December 2023 arXiv papers — page 71

Daniel Fernandes Gomes, Wenxuan Mou, Paolo Paoletti, Shan Luo

End-to-end self-supervised models have been proposed for estimating the success of future candidate grasps and video predictive models for generating future observations. However, none have yet studied these two strategies side-by-side for addressing the aforementioned grasping problem. We investigate and compare a model-free approach, to estimate the succes

Stefano Di Noi, Ramona Gröber

We study the effects of renormalisation group running of the Wilson coefficients in Standard Model Effective Field Theory, using the process $pp \to t \bar{t}h$ as a showcase. We consider both strong and top Yukawa running effects, since the latter can be relevant in presence of large Wilson coefficients. We study the difference between the use of a dynamica

Marcelo Sartori Locatelli, Pedro Calais, Matheus Prado Miranda, João Pedro Junho

Politicization is a social phenomenon studied by political science characterized by the extent to which ideas and facts are given a political tone. A range of topics, such as climate change, religion and vaccines has been subject to increasing politicization in the media and social media platforms. In this work, we propose a computational method for assessin

Iurii Karpenko, Jakub Cimerman

We present directed flow of protons and pions, as well as mean polarization of $\Lambda$ and $\bar\Lambda$ hyperons computed for Au-Au collisions at $\sqrt{s_\mathrm{NN}}=5...19.6$ GeV in MUFFIN model. MUlti Fluid simulation for Fast IoN collisions, or MUFFIN, is a state-of-the-art 3-fluid dynamic model for simulating heavy-ion collisions in the region from

Augusto Santos, Diogo Rente, Rui Seabra, José M. F. Moura

In a Networked Dynamical System (NDS), each node is a system whose dynamics are coupled with the dynamics of neighboring nodes. The global dynamics naturally builds on this network of couplings and it is often excited by a noise input with nontrivial structure. The underlying network is unknown in many applications and should be inferred from observed data.

Georgios Vardakas, Argyris Kalogeratos, Aristidis Likas

Estimating the number of clusters k while clustering the data is a challenging task. An incorrect cluster assumption indicates that the number of clusters k gets wrongly estimated. Consequently, the model fitting becomes less important. In this work, we focus on the concept of unimodality and propose a flexible cluster definition called locally unimodal clus

Vegard Undheim, Alex Bentley Nielsen, Eirik Eik Svanes

Within the framework of string theory, a number of new fields are possible correcting the Einstein-Hilbert action, including a Kalb-Ramond two-form field. In this work we derive explicitly first order relativistic corrections to conservative dynamics with a Kalb-Ramond field, using the effective field theory approach. The resulting additional terms in the La

Louis Bremaud, Olivier Giraud, Denis Ullmo

The ability to actually implement epidemic models is a crucial stake for public institutions, as they may be overtaken by the increasing complexity of current models and sometimes tend to revert to less elaborate models such as the SIR. In our work, we study a simple epidemic propagation model, called SIR-$k$, which is based on a homogeneous network of degre

K. Deja, V. Martinez-Fernandez, B. Pire, P. Sznajder

Double deeply virtual Compton scattering (DDVCS) is a very precise tool for the nucleon tomography. Its measurement requires high luminosity electron beams and precise dedicated detectors, since its amplitude is quite small in the interesting kinematical domain where collinear QCD factorization allows the extraction of quark and gluon generalized parton dist

Jan Cepila, Jesus Guillermo Contreras, Marek Matas, Alexandra Ridzikova

We predict that the onset of gluon saturation can be uniquely identified using incoherent ${\rm J}/\psi$ production in Pb$\unicode{x2013}$Pb collisions at currently accessible energies of the LHC. The diffractive incoherent photo-production of a ${\rm J}/\psi$ vector meson off a hadron provides information on the partonic structure of the hadron. Within the

Hui Chen, Yinxu Jia, Guanghui Wang, Changliang Zou

Accurately detecting multiple change-points is critical for various applications, but determining the optimal number of change-points remains a challenge. Existing approaches based on information criteria attempt to balance goodness-of-fit and model complexity, but their performance varies depending on the model. Recently, data-driven selection criteria base

Ming Che

We propose a method that uses inaudible ultrasonic waves to address the issue of uplink transmission in visible light communication. Our scheme, which applies frequency-shift keying modulation and receive beamforming by a microphone array, has been experimentally confirmed. This system has an adjustable receiving direction to enhance the anti-interference ab

Xilong Zhao, Siyuan Bian, Yaoyun Zhang, Yuliang Zhang

Out-of-distribution (OOD) generalization has long been a challenging problem that remains largely unsolved. Gaussian processes (GP), as popular probabilistic model classes, especially in the small data regime, presume strong OOD generalization abilities. Surprisingly, their OOD generalization abilities have been under-explored before compared with other line

Andrei A. Agrachev, Michele Motta

We explicitly compute the maximal Lyapunov exponent for a switched system on $\mathrm{SL}_2(\mathbb R)$. This computation is reduced to the characterization of optimal trajectories for an optimal control problem on the Lie group.

Fabio Vito Difonzo, Luciano Lopez, Sabrina Francesca Pellegrino

Deep learning is a powerful tool for solving data driven differential problems and has come out to have successful applications in solving direct and inverse problems described by PDEs, even in presence of integral terms. In this paper, we propose to apply radial basis functions (RBFs) as activation functions in suitably designed Physics Informed Neural Netw

Franz Thaler, Matthias A. F. Gsell, Gernot Plank, Martin Urschler

Late gadolinium enhanced (LGE) magnetic resonance (MR) imaging is widely established to assess the viability of myocardial tissue of patients after acute myocardial infarction (MI). We propose the Cascading Refinement CNN (CaRe-CNN), which is a fully 3D, end-to-end trained, 3-stage CNN cascade that exploits the hierarchical structure of such labeled cardiac

Rohan Mitta, Hosein Hasanbeig, Jun Wang, Daniel Kroening

This paper addresses the problem of maintaining safety during training in Reinforcement Learning (RL), such that the safety constraint violations are bounded at any point during learning. In a variety of RL applications the safety of the agent is particularly important, e.g. autonomous platforms or robots that work in proximity of humans. As enforcing safety

Jazon Szabo, Jose Such, Natalia Criado, Sanjay Modgil

While there is universal agreement that agents ought to act ethically, there is no agreement as to what constitutes ethical behaviour. To address this problem, recent philosophical approaches to `moral uncertainty' propose aggregation of multiple ethical theories to guide agent behaviour. However, one of the foundational proposals for aggregation - Maximisin

D. Freire-Fernández, W. Korten, R. J. Chen, S. Litvinov

The nuclear two-photon or double-gamma ($2\gamma$) decay is a second-order electromagnetic process whereby a nucleus in an excited state emits two gamma rays simultaneously. To be able to directly measure the $2\gamma$ decay rate in the low-energy regime below the electron-positron pair-creation threshold, we combined the isochronous mode of a storage ring w

Akshay Batheja, Sourabh Deoghare, Diptesh Kanojia, Pushpak Bhattacharyya

Automatic Post-Editing (APE) is the task of automatically identifying and correcting errors in the Machine Translation (MT) outputs. We propose a repair-filter-use methodology that uses an APE system to correct errors on the target side of the MT training data. We select the sentence pairs from the original and corrected sentence pairs based on the quality s

Mengge Yuan, Ning Zhao, Kan Wu, Lulu Cheng

In the smart hospital, optimizing prescription order fulfilment processes in outpatient pharmacies is crucial. A promising device, automated drug dispensing systems (ADDSs), has emerged to streamline these processes. These systems involve human order pickers who are assisted by ADDSs. The ADDS's robotic arm transports bins from storage locations to the input

Chi Zhang, Akhil Sathuluri, Markus Zimmermann

We present a solution of the swing-up and balance task for the pendubot and acrobot for the participation in the AI Olympics competition at IJCAI 2023. Our solution is based on the Soft Actor Crtic (SAC) reinforcement learning (RL) algorithm for training a policy for the swing-up and entering the region of attraction of a linear quadratic regulator(LQR) cont

Joscha Henheik, Asbjørn Bækgaard Lauritsen

We consider the BCS energy gap $\Xi(T)$ (essentially given by $\Xi(T) \approx \Delta(T, \sqrt\mu)$, the BCS order parameter) at all temperatures $0 \le T \le T_c$ up to the critical one, $T_c$, and show that, in the limit of weak coupling, the ratio $\Xi(T)/T_c$ is given by a universal function of the relative temperature $T/T_c$. On the one hand, this recov

Zebin Yun, Achi-Or Weingarten, Eyal Ronen, Mahmood Sharif

To help adversarial examples generalize from surrogate machine-learning (ML) models to targets, certain transferability-based black-box evasion attacks incorporate data augmentations (e.g., random resizing). Yet, prior work has explored limited augmentations and their composition. To fill the gap, we systematically studied how data augmentation affects trans

David Amram, Killian Bouzoud, Nicolas Chanon, Hubert Hansen

New calculations for the kinematics of photon decay to fermions in vacuo under an isotropic violation of Lorentz invariance (LV), parameterized by the Standard-Model Extension (SME), are presented in this paper and used to interpret prompt photon production in LHC data. The measurement of inclusive prompt photon production at the LHC Run 2, with photons obse

Mengge Yuan, Kan Wu, Ning Zhao

Automated drug dispensing systems (ADDSs) are increasingly in demand in today's pharmacies, primarily driven by the growing ageing population. Recognizing the practical challenges faced by pharmacies implementing ADDSs, this study aims to optimize the layout design and sequencing issues within a human-machine cooperation environment to enhance the system thr

Renu Chaudhary, Kai Diethelm

In this paper, we revisit the diffusive representations of fractional integrals established in \cite{diethelm2023diffusive} to explore novel variants of such representations which provide highly efficient numerical algorithms for the approximate numerical evaluation of fractional integrals.

Peyman Faratin, Ray Garcia, Jacomo Corbo

Foundation models offer a new opportunity to redesign existing systems and workflows with a new AI first perspective. However, operationalizing this opportunity faces several challenges and tradeoffs. The goal of this article is to offer an organizational framework for making rational choices as enterprises start their transformation journey towards an AI fi

Ryohei Chihara

We sketch an application of proximal algorithms to the deformation of de Rham currents into cycles, which is presented as a convex optimization problem. Emphasis is placed on the use of total variation denoising for differential forms, specifically in constructing calibrated cycles in calibrated manifolds.

Gabriel V. Cardoso, Lisa Bedin, Josselin Duchateau, Rémi Dubois

In this work, we propose a denoising diffusion generative model (DDGM) trained with healthy electrocardiogram (ECG) data that focuses on ECG morphology and inter-lead dependence. Our results show that this innovative generative model can successfully generate realistic ECG signals. Furthermore, we explore the application of recent breakthroughs in solving li

Taha Laroussi, Mojtaba Jarrahi, Gabriel Amselem

Phototaxis, the directed motion in response to a light stimulus, is crucial for motile microorganisms that rely on photosynthesis, such as the unicellular microalga Chlamydomonas reinhardtii. It is well known that microalgae adapt to ambient light stimuli. On time scales of several dozen minutes, when stimulated long enough, the response of the microalga evo

Qu Luo, Pei Xiao, Zilong Liu, Ziwei Wan

This paper studies the affine frequency division multiplexing (AFDM)-empowered sparse code multiple access (SCMA) system, referred to as AFDM-SCMA, for supporting massive connectivity in high-mobility environments. First, by placing the sparse codewords on the AFDM chirp subcarriers, the input-output (I/O) relation of AFDM-SCMA systems is presented. Next, we

Lojenaa Navanesana, Nhien-An Le-Khac, Mark Scanlon, Kasun De Zoysa

Investigation on smart devices has become an essential subdomain in digital forensics. The inherent diversity and complexity of smart devices pose a challenge to the extraction of evidence without physically tampering with it, which is often a strict requirement in law enforcement and legal proceedings. Recently, this has led to the application of non-intrus

Sundaraparipurnan Narayanan, Mark Potkewitz

Artificial intelligence can cause inconvenience, harm, or other unintended consequences in various ways, including those that arise from defects or malfunctions in the AI system itself or those caused by its use or misuse. Responsibility for AI harms or unintended consequences must be addressed to hold accountable the people who caused such harms and ensure

S. A. Larin

We suggest a new solution to the strong CP problem. The solution is based on the proper use of the boundary conditions for the QCD generating functional integral. We expand the perturbative boundary conditions to both perturbative and nonperturbative fields integrated in the QCD generating functional integral. It allows to nullify the CP odd term in the QCD

Selim Kuzucu, Jiaee Cheong, Hatice Gunes, Sinan Kalkan

Unfair predictions of machine learning (ML) models impede their broad acceptance in real-world settings. Tackling this arduous challenge first necessitates defining what it means for an ML model to be fair. This has been addressed by the ML community with various measures of fairness that depend on the prediction outcomes of the ML models, either at the grou

Francesca Cuteri, Anthony Francis, Patrick Fritzsch, Giovanni Pederiva

The continued generation of $N_f=2+1$ quark flavor gauge configurations using stabilized Wilson fermions by the open lattice initiative (OpenLat) is reported. We present the status of our ongoing production and show updates on increasing statistics at the four lattice spacings $a=0.12, 0.094, 0.077$ and $0.064$ fm. Aside from the $SU(3)$ flavor symmetric poi

Xinyue Zhang, Pan Hu, Yavor Nenov, Ian Horrocks

Materialisation facilitates Datalog reasoning by precomputing all consequences of the facts and the rules so that queries can be directly answered over the materialised facts. However, storing all materialised facts may be infeasible in practice, especially when the rules are complex and the given set of facts is large. We observe that for certain combinatio

Julita Bielaniewicz, Przemysław Kazienko

The vast area of subjectivity in Natural Language Processing (NLP) poses a challenge to the solutions typically used in generalized tasks. As exploration in the scope of generalized NLP is much more advanced, it implies the tremendous gap that is still to be addressed amongst all feasible tasks where an opinion, taste, or feelings are inherent, thus creating

Andrew Frohmader

This paper contains two main results. First, we provide combinatorial branching rules for $\mathrm{GL}_n \downarrow \mathrm{O}_n$ and $\mathrm{GL}_{2n} \downarrow \mathrm{Sp}_{2n}$ extending the Littlewood restriction rules. Second, we use these branching rules and the combinatorics of $\mathrm{GL}_n$-crystals to derive a formula for the graded multiplicity

Ahmad Barhoumi

We obtain asymptotics of polynomials satisfying the orthogonality relations $$ \int_{\mathbb{R}} z^k P_n(z; t , N) \mathrm{e}^{-N \left(\frac{1}{4}z^4 + \frac{t}{2}z^2 \right)} \mathrm{d} z = 0 \quad \text{ for } \quad k = 0, 1, ..., n-1, $$ where the complex parameter $t$ is in the so-called two-cut region. As an application, we deduce asymptotic formulas f

Mohammad H. A. Badarneh, Grzegorz J. Kwiatkowski, Pavel F. Bessarab

Energy-efficient switching of nanoscale magnets requires the application of a time-varying magnetic field characterized by microwave frequency. At finite temperatures, even weak thermal fluctuations create perturbations in the magnetization that can accumulate in time, break the phase locking between the magnetization and the applied field, and eventually co

Frank Breitinger, Jan-Niclas Hilgert, Christopher Hargreaves, John Sheppard

Conducting a systematic literature review and comprehensive analysis, this paper surveys all 135 peer-reviewed articles published at the Digital Forensics Research Conference Europe (DFRWS EU) spanning the decade since its inaugural running (2014-2023). This comprehensive study of DFRWS EU articles encompasses sub-disciplines such as digital forensic science

Dominik Stöckinger, Matthias Weißwange

In this work we present a complete three-loop renormalisation of an abelian chiral gauge theory within the Breitenlohner-Maison/'t Hooft-Veltman (BMHV) scheme of dimensional regularisation (DReg). In this scheme the $\gamma_5$-matrix appearing in gauge interactions is a non-anticommuting object, leading to a breaking of gauge and BRST invariance. Employing a

Ammar chouchane, Mohcene Bessaoudi, Abdelmalik Ouamane

Kinship verification using facial photographs captured in the wild is difficult area of research in the science of computer vision. It might be used for a variety of applications, including image annotation and searching for missing children, etc. The largest challenge to kinship verification in practice is the fact that parent and child photos frequently di

Peiran Li, Haoran Zhang, Wenjing Li, Dou Huang

The importance of personal mobility data is widely recognized in various fields. However, the utilization of real personal mobility data raises privacy concerns. Therefore, it is crucial to generate pseudo personal mobility data that accurately reflects real-world mobility patterns while safeguarding user privacy. Nevertheless, existing methods for generatin

Khaled Mnaymneh

We argue that it is the assumption of counterfactual definiteness and not locality or realism that results in Bell inequality violations. Furthermore, this assumption of counterfactual definiteness is not supported in classical mechanics. This means that the Bell inequality must fail classically, effectively removing the classical-quantum boundary, a conclus

Aki Mori, Kenta Mori, Hidefumi Ohsugi

Symmetric edge polytopes of graphs are important object in Ehrhart theory,and have an application to Kuramoto models. In the present paper, we study the upper and lower bounds for the number of facets of symmetric edge polytopes of connected graphs conjectured by Braun and Bruegge. In particular, we show that their conjecture is true for any graph that is th

Haris Aziz, Isaiah Iliffe, Bo Li, Angus Ritossa

We study the envy-free house allocation problem when agents have uncertain preferences over items and consider several well-studied preference uncertainty models. The central problem that we focus on is computing an allocation that has the highest probability of being envy-free. We show that each model leads to a distinct set of algorithmic and complexity re

Decheng Liu, Xijun Wang, Chunlei Peng, Nannan Wang

Adversarial attacks involve adding perturbations to the source image to cause misclassification by the target model, which demonstrates the potential of attacking face recognition models. Existing adversarial face image generation methods still can't achieve satisfactory performance because of low transferability and high detectability. In this paper, we pro

Amit Kumar Bhuyan, Hrishikesh Dutta, Subir Biswas

This paper proposes an unmanned aerial vehicle (UAV) aided content management system in communication-challenged disaster scenarios. Without cellular infrastructure in such scenarios, community of stranded users can be provided access to situation-critical contents using a hybrid network of static and traveling UAVs. A set of relatively static anchor UAVs ca

Masakiyo Miyazawa

We consider a single server queue which has a threshold to change its arrival process and service speed by its queue length, which is referred to as a two-level single server queue. This model is motivated by an energy saving problem for a single server queue whose arrival process and service speed are controlled. To get its performance in tractable form, we

John M. Abowd, Tamara Adams, Robert Ashmead, David Darais

We show that individual, confidential microdata records from the 2010 U.S. Census of Population and Housing can be accurately reconstructed from the published tabular summaries. Ninety-seven million person records (every resident in 70% of all census blocks) are exactly reconstructed with provable certainty using only public information. We further show that

Yuxuan Huang

The development of large language models (LLMs) has been catalyzed by advancements in pre-training techniques. These models have demonstrated robust reasoning capabilities through manually designed prompts. In this work, we evaluate the conversational reasoning capabilities of the current state-of-the-art LLM (GPT-4) on knowledge graphs (KGs). However, the p

Oriol Cabanas-Tirapu, Lluís Danús, Esteban Moro, Marta Sales-Pardo

Modeling of human mobility is critical to address questions in urban planning and transportation, as well as global challenges in sustainability, public health, and economic development. However, our understanding and ability to model mobility flows within and between urban areas are still incomplete. At one end of the modeling spectrum we have simple so-cal

Daman Deep Singh, Amit Kumar, Abhijnan Chakraborty

The k-SERVER problem is one of the most prominent problems in online algorithms with several variants and extensions. However, simplifying assumptions like instantaneous server movements and zero service time has hitherto limited its applicability to real-world problems. In this paper, we introduce a realistic generalization of k-SERVER without such assumpti

Hariprasadh Godindasamy, Babak Esfandiari, Paulo Garcia

We present a hardware-accelerated SAT solver suitable for processor/Field Programmable Gate Arrays (FPGA) hybrid platforms, which have become the norm in the embedded domain. Our solution addresses a known bottleneck in SAT solving acceleration: unlike prior state-of-the-art solutions that have addressed the same bottleneck by limiting the amount of exploite

Arjav Shah, Shakul Pathak, Slaven Garaj, Martin Z. Bazant

Nanopore-based sensing platforms have transformed single-molecule detection and analysis. The foundation of nanopore translocation experiments lies in conductance measurements, yet existing models, which are largely phenomenological, are inaccurate in critical experimental conditions such as thin and tightly fitting pores. Of the two components of the conduc

V. Yu. Pomjakushin, A. Podlesnyak, A. Furrer, E. V. Pomjakushina

The crystal and magnetic structures of the spin $S$=1 hexamer cluster fedotovite-like A$_{2}$Cu$_{3}$O(SO$_4$)$_3$ (A$_2$=K$_2$, NaK, Na$_2$) were studied by neutron powder diffraction at temperatures 1.6-290 K. The crystal structures in all compounds are well refined in the monoclinic space group C2/c. The basic magnetic units of the compounds are copper he

Yuyang Chai, Zhuang Li, Jiahui Liu, Lei Chen

Despite significant advancements in multi-label text classification, the ability of existing models to generalize to novel and seldom-encountered complex concepts, which are compositions of elementary ones, remains underexplored. This research addresses this gap. By creating unique data splits across three benchmarks, we assess the compositional generalizati

G. Forte, S. Buonomo, P. R. Cook, N. Gilbert

We propose a polymer model for the dynamics of chromatin replication in three dimensional space. Our simulations indicate that both immobile and tracking replisomes may self-assemble during the process, reconciling previous apparently discordant experimental evidence in favour of either scenario. Which of the two morphologies appears in our model depends on

Danielle R. Thomas, Jionghao Lin, Erin Gatz, Ashish Gurung

Artificial intelligence (AI) applications to support human tutoring have potential to significantly improve learning outcomes, but engagement issues persist, especially among students from low-income backgrounds. We introduce an AI-assisted tutoring model that combines human and AI tutoring and hypothesize that this synergy will have positive impacts on lear

Lotte van Hezewijk, Nico Dellaert, Willem van Jaarsveld

Methods to generate realistic non-stationary demand scenarios are a key component for analyzing and optimizing decision policies in supply chains. Typical forecasting techniques recommended in standard inventory control textbooks consist of some form of simple exponential smoothing (SES) for both the estimates for the mean and standard deviation. We study de

Vivi Nastase, Paola Merlo

Sentence and word embeddings encode structural and semantic information in a distributed manner. Part of the information encoded -- particularly lexical information -- can be seen as continuous, whereas other -- like structural information -- is most often discrete. We explore whether we can compress transformer-based sentence embeddings into a representatio

Rémi Abgrall, Jianfang Lin, Yongle Liu

In this article, we show how to construct a numerical method for solving hyperbolic problems, whether linear or nonlinear, using a continuous representation of the variables and their mean value in each triangular element. This type of approach has already been introduced by Roe, and others, in the multidimensional framework under the name of Active flux, se

Roman Ludwig, Adrian Schubert, Dorothea Barbatei, Lauence Bauwens

The elective clinical target volume (CTV-N) in oropharyngeal squamous cell carcinoma (OPSCC) is currently based mostly on the prevalence of lymph node metastases in different lymph node levels (LNLs) for a given primary tumor location. We present a probabilistic model for ipsilateral lymphatic spread that can quantify the microscopic nodal involvement risk b

Sangyun Shin, Kaichen Zhou, Madhu Vankadari, Andrew Markham

Coarse-to-fine 3D instance segmentation methods show weak performances compared to recent Grouping-based, Kernel-based and Transformer-based methods. We argue that this is due to two limitations: 1) Instance size overestimation by axis-aligned bounding box(AABB) 2) False negative error accumulation from inaccurate box to the refinement phase. In this work, w

Ljubica Davidović, Ilija Ivanišević, Branislav Sazdović

This paper investigates the simultaneous twisting of the Courant bracket by a 2-form $B$ and a bi-vector $\theta$, exploring the generalized fluxes obtained in Courant algebroid relations. We define the twisted Lie bracket and demonstrate that the generalized $H$-flux can be expressed as the field strength defined on this Lie algebroid. Similarly, we show th

Cordian Riener, Jan Rolfes, Frank Vallentin

In this paper we present a new semidefinite programming hierarchy for covering problems in compact metric spaces. Over the last years, these kind of hierarchies were developed primarily for geometric packing and for energy minimization problems; they frequently provide the best known bounds. Starting from a semidefinite programming hierarchy for the dominati

Klaus Ziegler

We study the invariant measure of the transport correlator for a chiral Hamiltonian and analyze its properties. The Jacobian of the invariant measure is a function of random phases. Then we distinguish the invariant measure before and after the phase integration. In the former case we found quantum diffusion of fermions and a uniform zero mode that is associ

Micheal Kahangirwe, Steffen A. Bass, Johannes Jahan, Pierre Moreau

The BEST Collaboration equation of state combining lattice data with the 3D Ising critical point encounters limitations due to the truncated Taylor expansion up to $\frac{\mu_B}{T} \sim 2.5$. This truncation consequently restricts its applicability at high densities. Through a resummation scheme, the lattice results have been extended to $\frac{\mu_B}{T} = 3

Koen van Greevenbroek, Aleksander Grochowicz, Marianne Zeyringer, Fred Espen Benth

The transition to net-zero emissions in Europe is determined by a patchwork of country-level and EU-wide policy, creating coordination challenges in an interconnected system. We use an optimisation model to map out near-optimal energy system designs for 2050, focussing on the planning flexibility of individual regions while maintaining overall system robustn

Mateus Figueiredo, Pavel Shumyatsky

Finite groups in which every element has prime power order (EPPO-groups) are nowadays fairly well understood. For instance, if $G$ is a soluble EPPO-group, then the Fitting height of $G$ is at most 3 and $|\pi(G)|\leqslant 2$ (Higman, 1957). Moreover, Suzuki showed that if $G$ is insoluble, then the soluble radical of $G$ is a 2-group and there are exactly e

Rasha Al-Marzoog, Ali Rezaei, Zahra Noorinejad, Mohsen Amini

This study is devoted to the profound implications of tilted Dirac cones on the quantum transport properties of two-dimensional (2D) Dirac materials. These materials, characterized by their linear conic energy dispersions in the vicinity of Dirac points, exhibit unique electronic behaviors, including the emulation of massless Dirac fermions and the manifesta

Nick Gurski, Niles Johnson

This work introduces a general theory of universal pseudomorphisms and develops their connection to diagrammatic coherence. The main results give hypotheses under which pseudomorphism coherence is equivalent to the coherence theory of strict algebras. Applications include diagrammatic coherence for plain, symmetric, and braided monoidal functors. The final s

Yongjin Yang, Taehyeon Kim, Se-Young Yun

Cross-domain few-shot learning presents a formidable challenge, as models must be trained on base classes and then tested on novel classes from various domains with only a few samples at hand. While prior approaches have primarily focused on parameter-efficient methods of using adapters, they often overlook two critical issues: shifts in batch statistics and

Nemin Wei, Yongxin Zeng, A. H. MacDonald

Spontaneous intervalley coherence is suspected in several different graphene multilayer systems, but is difficult to confirm because of a paucity of convenient experimental signatures. Here we suggest that magneto-conductance features associated with quantum corrections to Drude conductivity can serve as a smoking gun for intervalley coherence that does not

Xiaopeng Wang, Yanbing Cai, Xurong Chen

This paper presents a comprehensive analysis of the MD-BFKL equation, considering both shadowing and anti-shadowing effects in gluon recombination processes. By deriving analytical expressions for unintegrated gluon distributions through the solution of the MD-BFKL equation, with and without the incorporation of anti-shadowing effect, we offer new insights i

Carl-Fredrik Nyberg-Brodda

We study the freeness problem for subgroups of $\operatorname{SL}_2(\mathbb{C})$ generated by two parabolic matrices. For $q = r/p \in \mathbb{Q} \cap (0,4)$, where $p$ is prime and $\gcd(r,p)=1$, we initiate the study of the algebraic structure of the group $\Delta_q$ generated by the two matrices \[ A = \begin{pmatrix} 1 & 0 \\ 1 & 1 \end{pmatrix}, \text{

Thomas Bagrel

Destination-passing style programming introduces destinations, which represent the address of a write-once memory cell. Those destinations can be passed as function parameters, and thus enable the caller of a function to keep control over memory management: the body of the called function will just be responsible of filling that memory cell. This is especial

Chong Zhang, Alban Gaignard, Matus Kalas, Florian Levet

Bio image analysis has recently become one keystone of biological research but biologists tend to get lost in a plethora of available software and the way to adjust available tools to their own image analysis problem. We present BIII, BioImage Informatic Index (www.biii.eu), the result of the first large community effort to bridge the communities of algorith

Kanghui He, Shengling Shi, Ton van den Boom, Bart De Schutter

Learning-based control with safety guarantees usually requires real-time safety certification and modifications of possibly unsafe learning-based policies. The control barrier function (CBF) method uses a safety filter containing a constrained optimization problem to produce safe policies. However, finding a valid CBF for a general nonlinear system requires

Junyan Zhang

Current-vortex sheet is one of the characteristic discontinuities in ideal compressible magnetohydrodynamics (MHD). The motion of current-vortex sheets is described by a free-interface problem of two-phase MHD flows with magnetic fields tangential to the interface. This paper is the first part of the two-paper sequence, which aims to present a comprehensive

Mohammadhossein Mohammadisiahroudi, Brandon Augustino, Pouya Sampourmahani, Tamás Terlaky

Iterative Refinement (IR) is a classical computing technique for obtaining highly precise solutions to linear systems of equations, as well as linear optimization problems. In this paper, motivated by the limited precision of quantum solvers, we develop the first IR scheme for solving semidefinite optimization (SDO) problems and explore two major impacts of

Kirill Boguslavski, Aleksi Kurkela, Tuomas Lappi, Florian Lindenbauer

We study universal features of the hydrodynamization process in heavy-ion collisions using QCD kinetic theory simulations for a wide range of couplings. We introduce the new concept of limiting attractors, which are obtained by extrapolation to vanishing and strong couplings. While the hydrodynamic limiting attractor emerges at strong couplings and is govern

Yun Li, Neil Yorke-Smith, Tamas Keviczky

Robust Optimal Control (ROC) with adjustable uncertainties has proven to be effective in addressing critical challenges within modern energy networks, especially the reserve and provision problem. However, prior research on ROC with adjustable uncertainties has predominantly focused on the scenario of uncertainties modeled as continuous variables. In this pa

Joel L. Lavanchy, Sanat Ramesh, Diego Dall'Alba, Cristians Gonzalez

Most studies on surgical activity recognition utilizing Artificial intelligence (AI) have focused mainly on recognizing one type of activity from small and mono-centric surgical video datasets. It remains speculative whether those models would generalize to other centers. In this work, we introduce a large multi-centric multi-activity dataset consisting of 1

Charlotte Dietze, Phan Thành Nam

We derive a family of interpolation estimates which improve Hardy's inequality and cover the Sobolev critical exponent. We also determine all optimizers among radial functions in the endpoint case and discuss open questions on nonrestricted optimizers.

Kaveh Delfanazari, Jiahui Li, Yusheng Xiong, Pengcheng Ma

Quantum point contact or QPC -- a constriction in a semiconducting two-dimensional (2D) electron system with a quantized conductance -- has been found as the building block of novel spintronic, and topological electronic circuits. They can also be used as readout electronic, charge sensor or switch in quantum nanocircuits. A short and impurity-free constrict

Vladimir Mikhailets, Aleksandr Murach

We study the most general class of eigenfunction expansions for abstract normal operators with pure point spectrum in a complex Hilbert space. We find sufficient conditions for such expansions to be unconditionally convergent in spaces with two norms and also estimate the degree of this convergence. Our result essentially generalizes and complements the know

Gregorio Baldi, Bruno Klingler, Emmanuel Ullmo

We study when the Picard group of smooth surfaces of degree $d\geq 5$ in $\mathbb{P}^3$ acquires extra classes. In particular we show that the so called exceptional components of the Noether-Lefschetz locus are not Zariski dense. This answers a 1991 question of C. Voisin. We also obtain similar results for the Noether-Lefschetz locus for suitable $(Y,L)$, wh

Lihao Zhang, Haijian Sun, Jin Sun, Rose Qingyang Hu

The accurate modeling of indoor radio propagation is crucial for localization, monitoring, and device coordination, yet remains a formidable challenge, due to the complex nature of indoor environments where radio can propagate along hundreds of paths. These paths are resulted from the room layout, furniture, appliances and even small objects like a glass cup

Qiuyi He, Xun Shi

Interstellar radio wave scattering leads to flux density fluctuations and pulse broadening of pulsar signals. However, Galactic distribution and the structure of the scattering medium are still poorly understood. Pulsar pulse broadening data available for a relatively large number of pulsars is well suited for such investigations. We collected an up-to-date

Kuldeep R Barad, Andrej Orsula, Antoine Richard, Jan Dentler

Vision-based grasping of unknown objects in unstructured environments is a key challenge for autonomous robotic manipulation. A practical grasp synthesis system is required to generate a diverse set of 6-DoF grasps from which a task-relevant grasp can be executed. Although generative models are suitable for learning such complex data distributions, existing

Bing Wang, Changyu Ren, Jian Yang, Xinnian Liang

Recent LLM-based Text-to-SQL methods usually suffer from significant performance degradation on "huge" databases and complex user questions that require multi-step reasoning. Moreover, most existing methods neglect the crucial significance of LLMs utilizing external tools and model collaboration. To address these challenges, we introduce MAC-SQL, a novel LLM

Nico Schuster, Nico Hamaus, Klaus Dolag, Jochen Weller

We utilize the Magneticum suite of state-of-the-art hydrodynamical, as well as dark-matter-only simulations to investigate the effects of baryonic physics on cosmic voids in the highest-resolution study of its kind. This includes the size, shape and inner density distributions of voids, as well as their radial density and velocity profiles traced by halos, b

Fábio Felix Dias, Moacir Antonelli Ponti, Mílton Cezar Ribeiro, Rosane Minghim

Taking advantage of the structure of large datasets to pre-train Deep Learning models is a promising strategy to decrease the need for supervised data. Self-supervised learning methods, such as contrastive and its variation are a promising way towards obtaining better representations in many Deep Learning applications. Soundscape ecology is one application i

Michael Kirby

We summarize the status of Deep Underground Neutrino Experiment (DUNE) Offline Software and Computing program. We describe plans for the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes in pursuit of the experiment's physics goals of precision measurements of neutrino

Holger Frahm, Sascha Gehrmann, Gleb A. Kotousov

We study the scaling limit of a statistical system, which is a special case of the integrable inhomogeneous six-vertex model. It possesses $U_q\big(\mathfrak{sl}(2)\big)$ invariance due to the choice of open boundary conditions imposed. An interesting feature of the lattice theory is that the spectrum of scaling dimensions contains a continuous component. By

Marko Berghoff

These notes loosely follow an introductory course on graph complexes, held at Humboldt-Universit\"at zu Berlin in summer 23. Instead of simply typing up my lecture notes I decided to give here an overview over (parts of) the topic (lecture notes can be found on my homepage). We introduce the associative, commutative and Lie graph complexes, and moduli spaces