporal data) due to its potential advantages in terms of cost and power efficiency. However, to eliminate the symmetry blur in the reconstructed images, a fixed background is required. This paper proposes a fusion-data-based 3D imaging

Frank Imbens

Black holes and other compact objects are powerful tools to observationally test Einsteins theory of General Relativity. We develop raytracing code to create visual images of compact objects that are solutions of Einsteins field equations. These include Kerr black holes and Manko-Novikov spacetimes with extra independent multipole moments. Using parallel pro

Cameron Lemon, Frédéric Courbin, Anupreeta More, Paul Schechter

Strong gravitational lenses provide unique laboratories for cosmological and astrophysical investigations, but they must first be discovered - a task that can be met with significant contamination by other astrophysical objects and asterisms. Here we review strong lens searches, covering various sources (quasars, galaxies, supernovae, FRBs, GRBs, and GWs), l

François Ledrappier, Pablo Lessa

We consider a representation of a finitely generated CAT(--K) group $\Gamma$ in SL(d, R) that is Zariski dense and k-Anosov for at least two values of k. We exhibit a gap for the Minkowski dimension of minimal sets for the action of $\Gamma$ on flags spaces. The proof uses a variational principle for the action on partial flags.

Muddappa Seetharama Gowda

In the setting of a self-dual cone in a finite-dimensional inner product space, we consider (zero-sum) linear games. In our previous work, we showed that a Z-transformation with positive value is completely mixed. The present paper considers the case when the value is zero. Motivated by the matrix game result that a Z-matrix with value zero is completely mix

Li Chen, Paul Nikolaev, David J. Prömel

The well-posedness and regularity properties of diffusion-aggregation equations, emerging from interacting particle systems, are established on the whole space for bounded interaction force kernels by utilizing a compactness convergence argument to treat the nonlinearity as well as a Moser iteration. Moreover, we prove a quantitative estimate in probability

Tony Stillfjord, Filip Tronarp

In this article, an efficient numerical method for computing both the matrix exponential and a finite horizon controllability Gramian in Cholesky-factored form is proposed. The method is applicable to general dense matrices of moderate size and produces a Cholesky factor of the Gramian without computing the full product. It is a generalization of the scaling

Haipeng Fang, Zhihao Sun, Ziyao Huang, Fan Tang

The advancement of generative AI has extended to the realm of Human Dance Generation, demonstrating superior generative capacities. However, current methods still exhibit deficiencies in achieving spatiotemporal consistency, resulting in artifacts like ghosting, flickering, and incoherent motions. In this paper, we present Dance-Your-Latents, a framework tha

Fucai Li, Houzhi Tang, Shuxing Zhang

The classical Fourier's law, which states that the heat flux is proportional to the temperature gradient, induces the paradox of infinite propagation speed for heat conduction. To accurately simulate the real physical process, the hyperbolic model of heat conduction named Cattaneo's law was proposed, which leads to the finite speed of heat propagation. A nat

Thomas Pethick, Wanyun Xie, Volkan Cevher

This paper presents a theoretical analysis of linear interpolation as a principled method for stabilizing (large-scale) neural network training. We argue that instabilities in the optimization process are often caused by the nonmonotonicity of the loss landscape and show how linear interpolation can help by leveraging the theory of nonexpansive operators. We

Jun-Yan He, Zhi-Qi Cheng, Chenyang Li, Jingdong Sun

This paper introduces WordArt Designer, a user-driven framework for artistic typography synthesis, relying on the Large Language Model (LLM). The system incorporates four key modules: the LLM Engine, SemTypo, StyTypo, and TexTypo modules. 1) The LLM Engine, empowered by the LLM (e.g., GPT-3.5), interprets user inputs and generates actionable prompts for the

Xiao-Peng Jin, An-Dong Xiong, Wei Zhang, Xiao-Qing Wang

Achieving both high-performance and wide field-of-view (FOV) super-resolution imaging has been attracting increasing attention in recent years. However, such goal suffers from long reconstruction time and huge storage space. Parallel compressive imaging (PCI) provides an efficient solution, but the super-resolution quality and imaging speed are strongly depe

Hakan Aktas, Yukie Nagai, Minoru Asada, Erhan Oztop

We observe a large variety of robots in terms of their bodies, sensors, and actuators. Given the commonalities in the skill sets, teaching each skill to each different robot independently is inefficient and not scalable when the large variety in the robotic landscape is considered. If we can learn the correspondences between the sensorimotor spaces of differ

Daniel Canarutto

A sketch of some of the fundamental notions related to the nature of knowledge is offered, with special focus on the role of mathematics and my own opinions. No single idea exposed here is entirely original; indeed, this topic has been explored by legions of philosophers, mathematicians, and scientists throughout history -- I listed a few related books among

Helge Dietert

The recent work [11] developed a general framework to show hypocoercivity for a stationary Gibbs state and allowed spatial degeneracy, confining potentials and boundary conditions. In this work, we show that the explicit energy approach in the weighted L$^2$ space works for general non-equilibrium steady states and that it can be adapted to cases with weaker

Michael Mandl, Julian J. Lenz

We study the (2+1)-dimensional Gross-Neveu model at non-zero chemical potential and subjected to a homogeneous background magnetic field. We do so both analytically, in the limit of an infinite number of fermion flavors in which mean-field approaches become exact, as well as on the lattice for a single flavor. The rich and exotic phase structure observed in

Asaf Farhi, Wei Dai, Seunghwi Kim, Andrea Alu

State transfer and photon detection are fundamental processes that have direct implications in fields such as quantum computing and photonic circuits. However, while naturally emitted photons decay exponentially in time, to perfectly capture a photon its envelope should increase exponentially to match the time-reversed response of the absorbing cavity. Here

Eduardo Brandao, Anthony Nakhoul, Stefan Duffner, Rémi Emonet

Ultrafast laser irradiation can induce spontaneous self-organization of surfaces into dissipative structures with nanoscale reliefs. These surface patterns emerge from symmetry-breaking dynamical processes that occur in Rayleigh-B\'enard-like instabilities. In this study, we demonstrate that the coexistence and competition between surface patterns of differe

Dror Hurwitz, Itzik Klein

Quadrotors are widely used for surveillance, mapping, and deliveries. In several scenarios the quadrotor operates in pure inertial navigation mode resulting in a navigation solution drift. To handle such situations and bind the navigation drift, the quadrotor dead reckoning (QDR) approach requires flying the quadrotor in a periodic trajectory. Then, using mo

Donghuo Zeng, Kazushi Ikeda

The cross-modal retrieval model leverages the potential of triple loss optimization to learn robust embedding spaces. However, existing methods often train these models in a singular pass, overlooking the distinction between semi-hard and hard triples in the optimization process. The oversight of not distinguishing between semi-hard and hard triples leads to

Rafal Gruszczynski, Dazhu Li

Mereology in its formal guise is usually couched in a language whose signature contains only one primitive binary predicate symbol representing the part of relation, either the proper or improper one. In this paper, we put forward an approach to mereology that uses mereological sum as its primitive notion, and we demonstrate that it is definitionally equival

Shiquan Ren

In this paper, we study the discrete differential calculus on hypergraphs by using the Kouzul complexes. We define the constrained (co)homology for hypergraphs and give the corresponding Mayer-Vietoris sequences. We prove the functoriality of the Mayer-Vietoris sequences for the constrained homology and the functoriality of the Mayer-Vietoris sequences for t

Duarte M. Alves, Nuno M. Guerreiro, João Alves, José Pombal

Large language models (LLMs) are a promising avenue for machine translation (MT). However, current LLM-based MT systems are brittle: their effectiveness highly depends on the choice of few-shot examples and they often require extra post-processing due to overgeneration. Alternatives such as finetuning on translation instructions are computationally expensive

Siyu Zhang, Yeming Chen, Yaoru Sun, Fang Wang

The key to integrating visual language tasks is to establish a good alignment strategy. Recently, visual semantic representation has achieved fine-grained visual understanding by dividing grids or image patches. However, the coarse-grained semantic interactions in image space should not be ignored, which hinders the extraction of complex contextual semantic

Mariia Kozlova, Antti Ahola, Pamphile T. Roy, Julian Scott Yeomans

Models of complex technological systems inherently contain interactions and dependencies among their input variables that affect their joint influence on the output. Such models are often computationally expensive and few sensitivity analysis methods can effectively process such complexities. Moreover, the sensitivity analysis field as a whole pays limited a

Simos G. Meintanis, John P. Nolan, Charl Pretorius

We consider goodness-of-fit methods for multivariate symmetric and asymmetric stable Paretian random vectors in arbitrary dimension. The methods are based on the empirical characteristic function and are implemented both in the i.i.d. context as well as for innovations in GARCH models. Asymptotic properties of the proposed procedures are discussed, while the

Marie Badreau, Frédéric Proïa

This paper deals with unit root issues in time series analysis. It has been known for a long time that unit root tests may be flawed when a series although stationary has a root close to unity. That motivated recent papers dedicated to autoregressive processes where the bridge between stability and instability is expressed by means of time-varying coefficien

Luis Manuel Navas Vicente, Francisco J. Plaza Martín, Álvaro Serrano Holgado

Our goal is to give a purely algebraic characterization of finite abelian Galois covers of a complete, irreducible, non-singular curve $X$ over an algebraically closed field $\k$. To achieve this, we make use of the Galois theory of commutative rings, in particular the Kummer theory of the ring of geometric adeles $\A_{X}$. After we establish the triviality

Gaspard Ohlmann

In this article, we study the well-posedness of the energy-critical half-wave maps equation (HWM) in dimension $1$. The half-wave maps equation emerges from the continuum limit of the Haldane Shastry spin chains and has been shown to arise as the continuum limit of Calogero-Moser classical spin systems. In higher dimension $d\geq 5$, it has been shown that (

Guillaume Allais

In typed functional languages, one can typically only manipulate data in a type-safe manner if it first has been deserialised into an in-memory tree represented as a graph of nodes-as-structs and subterms-as-pointers. We demonstrate how we can use QTT as implemented in \idris{} to define a small universe of serialised datatypes, and provide generic programs

Emi Baylor, Esther Ploeger, Johannes Bjerva

Typological information has the potential to be beneficial in the development of NLP models, particularly for low-resource languages. Unfortunately, current large-scale typological databases, notably WALS and Grambank, are inconsistent both with each other and with other sources of typological information, such as linguistic grammars. Some of these inconsist

Rıdvan Keskin, Ibrahim Aliskan

Boost, buck-boost, and fly-back DC-DC converters which are utilized in power lines of any electric vehicles, solar energy, and power factor correction applications require control systems to regulate the output voltage under mismatched disturbances i.e. load current and input voltage. In continuous current mode operation, the converters, however, are bandwid

Henning Bartsch, Ole Jorgensen, Domenic Rosati, Jason Hoelscher-Obermaier

Large language models (LLMs) that do not give consistent answers across contexts are problematic when used for tasks with expectations of consistency, e.g., question-answering, explanations, etc. Our work presents an evaluation benchmark for self-consistency in cases of under-specification where two or more answers can be correct. We conduct a series of beha

Oleksandr V. Pylypovskyi, Sophie F. Weber, Pavlo Makushko, Igor Veremchuk

Antiferromagnets are normally thought of as materials with compensated magnetic sublattices. This adds to their technological advantages but complicates readout of the antiferromagnetic state. We demonstrate theoretically the existence of a Dzyaloshinskii-Moriya interaction (DMI) which is determined by the magnetic symmetry classes of Cr$_2$O$_3$ surfaces wi

Kiril Hristov

It was recently observed in arXiv:2304.07320 for thermal Kerr-Newman black holes in 4d flat space that one can rewrite the conventional thermodynamics on the inner and outer horizons in terms of left- and right-moving variables with a remarkable simplification of the corresponding expressions. With the goal of illustrating the wide applicability of these new

Feng Zhang, Rui Bao, Congqi Dai, Wanlu Zhang

This study mainly focuses on the performance of different multi-spectral light sources on different object colors in machine vision and tries to enhance machine vision with multi-spectral light sources. Using different color pencils as samples, by recognizing the collected images with two classical neural networks, AlexNet and VGG19, the performance was inve

Emmet Hall-Hoffarth

Recently a number of papers have suggested using neural-networks in order to approximate policy functions in DSGE models, while avoiding the curse of dimensionality, which for example arises when solving many HANK models, and while preserving non-linearity. One important step of this method is to represent the constraints of the economic model in question in

Makoto Ochiai

Particle--anti-particle interpretation under spatially inhomogeneous external fields within the framework of quantum field theory is a nontrivial problem. In this paper, we focus on the two interpretations established in [Phys. Rev. D 93, 045002 (2016)] and [Prog. Theor. Exp. Phys. 2022, 073B02 (2022)], both of which give consistent results of vacuum instabi

Vasilii Feofanov, Malik Tiomoko, Aladin Virmaux

We propose a theoretical framework to analyze semi-supervised classification under the low density separation assumption in a high-dimensional regime. In particular, we introduce QLDS, a linear classification model, where the low density separation assumption is implemented via quadratic margin maximization. The algorithm has an explicit solution with rich t

Jannis Chemseddine, Paul Hagemann, Christian Wald

In inverse problems, many conditional generative models approximate the posterior measure by minimizing a distance between the joint measure and its learned approximation. While this approach also controls the distance between the posterior measures in the case of the Kullback Leibler divergence, it does not hold true for the Wasserstein distance. We will in

Yan-Qing Zhao, Song He, Defu Hou, Li Li

We explore the phase structure of Quantum Chromodynamics (QCD) with two dynamical quark flavors at finite temperature and baryon chemical potential, employing the non-perturbative gauge/gravity duality approach. Our gravitational model is tailored to align with state-of-the-art lattice data regarding the thermal properties of multi-flavor QCD. Following a ri

Clemens Heuberger, Jutta Rath, Roswitha Rissner

The sequence $(\operatorname{Ass}(R/I^n))_{n\in\mathbb{N}}$ of associated primes of powers of a monomial ideal $I$ in a polynomial ring $R$ eventually stabilizes by a known result by Markus Brodmann. L\^e Tu\^an Hoa gives an upper bound for the index where the stabilization occurs. This bound depends on the generators of the ideal and is obtained by separate

Etienne Thuillier, Craig Jin, Vesa Välimäki

Several individualization methods have recently been proposed to estimate a subject's Head-Related Transfer Function (HRTF) using convenient input modalities such as anthropometric measurements or pinnae photographs. There exists a need for adaptively correcting the estimation error committed by such methods using a few data point samples from the subject's

Ugo Bessi

P. Alonso-Ruiz, U. Freiberg and J. Kigami have defined a large family of resistance forms on the Stretched Sierpinski Gasket $G$. In the present paper we introduce a system of coordinates on $G$ (technically, an embedding of $G$ into $\R^2$) such that \noindent$\bullet$) these forms are defined on $C^1(\R^2,\R)$ and \noindent$\bullet$) all affine functions a

Alan C. Dassie, Rodolfo M. Id Betan

Microscopic determination of alpha-decay half-lives requires structure and reaction calculations. The structure part is given by the microscopic distribution of the constituent nucleons, while the relative motion of the product's decay provides the reaction part. This paper studies the clusterization of the $0^+$ excited states of $^{44}$Ti arising from the

Luca Carai, Serafina Lapenta, Luca Spada

Combining tools from category theory, model theory, and non-standard analysis we extend Baker-Beynon dualities to the classes of all Abelian $\ell$-groups and all Riesz spaces (also known as vector lattices). The extended dualities have a strong geometrical flavor, as they involve a non-standard version of the category of polyhedral cones and piecewise (homo

Yakov I. Korepanov

In solid-state electrochemical experiments, the boundary between the sample and the electrolyte plays a crucial role, and the rest of the sample acting as a buffer that maintains a fixed composition. Due to the presence of an electrochemical circuit in the cell (ionic conductivity in the electrolyte and electronic conductivity in the sample system), the chem

Lucas Mertens, Lena-Antonia Wolbeck, David Rößler, Lin Xie

Public transport is vital for meeting people's mobility needs. Providers need to plan their services well to offer high quality and low cost. Optimized planning can benefit providers, customers, and municipalities. The planning process for public transport involves various decision problems, such as vehicle and crew planning. These problems are usually solve

Xinyu Zhang, Qingyu Liu, Zhongjie Ba, Yuan Hong

Federated Learning (FL) is a promising distributed learning approach that enables multiple clients to collaboratively train a shared global model. However, recent studies show that FL is vulnerable to various poisoning attacks, which can degrade the performance of global models or introduce backdoors into them. In this paper, we first conduct a comprehensive

Piyabut Burikham, Tiberiu Harko, Kulapant Pimsamarn, Shahab Shahidi

In a recent Comment on the paper "Dark matter as a Weyl geometric effect", by Burikham et al., Phys. Rev. D 107, 064008 (2023), posted on arxiv. org as eprint arXiv:2306.11926, it was claimed that the exact solution found in the above mentioned paper by Burikham et al. "is wrong". In this Reply to the Comment we present, in a clear and comprehensive way, a s

Kaave Lajevardi, Saeed Salehi

We respond to some of the points made by Bennet and Blanck (2022) concerning a previous publication of ours (2021).

Lukas Hantzko, Lennart Binkowski, Sabhyata Gupta

This paper introduces a novel general-purpose algorithm for Pauli decomposition that employs matrix slicing and addition rather than expensive matrix multiplication, significantly accelerating the decomposition of multi-qubit matrices. In a detailed complexity analysis, we show that the algorithm admits the best known worst-case scaling and more favorable ru

Jiarun Liu, Wentao Hu, Chunhong Zhang

Large Language Models (LLMs) have emerged as promising agents for web navigation tasks, interpreting objectives and interacting with web pages. However, the efficiency of spliced prompts for such tasks remains underexplored. We introduces AllTogether, a standardized prompt template that enhances task context representation, thereby improving LLMs' performanc

Jihyoung Jang, Minseong Boo, Hyounghun Kim

In the field of natural language processing, open-domain chatbots have emerged as an important research topic. However, a major limitation of existing open-domain chatbot research is its singular focus on short single-session dialogue, neglecting the potential need for understanding contextual information in multiple consecutive sessions that precede an ongo

A. S. Sotirova, B. Sun, J. D. Leppard, A. Wang

Individual optical addressing in chains of trapped atomic ions requires generation of many small, closely spaced beams with low cross-talk. Furthermore, implementing parallel operations necessitates phase, frequency, and amplitude control of each individual beam. Here we present a scalable method for achieving all of these capabilities using a novel integrat

Yingying Gao, Shilei Zhang, Zihao Cui, Yanhan Xu

Self-supervised pre-trained models such as HuBERT and WavLM leverage unlabeled speech data for representation learning and offer significantly improve for numerous downstream tasks. Despite the success of these methods, their large memory and strong computational requirements hinder their application on resource restricted devices. Therefore, this paper intr

Sumanti Patra, Madhurita Das, Priya Mahadevan

We consider two high symmetry stackings AA and AB and examine the changes induced in the electronic structure by considering small angles of rotation of 3.48degrees from both these stackings. In both cases we largely recover the low energy electronic structure of the untwisted limit. We additionally find flat bands emerging above the dispersing bands. Surpri

Shweta Didel, Jeewan C. Pandey, A. K. Srivastava, Gurpreet Singh

We present the analyses of intense X-ray flares detected on the active fast rotator AB Dor using observations from the XMM-Newton. A total of 21 flares are detected, and 13 flares are analysed in detail. The total X-ray energy of these flares is found to be in the range of 10$^{34-36}$ erg, in which the peak flare flux increased up to 34 times from the pre-/

Ali Nikoutadbir, Sajjad Torabi, Sadegh Bolouki

This paper addresses the problem of achieving secure consensus in a vehicular platoon using event-triggered control. The platoon consists of a leader and multiple follower vehicles exchanging their position and velocity information discretely to maintain stability. The paper focuses on the issue of gain modification attacks, where a malicious actor attempts

Zhongliang Chen, Zhuofei Huang, Wenxiong Kang

Fault diagnosis of rotating machinery plays a important role for the safety and stability of modern industrial systems. However, there is a distribution discrepancy between training data and data of real-world operation scenarios, which causing the decrease of performance of existing systems. This paper proposed a transfer learning based method utilizing aco

Boccaletti A., Mâlin M., Baudoz P., Tremplin P.

The multi planet system HR8799 is the first target observed with MIRI's coronagraphs as part of the MIRI-EC Guaranteed Time Observations exoplanets programme in Nov. 2022. We obtained deep observations in three coronagraphic filters from 10 to 15mic (F1065C, F1140C, F1550C), and one standard imaging filter at 20 mic (F2100W), with the goal to extract the pho

Guillaume Allais

Using a dependently typed host language, we give a well scoped-and-typed by construction presentation of a minimal two level simply typed calculus with a static and a dynamic stage. The staging function partially evaluating the part of a term that are static is obtained by a model construction inspired by normalisation by evaluation. We then go on to demonst

Muhammad Rizwan, Kimet Jusufi

In this paper we explore the topological classes of thermodynamics of a family of black holes. In particular we investigate the influence of distinct fields, including the electric field, non-linear magnetic field, along with the perfect fluid matter background that can mimic dark matter in large distances. In light of these considerations, we shall hencefor

Xiaoju Chang, Bo Chen, Qiyu Zeng, Han Wang

The immiscibility of hydrogen-helium mixture under the temperature and pressure conditions of planetary interiors is crucial for understanding the structures of gas giant planets (e.g., Jupiter and Saturn). While the experimental probe at such extreme conditions is challenging, theoretical simulation is heavily relied in an effort to unravel the mixing behav

Shuhan Wu, Huaiyu Wan, Wei Chen, Yuting Wu

Graph neural networks (GNNs) have shown promising performance for knowledge graph reasoning. A recent variant of GNN called progressive relational graph neural network (PRGNN), utilizes relational rules to infer missing knowledge in relational digraphs and achieves notable results. However, during reasoning with PRGNN, two important properties are often over