May 2024 arXiv papers — page 129

Kaiyuan Cao, Peiqing Tong

We investigate the nonequilibrium dynamics induced by a finite-time linear quench in the XY chain. Initially, we examine the dynamical quantum phase transition, characterized by the nonanalytic behavior of the Loschmidt amplitude. We find distinct behaviors of DQPTs during and following the ramp. Following the ramp, the ramp crossing the critical point $h_{c

Yunhao Tang, Daniel Zhaohan Guo, Zeyu Zheng, Daniele Calandriello

Reinforcement learning from human feedback (RLHF) is the canonical framework for large language model alignment. However, rising popularity in offline alignment algorithms challenge the need for on-policy sampling in RLHF. Within the context of reward over-optimization, we start with an opening set of experiments that demonstrate the clear advantage of onlin

Elena L. Glassman, Ziwei Gu, Jonathan K. Kummerfeld

AI is powerful, but it can make choices that result in objective errors, contextually inappropriate outputs, and disliked options. We need AI-resilient interfaces that help people be resilient to the AI choices that are not right, or not right for them. To support this goal, interfaces need to help users notice and have the context to appropriately judge tho

Jinyu Guo

In this paper, we study a mean curvature type flow with capillary boundary in a horoball in hyperbolic space. Our flow preserves the volume of the bounded domain enclosed by the hypersurface and monotonically decreases the energy functional. We show that it has the long time existence and converges to a truncated umbilical hypersurface in hyperbolic space. A

Ciarán Rogers, Bernhard Brandl, Guido de Marchi

Context. A necessary ingredient in understanding the star formation history of a young cluster is knowledge of the extinction towards the region. This has typically been done by making use of the colour-difference method with photometry, or similar methods utilising the colour-colour diagram. Aims. The colour-excess can be independently determined by studyin

Jose Pedro Gaivao, Benito Pires

Piecewise contractions (PCs) are piecewise smooth maps that decrease distance between pairs of points in the same domain of continuity. The dynamics of a variety of systems is described by PCs. During the last decade, a lot of effort has been devoted to proving that in parametrized families of one-dimensional PCs, the $\omega$-limit set of a typical PC consi

Yang Qu, Jinming Ma, Feng Wu

Active voltage control presents a promising avenue for relieving power congestion and enhancing voltage quality, taking advantage of the distributed controllable generators in the power network, such as roof-top photovoltaics. While Multi-Agent Reinforcement Learning (MARL) has emerged as a compelling approach to address this challenge, existing MARL approac

Meng-Che "Turbo" Ho, Khanh Le, Dino Rossegger

We answer a question of Calderoni and Clay by showing that the conjugation equivalence relation of left orderings of the Baumslag-Solitar groups $\mathrm{BS}(1,n)$ is hyperfinite for any $n$. Our proof relies on a classification of $\mathrm{BS}(1,n)$'s left-orderings via its one-dimensional dynamical realizations. We furthermore use the effectiveness of the

Chenfeng Cao, Filippo Maria Gambetta, Ashley Montanaro, Raul A. Santos

Understanding quantum phase transitions in physical systems is fundamental to characterize their behavior at low temperatures. Achieving this requires both accessing good approximations to the ground state and identifying order parameters to distinguish different phases. Addressing these challenges, our work introduces a hybrid algorithm that combines quantu

Qinshuo Liu, Yanwen Fang, Pengtao Jiang, Guodong Li

Multivariate time series forecasting tasks are usually conducted in a channel-dependent (CD) way since it can incorporate more variable-relevant information. However, it may also involve a lot of irrelevant variables, and this even leads to worse performance than the channel-independent (CI) strategy. This paper combines the strengths of both strategies and

Sebastian Gemsheim

Dynamics, the physical change in time and a pillar of natural sciences, can be regarded as an emergent phenomenon when the system of interest is part of a larger, static one. This "relational approach to time", in which the system's environment provides a temporal reference, does not only provide insight into foundational issues of physics, but holds the pot

Xiaohan Kong, Boyang Wen, Kaiyi Guo, Ying Liang

We have investigated the magnetism and pairing correlations of the triangular lattice based on the Hubbard model using the determinant quantum Monte Carlo method and the constrained path Monte Carlo. The results show that the presence of the next-nearest-neighbor hopping integral $t^{\prime}$ introduces an additional energy scale to the system, and through $

Xin Hu, X. S. Wang, Zhenyu Wang

We theoretically investigate the antivortex stabilized by anisotropic Dzyaloshinskii-Moriya interaction (DMI) in nanodisks. It is remarkably found that the antivortex remains stable even when the nanodisk radius is reduced to 15 nm, owing to the short-range nature of the DMI. We also investigate the antivortex dynamics under a static in-plane magnetic field,

Katsuyoshi Sone, Tetsuo Hyodo

We discuss the general behavior of the scattering amplitude with channel couplings near the two-body threshold. It is known that the Flatt\'{e} amplitude, which is often used in the analysis of experimental data involving exotic hadrons, has some constraint in the near-threshold energy region. While the M-matrix gives the general expression of the scattering

Cesar Gomez

We construct a model that describes the quantum black hole evaporation unitarily in a Hilbert space of infinite dimension. This construction generalizes Page's finite dimensional approach to infinite dimensions. The basic ingredient is the Murray-von Neumann coupling for finite type II factors. This coupling measures, at each time of the evaporation, the rel

Liming Han, Zhaoxiang Liu, Shiguo Lian

Image matching is still challenging in such scenes with large viewpoints or illumination changes or with low textures. In this paper, we propose a Transformer-based pseudo 3D image matching method. It upgrades the 2D features extracted from the source image to 3D features with the help of a reference image and matches to the 2D features extracted from the de

Chiara Nicotera

We consider groups $G$ such that the set $[G,\varphi]=\{g^{-1}g^{\varphi}|g\in G\}$ is a subgroup for every automorphism $\varphi$ of $G$, and we prove that there exists such a group $G$ that is finite and nilpotent of class $n$ for every $n\in\mathbb N$. Then there exists an infinite nonnilpotent group with the above property and the conjecture 18.14 of $[5

Fernando Sancho de Salas, Alejandro Torres Sancho

We give an elementary proof and generalize some Hochsters's type formulae on local cohomology and Ext's of squarefree modules

Melanie Dohmen, Mark A. Klemens, Ivo M. Baltruschat, Tuan Truong

Image-to-image translation can create large impact in medical imaging, as images can be synthetically transformed to other modalities, sequence types, higher resolutions or lower noise levels. To ensure patient safety, these methods should be validated by human readers, which requires a considerable amount of time and costs. Quantitative metrics can effectiv

Andrei Moroianu, Mihaela Pilca

A conformal product structure on a Riemannian manifold is a Weyl connection with reducible holonomy. We give the geometric description of all compact K\"ahler manifolds admitting conformal product structures

Martín Bayón-Gutiérrez, María Teresa García-Ordás, Héctor Alaiz Moretón, Jose Aveleira-Mata

Robust road surface estimation is required for autonomous ground vehicles to navigate safely. Despite it becoming one of the main targets for autonomous mobility researchers in recent years, it is still an open problem in which cameras and LiDAR sensors have demonstrated to be adequate to predict the position, size and shape of the road a vehicle is driving

Ye Ke, Arindam Basu

With the sensor scaling of next-generation Brain-Machine Interface (BMI) systems, the massive A/D conversion and analog multiplexing at the neural frontend poses a challenge in terms of power and data rates for wireless and implantable BMIs. While previous works have reported the neuromorphic compression of neural signal, further compression requires integra

Yuanchen Shi, Biao Ma, Longyin Zhang, Fang Kong

Stickers are increasingly used in social media to express sentiment and intent. Despite their significant impact on sentiment analysis and intent recognition, little research has been conducted in this area. To address this gap, we propose a new task: \textbf{M}ultimodal chat \textbf{S}entiment \textbf{A}nalysis and \textbf{I}ntent \textbf{R}ecognition invol

Sabir M. Gusein-Zade, Ignacio Luengo, Alejandro Melle-Hernández, Antonio Viruel

We discuss the universal orbifold Euler characteristic and generalized orbifold Euler characteristics corresponding to finitely generated groups $A$ (the $A$-Euler characteristics). We show that the collection of all $A$-Euler characteristics for $A$ of the form $A'\times Z$ ($Z$ is the group of integers) with finite $A'$ determine the universal orbifold Eul

Geoffrey B. Campbell

We describe the story of the Rogers-Ramanujan identities; being known for 85 years and having about 130 pure mathematics proofs, suddenly entering physics when Rodney Baxter solved the Hard Hexagon Model in Statistical Mechanics in 1980. We next cover the accompanying proofs by George E Andrews of other related Baxter identities arisen of Rogers-Ramanujan ty

Fanchen Bu, Hyeonsoo Jo, Soo Yong Lee, Sungsoo Ahn

Combinatorial optimization (CO) is naturally discrete, making machine learning based on differentiable optimization inapplicable. Karalias & Loukas (2020) adapted the probabilistic method to incorporate CO into differentiable optimization. Their work ignited the research on unsupervised learning for CO, composed of two main components: probabilistic objectiv

Yihong Chen, Zhen Fan, Shuai Dong, Zhiwei Chen

Stereo image super-resolution (SR) refers to the reconstruction of a high-resolution (HR) image from a pair of low-resolution (LR) images as typically captured by a dual-camera device. To enhance the quality of SR images, most previous studies focused on increasing the number and size of feature maps and introducing complex and computationally intensive stru

Vladimir E. Karpov

It is well known that whenever a class of structures $\mathcal{K}_1$ is interpretable in a class of structures $\mathcal{K}_2$, then the hereditary undecidability of (a fragment of) the theory of $\mathcal{K}_1$ implies the hereditary undecidability of (a suitable fragment of) the theory of $\mathcal{K}_2$. In the present paper, we construct a $\Sigma_1$-int

Andrea Muratori, Guilhem Semerjian

The correlated Erd\"os-R\'enyi random graph ensemble is a probability law on pairs of graphs with $n$ vertices, parametrized by their average degree $\lambda$ and their correlation coefficient $s$. It can be used as a benchmark for the graph alignment problem, in which the labels of the vertices of one of the graphs are reshuffled by an unknown permutation;

Alexandra Ivanova, Lev Luchnikov, Margarita Golikova, Dmitry S. Muratov

The intense research for efficient low-temperature thermoelectric materials motivates the exploration of innovative compounds and composite systems. This study examines the effects of integrating low-dimensional titanium trisulfide (TiS$_3$) into bulk tin-based halide perovskites (CsSnI$_3$) for use in thermoelectric applications. The addition of small amoun

Meisheng Guan, Haiyong Xu, Gangyi Jiang, Mei Yu

Underwater imaging often suffers from low quality due to factors affecting light propagation and absorption in water. To improve image quality, some underwater image enhancement (UIE) methods based on convolutional neural networks (CNN) and Transformer have been proposed. However, CNN-based UIE methods are limited in modeling long-range dependencies, and Tra

Hassen Nigatu, Li Jihao, Keqi Zhu, Junhan Zhang

This study investigates the stiffness characteristics of the Sprint Z3 head, also known as 3-PRS Parallel Kinematics Machines, which are among the most extensively researched and viably successful manipulators for precision machining applications. Despite the wealth of research on these robotic manipulators, no previous work has demonstrated their stiffness

Andreas Brendel, Nicola Pia, Kishan Gupta, Lyonel Behringer

Neural audio coding has emerged as a vivid research direction by promising good audio quality at very low bitrates unachievable by classical coding techniques. Here, end-to-end trainable autoencoder-like models represent the state of the art, where a discrete representation in the bottleneck of the autoencoder is learned. This allows for efficient transmissi

Árpád Bényi, Guopeng Li, Tadahiro Oh, Rodolfo H. Torres

We prove a compact $T(1)$ theorem, involving quantitative estimates, analogous to the quantitative classical $T(1)$ theorem due to Stein. We also discuss the $C_c^\infty$-to-$CMO$ mapping properties of non-compact Calder\'on-Zygmund operators.

Franz Luef, Johannes Testorf, Xu Wang

We give a criterion for higher-dimensional Gaussian Gabor frames, which is a reformulation of one of the main results in in a previous article by the first and last authors in more explicit terms. We use this formulation in order to extend a result of Romero, Ulanovskii, and Zlotnikov to lattices given by irrational rotations. We also show that this density

J. P. Deka, A. Govindarajan, A. K. Sarma

In this article, we investigate the implications of the unsupervised learning rule known as Input-Correlations (ICO) learning in the nonlinear dynamics of two linearly coupled PT-symmetric Li\'enard oscillators. The fixed points of the oscillator have been evaluated analytically and the Jacobian linearization is employed to study their stability. We find tha

Pierre Gosselin, Aïleen Lotz

In a series of precedent papers, we have presented a comprehensive methodology, termed Field Economics, for translating a standard economic model into a statistical field-formalism framework. This formalism requires a large number of heterogeneous agents, possibly of different types. It reveals the emergence of collective states among these agents or type of

Marco Marinucci, Kevin Pardede, Massimo Pietroni

We develop a model-independent approach to lagrangian perturbation theory for the large scale structure of the universe. We focus on the displacement field for dark matter particles, and derive its most general structure without assuming a specific form for the equations of motion, but implementing a set of general requirements based on symmetry principles a

Árpád Bényi, Guopeng Li, Tadahiro Oh, Rodolfo H. Torres

We present a new proof of the compactness of bilinear paraproducts with CMO symbols. By drawing an analogy to compact linear operators, we first explore further properties of compact bilinear operators on Banach spaces and present examples. We then prove compactness of bilinear paraproducts with CMO symbols by combining one of the properties of compact bilin

Tao Xiong, Yong Wang

Online controlled experiment (also called A/B test or experiment) is the most important tool for decision-making at a wide range of data-driven companies like Microsoft, Google, Meta, etc. Metric computation is the core procedure for reaching a conclusion during an experiment. With the growth of experiments and metrics in an experiment platform, computing me

Rachel Lee, Karin Melnick

We classify closed, conformally flat Lorentzian manifolds of dimension $n \geq 3$ with unipotent holonomy in PO(2,n). They are all Kleinian and fall into four different geometric types according to the intersection of the image of the developing map with a holonomy-invariant isotropic flag. They are homeomorphic to $S^{n-1} \times S^1$ or a nilmanifold of de

Kotaro Muramatsu, Hiroshi Kori

The neural oscillator model proposed by Matsuoka is a piecewise affine system, which exhibits distinctive periodic solutions. Although such typical oscillation patterns have been widely studied, little is understood about the dynamics of convergence to certain fixed points and bifurcations between the periodic orbits and fixed points in this model. We perfor

Huawei Fan, Yafeng Wang, Yao Du, Haibo Qiu

Cluster synchronization in synthetic networks of coupled chaotic oscillators is investigated. It is found that despite the asymmetric nature of the network structure, a subset of the oscillators can be synchronized as a cluster while the other oscillators remain desynchronized. Interestingly, with the increase of the coupling strength, the cluster is expandi

M. Bouvier, S. Viti, E. Behrens, J. Butterworth

Sulphur-bearing species are detected in various environments within Galactic star-forming regions and are particularly abundant in the gas phase of outflows and shocks, and photo-dissociation regions. In this work, we aim to investigate the nature of the emission from the most common sulphur-bearing species observable at millimetre wavelengths towards the nu

Daoyin He, Qianqian Li, Huicheng Yin

In this paper, we are concerned with the global existence of small data weak solutions to the $n-$dimensional semilinear wave equation $\partial_t^2u-\Delta u+\frac{\mu}{t}\partial_tu=|u|^p$ with time-dependent scale-invariant damping, where $n\geq 2$, $t\geq 1$, $\mu\in(0,1)\cup(1,2]$ and $p>1$. This equation can be changed into the semilinear generalized T

Tarik Sahin, Daniel Wolff, Max von Danwitz, Alexander Popp

In this study, we investigate the potential of fast-to-evaluate surrogate modeling techniques for developing a hybrid digital twin of a steel-reinforced concrete beam, serving as a representative example of a civil engineering structure. As surrogates, two distinct models are developed utilizing physics-informed neural networks, which integrate experimental

Anne Rubbens, Julien M. Hendrickx

We consider the problem of obtaining interpolation constraints for function classes, i.e., necessary and sufficient constraints that a set of points, function values and (sub)gradients must satisfy to ensure the existence of a global function of the class considered, consistent with this set. The derivation of such constraints is crucial, e.g., in the perfor

Camille Coron, Yves Le Jan

We consider a population of N individuals, whose dynamics through time is represented by a biparental Moran model with two types: an advantaged type and a disadvantaged type. The advantage is due to a mutation, transmitted in a Mendelian way from parent to child that reduces the death probability of individuals carrying it. We assume that initially this muta

Xinhao Zhang, Zaitian Wang, Lu Jiang, Wanfu Gao

In this paper, we propose a novel feature weighting method to address the limitation of existing feature processing methods for tabular data. Typically the existing methods assume equal importance across all samples and features in one dataset. This simplified processing methods overlook the unique contributions of each feature, and thus may miss important f

Valentin Vielzeuf

Self-supervised learning has shown great success in Speech Recognition. However, it has been observed that finetuning all layers of the learned model leads to lower performance compared to resetting top layers. This phenomenon is attributed to the ''autoencoder'' behavior: top layers contain information closer to the input and are less suitable for tasks tha

F. Duerr, J. Ziehn, R. Kohlhaas, M. Roschani

In the event of a critical system failures in auto-mated vehicles, fail-operational or fail-safe measures provide minimum guarantees for the vehicle's performance, depending on which of its subsystems remain operational. Various such methods have been proposed which, upon failure, use different remaining sets of operational subsystems to execute maneuvers th

Georg Niess, Roman Kern

The rapid advancement of large language models (LLMs) has made it increasingly difficult to distinguish between text written by humans and machines. Addressing this, we propose a novel method for generating watermarks that strategically alters token probabilities during generation. Unlike previous works, this method uniquely employs linguistic features such

Duc Thinh Ngo, Kandaraj Piamrat, Ons Aouedi, Thomas Hassan

From a telecommunication standpoint, the surge in users and services challenges next-generation networks with escalating traffic demands and limited resources. Accurate traffic prediction can offer network operators valuable insights into network conditions and suggest optimal allocation policies. Recently, spatio-temporal forecasting, employing Graph Neural

Maung Thway, Andy Paul Chen, Haiwen Dai, Jose Recatala-Gomez

Recent advances in machine learning techniques have made it possible to use high-throughput screening to identify novel materials with specific properties. However, the large number of potential candidates produced by these techniques can make it difficult to select the most promising ones. In this study, we develop the oxidation state probability (OSP) meth

David Abella, Johann H. Martínez, Mattia Mazzoli, Thibault Le Corre

The real estate market shows an inherent connection to space. Real estate agencies unevenly operate and specialize across space, price and type of properties, thereby segmenting the market into submarkets. We introduce here a methodology based on multipartite networks to detect the spatial segmentation emerging from data on housing online listings. Consideri

Julie Keisler, Sandra Claudel, Gilles Cabriel, Margaux Brégère

Accurate forecasting of electricity consumption is essential to ensure the performance and stability of the grid, especially as the use of renewable energy increases. Forecasting electricity is challenging because it depends on many external factors, such as weather and calendar variables. While regression-based models are currently effective, the emergence

Julien Laval, Aymeric Gaudin, Vincent Frouin, Jessica Dubois

Brain folding patterns have been reported to carry clinically relevant information. The brain folds mainly during the last trimester of pregnancy, and the process might be durably disturbed by preterm birth. Yet little is known about preterm-specific patterns. In this work, we train a self-supervised model (SimCLR) on the UKBioBank cohort (21070 adults) to r

Stella Civelli, Debi Pada Jana, Enrico Forestieri, Marco Secondini

We propose a novel digital backpropagation (DBP) technique that combines perturbation theory, subband processing, and splitting ratio optimization. We obtain 0.23 dB, 0.47 dB, or 0.91 dB gains w.r.t. dispersion compensation with only 74, 161, or 681 real multiplications/2D-symbol, improving significantly on existing DBP techniques.

Kelly Charniga, Sang Woo Park, Andrei R Akhmetzhanov, Anne Cori

Epidemiological delays, such as incubation periods, serial intervals, and hospital lengths of stay, are among key quantities in infectious disease epidemiology that inform public health policy and clinical practice. This information is used to inform mathematical and statistical models, which in turn can inform control strategies. There are three main challe

Michael Sober, Giulia Scaffino, Stefan Schulte

The closed architecture of prevailing blockchain systems renders the usage of this technology mostly infeasible for a wide range of real-world problems. Most blockchains trap users and applications in their isolated space without the possibility of cooperating or switching to other blockchains. Therefore, blockchains need additional mechanisms for seamless c

Anxiang Huang

In this paper, we showed that for some given suitable density and pressure, there exist infinitely many compactly supported solutions with prescribed energy profile. The proof is mainly based on the convex integration scheme. We construct suitable subsolutions and localized plane-wave solutions to the reformulated system, and weak solutions are obtained by i

Thibaut Lemoine, Mylène Maïda

We study a Gaussian measure with parameter $q\in(0,1)$ on the dual of the unitary group of size $N$: we prove that a random highest weight under this measure is the coupling of two independent $q$-uniform random partitions $\alpha,\beta$ and a random highest weight of $\mathrm{U}(1)$. We prove deviation inequalities for the $q$-uniform measure, and use them

Kongyang Chen, Dongping Zhang, Sijia Guan, Bing Mi

Wearable data serves various health monitoring purposes, such as determining activity states based on user behavior and providing tailored exercise recommendations. However, the individual data perception and computational capabilities of wearable devices are limited, often necessitating the joint training of models across multiple devices. Federated Human A

Reza Ahmadvand, Sarah Safura Sharif, Yaser Mike Banad

State estimation of nonlinear dynamical systems has long aimed to balance accuracy, computational efficiency, robustness, and reliability. The rapid evolution of various industries has amplified the demand for estimation frameworks that satisfy all these factors. This study introduces a neuromorphic approach for robust filtering of nonlinear dynamical system

Laurent Goffart

At the turn of the 20th century, Henri Poincar{\'e} explained that geometry is a convention and that the properties of space and time are the properties of our measuring instruments. Intriguingly, numerous contemporary authors argue that space, time and even number are ''encoded'' within the brain, as a consequence of evolution, adaptation and natural select

Anxiang Huang

In this paper, we prove the non-uniqueness of stationary solutions to steady incompressible Euler equations with source terms. Based on the convex integration scheme developed by De Lellis and Sz\'{e}kelyhidi, the Euler system is reformulated as a differential inclusion. The key point is to construct the corresponding plane-wave solutions via high frequency

Xingfeng Sang, Francis White, Francis Nier

We study in this article the combined asymptotic analysis of Bismut's hypoelliptic Laplacian, in the high friction b $\rightarrow$ 0+ and possibly low temperature h $\rightarrow$ 0+ regimes.

Christopher Anderson, Philippe Berger, Tzu-Ching Chang, Olivier Doré

We present six nearly full-sky maps made from data taken by radiometers on the Juno satellite during its 5-year flight to Jupiter. The maps represent integrated emission over $\sim 4\%$ passbands spaced approximately in octaves between 600 MHz and 21.9 GHz. Long time-scale offset drifts are removed in all bands, and, for the two lowest frequency bands, gain

Yohei Sawada

It is a grand challenge to find a feasible weather modification method to mitigate the impact of extreme weather events such as tropical cyclones. Previous works have proposed potentially effective actuators and assessed their capabilities to achieve weather modification objectives through numerical simulations. However, few studies have explored efficient m

Sarah Winkler, Joachim R. Krenn, Jakob Wahl, Alexander Zesar

A promising solution for scalable integrated optics of trapped-ion quantum processors are curved waveguides guiding visible light within sapphire bulk material. To the best of our knowledge, no curved waveguides were investigated in sapphire so far, and no measurements of waveguides with visible light in undoped planar sapphire substrates were reported. Here

Feng Chen, Wei-Wei Luo, Wei Zhu, D. N. Sheng

A recent experiment observes a series of quantum spin Hall effects in transition metal dichalcogenide moir\'e MoTe$_2$ [K. Kang, et. al, Nature 628, 522-526 (2024)]. Among them, the vanishing Hall signal at the filling factor $\nu=3$ implies a possible realization of a time-reversal pair of the even-denominator fractional Chern insulators (FCIs). Inspired by

Yiwei Bao, Pasquale Blasi, Yang Chen

The recent discovery of the so-called TeV halos has attracted much attention. The morphology of the emission requires that the region is characterized by severe suppression of the diffusion coefficient. This finding raises many questions as to its origin: 1) is the suppressed diffusion to be attributed to instabilities induced by the same radiating particles

Mario Ayala, Jérôme Coville, Samuel Soubeyrand

In this paper we revisit the notion of grouped dispersal that have been introduced by Soubeyrand and co-authors \cite{soubeyrand2011patchy} to model the simultaneous (and hence dependent) dispersal of several propagules from a single source in a homogeneous environment. We built a time continuous measure valued process that takes into account the main featur

Robert J. Lemke Oliver, Alexander Smith

Given a finite group G, we prove that the vector space spanned by the faithful irreducible characters of G is generated by the monomial characters in the vector space. As a consequence, we show that in any family of G-extensions of a fixed number field F, almost all are subject to a strong effective version of the Chebotarev density theorem. We use this vers

Yunwen Liu, Jiang Xiao

We propose a novel approach for precision measurement utilizing an ensemble of probabilistic bits (p-bits). This method leverages the inherent fluctuations of p-bits to achieve high sensitivity in various applications, including magnetic field sensing, temperature monitoring and timekeeping. The sensitivity scales proportionally to the square root of the tot

Hendrik Baers, Giovanni Covi, Angkana Rüland

We prove exponential instability properties for the fractional Calder\'on problem and the conductivity formulation of the fractional Calder\'on problem in the regime of fractional powers $s\in (0,1)$. We particularly focus on two settings: First, we discuss instability properties in general domain geometries with scaling critical $L^{\frac{n}{2s}}$ potential

Jingwen Wang, Dehui Du, Yida Li, Yiyang Li

In the training process of Deep Reinforcement Learning (DRL), agents require repetitive interactions with the environment. With an increase in training volume and model complexity, it is still a challenging problem to enhance data utilization and explainability of DRL training. This paper addresses these challenges by focusing on the temporal correlations wi

Arshika Lalan, Shresth Verma, Paula Rodriguez Diaz, Panayiotis Danassis

Harnessing the wide-spread availability of cell phones, many nonprofits have launched mobile health (mHealth) programs to deliver information via voice or text to beneficiaries in underserved communities, with maternal and infant health being a key area of such mHealth programs. Unfortunately, dwindling listenership is a major challenge, requiring targeted i

Christopher Hojny

Symmetries in mixed-integer (nonlinear) programs (MINLP), if not handled appropriately, are known to negatively impact the performance of (spatial) branch-and-bound algorithms. Usually one thus tries to remove symmetries from the problem formulation or is relying on a solver that automatically detects and handles symmetries. While modelers of a problem can h

Mathis Fitoussi, Benjamin Jourdain, Stéphane Menozzi

We are interested in the discretization of stable driven SDEs with additive noise for $\alpha$ $\in$ (1, 2) and Lq -- Lp drift under the Serrin type condition $\alpha$/q + d/p < $\alpha$ -- 1. We show weak existence and uniqueness as well as heat kernel estimates for the SDE and obtain a convergence rate of order (1/$\alpha$)*($\alpha$ -- 1 -- $\alpha$/q - d

MIT Hardness Group, Josh Brunner, Lily Chung, Erik D. Demaine

We prove that Hamiltonicity in maximum-degree-3 grid graphs (directed or undirected) is ASP-complete, i.e., it has a parsimonious reduction from every NP search problem (including a polynomial-time bijection between solutions). As a consequence, given k Hamiltonian cycles, it is NP-complete to find another; and counting Hamiltonian cycles is #P-complete. If

P. L. Liu

In this talk, we present the recent results of charm physics from the BESIII experiment. It covers the studies of the pure leptonic and semi-leptonic decays of charmed hadrons, from which the |Vcs| are precisely determined and the LFU is tested.

Antonio Corbo Esposito, Rosa Fera, Francesco Romeo

In this paper, we present OliVier a new Public Key Exchange cryptosystem that is based on a multivariate quadratic polynomial system: Oil & Vinegar polynomials together with fully quadratic ones. We describe its designing process, usage, complexity

Eric O. Endo, Aernout C. D. van Enter, Arnaud Le Ny

We consider polynomial long-range Ising models in one dimension, with ferromagnetic pair interactions decaying with power $2-\alpha$ (for $0 \leq \alpha < 1$), and prepared with randomly chosen boundary conditions. We show that at low temperatures in the thermodynamic limit the finite-volume Gibbs measures do not converge, but have a distributional limit, th

Satya K Gundabathula, Sriram R Kolar

This paper presents our approach to the EHRSQL-2024 shared task, which aims to develop a reliable Text-to-SQL system for electronic health records. We propose two approaches that leverage large language models (LLMs) for prompting and fine-tuning to generate EHRSQL queries. In both techniques, we concentrate on bridging the gap between the real-world knowled

Satya Kesav Gundabathula, Sriram R Kolar

This paper describes our approach to the MEDIQA-CORR shared task, which involves error detection and correction in clinical notes curated by medical professionals. This task involves handling three subtasks: detecting the presence of errors, identifying the specific sentence containing the error, and correcting it. Through our work, we aim to assess the capa

Federico Poli, Xavier Denis, Peter Müller, Alexander J. Summers

Existing automated verification techniques for safe Rust code rely on the strong type-system properties to reason about programs, especially to deduce which memory locations do not change (i.e., are framed) across function calls. However, these type guarantees do not hold in the presence of interior mutability (e.g., when interacting with any concurrent data

Tullio Ceccherini-Silberstein, Fabio Scarabotti, Filippo Tolli

Let $K\leq H$ be two finite groups and let $C\leq A$ be two finite abelian groups, with $H$ acting on $A$ as a group of isomorphisms admitting $C$ as a $K$-invariant subgroup. We study the homogeneous space $X\coloneqq\left(H\ltimes A\right)/\left(K\ltimes C\right)$ and determine the decomposition of the permutation representation of $H\ltimes A$ acting on $

Kunle Adegoke, Robert Frontczak

In this note, we show how a combinatorial identity of Frisch can be applied to prove and generalize some well-known identities involving harmonic numbers. We also present some combinatorial identities involving odd harmonic numbers which can be inferred straightforwardly from our results.

Sujay K. Ashok, Jan Troost

We revisit the flavored elliptic genus of the N=2 superconformal cigar model and generalize the analysis of the path integral result to the case of real central charge. It gives rise to a non-holomorphic modular covariant function generalizing completed mock modular forms. We also compute the genus for angular orbifolds of the cigar and Liouville theory and

Brice Franke, Shuenn-Jyi Sheu

We study how the resolvent-family of a diffusion behaves, as thedrift grows to infinity. The limit turns out to be a selfadjoint pseudo-resolvent.After reduction of the underlying Hilbert-space, this pseudo-resolvent becomesa resolvent to a strongly continuous semi-group of contractions. We prove thatthis semi-group is associated to some Hunt-process on some

J. A. Sheikh, S. Jehangir, G. H. Bhat

A systematic investigation of the wobbling band structures observed in odd-mass nuclei of $^{161,163,165,167}$Lu, $^{167}$Ta $^{131}$Cs, $^{135}$Pr, $^{151}$Eu, $^{183}$Au, $^{133}$Ba, $^{105}$Pd, $^{133}$La, $^{187}$Au and $^{127}$Xe is performed using the triaxial projected shell model (TPSM) approach. It is demonstrated that all the studied band structure

Ko Nakamura, Tomoya Takiwaki, Jin Matsumoto, Kei Kotake

We present results from three-dimensional, magnetohydrodynamic, core-collapse simulations of sixteen progenitors following until 0.5 s after bounce. We use non-rotating solar-metallicity progenitor models with zero-age main-sequence mass between 9 and 24 $M_{\odot}$. The examined progenitors cover a wide range of the compactness parameter including a peak ar

Aleksandar Makelov, George Lange, Neel Nanda

Disentangling model activations into meaningful features is a central problem in interpretability. However, the absence of ground-truth for these features in realistic scenarios makes validating recent approaches, such as sparse dictionary learning, elusive. To address this challenge, we propose a framework for evaluating feature dictionaries in the context

Wen Huang, Wutao Si

Recently, a Riemannian proximal Newton method has been developed for optimizing problems in the form of $\min_{x\in\mathcal{M}} f(x) + \mu \|x\|_1$, where $\mathcal{M}$ is a compact embedded submanifold and $f(x)$ is smooth. Although this method converges superlinearly locally, global convergence is not guaranteed. The existing remedy relies on a hybrid appr

Friedrich Wehrung

A map $f\colon R\to S$ between (associative, unital, but not necessarily commutative) rings is a\emph{brachymorphism} if $f(1+x)=1+f(x)$ and $f(xy)=f(x)f(y)$ whenever $x,y\in R$. We tackle the problem whether every brachymorphism is additive (i.e., $f(x+y)=f(x)+f(y)$), showing that in many contexts, including the following, the answer is positive: $R$ is fin

Andre Kassis, Urs Hengartner

Reports regarding the misuse of Generative AI (GenAI) to create deepfakes are frequent. Defensive watermarking enables GenAI providers to hide fingerprints in their images and use them later for deepfake detection. Yet, its potential has not been fully explored. We present UnMarker -- the first practical universal attack on defensive watermarking. Unlike exi

Georges Gagneré

In parallel with the dissemination of information technology, we note the persistence of frontiers within creative practices, in particular between the digital arts and the performing arts. Crossings of these frontiers brought to light the need for a common appropriation of digital issues. As a result of this appropriation, the AvatarStaging platform and its

Arash Dehzangi

Recent increasing interest in strain balanced Type-II superlattices material causing close attention from industry. Tremendous investment was drawn toward establishing strain balanced superlattice (SLS) as new alternative for infrared photodetectors across the broad range of infrared spectrum. In recent years, SLS material system has shown capability in part

Rhiannon Savage

The representability theorem for stacks, due to Artin in the underived setting and Lurie in the derived setting, gives conditions under which a stack is representable by an $n$-geometric stack. In recent work of Ben-Bassat, Kelly, and Kremnizer, a new theory of derived analytic geometry has been proposed as geometry relative to the $(\infty,1)$-category of s