December 2023 arXiv papers — page 61

Denjoe O'Connor, Sanjaye Ramgoolam

We give a path integral construction of the quantum mechanical partition function for gauged finite groups. Our construction gives the quantization of a system of $d$, $N\times N$ matrices invariant under the adjoint action of the symmetric group $S_N$. The approach is general to any discrete group. For a system of harmonic oscillators, i.e. for the non-inte

Konstantin Ardakov, Simon Wadsley

Let $F$ be a finite extension of $\mathbb{Q}_p$, let $\Omega_F$ be Drinfeld's upper half-plane over $F$ and let $G^0$ the subgroup of $GL_2(F)$ consisting of elements whose determinant has norm $1$. Let $\mathscr{L}$ be a torsion $G^0$-equivariant line bundle with connection on $\Omega_F$. We show that the strong dual of $\mathscr{L}(\Omega_F)$ is an admissi

Walker Melton, Sruthi A. Narayanan

We show that, given a two-dimensional realization of the celestial OPE in self-dual Yang-Mills, we can find a scalar source around which scattering amplitudes replicate correlation functions computed from the 2D `gluon' operators in a limit where a dynamic massless scalar decouples. We derive conditions on the two-dimensional three-point correlation function

Adam Z. Kaczmarek, Dominik Szczęśniak

In this work, the $f(\mathcal{G},T)$ theory of gravity is recast in terms of the $\phi$ and $\psi$ fields within the scalar-tensor formulation, where $\mathcal{G}$ is the Gauss-Bonnet term and $T$ denotes the trace of the energy-momentum tensor. The general aspects of the introduced reformulation are discussed and the reconstruction of the cosmological scena

K Lakshmanan

While it is well known that finding approximate optima of non-convex functions is computationally intractable, we show that the problem is, in fact, uncomputable in the oracle model. Specifically, we prove that no algorithm with access only to a function oracle can compute the global minimum or even an $\epsilon$-approximation of the minimizer or minimal val

Alessio Marrani

Within the extremal black hole attractors arising in ungauged $\mathcal{N}\geqslant 2$-extended Maxwell Einstein supergravity theories in $3+1$ space-time dimensions, we provide an overview of the stratification of the electric-magnetic charge representation space into "large" orbits and related "moduli spaces", under the action of the (continuous limit of t

Vicki Kuhn, Yicheng Guo, Alec Martin, Julianna Bayless

Spiral arms are one of the most important features used to classify the morphology of local galaxies. The cosmic epoch when spiral arms first appeared contains essential clues to the evolution of disk galaxies. In this letter, we used James Webb Space Telescope (JWST) images from the Cosmic Evolution Early Release Science Survey to visually identify spiral g

Steffen Borgwardt, Angela Morrison

There is a wealth of combinatorial algorithms for classical min-cost flow problems and their simpler variants like max flow or shortest path problems. It is well-known that many of these algorithms are related to the Simplex method and the more general circuit augmentation schemes: prime examples are the network Simplex method, a refinement of the primal Sim

Nihat Sadik Deger, Marc Geiller, Jan Rosseel, Henning Samtleben

We present an action for minimal massive gravity (MMG) in three dimensions in terms of a dreibein and an independent spin connection. Furthermore, the construction provides an action principle for an infinite family of so-called third-way consistent generalizations of the three-dimensional Einstein field equations, including exotic massive gravity and new hi

Phillip W. K. Jensen, Erik Rosendahl Kjellgren, Peter Reinholdt, Karl Michael Ziems

Determining the properties of molecules and materials is one of the premier applications of quantum computing. A major question in the field is how to use imperfect near-term quantum computers to solve problems of practical value. Inspired by the recently developed variants of the quantum counterpart of the equation-of-motion (qEOM) approach and the orbital-

Federico Buccioni, Federica Devoto, Abdelhak Djouadi, John Ellis

The ATLAS and CMS collaborations at the LHC have recently announced evidence for the rare Higgs boson decay into a $Z$ boson and a photon. We analyze the interference between the process $gg\! \to \! H \! \to \! Z \gamma$ induced by loops of heavy particles, which is by far the dominant contribution to the signal, and the continuum $gg \to Z \gamma$ QCD back

Akio Kodaira, Chenfeng Xu, Toshiki Hazama, Takanori Yoshimoto

We introduce StreamDiffusion, a real-time diffusion pipeline designed for interactive image generation. Existing diffusion models are adept at creating images from text or image prompts, yet they often fall short in real-time interaction. This limitation becomes particularly evident in scenarios involving continuous input, such as Metaverse, live video strea

Fabio Cuzzolin

In this paper, we discuss a potential agenda for future work in the theory of random sets and belief functions, touching upon a number of focal issues: the development of a fully-fledged theory of statistical reasoning with random sets, including the generalisation of logistic regression and of the classical laws of probability; the further development of th

José de-la-Cruz-Moreno, James T. Liu, Leopoldo A. Pando Zayas

We study the entanglement entropy associated with a holographic RG flow from $\textrm{AdS}_7$ to $\textrm{AdS}_{4} \times \mathbb{H}_3$, where $\mathbb{H}_3$ is a $3$-dimensional hyperbolic manifold with curvature $\kappa$. The dual six-dimensional RG flow is disconnected from Lorentz-invariant flows. In this context we address various notions of central cha

Adit H. Edward, Michael L. Balogh, Yannick M. Bahe, Michael C. Cooper

We present an analysis of the galaxy stellar mass function (SMF) of 14 known protoclusters between $2.0 < z < 2.5$ in the COSMOS field, down to a mass limit of $10^{9.5}$ M$_{\odot}$. We use existing photometric redshifts with a statistical background subtraction, and consider star-forming and quiescent galaxies identified from $(NUV - r)$ and $(r - J)$ colo

Yunhao Gou, Zhili Liu, Kai Chen, Lanqing Hong

Instruction tuning of Large Vision-language Models (LVLMs) has revolutionized the development of versatile models with zero-shot generalization across a wide range of downstream vision-language tasks. However, the diversity of training tasks of different sources and formats would lead to inevitable task conflicts, where different tasks conflict for the same

N. Furey

Expanding the results of [1], [2], [3], we demonstrate a network of algebraic connections between six well-known particle theories. These are the Spin(10) model, the Georgi-Glashow model, the Pati-Salam model, the Left-Right Symmetric model, the Standard Model both pre- and post-Higgs mechanism. A new inclusion of a quaternionic reflection within the network

Gregoire Pihan, Akihiko Monnai, Björn Schenke, Chun Shen

It is of fundamental interest to understand the carrier of conserved quantum charges within protons and nuclei at high energy. Preliminary data from isobar collisions at RHIC reveal a scaled net-baryon to net-electric charge ratio ($B/\Delta Q \times \Delta Z/A$) at mid-rapidity between 1.2 and 2, consistent with string junction model predictions. Here, we c

Abdulla Alseiari, Michael Hilke

Thermal rectification devices can be important for various thermal management applications. For oscillator chains, thermal rectification was observed when masses are distributed non-uniformly. Leaning on the importance of topological materials, we consider here a simple vibrational topological system, the binary isotope superlattice (BISL). We show that the

Gregor Rauw

Gamma~Cas stars are early-type Be stars that exhibit an unusually hard and bright thermal X-ray emission. One of the proposed scenarios to explain these properties postulates the existence of a neutron star companion in the propeller stage, during which the magnetosphere of a rapidly rotating neutron star repels infalling material. To test this model, we exa

Alejandro Vivas-Viaña, Diego Martín-Cano, Carlos Sánchez Muñoz

We report a driven-dissipative mechanism to generate stationary entangled $W$ states among strongly-interacting quantum emitters placed within a cavity. Driving the ensemble into the highest energy state -- whether coherently or incoherently -- enables a subsequent cavity-enhanced decay into an entangled steady state consisting of a single de-excitation shar

Alessio Marrani

We introduce the so-called Magic Star (MS) projection within the root lattice of finite-dimensional exceptional Lie algebras, and relate it to rank-3 simple and semi-simple Jordan algebras. By relying on the Bott periodicity of reality and conjugacy properties of spinor representations, we present the so-called Exceptional Periodicity (EP) algebras, which ar

Samuel Lavenir

In this note we show that the classical theorem of Hilton-Milnor on finite wedges of suspension spaces remains valid in any $\infty$-topos. Our result relies on a version of James' splitting and uses only basic constructions native to any model of $\infty$-categories.

Zhimeng Jiang, Xiaotian Han, Chao Fan, Zirui Liu

There has been significant progress in improving the performance of graph neural networks (GNNs) through enhancements in graph data, model architecture design, and training strategies. For fairness in graphs, recent studies achieve fair representations and predictions through either graph data pre-processing (e.g., node feature masking, and topology rewiring

Teo Banica

A closed subgroup $G\subset_uU_N^+$ is called easy when its associated Tannakian category $C_{kl}=Hom(u^{\otimes k},u^{\otimes l})$ appears from a category of partitions, $C=span(D)$ with $D=(D_{kl})\subset P$, via the standard implementation of partitions as linear maps. The examples abound, and the main known subgroups $G\subset U_N^+$ are either easy, or

Hangjie Yuan, Shiwei Zhang, Xiang Wang, Yujie Wei

Diffusion models have emerged as the de facto paradigm for video generation. However, their reliance on web-scale data of varied quality often yields results that are visually unappealing and misaligned with the textual prompts. To tackle this problem, we propose InstructVideo to instruct text-to-video diffusion models with human feedback by reward fine-tuni

M. Fasano, Y. Li, J. A. Diez, J. D'Addesa

We present a theoretical study, supported by simulations and experiments, on the spreading of a silicone oil drop under MHz-frequency surface acoustic wave (SAW) excitation in the underlying solid substrate. Our time-dependent theoretical model uses the long wave approach and considers interactions between fluid dynamics and acoustic driving. While similar m

L. Sillari, A. Tomassini

In 1954, Hirzebruch reported a problem posed by Kodaira and Spencer: on compact almost complex manifolds, is the dimension $h^{p,q}_{\bar \partial}$ of the kernel of the Dolbeault Laplacian independent of the choice of almost Hermitian metric? In this paper, we review recent progresses on the original problem and we introduce a similar one: on compact almost

Rebecca M. Crossley, Samuel Johnson, Erika Tsingos, Zoe Bell

The extracellular matrix (ECM) is a highly complex structure through which biochemical and mechanical signals are transmitted. In processes of cell migration, the ECM also acts as a scaffold, providing structural support to cells as well as points of potential attachment. Although the ECM is a well-studied structure, its role in many biological processes rem

Piotr Pęzik, Sylwia Karasińska, Anna Cichosz, Łukasz Jałowiecki

This paper announces the early release of SpokesBiz, a freely available corpus of conversational Polish developed within the CLARIN-BIZ project and comprising over 650 hours of recordings. The transcribed recordings have been diarized and manually annotated for punctuation and casing. We outline the general structure and content of the corpus, showcasing sel

Remke Kloosterman

For each $k \geq 5$ we give a counterexample to a conjecture of Movasati on the dimension of certain Hodge loci of cubic hypersurfaces in $\mathbf{P}^{2k+1}$ containing two $k$-planes intersecting in dimension $k-3$. We give similar examples for Hodge loci of cubic hypersurfaces in $\mathbf{P}^{2k+1}$ containing two $k$-planes intersecting in dimension $k-2$

Kuldeep S. Meel, Supratik Chakraborty, S. Akshay

Model counting, or counting the satisfying assignments of a Boolean formula, is a fundamental problem with diverse applications. Given #P-hardness of the problem, developing algorithms for approximate counting is an important research area. Building on the practical success of SAT-solvers, the focus has recently shifted from theory to practical implementatio

Andrea Zanoni, Gianluca Geraci, Matteo Salvador, Karthik Menon

We study the problem of multifidelity uncertainty propagation for computationally expensive models. In particular, we consider the general setting where the high-fidelity and low-fidelity models have a dissimilar parameterization both in terms of number of random inputs and their probability distributions, which can be either known in closed form or provided

J. R. Espinosa, T. Konstandin

The tunneling potential formalism makes it easy to construct exact solutions to the vacuum decay problem in potentials with multiple fields. While some exact solutions for single-field decays were known, we present the first nontrivial analytic examples with two and three scalar fields, and show how the method can be generalized to include gravitational corr

Michael Roberts, Alon Hazan, Sören Dittmer, James H. F. Rudd

Whilst the size and complexity of ML models have rapidly and significantly increased over the past decade, the methods for assessing their performance have not kept pace. In particular, among the many potential performance metrics, the ML community stubbornly continues to use (a) the area under the receiver operating characteristic curve (AUROC) for a valida

Monika Wysoczańska, Oriane Siméoni, Michaël Ramamonjisoa, Andrei Bursuc

The popular CLIP model displays impressive zero-shot capabilities thanks to its seamless interaction with arbitrary text prompts. However, its lack of spatial awareness makes it unsuitable for dense computer vision tasks, e.g., semantic segmentation, without an additional fine-tuning step that often uses annotations and can potentially suppress its original

Baojia Luo, Yili Deng, Miaomiao Dong, Zhongyi Huang

In millimeter-wave (mmWave) cellular systems, reconfigurable intelligent surfaces (RISs) are foreseeably deployed with a large number of reflecting elements to achieve high beamforming gains. The large-sized RIS will make radio links fall in the near-field localization regime with spatial non-stationarity issues. Moreover, the discrete phase restriction on t

Yanru Wu, Jianning Wang, Weida Wang, Yang Li

Multi-source transfer learning is an effective solution to data scarcity by utilizing multiple source tasks for the learning of the target task. However, access to source data and model details is limited in the era of commercial models, giving rise to the setting of multi-source-free (MSF) transfer learning that aims to leverage source domain knowledge with

Edoardo Filippi-Mazzola, Ernst C. Wit

Dynamic networks offer an insight of how relational systems evolve. However, modeling these networks efficiently remains a challenge, primarily due to computational constraints, especially as the number of observed events grows. This paper addresses this issue by introducing the Deep Relational Event Additive Model (DREAM) as a solution to the computational

Christian Espíndola, Kristóf Kanalas

We give a detailed and self-contained introduction to the theory of $\lambda $-toposes and prove the following: 1) A $\lambda $-separable $\lambda $-topos has enough $\lambda $-points. 2) The classifying $\lambda $-topos of a $\kappa $-site $(\mathcal{C},E)$ is a presheaf topos (assuming $\kappa \vartriangleleft \lambda =\lambda ^{<\lambda }$, $|\mathcal{C}|

Long Chen, Ruchi Guo, Jingrong Wei

This paper introduces a novel Transformed Primal-Dual with variable-metric/preconditioner (TPDv) algorithm, designed to efficiently solve affine constrained optimization problems common in nonlinear partial differential equations (PDEs). Diverging from traditional methods, TPDv iteratively updates time-evolving preconditioning operators, enhancing adaptabili

Johannes Carmesin, Sarah Frenkel

Graph decompositions are the natural generalisation of tree decompositions where the decomposition tree is replaced by a genuine graph. Recently they found theoretical applications in the theory of sparsity, topological graph theory, structural graph theory and geometric group theory. We demonstrate applicability of graph decompositions on large networks by

Xiaodan Zhang, Sandeep Vemulapalli, Nabasmita Talukdar, Sumyeong Ahn

This study assesses the ability of state-of-the-art large language models (LLMs) including GPT-3.5, GPT-4, Falcon, and LLaMA 2 to identify patients with mild cognitive impairment (MCI) from discharge summaries and examines instances where the models' responses were misaligned with their reasoning. Utilizing the MIMIC-IV v2.2 database, we focused on a cohort

Olga Mula, Cecilia Pagliantini, Federico Vismara

We consider the inverse problem of reconstructing an unknown function $u$ from a finite set of measurements, under the assumption that $u$ is the trajectory of a transport-dominated problem with unknown input parameters. We propose an algorithm based on the Parameterized Background Data-Weak method (PBDW) where dynamical sensor placement is combined with app

Luis A. Anchordoqui, Ignatios Antoniadis, Dieter Lust

Over the last few years, low- and high-redshift observations set off tensions in the measurement of the present-day expansion rate $H_0$ and in the determination of the amplitude of the matter clustering in the late Universe (parameterized by $S_8$). It was recently noted that both these tensions can be resolved if the cosmological constant parametrizing the

R. Carini, A. Sollima, E. Brocato, K. Biazzo

We present the result of a sample of B-stars in the Large Magellanic Cloud young double stellar cluster NGC 1850 A and NGC 1850 B, observed with the integral-field spectrograph at the Very Large Telescope, the Multi Unit Spectroscopic Explorer. We compare the observed equivalent widths (EWs) of four He lines (4922 $\mathring{\mathrm A}$, 5015 $\mathring{\mat

Maron F. Anka, Thiago R. de Oliveira, Daniel Jonathan

We study the performance of a quantum Otto heat engine with two spins coupled by a Heisenberg interaction, taking into account not only the mean values of work and efficiency but also their fluctuations. We first show that, for this system, the output work and its fluctuations are directly related to the magnetization and magnetic susceptibility of the syste

Sergio E. Aguilar-Gutierrez, Ben Craps, Juan Hernandez, Mikhail Khramtsov

We explore the complexity equals volume proposal for planar black holes in anti-de Sitter (AdS) spacetime in 2+1 dimensions, with an end of the world (ETW) brane behind the horizon. We allow for the possibility of intrinsic gravitational dynamics in the form of Jackiw-Teitelboim (JT) gravity to be localized on the brane. We compute the asymptotic rate of cha

A. Faggionato

We prove a multidimensional ergodic theorem with weighted averages for the action of the group $\mathbb{Z}^d$ on a probability space. At level $n$ weights are of the form $n^{-d} \psi(j/n)$, $ j\in \mathbb{Z}^d$, for real functions $\psi$ decaying suitably fast. We discuss applications to random measures and to quenched stochastic homogenization of random wa

Feixiang Zhou, Zheheng Jiang, Huiyu Zhou, Xuelong Li

Semi-supervised temporal action segmentation (SS-TA) aims to perform frame-wise classification in long untrimmed videos, where only a fraction of videos in the training set have labels. Recent studies have shown the potential of contrastive learning in unsupervised representation learning using unlabelled data. However, learning the representation of each fr

Lorenzo Guerra, Santanil Jana

We show that the direct sum of the cohomology groups of the alternating subgroups of the family of Coxeter groups of Type B exhibits an almost-Hopf ring structure. We apply techniques developed by Giusti and Sinha to fully compute a presentation of this structure for mod 2 coefficient.

Norman Di Palo, Edward Johns

Imitation learning with visual observations is notoriously inefficient when addressed with end-to-end behavioural cloning methods. In this paper, we explore an alternative paradigm which decomposes reasoning into three phases. First, a retrieval phase, which informs the robot what it can do with an object. Second, an alignment phase, which informs the robot

HyeongGwon Hong, Yooshin Cho, Hanbyel Cho, Jaesung Ahn

Gradient inversion attacks can leak data privacy when clients share weight updates with the server in federated learning (FL). Existing studies mainly use L2 or cosine distance as the loss function for gradient matching in the attack. Our empirical investigation shows that the vulnerability ranking varies with the loss function used. Gradient norm, which is

Mark Lacy, Athena Engholm, Duncan Farrah, Kiana Ejercito

Coupling of black hole mass to the cosmic expansion has been suggested as a possible path to understanding the dark energy content of the Universe. We test this hypothesis by comparing the supermassive black hole (SMBH) mass density at $z=0$ to the total mass accreted in AGN since $z=6$, to constrain how much of the SMBH mass density can arise from cosmologi

Yucheng Li, Frank Guerin, Chenghua Lin

Data contamination in evaluation is getting increasingly prevalent with the emergence of language models pre-trained on super large, automatically crawled corpora. This problem leads to significant challenges in the accurate assessment of model capabilities and generalisations. In this paper, we propose LatestEval, an automatic method that leverages the most

Xiaojun Yuan, Yuqing Zheng, Mingchen Zhang, Boyu Teng

This paper studies a passive localization system, where an extremely large-scale antenna array (ELAA) is deployed at the base station (BS) to locate a user equipment (UE) residing in its near-field (Fresnel) region. We propose a novel algorithm, named array partitioning-based location estimation (APLE), for scalable near-field localization. The APLE algorith

Suwei Yang, Kuldeep S. Meel

Model counting, a fundamental task in computer science, involves determining the number of satisfying assignments to a Boolean formula, typically represented in conjunctive normal form (CNF). While model counting for CNF formulas has received extensive attention with a broad range of applications, the study of model counting for Pseudo-Boolean (PB) formulas

Ruiyuan Zhang, Jiaxiang Liu, Zexi Li, Hao Dong

Geometric fracture assembly presents a challenging practical task in archaeology and 3D computer vision. Previous methods have focused solely on assembling fragments based on semantic information, which has limited the quantity of objects that can be effectively assembled. Therefore, there is a need to develop a scalable framework for geometric fracture asse

Kiran Lekkala, Henghui Bao, Sumedh A. Sontakke, Erdem Biyik

Understanding visual inputs for a given task amidst varied changes is a key challenge posed by visual reinforcement learning agents. We propose \textit{Value Explicit Pretraining} (VEP), a method that learns generalizable representations for transfer reinforcement learning. VEP enables efficient learning of new tasks that share similar objectives as previous

Angela Castillo, Jonas Kohler, Juan C. Pérez, Juan Pablo Pérez

This paper presents a comprehensive study on the role of Classifier-Free Guidance (CFG) in text-conditioned diffusion models from the perspective of inference efficiency. In particular, we relax the default choice of applying CFG in all diffusion steps and instead search for efficient guidance policies. We formulate the discovery of such policies in the diff

Behzad J. Balabaygloo, Barituka Bekee, Samuel W. Blair, Suzanne Fey

To meet the grand challenges of agricultural production including climate change impacts on crop production, a tight integration of social science, technology and agriculture experts including farmers are needed. There are rapid advances in information and communication technology, precision agriculture and data analytics, which are creating a fertile field

Divya Mereddy

With advanced AI, while every industry is growing at rocket speed, the smart home industry has not reached the next generation. There is still a huge leap of innovation that needs to happen before we call a home a Smart home. A Smart home should predict residents' needs and fulfill them in a timely manner. One of the important tasks of maintaining a home is

David Charatan, Sizhe Li, Andrea Tagliasacchi, Vincent Sitzmann

We introduce pixelSplat, a feed-forward model that learns to reconstruct 3D radiance fields parameterized by 3D Gaussian primitives from pairs of images. Our model features real-time and memory-efficient rendering for scalable training as well as fast 3D reconstruction at inference time. To overcome local minima inherent to sparse and locally supported repre

Tiago D. Ferreira, Ariel Guerreiro, Nuno A. Silva

Easily accessible through tabletop experiments based on laser propagation inside nonlinear optical media, Paraxial Fluids of Light are emerging as promising platforms for the simulation and exploration of quantum-like phenomena. In particular, the analogy builds on a formal equivalence between the governing model for a Bose-Einstein Condensate under the mean

Alexander Taveira Blomenhofer, Alex Casarotti

We show that a large class of secant varieties is nondefective. In particular, we positively resolve most cases of the Baur-Draisma-de Graaf conjecture on Grassmannian secants in large dimensions. Our result improves the known bounds on nondefectivity for various other secant varieties, including Chow varieties, Segre-Veronese varieties and Gaussian moment v

Efthymios Georgiou, Yannis Avrithis, Alexandros Potamianos

Multimodal sentiment analysis (MSA) leverages heterogeneous data sources to interpret the complex nature of human sentiments. Despite significant progress in multimodal architecture design, the field lacks comprehensive regularization methods. This paper introduces PowMix, a versatile embedding space regularizer that builds upon the strengths of unimodal mix

Maxwell Hammond, Venanzio Cichella, Amirreza F. Golestaneh, Caterina Lamuta

This paper presents a method for optimal motion planning of continuum robots by employing Bernstein surfaces to approximate the system's dynamics and impose complex constraints, including collision avoidance. The main contribution is the approximation of infinite-dimensional continuous problems into their discrete counterparts, facilitating their solution us

Mackenzie A. Baird, Sushanta C. Tripathy, Kiran Jain

We investigate spatio-temporal evolution of high-degree acoustic mode frequencies of the Sun and the surface magnetic activity, over the course of multiple solar cycles, to improve our understanding of the connection between the solar interior and atmosphere. We focus on high-degree modes due to their ability to characterize conditions in the shear layer jus

Sabrina Kombrink, Lucas Schmidt

We apply recent results by the authors to obtain bounds on remainder terms of the Dirichlet Laplace eigenvalue counting function for domains that can be realised as countable disjoint unions of scaled Koch snowflakes. Moreover we compare the resulting exponents to the exponents in the asymptotic expansion of the domain's inner parallel volume.

Nicolò Dalmasso, Michele Trenti, Nicha Leethochawalit

We present a novel approach for measuring the two-point correlation function of galaxies in narrow pencil beam surveys with varying depths. Our methodology is utilized to expand high-redshift galaxy clustering investigations up to $z \sim 8$ by analyzing a comprehensive sample consisting of $N_g = 160$ Lyman break galaxy candidates obtained through optical a

Mohsen Abedi, Alexis A. Dowhuszko, Risto Wichman

Optical wireless technology has the potential to complement the wireless access services provided so far over RF. Apart from the abundant unlicensed bandwidth available for ultra-dense deployments over optical wireless bands, optical wireless also has the potential to offer inexpensive, private, secure, and environmentally friendly communications. However, t

Egon Peršak, Miguel F. Anjos

Decision-focused learning is a promising development for contextual optimisation. It enables us to train prediction models that reflect the contextual sensitivity structure of the problem. However, there have been limited attempts to extend this paradigm to robust optimisation. We propose a double implicit layer model for training prediction models with resp

Fuyudi Zhang, Fan Hu, Shishen Xian, Wei Tian

Next generation neutrino telescopes are highly anticipated to boost the development of neutrino astronomy. A multi-cubic-kilometer neutrino telescope, TRopIcal DEep-sea Neutrino Telescope (TRIDENT), was proposed to be built in the South China Sea. The detector aims to achieve ~ 0.1 degree angular resolution for track-like events at energy above 100 TeV by us

Peishen Yan, Hao Wang, Tao Song, Yang Hua

Federated Learning (FL) is becoming a popular paradigm for leveraging distributed data and preserving data privacy. However, due to the distributed characteristic, FL systems are vulnerable to Byzantine attacks that compromised clients attack the global model by uploading malicious model updates. With the development of layer-level and parameter-level fine-g

Colin Cooper, Alan Frieze

In the classical model of Diffusion Limited Aggregation (DLA), introduced by Witten and Sander, the process begins with a single particle cluster placed at the origin of a space, and then, one at a time, particles make a random walk from infinity until they collide with, and stick to, the existing cluster. We consider an analogous version of this process on

David Klaška, Antonín Kučera, Vojtěch Kůr, Vít Musil

Long-run average optimization problems for Markov decision processes (MDPs) require constructing policies with optimal steady-state behavior, i.e., optimal limit frequency of visits to the states. However, such policies may suffer from local instability, i.e., the frequency of states visited in a bounded time horizon along a run differs significantly from th

Ahmed Bouhlal, Mohammed El Azar, Ahmed Siari, Ahmed Jellal

We investigate the energy levels of fermions within a circular graphene quantum dot (GQD) subjected to external magnetic and Aharonov-Bohm fields. Solving the eigenvalue equation for two distinct regions allows us to determine the eigenspinors for the valleys $K$ and $K^\prime$. By establishing the continuity of eigenspinors at the GQD interface, we derive a

Vanessa Piccolo

We study the annealed complexity of Gaussian random homogeneous polynomials on the $(N-1)$-dimensional unit sphere in the presence of deterministic perturbations depending on fixed orthonormal vectors and external parameters. We derive variational formulas for the exponential asymptotics of the average number of critical points and local maxima. Our approach

Satyabrata Mahapatra, Sujit Kumar Sahoo, Narendra Sahu, Vicky Singh Thounaojam

In this paper, we put forward a connection between the self-interacting dark matter and the Dirac nature of neutrinos. Our exploration involves a $Z_4 \otimes Z_4'$ discrete symmetry, wherein the Dirac neutrino mass is produced through a type-I seesaw mechanism. This symmetry not only contributes to the generation of the Dirac neutrino mass but also facilita

Jason Vega, Isha Chaudhary, Changming Xu, Gagandeep Singh

With the recent surge in popularity of LLMs has come an ever-increasing need for LLM safety training. In this paper, we investigate the fragility of SOTA open-source LLMs under simple, optimization-free attacks we refer to as $\textit{priming attacks}$, which are easy to execute and effectively bypass alignment from safety training. Our proposed attack impro

Shih-Kai Chou, Jyh-Pin Chou, Alice Hu, Yuan-Chung Cheng

During the noisy intermediate-scale quantum (NISQ) era, quantum computational approaches refined to overcome the challenge of limited quantum resources are highly valuable. However, the accuracy of the molecular properties predicted by most of the quantum computations nowadays is still far off (not within chemical accuracy) compared to their corresponding ex

Evgeniya Akhmedova, Ran J. Tessler

The Amplituhedron is a subspace of the Grassmannian that was recently defined by Arkani-Hamed and Trnka in their study of scattering amplitudes in planar $\mathcal{N}=4$ super Yang Mills theory (arXiv:1312.2007), and was the subject of many papers in the last decade. In this work we define a tropical analog of the amplituhedron, and develop techniques to add

Benjamin Colburn, Jose C. Principe, Luis G. Sanchez Giraldo

Kernel Adaptive Filtering (KAF) are mathematically principled methods which search for a function in a Reproducing Kernel Hilbert Space. While they work well for tasks such as time series prediction and system identification they are plagued by a linear relationship between number of training samples and model size, hampering their use on the very large data

Zihao Qi, Chen Feng, Duolikun Danier, Fan Zhang

Unlike video coding for professional content, the delivery pipeline of User Generated Content (UGC) involves transcoding where unpristine reference content needs to be compressed repeatedly. In this work, we observe that existing full-/no-reference quality metrics fail to accurately predict the perceptual quality difference between transcoded UGC content and

Robin R. Neumann, Jürgen Henk, Ingrid Mertig, Alexander Mook

Topological magnon insulators support chiral edge excitations, whose lack of electric charge makes them notoriously difficult to detect experimentally. We show that relativistic magnetoelectric coupling universally renders chiral edge magnons electrically active, thereby facilitating electrical probes of magnon topology. Considering a two-dimensional out-of-

Zi-Yu Khoo, Gokul Rajiv, Abel Yang, Jonathan Sze Choong Low

Can a machine or algorithm discover or learn the elliptical orbit of Mars from astronomical sightings alone? Johannes Kepler required two paradigm shifts to discover his First Law regarding the elliptical orbit of Mars. Firstly, a shift from the geocentric to the heliocentric frame of reference. Secondly, the reduction of the orbit of Mars from a three- to a

Stefan Schoder

This study investigates the application of single and two-stage 2D-object detection algorithms like You Only Look Once (YOLO), Real-Time DEtection TRansformer (RT-DETR) algorithm for automated object detection to enhance road safety for autonomous driving on Austrian roads. The YOLO algorithm is a state-of-the-art real-time object detection system known for

Esther Banaian, Sunita Chepuri, Elizabeth Kelley, Sylvester W. Zhang

Graph LP algebras are a generalization of cluster algebras introduced by Lam and Pylyavskyy. We provide a combinatorial proof of positivity for certain cluster variables in these algebras. This proof uses a hypergraph generalization of snake graphs, a class of planar graphs which were used by Musiker, Schiffler, and Williams to prove positivity for cluster a

Maxwell Hammond, Venanzio Cichella, Caterina Lamuta

Purpose of Review: This review provides an overview of the state of the art in bioinspired soft robotics with by examining advancements in actuation, functionality, modeling, and control. Recent Findings: Recent research into actuation methods, such as artificial muscles, have expanded the functionality and potential use of bioinspired soft robots. Additiona

Bobby Samir Acharya, Daniel Andrew Baldwin

Inspired by considerations in $M$-theory, we prove the equivalence between the moduli spaces of (suitably complexified) torsion free $G_{2}$-structures on 7-manifolds which are families of hyperK\"ahler ALE 4-manifolds fibered over compact flat 3-manifolds $T^{3}/K$ and certain moduli spaces of flat $G^{\mathbb{C}}_{ADE}$ connections on $T^{3}/K$.

Shao-Xiong Wu, Cheng-Hua Bai, Gang Li, Chang-shui Yu

We propose a theoretical project in which quantum squeezing induces quantum entanglement and Einstein-Podolsky-Rosen steering in a coupled whispering-gallery-mode optomechanical system. Through pumping the $\chi^{(2)}$-nonlinear resonator with the phase matching condition, the generated squeezed resonator mode and the mechanical mode of the optomechanical re

Demircan Tas, Dimitrios Chatzinikolis

Remote collaboration is a common reality of spatial design processes, but tools for computer aided design were made for single users. Via TeamCAD, we introduce a user experience where online remote collaboration experience is more like working on a table. Using speech and gesture recognition based on state of the art machine learning through webcam and micro

Sabrina Kombrink, Lucas Schmidt

We provide a new constructive method for obtaining explicit remainder estimates of eigenvalue counting functions of Neumann Laplacians on domains with fractal boundary. This is done by establishing estimates for first non-trivial eigenvalues through Rayleigh quotients. A main focus lies on domains whose boundary can locally be represented as a limit set of a

Govert Nijs, Bruno Scheihing-Hitschfeld, Xiaojun Yao

We report on progress in the nonperturbative understanding of quarkonium dynamics inside a thermal plasma. The time evolution of small-size quarkonium is governed by two-point correlation functions of chromoelectric fields dressed with an adjoint Wilson line, known in this context as generalized gluon distributions (GGDs). The GGDs have been calculated in bo

A. Psaltis, M. Jacobi, F. Montes, A. Arcones

The elemental abundances between strontium and silver ($Z = 38-47$) observed in the atmospheres of very metal-poor stars (VMP) in the Galaxy may contain the fingerprint of the weak $r$-process and $\nu p$-process occurring in early core-collapse supernovae explosions. In this work, we combine various astrophysical conditions based on a steady-state model to

Richard J. Martin

We give a new improvement over Newton's method for root-finding, when the function in question is doubly differentiable. It generally exhibits faster and more reliable convergence. It can be also be thought of as a correction to Halley's method, as this can exhibit undesirable behaviour.

Zhen Li, Steen H. Hansen

Understanding the nature of dark matter is among the top priorities of modern physics. However, due to its inertness, detecting and studying it directly in terrestrial experiments is extremely challenging. Numerical N-body simulations currently represent the best approach for studying the particle properties and phase space distribution, assuming the collisi

Adam Richardson, Boi Faltings

Peer prediction incentive mechanisms for crowdsourcing are generally limited to eliciting samples from categorical distributions. Prior work on extending peer prediction to arbitrary distributions has largely relied on assumptions on the structures of the distributions or known properties of the data providers. We introduce a novel class of incentive mechani

L. Filipe O. Costa, José Natário

It has been suggested in recent literature that nonlinear and/or gravitomagnetic general relativistic effects can play a leading role in galactic dynamics, partially or totally replacing dark matter. Using the 1+3 "quasi-Maxwell" formalism, we show, on general grounds, such hypothesis to be impossible.

Alexandra-Gabriela Serban, Andrea Coronetti, Ruben Garcia Alia, Francesc Salvat Pujol

FLUKA is among the general-purpose codes for the Monte Carlo simulation of radiation transport that are routinely employed to estimate the production of single-event-upsets (SEUs) in commercial static random access memories (SRAMs) exposed to radiation. Earlier studies concerning the production of SEUs in commercial SRAMs under proton irradiation revealed ve