arXiv papers from July 2024

Yingyi Huang

In contrast to conventional Weyl semimetals in achiral crystals, chiral topological semimetals in chiral crystals exhibit Weyl nodes at time-reversal-invariant momenta. A Fermi surface spin texture with parallel spin-momentum locking in these material has been observed by a recent experiment [Nat. Comm. 15,3720(2024)]. We find that the Weyl nodes location an

Michael Hartung, Andreas Maier, Yuliya Burankova, Fernando Delgado-Chaves

Unsupervised patient stratification is essential for disease subtype discovery, yet, despite growing evidence of molecular heterogeneity of non-oncological diseases, popular methods are benchmarked primarily using cancers with mutually exclusive molecular subtypes well-differentiated by numerous biomarkers. Evaluating 22 unsupervised methods, including clust

Takashi Yokokura, Chao Duan, Rui Wang

Polyelectrolyte (PE) brushes have ubiquitous applications as surface modifiers which regulate various structural and dynamic properties. Here, we apply a continuous-space self-consistent field theory to study the structural heterogeneity in PE brushes induced by competing electrostatic and hydrophobic interactions. For brushes with high grafting densities, w

Landon Dyken, Saugat Adhikari, Pravin Poudel, Steve Petruzza

Mapping the extent of flood events is a necessary and important aspect of disaster management. In recent years, deep learning methods have evolved as an effective tool to quickly label high resolution imagery and provide necessary flood extent mappings. These methods, though, require large amounts of annotated training data to create models that are accurate

Jesse Franklin, Sheng-Yang Kevin Ho, Mihran Papikian

We study the Drinfeld modular curves arising from the Hecke congruence subgroups of $\mathrm{SL}_2(\mathbb{F}_q[T])$. Using a combinatorial method of Gekeler and Nonnengardt, we obtain a genus formula for these curves. In cases when the genus is one, we compute the Weierstrass equation of the corresponding curve.

Elijah Pelofske, Vincent Urias, Lorie M. Liebrock

Generative Pre-Trained Transformer models have been shown to be surprisingly effective at a variety of natural language processing tasks -- including generating computer code. We evaluate the effectiveness of open source GPT models for the task of automatic identification of the presence of vulnerable code syntax (specifically targeting C and C++ source code

Nils Demerlé, Philippe Esling, Guillaume Doras, David Genova

Deep generative models are now able to synthesize high-quality audio signals, shifting the critical aspect in their development from audio quality to control capabilities. Although text-to-music generation is getting largely adopted by the general public, explicit control and example-based style transfer are more adequate modalities to capture the intents of

Haruo Minami

Let $G$ be a compact simple Lie group equipped with the left invariant framing $L$. It is known that there are several groups $G$ such that $(G, L)$ is non-null framed bordant. Previously we gave an alternative proof of these results using the decomposition formula of its bordism class into a Kronecker product by E. Ossa. In this note we propose a verificati

Frederic Hummel, Sebastian Weber, Johannes Moegerle, Henri Menke

Quantum information processing with neutral atoms relies on Rydberg excitation for entanglement generation. While the use of heavy divalent or open-shell elements, such as strontium or ytterbium, has benefits due to their optically active core and a variety of possible qubit encodings, their Rydberg structure is generally complex. For some isotopes in partic

E. G. S. Luna, M. G. Ryskin

The multiplicity distribution of charged particles produced in the central rapidity ($|\eta|<2.5$) region is calculated for the eikonal and the $U$-matrix unitarization schemes using the AGK cutting rules and compared with the ATLAS 13 TeV data. The data favours the eikonal approach.

Sazzad Sayyed, Milin Zhang, Shahriar Rifat, Ananthram Swami

In order to deploy deep neural networks (DNNs) in high-stakes scenarios, it is imperative that DNNs provide inference robust to external perturbations - both intentional and unintentional. Although the resilience of DNNs to intentional and unintentional perturbations has been widely investigated, a unified vision of these inherently intertwined problem domai

Jacob Ashworth, Luca Grossmann, Fausto Navarro, Leyda Almodovar

Recent advancements in microbiology have motivated the study of the production of nanostructures with applications such as biomedical computing and molecular robotics. One way to construct these structures is to construct branched DNA molecules that bond to each other at complementary cohesive ends. One practical question is: given a target nanostructure, wh

Andrea Kim, Niloufar Saharkhiz, Elena Sizikova, Miguel Lago

Development of artificial intelligence (AI) techniques in medical imaging requires access to large-scale and diverse datasets for training and evaluation. In dermatology, obtaining such datasets remains challenging due to significant variations in patient populations, illumination conditions, and acquisition system characteristics. In this work, we propose S

Sahabub Jahedi, Abhik Sarkar

We analyze lepton flavor violation (LFV) using the Standard Model Effective Field Theory (SMEFT) framework at the future lepton colliders. Our focus is on the associated production of tau lepton with electron/muon at the electron-positron ($e^+e^-$) colliders, related to four-Fermi SMEFT effective operators. In accordance with the upper limits on effective c

Ganga P. Sharma, Shantanu Chakraborty, Bilas Paul

Physics has a reputation among majority of life sciences students for being very complicated and tough. If we leave students with this impression, it is likely that students see physics class as useless and irrelevant to life sciences. Concepts of physics are vital in oder to understand physics based technological tools and biophysical topics essential and r

L. Costa, I. Macías Tarrío, L. Roa-Leguizamón

Let X be a smooth irreducible projective surface. The aim of this paper is to establish a version of Clifford's theorem for coherent systems on X.

Ghaith Hiary, Summer Ireland, Megan Kyi

Riemann numerically approximated at least three zeta zeros. According to Edwards, Riemann even took steps to verify that the lowest zero he computed was indeed the first zeta zero. This approach to verification is developed, improved, and generalized to a large class of $L$-functions. Results of numerical calculations demonstrating the efficacy of the method

Hao Zhong, Leqi Zhao

This paper presents a symbolic computation method for automatically transforming $q$-hypergeometric identities to $q$-binomial identities. Through this method, many previously proven $q$-binomial identities, including $q$-Saalsch\"utz's formula and $q$-Suranyi's formula, are re-fund, and numerous new ones are discovered. Moreover, the generation of the ident

Fabian Hotz, Matjaž Gomilšek, Tina Arh, Thomas Hicken

The quantum behavior of light nuclei and other particles in materials challenges classical intuition and introduces novel phenomena. Here we demonstrate that muon spin spectroscopy ( $\mu$SR) is a powerful tool for exploring the quantum effects of light particles, such as the muon, in condensed matter. The muon's quantum nature is profoundly influenced by th

Amir Akbary, Yash Totani

Let $-D$ be a fundamental discriminant. We express the number of representations of an integer by a positive definite binary quadratic form of discriminant $-D$ with an odd class number $h(-D)$ as a rational linear expression involving the Kronecker symbol $\left(\frac{-D}{.}\right)$ and the Fourier coefficients of certain cusp forms. We prove these cusp for

Alain Couvreur, Gilles Zémor

Freiman's $3k-4$ Theorem states that if a subset $A$ of $k$ integers has a Minkowski sum $A+A$ of size at most $3k-4$, then it must be contained in a short arithmetic progression. We prove a function field analogue that is also a generalisation: it states that if $K$ is a perfect field and if $S\supset K$ is a vector space of dimension $k$ inside an extensio

Marius L. Palm, Chaoxin Ding, William S. Huxter, Takashi Taniguchi

Electron-electron interactions in high-mobility conductors can give rise to transport signatures resembling those described by classical hydrodynamics. Using a nanoscale scanning magnetometer, we imaged a distinctive hydrodynamic transport pattern - stationary current vortices - in a monolayer graphene device at room temperature. By measuring devices with in

Shreyank N Gowda, David A. Clifton

The Segment Anything Model (SAM) has achieved remarkable successes in the realm of natural image segmentation, but its deployment in the medical imaging sphere has encountered challenges. Specifically, the model struggles with medical images that feature low contrast, faint boundaries, intricate morphologies, and small-sized objects. To address these challen

Leonardo Ermann, Dima L. Shepelyansky

We introduce the Ising Network Opinion Formation (INOF) model and apply it for the analysis of networks of 6 Wikipedia language editions. In the model, Ising spins are placed at network nodes/articles and the steady-state opinion polarization of spins is determined from the Monte Carlo iterations in which a given spin orientation is determined by in-going li

A. O. Nelson, C. Vincent, H. Anand, J. Lovell

A plasma scenario with negative triangularity (NT) shaping is achieved on MAST-U for the first time. While edge localized modes (ELMs) are eventually suppressed as the triangularity is decreased below $\delta$ < -0.06, an extended period of H-mode operation with Type-III ELMs is sustained at less negative $\delta$ even through access to the second stability

Simon Hartmann, Uwe Thiele

We present a mesoscopic hydrodynamic model for a spreading drop of volatile partially wetting liquid on a solid porous layer of small thickness. Thereby, evaporation takes place under strong confinement, i.e., we consider a drop that spreads on one of two parallel plates that form a narrow gap. Our gradient dynamics model describes the coupled dynamics of th

Georgios Papagiannis, Kamil Dreczkowski, Vitalis Vosylius, Edward Johns

In this paper, we study the problem of adapting manipulation trajectories involving grasped objects (e.g. tools) defined for a single grasp pose to novel grasp poses. A common approach to address this is to define a new trajectory for each possible grasp explicitly, but this is highly inefficient. Instead, we propose a method to adapt such trajectories direc

Chengqian Xian, Camila P. E. de Souza, Wenqing He, Felipe F. Rodrigues

Correlated survival data are prevalent in various clinical settings and have been extensively discussed in literature. One of the most common types of correlated survival data is clustered survival data, where the survival times from individuals in a cluster are associated. Our study is motivated by invasive mechanical ventilation data from different intensi

Liam Wheen, Oscar Benjamin

As part of the Bristol PROVE mission, a nano satellite in low Earth orbit will be required to track a ground based target during a 400 second flyover. This requires agile attitude control that will be achieved using a system of flywheels. To calculate the necessary torque from these flywheels, a controller was designed. Using newly derived equations of motio

A. M. Moro, J. Casal, M. Gomez-Ramos

We give an overview of the theoretical description of nuclear reactions involving weakly-bound nuclei. Some of the more widespread reaction formalisms employed in the analysis of these reactions are briefly introduced, including various recent developments. We put special emphasis on the continuum-discretized coupled-channel (CDCC) method and its extensions

P. Hanlet, M. Gonzalez, J. Diamond, K. S. Martin

Fermilab has traditionally not been an EPICS house; as such expertise in EPICS is limited and scattered. PIP-II will be using EPICS for its control system. When in operation, it will need to interface with the existing, modernized (see ACORN) legacy control system. Treating EPICS controls at Fermilab as a green field, we have developed and deployed a softwar

Huy Truong, Pietro Poggi-Corradini

Homogeneous matroids are characterized by the property that strength equals fractional arboricity, and arise in the study of base modulus [22]. For graphic matroids, Cunningham [9] provided efficient algorithms for calculating graph strength, and also for determining minimum cost reinforcement to achieve a desired strength. This paper extends this latter pro

Mandana Amiri, Arnab Chakraborty, Simon Foreman, Mark Halpern

We present the first results of the holographic beam mapping program for the Canadian Hydrogen Intensity Mapping Experiment (CHIME). We describe the implementation of the holographic technique as adapted for CHIME, and introduce the processing pipeline which prepares the raw holographic timestreams for analysis of beam features. We use data from six bright s

Andreas Athenodorou, Ed Bennett, Georg Bergner, Pietro Butti

We provide an extended lattice study of the SU(2) gauge theory coupled to one Dirac fermion flavour ($N_{\mathrm{f}} =1$) transforming in the adjoint representation as the continuum limit is approached. This investigation is supplemented by numerical results obtained for the SU(2) gauge theory with two Dirac fermion flavours ($N_{\mathrm{f}} =2$) transformin

Lingyu Zhang, Zhengran Ji, Boyuan Chen

With the increasing deployment of artificial intelligence (AI) technologies, the potential of humans working with AI agents has been growing at a great speed. Human-AI teaming is an important paradigm for studying various aspects when humans and AI agents work together. The unique aspect of Human-AI teaming research is the need to jointly study humans and AI

Stéphane Vujasinović, Stefan Becker, Sebastian Bullinger, Norbert Scherer-Negenborn

In this paper, we introduce a variant of video object segmentation (VOS) that bridges interactive and semi-automatic approaches, termed Lazy Video Object Segmentation (ziVOS). In contrast, to both tasks, which handle video object segmentation in an off-line manner (i.e., pre-recorded sequences), we propose through ziVOS to target online recorded sequences. H

Rahil N. Valani, Bruno S. Dandogbessi

On applying a small bias force, non-equilibrium systems may respond in paradoxical ways such as with giant negative mobility (GNM) -- a large net drift opposite to the applied bias, or giant positive mobility (GPM) -- an anomalously large drift in the same direction as the applied bias. Such behaviors have been extensively studied in idealized models of exte

Giulio Corallo, Paolo Papotti

Recent large language model applications, such as Retrieval-Augmented Generation and chatbots, have led to an increased need to process longer input contexts. However, this requirement is hampered by inherent limitations. Architecturally, models are constrained by a context window defined during training. Additionally, processing extensive texts requires sub

Thanet Markchom, Huizhi Liang, James Ferryman

Explainability of recommender systems has become essential to ensure users' trust and satisfaction. Various types of explainable recommender systems have been proposed including explainable graph-based recommender systems. This review paper discusses state-of-the-art approaches of these systems and categorizes them based on three aspects: learning methods, e

Yuanqing Wang, Kyunghyun Cho

Rethink convolution-based graph neural networks (GNN) -- they characteristically suffer from limited expressiveness, over-smoothing, and over-squashing, and require specialized sparse kernels for efficient computation. Here, we design a simple graph learning module entirely free of convolution operators, coined random walk with unifying memory (RUM) neural n

Carlos Toxtli, Christopher Curtis, Saiph Savage

Crowdsourcing markets are expanding worldwide, but often feature standardized interfaces that ignore the cultural diversity of their workers, negatively impacting their well-being and productivity. To transform these workplace dynamics, this paper proposes creating culturally-aware workplace tools, specifically designed to adapt to the cultural dimensions of

Manish Ramchander

We study the half-sided translations associated to Rindler wedge algebras for conformal field theories in 1+1 Minkowski spacetime, generated by an unbounded operator $\mathcal{G}$, in terms of bilinear forms $G, G'$ made from entanglement Hamiltonians of the underlying algebras such that $\mathcal{G} = G+G'$. We show that despite entanglement Hamiltonians be

Simonetta Liuti, Douglas Adams, Marie Boër, Gia-Wei Chern

In overview of the recent activity of the newly funded EXCLusives with AI and Machine learning (EXCLAIM) collaboration is presented. The main goal of the collaboration is to develop a framework to implement AI and machine learning techniques in problems emerging from the phenomenology of high energy exclusive scattering processes from nucleons and nuclei, ma

Gandalf Nicolas, Aylin Caliskan

This study introduces a taxonomy of stereotype content in contemporary large language models (LLMs). We prompt ChatGPT 3.5, Llama 3, and Mixtral 8x7B, three powerful and widely used LLMs, for the characteristics associated with 87 social categories (e.g., gender, race, occupations). We identify 14 stereotype dimensions (e.g., Morality, Ability, Health, Belie

Ying Li, Rahul Singh, Tarun Joshi, Agus Sudjianto

Recent work in behavioral testing for natural language processing (NLP) models, such as Checklist, is inspired by related paradigms in software engineering testing. They allow evaluation of general linguistic capabilities and domain understanding, hence can help evaluate conceptual soundness and identify model weaknesses. However, a major challenge is the cr

Mridul Khurana, Arka Daw, M. Maruf, Josef C. Uyeda

A central problem in biology is to understand how organisms evolve and adapt to their environment by acquiring variations in the observable characteristics or traits of species across the tree of life. With the growing availability of large-scale image repositories in biology and recent advances in generative modeling, there is an opportunity to accelerate t

Junxian He, Shrinivas Pundlik, Gang Luo

Objective: Micro-navigation poses challenges for blind and visually impaired individuals. They often need to ask for sighted assistance. We explored the feasibility of utilizing ChatGPT as a virtual assistant to provide navigation directions. Methods: We created a test set of outdoor and indoor micro-navigation scenarios consisting of 113 scene images and th

Rabindra Basnet, Jin Hu

Over the past two decades, significant progress in two-dimensional (2D) materials has invigorated research in condensed matter and material physics in low dimensions. While traditionally studied in three-dimensional systems, magnetism has now been extended to the 2D realm. Recent breakthroughs in 2D magnetism have captured substantial interest from the scien

Teng Ee Yap, Konstantin Batygin

The degree of coupling between dust particles and their surrounding gas in protoplanetary disks is quantified by the dimensionless Stokes number. The Stokes number (St) governs particle size and spatial distributions, in turn establishing the dominant mode of planetary accretion in different disk regions. In this paper, we model the characteristic St of part

Chai Wah Wu

We study the square of opposition and its various geometric generalizations from an algebraic viewpoint. In particular, we show how the various shapes of oppositions can be framed under an algebraic framework and we illustrate this approach with algebraic structures beyond the traditional logical structures.

Sheng-En Huang, Kazi Farha Farzana Suhi, Md Jahidul Islam

Existing technologies for distributed light-field mapping and light pollution monitoring (LPM) rely on either remote satellite imagery or manual light surveying with single-point sensors such as SQMs (sky quality meters). These modalities offer low-resolution data that are not informative for dense light-field mapping, pollutant factor identification, or sus

Jiyoung Lee, Keeheon Lee

This research investigates the extent of misinformation in certain journalistic articles by introducing a novel measurement tool to assess the degrees of falsity. It aims to measure misinformation using two metrics (concealment and overstatement) to explore how information is interpreted as false. This should help examine how articles containing partly true

David W. Jensen

Designing for rotational stability can dramatically affect the geometry of a space station. If improperly designed, the rotating station could end up catastrophically tumbling end-over-end. Active stabilization can address this problem; however, designing the station with passive rotation stability provides a lower-cost solution. This paper presents passive

Níckolas de Aguiar Alves, Andre G. S. Landulfo, Bruno Arderucio Costa

A long-standing problem in physics is why observed masses are always positive. While energy conditions in quantum field theory can partly answer this problem, in this paper we find evidence that classical general relativity abhors negative masses, without the need for quantum theory or energy conditions. This is done by considering many different models of n

Jason Sinaga, Victoria Clerico, Md Abdullah-Al Kaiser, Shay Snyder

Recent advances in retinal neuroscience have fueled various hardware and algorithmic efforts to develop retina-inspired solutions for computer vision tasks. In this work, we focus on a fundamental visual feature within the mammalian retina, Object Motion Sensitivity (OMS). Using DVS data from EV-IMO dataset, we analyze the performance of an algorithmic imple

Arumoy Shome, Luis Cruz, Diomidis Spinellis, Arie van Deursen

The machine learning development lifecycle is characterized by iterative and exploratory processes that rely on feedback mechanisms to ensure data and model integrity. Despite the critical role of feedback in machine learning engineering, no prior research has been conducted to identify and understand these mechanisms. To address this knowledge gap, we mine

David W. Jensen

As the space industry matures, large space stations will be built. This paper organizes and documents constraints on the size of these space stations. Human frailty, station design, and construction impose these constraints. Human limitations include gravity, radiation, air pressure, rotational stability, population, and psychology. Station design limitation

Lucrezia Grassi, Carmine Tommaso Recchiuto, Antonio Sgorbissa

This research investigates the impact of social robot participation in group conversations and assesses the effectiveness of various addressing policies. The study involved 300 participants, divided into groups of four, interacting with a humanoid robot serving as the moderator. The robot utilized conversation data to determine the most appropriate speaker t

Kaiyuan Tang, Chaoli Wang

In volume visualization, visualization synthesis has attracted much attention due to its ability to generate novel visualizations without following the conventional rendering pipeline. However, existing solutions based on generative adversarial networks often require many training images and take significant training time. Still, issues such as low quality,

E. M. Ainley, A. Agrawal, D. Main, P. Drmota

Scaling the number of entangled nodes in a quantum network is a challenge with significant implications for quantum computing, clock synchronisation, secure communications, and quantum sensing. In a quantum network, photons interact with matter qubits at different nodes, flexibly enabling the creation of remote entanglement between them. Multipartite entangl

Fei Cao, Stephanie Reed

In this paper, we introduce the Iterative Persuasion-Polarization (IPP) model to study the dynamics of opinion formation and change within a population. The IPP model integrates mechanisms of persuasion and repulsion, where individuals influence each other through interactions that can either align opinions incrementally or lead to greater divergence. The pr

Colin Shea-Blymyer, Houssam Abbas

When designing agents for operation in uncertain environments, designers need tools to automatically reason about what agents ought to do, how that conflicts with what is actually happening, and how a policy might be modified to remove the conflict. These obligations include ethical and social obligations, permissions and prohibitions, which constrain how th

Bashir Elbousefi, William Schupbach, Kannan N. Premnath, Samuel W. J. Welch

Self-rewetting fluids (SRFs) (e.g., aqueous solutions of long-chain alcohols) show anomalous nonlinear (quadratic) variations of surface tension with temperature involving a positive gradient, leading to different thermocapillary convection compared to normal fluids (NFs). Moreover, surface-active materials or surfactants can significantly alter interfacial

Siqi Liang, Sumyeong Ahn, Jiayu Zhou

Advancements in large language models (LLMs) have shown their effectiveness in multiple complicated natural language reasoning tasks. A key challenge remains in adapting these models efficiently to new or unfamiliar tasks. In-context learning (ICL) provides a promising solution for few-shot adaptation by retrieving a set of data points relevant to a query, c

Bhargav Karamched, Jack Schmidt, David Murrugarra

Many systems in biology, physics, and engineering are modeled by nonlinear dynamical systems where the states are usually unknown and only a subset of the state variables can be physically measured. Can we understand the full system from what we measure? In the mathematics literature, this question is framed as the observability problem. It has to do with re

Yao Hu, Haihui Lan, Bo Hu, Jiaxuan Gong

Nanometric solid solution alloys are utilized in a broad range of fields, including catalysis, energy storage, medical application, and sensor technology. Unfortunately, the synthesis of these alloys becomes increasingly challenging as the disparity between the metal elements grows, due to differences in atomic sizes, melting points, and chemical affinities.

Alexey N. Pyrkov, Ilia D. Lazarev, Tim Byrnes

Distributing long-distance entanglement is a fundamental goal that is necessary for a variety of tasks such as quantum communication, distributed quantum computing, and quantum metrology. Currently quantum repeater schemes typically aim to distribute one ebit at a time, the equivalent of one Bell pair's worth of entanglement. Here we present a method to dist

J. Gregorio-Hetem, A. Hetem

Recent studies have identified star clusters with multiple components based on accurate spatial distributions and/or proper motions from Gaia DR3, utilising diverse diagnostics to improve our understanding of subgroup evolution. These findings motivated us to search for subgroups among the objects examined in our previous work, which employed fractal statist

Letizia Iannucci, Ali Faqeeh, Ali Salloum, Ted Hsuan Yun Chen

The related concepts of partisan belief systems, issue alignment, and partisan sorting are central to our understanding of politics. These phenomena have been studied using measures of alignment between pairs of topics, or how much individuals' attitudes toward a topic reveal about their attitudes toward another topic. We introduce a higher-order measure tha

Ghislain Raze, Gaëtan Abeloos, Gaëtan Kerschen

Experimental continuation encompasses a set of methods that combine control and continuation to obtain the full bifurcation diagram of a nonlinear system experimentally, including responses that would be unstable in the system without feedback control. Such control-based methods thus allow the experimenter to directly and exhaustively explore the dynamics of

Sangwon Yu, Jongyoon Song, Bongkyu Hwang, Hoyoung Kang

A binary decision task, like yes-no questions or answer verification, reflects a significant real-world scenario such as where users look for confirmation about the correctness of their decisions on specific issues. In this work, we observe that language models exhibit a negative bias in the binary decisions of complex reasoning tasks. Based on our observati

Jesus Silva-Rodriguez, Elias Raffoul, Xingpeng Li

The rising integration of variable renewable energy sources (RES), like solar and wind power, introduces considerable uncertainty in grid operations and energy management. Effective forecasting models are essential for grid operators to anticipate the net load - the difference between consumer electrical demand and renewable power generation. This paper prop

Daniel Baratta, Luigi Muglia, Domenico Vuono

We consider solutions to degenerate anisotropic elliptic equations in order to study their regularity. In particular we establish second-order estimates and enclose regularity results for the stress field. All our results are new even in the euclidean case.

Mark Edelman

In regular dynamics, discrete maps are model presentations of discrete dynamical systems, and they may approximate continuous dynamical systems. Maps are used to investigate general properties of dynamical systems and to model various natural and socioeconomic systems. They are also used in engineering. Many natural and almost all socioeconomic systems posse

Asad Ali, Saif Al-Kuwari, M. I. Hussain, Tim Byrnes

This study examines the performance of finite spin quantum batteries (QBs) using Heisenberg spin models with Dzyaloshinsky-Moriya (DM) and Kaplan--Shekhtman--Entin-Wohlman--Aharony (KSEA) interactions. The QBs are modeled as interacting quantum spins in local inhomogeneous magnetic fields, inducing variable Zeeman splitting. We derive analytical expressions

Giorgio Leone

In this Thesis we investigate properties of stability, rigidity and unitarity of the string landscape in ten and lower dimensions. The dissertation explores these aspects by intertwining a detailed analysis of string vacua, with and without supersymmetry, with a bottom-up study driven by unitarity. In particular, in Chapter 1 the possibility of formulating a

Patrick Kuiper, Ali Hasan, Wenhao Yang, Yuting Ng

The goal of this paper is to develop distributionally robust optimization (DRO) estimators, specifically for multidimensional Extreme Value Theory (EVT) statistics. EVT supports using semi-parametric models called max-stable distributions built from spatial Poisson point processes. While powerful, these models are only asymptotically valid for large samples.

Fabian Kröninger, Caroline Lasser, Jiri J. L. Vanicek

When computing quantum-mechanical observables, the ``curse of dimensionality'' limits the naive approach that uses the quantum-mechanical wavefunction. The semiclassical Herman--Kluk propagator mitigates this curse by employing a grid-free ansatz to evaluate the expectation values of these observables. Here, we investigate quadrature techniques for this high

Minxing Zhang, Ahmed Salem, Michael Backes, Yang Zhang

The increasing cost of training machine learning (ML) models has led to the inclusion of new parties to the training pipeline, such as users who contribute training data and companies that provide computing resources. This involvement of such new parties in the ML training process has introduced new attack surfaces for an adversary to exploit. A recent attac

Benjamin Dodson

In this paper we prove a rigidity result for a solution to the non self-dual Chern--Simons--Schr{\"o}dinger equation at the level of the soliton.

Yinshan Chang, Xue Peng

In this paper, we consider the Littlewood-Offord problems in one dimension for the Curie-Weiss models. Let \[Q_n^{+}:=\sup_{x\in\mathbb{R}}\sup_{v_1,v_2,\ldots,v_n\geq 1}P(\sum_{i=1}^{n}v_i\varepsilon_i\in(x-1,x+1)),\] \[Q_n=\sup_{x\in\mathbb{R}}\sup_{|v_1|,|v_2|,\ldots,|v_n|\geq 1}P(\sum_{i=1}^{n}v_i\varepsilon_i\in(x-1,x+1))\] where the random variables $(

Z. Jennings, J. Southworth, S. A. Rappaport, T. Borkovits

Stellar theory enables us to understand the properties of stars at different stages of their evolution, and contributes to other fields of astrophysics such as galactic and exoplanet studies. Assessing the accuracy of stellar theories necessitates high precision, model-independent measurements of the properties of real stars, such as those obtainable for the

Tin Long Sunny Wong, Christopher White, Lars Bildsten

Type Ia supernovae arise from thermonuclear explosions of white dwarfs accreting from a binary companion. Following the explosion, the surviving donor star leaves at roughly its orbital velocity. The discovery of the runaway helium subdwarf star US 708, and seven hypervelocity stars from Gaia data, all with spatial velocities $\gtrsim 900$ km/s, strongly sup

Martin Stanek

The Monte Carlo method, proposed by Dell'Amico and Filippone, estimates a password's rank within a probabilistic model for password generation, i.e., it determines the password's strength according to this model. We propose several ideas to improve the precision or speed of the estimation. Through experimental tests, we demonstrate that improved sampling can

Zheqi Lv, Shaoxuan He, Tianyu Zhan, Shengyu Zhang

Dynamic sequential recommendation (DSR) can generate model parameters based on user behavior to improve the personalization of sequential recommendation under various user preferences. However, it faces the challenges of large parameter search space and sparse and noisy user-item interactions, which reduces the applicability of the generated model parameters

Yufang Hou, Thy Thy Tran, Doan Nam Long Vu, Yiwen Cao

This paper presents a shared task that we organized at the Foundations of Language Technology (FoLT) course in 2023/2024 at the Technical University of Darmstadt, which focuses on evaluating the output of Large Language Models (LLMs) in generating harmful answers to health-related clinical questions. We describe the task design considerations and report the

Ricardo Chicalé, Vanderlei Horita

We prove existence and uniqueness of absolutely continuous invariant measures for generalizations of Viana maps admitting a higher order critical point introduced in arXiv:2312.00906. As a consequence of our approach, we obtain super-polynomial decay of correlations.

Minghan Chu

This proposed work introduces a data-assimilation-assisted approach to train neural networks, aimed at effectively reducing epistemic uncertainty in state estimates of separated flows. This method, referred to as model-consistent training, ensures that input features are derived directly from physics-based models, such as Reynolds Averaged Navier Stokes (RAN

Robert de Keijzer, Jurgen Snijders, André Carvalho, Servaas Kokkelmans

Parametrized gate circuits are used in plentiful applications in the current NISQ era of quantum computing. These parametrized gates are chiefly implemented using analytically found pulse protocols, often yielding suboptimal gate times, and consequently, fidelities. Alternatively, gate optimization algorithms are designed to construct high fidelity pulses fo

Gemma Team, Morgane Riviere, Shreya Pathak, Pier Giuseppe Sessa

In this work, we introduce Gemma 2, a new addition to the Gemma family of lightweight, state-of-the-art open models, ranging in scale from 2 billion to 27 billion parameters. In this new version, we apply several known technical modifications to the Transformer architecture, such as interleaving local-global attentions (Beltagy et al., 2020a) and group-query

Doğa Yılmaz, He Wang, Towaki Takikawa, Duygu Ceylan

Emerging immersive display technologies efficiently utilize resources with perceptual graphics methods such as foveated rendering and denoising. Running multiple perceptual graphics methods challenges devices with limited power and computational resources. We propose a computationally-lightweight learned multitasking perceptual graphics model. Given RGB imag

Xusheng Luo, Tianhao Wei, Simin Liu, Ziwei Wang

This work addresses the certification of the local robustness of vision-based two-stage 6D object pose estimation. The two-stage method for object pose estimation achieves superior accuracy by first employing deep neural network-driven keypoint regression and then applying a Perspective-n-Point (PnP) technique. Despite advancements, the certification of thes

Omar Fawzi, Mizanur Rahaman, Mostafa Taheri

Given a quantum Markovian noise model, we study the maximum dimension of a classical or quantum system that can be stored for arbitrarily large time. We show that, unlike the fixed time setting, in the limit of infinite time, the classical and quantum capacities are characterized by efficiently computable properties of the peripheral spectrum of the quantum

Valentin Leeb, Johannes Knolle

Quantum oscillation (QOs) measurements constitute one of the most powerful methods for determining the Fermi surface (FS) of metals, exploiting the famous Onsager relation between the FS area and the QO frequency. The recent observation of non-Onsager QOs with a frequency set by the difference of two FS orbits in a bulk three-dimensional metal can be underst

Kewei Cheng, Jingfeng Yang, Haoming Jiang, Zhengyang Wang

Reasoning encompasses two typical types: deductive reasoning and inductive reasoning. Despite extensive research into the reasoning capabilities of Large Language Models (LLMs), most studies have failed to rigorously differentiate between inductive and deductive reasoning, leading to a blending of the two. This raises an essential question: In LLM reasoning,

Adam Karvonen, Benjamin Wright, Can Rager, Rico Angell

What latent features are encoded in language model (LM) representations? Recent work on training sparse autoencoders (SAEs) to disentangle interpretable features in LM representations has shown significant promise. However, evaluating the quality of these SAEs is difficult because we lack a ground-truth collection of interpretable features that we expect goo

Wenyuan Chen, Haocong Song, Changsheng Dai, Aojun Jiang

Traditional sperm morphology analysis is based on tedious manual annotation. Automated morphology analysis of a high number of sperm requires accurate segmentation of each sperm part and quantitative morphology evaluation. State-of-the-art instance-aware part segmentation networks follow a "detect-then-segment" paradigm. However, due to sperm's slim shape, t

Armando Genco, Charalambos Louca, Cristina Cruciano, Kok Wee Song

Ultrafast all-optical logic devices based on nonlinear light-matter interactions hold the promise to overcome the speed limitations of conventional electronic devices. Strong coupling of excitons and photons inside an optical resonator enhances such interactions and generates new polariton states which give access to unique nonlinear phenomena, such as Bose-

Lewis Bowen, Michael Chapman, Alexander Lubotzky, Thomas Vidick

This paper, and its companion [BCV24], are devoted to a negative resolution of the Aldous--Lyons Conjecture [AL07, Ald07]. This conjecture, originated in probability theory, is well known (cf. [Gel18]) to be equivalent to the statement that every invariant random subgroup of the free group is co-sofic. We disprove this last statement. In this part we introdu

Ábel Ságodi, Guillermo Martín-Sánchez, Piotr Sokół, Il Memming Park

Continuous attractors offer a unique class of solutions for storing continuous-valued variables in recurrent system states for indefinitely long time intervals. Unfortunately, continuous attractors suffer from severe structural instability in general--they are destroyed by most infinitesimal changes of the dynamical law that defines them. This fragility limi