December 2024 arXiv papers — page 138

Lukas Seemann, Jana Lukin, Max Häßler, Sibylle Gemming

While billiard systems of various shapes have been used as paradigmatic model systems in the fields of nonlinear dynamics and quantum chaos, few studies have investigated anisotropic billiards. Motivated by the tremendous advances in using and controlling electronic and optical mesoscopic systems with bilayer graphene representing an easily accessible anisot

Juan Manuel Aguiar Hualde, Marek Kowalik, Lian Remme, Franziska Elisabeth Wolff

Corrosion presents a major challenge to the longevity and reliability of products across various industries, particularly in the aerospace sector. Corrosion arises from chemical processes occurring on an atomistic scale, which lead to macroscopic degradation. Addressing this issue requires multi-scale modeling approaches, which rely on microscopic parameters

Mohamed Mahmoud Chems-Eddin, Badr Feryouch, Hakima Mouanis, Ali Tamoussit

Let $D$ be an integral domain with quotient field $K$ and $E$ a subset of $K$. The \textit{ring of integer-valued rational functions on} $E$ is defined as $$\mathrm{int}_R(E,D):=\lbrace \varphi \in K(X);\; \varphi(E)\subseteq D\rbrace.$$ The main goal of this paper is to investigate the Krull dimension of the ring $\mathrm{int}_R(E,D).$ Particularly, we are

Duifje Maria van Egmond, Orlando Oliveira, Urko Reinosa, Julien Serreau

A lattice implementation of the recently introduced center-symmetric Landau gauge is discussed and its predictions confronted with numerical Monte Carlo simulations. It is shown that the link average and the link correlators computed in that gauge are order parameters of the confinement-deconfinement transition at nonzero temperature. Strictly speaking, this

Robert Kutri, Robert Scheichl

Gaussian processes (GPs) and Gaussian random fields (GRFs) are essential for modelling spatially varying stochastic phenomena. Yet, the efficient generation of corresponding realisations on high-resolution grids remains challenging, particularly when a large number of realisations are required. This paper presents two novel contributions. First, we propose a

Mauro Artigiani, Pascal Hubert, Alexandra Skripchenko

We study a class of interval translation mappings introduced by Bruin and Troubetzkoy, describing a new renormalization scheme, inspired by the classical Rauzy induction for this class. We construct a measure, invariant under the renormalization, supported on the parameters yielding infinite type interval translation mappings in this class. With respect to t

Mohsen Hesamolhokama, Amirahmad Shafiee, Mohammadreza Ahmaditeshnizi, Mohammadamin Fazli

Ensuring software quality remains a critical challenge in complex and dynamic development environments, where software defects can result in significant operational and financial risks. This paper proposes an innovative framework for software defect prediction that combines ensemble feature extraction with reinforcement learning (RL)--based feature selection

Lijie Ding, Yihao Chen, Changwoo Do

We carry out theoretical analysis, Monte Carlo simulations and Machine Learning analysis to quantify microscopic rearrangements of dilute dispersions of spherical colloidal particles from coherent scattering intensity. Both monodisperse and polydisperse dispersions of colloids are created and undergo a rearrangement consisting of an affine simple shear and n

Ali Hasan Ali, Zsolt Páles

Motivated by classical results of approximation theory, we define an Hermite-type interpolation in terms of $n$-dimensional subspaces of the space of $n$ times continuously differentiable functions. In the main result of this paper, we establish an error term in integral form for this interpolation in the case when the $n$-dimensional subspace is the kernel

Emily Robitschek, Asal Bastani, Kathryn Horwath, Savyon Sordean

Patient life circumstances, including social determinants of health (SDOH), shape both health outcomes and care access, contributing to persistent disparities across gender, race, and socioeconomic status. Liver transplantation exemplifies these challenges, requiring complex eligibility and allocation decisions where SDOH directly influence patient evaluatio

Sagi Shaier, Mario Sanz-Guerrero, Katharina von der Wense

This study investigates whether repeating questions within prompts influences the performance of large language models (LLMs). We hypothesize that reiterating a question within a single prompt might enhance the model's focus on key elements of the query. We evaluate five recent LLMs -- including GPT-4o-mini, DeepSeek-V3, and smaller open-source models -- on

Xinyue Hu, Wei Ye, Jiaxiang Tang, Eman Ramadan

Multiple Description Coding (MDC) is a promising error-resilient source coding method that is particularly suitable for dynamic networks with multiple (yet noisy and unreliable) paths. However, conventional MDC video codecs suffer from cumbersome architectures, poor scalability, limited loss resilience, and lower compression efficiency. As a result, MDC has

Lukas M. Bongartz, Garrett LeCroy, Tyler J. Quill, Nicholas Siemons

Organic electrochemical transistors are extensively studied for applications ranging from bioelectronics to analog and neuromorphic computing. Despite significant advances, the fundamental interactions between the polymer semiconductor channel and the electrolyte, which critically determine the device performance, remain underexplored. Here, we examine the c

Lars Niedorf

We prove an $L^p$-spectral multiplier theorem under the sharp regularity condition $s > d\left|1/p - 1/2\right|$ for sub-Laplacians on M\'etivier groups. The proof is based on a restriction type estimate which, at first sight, seems to be suboptimal for proving sharp spectral multiplier results, but turns out to be surprisingly effective. This is achieved by

Diederik Aerts, Jonito Aerts Arguëlles, Lester Beltran, Massimiliano Sassoli de Bianchi

We present a theoretical and empirical investigation of the statistical behaviour of the words in a text produced by human language. To this aim, we analyse the word distribution of various texts of Italian language selected from a specific literary corpus. We firstly generalise a theoretical framework elaborated by ourselves to identify 'quantum mechanical

Alex Keene, Christian Soltermann, Gaywalee Yamskulna

This paper investigates the algebraic structure of indecomposable $\mathbb{N}$-graded vertex algebras $V = \bigoplus_{n=0}^{\infty} V_n$, emphasizing the intricate interactions between the commutative associative algebra $V_0$, the Leibniz algebra $V_1$ and how non-degenerate bilinear forms on $V_0$ influence their overall structure. We establish foundationa

Sathya Narayana Mohan, Gelli Ravikumar, Manimaran Govindarasu

Cyber-physical system (CPS) security for the smart grid enables secure communication for the SCADA and wide-area measurement system data. Power utilities world-wide use various SCADA protocols, namely DNP3, Modbus, and IEC 61850, for the data exchanges across substation field devices, remote terminal units (RTUs), and control center applications. Adversaries

Omar Gallegos, Tonatiuh Matos, Hugo A. Morales-Técotl

Loop quantum cosmology was shown to interpolate between de Sitter and FLRW Universe phases through a bounce by including Euclidean and Lorentzian terms of the Hamiltonian constraint with weight one -that corresponding to classical General Relativity. Unitary evolution required self-adjoint extensions of the constraint and a Planckian cosmological constant wa

Gabriele Agliardi, Giorgio Cortiana, Anton Dekusar, Kumar Ghosh

Fidelity quantum kernels have shown promise in classification tasks, particularly when a group structure in the data can be identified and exploited through a covariant feature map. In fact, there exist classification problems on which covariant kernels provide a provable advantage, thus establishing a separation between quantum and classical learners. Howev

Davide Baiocco, Ignacio Lopez-Quintas, Javier R. Vázquez de Aldana, Alessandro di Maggio

In this article we report the fabrication of a diode-pumped Dy,Tb:LiLuF4 waveguide laser operating in the yellow region of the visible spectrum. The circular depressed-cladding waveguides have been fabricated by direct femtosecond laser writing, and showed propagation losses as low as 0.07 dB/cm. By employing these structures, we obtain a maximum output powe

Thuc T. Mai, Yufei Li, K. F. Garrity, D. Shaw

The entanglement of electronic spin and orbital degrees of freedom is often the precursor to emergent behaviors in condensed matter systems. With considerable spin-orbit coupling strength, the cobalt atom on a honeycomb lattice offers a platform that can make accessible the study of novel magnetic ground states. Using temperature-dependent Raman spectroscopy

Bora Tarlan, Nisa Erdal

This study explores human perceptions of intelligent agents by comparing interactions with a humanoid robot and a virtual human avatar, both utilizing GPT-3 for response generation. The study aims to understand how physical and virtual embodiments influence perceptions of anthropomorphism, animacy, likeability, and perceived intelligence. The uncanny valley

Erik Connerty, Ethan Evans, Gerasimos Angelatos, Vignesh Narayanan

Recent advancements in artificial neural networks have enabled impressive tasks on classical computers, but they demand significant computational resources. While quantum computing offers potential beyond classical systems, the advantages of quantum neural networks (QNNs) remain largely unexplored. In this work, we present and examine a quantum circuit (QC)

Can Yaras, Siyi Chen, Peng Wang, Qing Qu

Multimodal learning has recently gained significant popularity, demonstrating impressive performance across various zero-shot classification tasks and a range of perceptive and generative applications. Models such as Contrastive Language-Image Pretraining (CLIP) are designed to bridge different modalities, such as images and text, by learning a shared repres

Florian Luca, Joel Ouaknine, James Worrell

We prove transcendence of the Hecke-Mahler series $\sum_{n=0}^\infty f(\lfloor n\theta+\alpha \rfloor) \beta^{-n}$, where $f(x) \in \mathbb{Z}[x]$ is a non-constant polynomial $\alpha$ is a real number, $\theta$ is an irrational real number, and $\beta$ is an algebraic number such that $|\beta|>1$.

Chin-Hung Chen, Boris Karanov, Ivana Nikoloska, Wim van Houtum

Blind estimation of intersymbol interference channels based on the Baum-Welch (BW) algorithm, a specific implementation of the expectation-maximization (EM) algorithm for training hidden Markov models, is robust and does not require labeled data. However, it is known for its extensive computation cost, slow convergence, and frequently converges to a local ma

Minxue Niu, Yara El-Tawil, Amrit Romana, Emily Mower Provost

Modern affective computing systems rely heavily on datasets with human-annotated emotion labels, for training and evaluation. However, human annotations are expensive to obtain, sensitive to study design, and difficult to quality control, because of the subjective nature of emotions. Meanwhile, Large Language Models (LLMs) have shown remarkable performance o

Michael Hellstern, Byol Kim, Zaid Harchaoui, Ali Shojaie

Spectral networks derived from multivariate time series data arise in many domains, from brain science to Earth science. Often, it is of interest to study how these networks change under different conditions. For instance, to better understand epilepsy, it would be interesting to capture the changes in the brain connectivity network as a patient experiences

Stephen Robbins

We derive a general change of variables formula for score functions, showing that for a smooth, invertible transformation $\mathbf{y} = \phi(\mathbf{x})$, the transformed score function $\nabla_{\mathbf{y}} \log q(\mathbf{y})$ can be expressed directly in terms of $\nabla_{\mathbf{x}} \log p(\mathbf{x})$. Using this result, we develop two applications: First

Simão S. Cardoso, A. J. Chaves, N. Asger Mortensen, N. M. R. Peres

This paper explores the application of Madelung hydrodynamic models to study two-dimensional electron gases, with a focus on nonlocal plasmonics and nonlinear optics. We begin by reviewing the derivation of the Madelung equations. Using the Madelung equations in conjunction with Poisson's equation, we calculate the spectrum of magnetoplasmons and the magneto

Meyer Scetbon, James Hensman

We consider the problem of model compression for Large Language Models (LLMs) at post-training time, where the task is to compress a well-trained model using only a small set of calibration input data. In this work, we introduce a new low-rank approach to correct for quantization errors of \emph{activations} in LLMs: we propose to add low-rank weight matrice

Abbas K. Rizi, Riccardo Michielan, Clara Stegehuis, Mikko Kivelä

Homophily -- the tendency of individuals to interact with similar others -- shapes how networks form and function. Yet existing approaches typically collapse homophily to a single scale, either one parameter for the whole network or one per community, thereby detaching it from other structural features. Here, we introduce a maximum-entropy random graph model

Samuel J. Milner, Adrian E. Feiguin

We present a density matrix renormalization group(DMRG) study of a generalized Hubbard chain describing effective spin S=3/2 fermions in an optical lattice.We determine the full phase diagram for the SU(4) symmetric case, and in the presence of single-ion anisotropy in terms of density and polarization.We investigate the stability and competition between dif

Julian De Freitas, Noah Castelo, Ahmet K. Uğuralp, Zeliha Oğuz-Uğuralp

Can consumers form especially deep emotional bonds with AI and be vested in AI identities over time? We leverage a natural app-update event at Replika AI, a popular US-based AI companion, to shed light on these questions. We find that, after the app removed its erotic role play (ERP) feature, preventing intimate interactions between consumers and chatbots th

Yeshwanth Kumar Adimoolam, Charalambos Poullis, Melinos Averkiou

Extraction of building footprint polygons from remotely sensed data is essential for several urban understanding tasks such as reconstruction, navigation, and mapping. Despite significant progress in the area, extracting accurate polygonal building footprints remains an open problem. In this paper, we introduce Pix2Poly, an attention-based end-to-end trainab

Maximilien Barbier, Arseni Goussev

Quantum mechanics introduces the possibility for particles to move in a direction opposite to their momentum -- a counter-intuitive and classically impossible phenomenon known as quantum backflow. The magnitude of this effect is relatively small, making its experimental observation, which has yet to be achieved, particularly challenging. Here, we investigate

Mark Bishop, Sean Ougthon, Tulasi Parashar, Yvette Perrott

We apply nested-sampling (NS) Bayesian analysis [AshtonEA22] to a model for the transport of MHD-scale solar wind fluctuations. The dual objectives are to obtain improved constraints on parameters present in the turbulence transport model (TTM) and to support comparisons of distinct versions of the TTM. The TTMs analysed are essentially 1D steady-state prese

Graham Andrew Smith

We study finite-type solutions of the elliptic sinh-Gordon equation along the strip $\Bbb{R}\times[0,L]$ with Durham conditions on each boundary component. We determine necessary rationality criteria for these conditions to be satisfied on both components. These rationality criteria are analogous to the necessary and sufficient criteria for finite-type solut

Anton Matsson, Lena Stempfle, Yaochen Rao, Zachary R. Margolin

Modeling policies for sequential clinical decision-making based on observational data is useful for describing treatment practices, standardizing frequent patterns in treatment, and evaluating alternative policies. For each task, it is essential that the policy model is interpretable. Learning accurate models requires effectively capturing the state of a pat

Haoyang Li, Fangcheng Fu, Sheng Lin, Hao Ge

To optimize large Transformer model training, both efficient parallel computing and advanced data management are indispensable. However, current methods often assume a stable and uniform training workload, neglecting data-induced imbalances-arising from both sampling and packing processes-which can impede training performance. Specifically, data sampling imb

Juho Vepsäläinen, Arto Hellas, Petri Vuorimaa

During its thirty years of existence, the World Wide Web has helped to transform the world and create digital economies. Although it started as a global information exchange, it has become the most significant available application platform on top of its initial target. One of the side effects of this evolution was perhaps suboptimal ways to deliver content

Jahid Chowdhury Choton, William H. Hsu

Coverage path planning (CPP) is the task of computing an optimal path within a region to completely scan or survey an area of interest using one or multiple mobile robots. Robots equipped with sensors and cameras can collect vast amounts of data on crop health, soil conditions, and weather patterns. Advanced analytics can then be applied to this data to make

Sharaf K. Magableh, Caisheng Wang, Feng Lin

Classical monofacial solar photovoltaic systems have gained prevalence and are widely reported in the literature because they have a lower initial cost compared with bifacial systems. However, limited investigation of both systems has been done on a utility scale with different performance indicators. This paper introduces a multifaceted comparative analysis

Aysan Aghazadeh, Adriana Kovashka

We address the task of advertisement image generation and introduce three evaluation metrics to assess Creativity, prompt Alignment, and Persuasiveness (CAP) in generated advertisement images. Despite recent advancements in Text-to-Image (T2I) generation and their performance in generating high-quality images for explicit descriptions, evaluating these model

Alexander Long

Frontier models are currently developed and distributed primarily through two channels: centralized proprietary APIs or open-sourcing of pre-trained weights. We identify a third paradigm - Protocol Learning - where models are trained across decentralized networks of incentivized participants. This approach has the potential to aggregate orders of magnitude m

Andrew Hamara, Benjamin Kilpatrick, Alex Baratta, Brendon Kofink

Recently, we have witnessed the rise of novel ``event-based'' camera sensors for high-speed, low-power video capture. Rather than recording discrete image frames, these sensors output asynchronous ``event'' tuples with microsecond precision, only when the brightness change of a given pixel exceeds a certain threshold. Although these sensors have enabled comp

J. Toivanen, V. Kolehmainen, A. Paldanius, A. Hänninen

Objective: To develop a fast image reconstruction method for stroke monitoring with electrical impedance tomography with image quality comparable to computationally expensive nonlinear model-based methods. Methods: A post-processing approach with graph convolutional networks is employed. Utilizing the flexibility of the graph setting, a graph U-net is traine

Nadine Lammer, Dominik Werhahn, Dirk Johrendt

The beta-modification of FeSe, which has an anti-PbO type structure, achieves superconductivity at 8 K without external doping or pressure and exhibits a nematic phase, which has been crucial for studies of unconventional pairing mechanisms. Although the critical temperature (Tc) in FeSe increases significantly with applied pressure, intercalation, and in th

Gyula Lakos

We review and provide simplified proofs related to the Magnus expansion, and improve convergence estimates. Observations and improvements concerning the Baker--Campbell--Hausdorff expansion are also made. In this Part IE, we consider the case of finite dimensional Banach algebras. We show that Magnus expansion is convergent (and works in logarithmic sense) i

Melvin Mokhtari

As the field of data analysis grows rapidly due to the large amounts of data being generated, effective data classification has become increasingly important. This paper introduces the RUle Mutation Classifier (RUMC), which represents a significant improvement over the Rule Aggregation ClassifiER (RACER). RUMC uses innovative rule mutation techniques based o

Giorgos Kapetanakis, Lucas Reis

In 2022, S.D. Cohen and the two authors introduced and studied the concept of $(r, n)$-freeness on finite cyclic groups $G$ for suitable integers $r, n$, which is an arithmetic way of capturing elements of special forms that lie in the subgroups of $G$. Combining this machinery with some character sum techniques, they explored the existence of points $(x_0,

Lorenzo Loconte, Antonio Vergari

Squared tensor networks (TNs) and their generalization as parameterized computational graphs -- squared circuits -- have been recently used as expressive distribution estimators in high dimensions. However, the squaring operation introduces additional complexity when marginalizing variables or computing the partition function, which hinders their usage in ma

Jose Benitez-Aurioles, Laure Wynants, Niels Peek, Patrick Goodley

Clinical prognostic models help inform decision-making by estimating a patient's risk of experiencing an outcome in the future. The net benefit is increasingly being used to assess the clinical utility of models. By calculating an appropriately weighted average of the true and false positives of a model, the net benefit assesses the value added by a binary d

Marius Köppel, Niklas Witzig, Tim Klausmann, Mattia Cerrato

The global Biochar Industry has witnessed a surge in biochar production, with a total of 350k mt/year production in 2023. With the pressing climate goals set and the potential of Biochar Carbon Removal (BCR) as a climate-relevant technology, scaling up the number of new plants to over 1000 facilities per year by 2030 becomes imperative. However, such a massi

Yunfan Zhao, Niclas Boehmer, Aparna Taneja, Milind Tambe

AI for social impact (AI4SI) offers significant potential for addressing complex societal challenges in areas such as public health, agriculture, education, conservation, and public safety. However, existing AI4SI research is often labor-intensive and resource-demanding, limiting its accessibility and scalability; the standard approach is to design a (base-l

Jose Benitez-Aurioles, Alice Joules, Irene Brusini, Niels Peek

There are concerns about the fairness of clinical prediction models. 'Fair' models are defined as those for which their performance or predictions are not inappropriately influenced by protected attributes such as ethnicity, gender, or socio-economic status. Researchers have raised concerns that current algorithmic fairness paradigms enforce strict egalitari

Shivraj Singh Bhatti, Aryan Yadav, Mitali Monga, Neeraj Kumar

The classification of harmful brain activities, such as seizures and periodic discharges, play a vital role in neurocritical care, enabling timely diagnosis and intervention. Electroencephalography (EEG) provides a non-invasive method for monitoring brain activity, but the manual interpretation of EEG signals are time-consuming and rely heavily on expert jud

Christopher Williams, Andrew Campbell, Arnaud Doucet, Saifuddin Syed

Denoising diffusion models (DDMs) offer a flexible framework for sampling from high dimensional data distributions. DDMs generate a path of probability distributions interpolating between a reference Gaussian distribution and a data distribution by incrementally injecting noise into the data. To numerically simulate the sampling process, a discretisation sch

Hernán Castro, Iván Proaño

In this paper we consider the following Sturm-Liouville equation \[ \left\{ \begin{aligned} -(x^{2\alpha}u'(x))'+u(x)&=f(x) && \text{in } (0,1],\\ u(1)&=0 \end{aligned} \right. \] where $\alpha<1$ is a nonzero real number and $f$ belongs to $L^p(0,1)$ for $p\geq 1$. We analyze the existence and regularity of solutions under suitable weighted Dirichlet bounda

Mohamed Kaber El Alem, Zohra Guessoum, Abdelkader Tatachak

Let $(X_N)_{N\geq 1}$ denote a sequence of real random variables and let $\vartheta$ be the mode of the random variable of interest $X$. In this paper, we study the kernel mode estimator (say) $\vartheta_n$ when the data are widely orthant dependent (WOD) and subject to Random Left Truncation (RLT) mechanism. We establish the uniform consistency rate of the

Steve Butler, Kimberly Hadaway, Victoria Lenius, Preston Martens

Parking functions correspond with preferences of $n$ cars which enter sequentially to park on a one-way street where (1) each car parks in the first available spot greater than or equal to its preference and (2) all cars successfully park. When a car parks in its preferred spot then the corresponding car and corresponding spot are deemed ``lucky.'' This pape

Thalita Mendonça Antico, Larissa F. Rodrigues Moreira, Rodrigo Moreira

The diagnosis of diseases in food crops based on machine learning seemed satisfactory and suitable for use on a large scale. The Convolutional Neural Networks (CNNs) perform accurately in the disease prediction considering the image capture of the crop leaf, being extensively enhanced in the literature. These machine learning techniques fall short in data pr

W. H. Elsanhoury, Haroon A. A, E. A. Elkholy, D. C. Çınar

In this study, we considered the optical wavelength of Gaia DR3 to analyze poorly studied three newly open star clusters namely OCSN 203, OCSN 213, and OCSN 244 clusters with ASTECA code. Here, we identified candidates of 227, 200, and 551 with highly probable ($P \geq 50\%$) members. Fitting King's profile within RDPs allows us to estimate inner stellar str

Qingtian Miao, G. S. Agarwal

We examine quantum statistical properties of transmission and reflection from a chiral waveguide coupled to qubits for arbitrary input powers. We report on several remarkable features of output fields such as transparency, quantum nonreciprocity and the second-order correlation function $g^{(2)}(0)$ values less than unity. In particular, for two qubits detun

Rabia Aktaş Karaman, Iván Area

The purpose of this paper is to obtain Fourier transforms of multivariate orthogonal polynomials on the cone such as Laguerre polynomials on the cone and Jacobi polynomials on the cone and to define two new families of multivariate orthogonal functions by using Parseval's identity. Also, the obtained results are expressed in terms of the continuous Hahn poly

Zinovy Malkin, Nina Golyandina, Roman Olenev

The C01 Earth orientation parameters (EOP) series provided by the International Earth Rotation and Reference Systems Service (IERS) is the longest reliable record of the Earth's rotation. In particular, the polar motion (PM) series beginning from 1846 provides a basis for investigation of the long-term PM variations. However, the pole coordinate $Y_p$ in the

Andrew J. Wildridge, Jack P. Rodgers, Ethan M. Colbert, Yao yao

Bumblebee is a foundation model for particle physics discovery, inspired by BERT. By removing positional encodings and embedding particle 4-vectors, Bumblebee captures both generator- and reconstruction-level information while ensuring sequence-order invariance. Pre-trained on a masked task, it improves dileptonic top quark reconstruction resolution by 10-20

Hernán Castro

In this article we study the quasi-linear equation \[ \left\{ \begin{aligned} \mathrm{div}\, \mathcal A(x,u,\nabla u)&=\mathcal B(x,u,\nabla u)&&\text{in }\Omega,\\ u\in H^{1,p}_{loc}&(\Omega;wdx) \end{aligned} \right. \] where $\mathcal A$ and $\mathcal B$ are functions satisfying $\mathcal A(x,u,\nabla u)\sim \mathcal B(x,u,\nabla u)\sim w(|\nabla u|^{p-2}

I-Hong Hou

This paper addresses network optimization in dynamic systems, where factors such as user composition, service requirements, system capacity, and channel conditions can change abruptly and unpredictably. Unlike existing studies that focus primarily on optimizing long-term performance in steady states, we develop online learning algorithms that enable rapid ad

Subhroneel Chakrabarti, Renann Lipinski Jusinskas

In this work, we investigate the consistency of a perturbative definition of the S-matrix in a particular class of non-Lagrangian theories. We focus on the $p$-form theories proposed in \cite{Broccoli:2021pvv}, which are fully defined by "third-way" consistent equations of motion. Using the perturbiner method, we show that the unitarity is absent even at the

S. Estrada-Dorado, M. A. Guerrero, J. A. Toalá, R. F. Maldonado

The central star of the Helix Nebula, WD 2226$-$210 presents enigmatic hard X-ray emission and mid-IR excess. The latter has been attributed to a dusty disk or a cloud-like structure around WD 2226$-$210 formed from material of Kuiper Belt-like or comet-like objects in highly eccentric orbits. We present here a detailed analysis of multi-epoch Chandra and XM

Seongwoong Cho, Donggyun Kim, Jinwoo Lee, Seunghoon Hong

Generalizing across robot embodiments and tasks is crucial for adaptive robotic systems. Modular policy learning approaches adapt to new embodiments but are limited to specific tasks, while few-shot imitation learning (IL) approaches often focus on a single embodiment. In this paper, we introduce a few-shot behavior cloning framework to simultaneously genera

M. Jimena Rodríguez, Janice C. Lee, Remy Indebetouw, B. C. Whitmore

The earliest stages of star and cluster formation are hidden within dense cocoons of gas and dust, limiting their detection at optical wavelengths. With the unprecedented infrared capabilities of JWST, we can now observe dust-enshrouded star formation with $\sim$10 pc resolution out to $\sim$20 Mpc. Early findings from PHANGS-JWST suggest that 3.3 $\mu$m pol

Andrea Giovanni De Marchi, Alessandro Granelli, Jacopo Nava, Filippo Sala

Models of blazar jets, that explain observations of their photon spectra, typically predict too few neutrinos to be possibly seen by existing telescopes. In particular, they fall short in reproducing the first neutrino ever detected from a blazar, TXS 0506+056, by IceCube in 2017. We predict larger neutrino fluxes by using the same jet models, extended to in

Zahra Ahmadian Dehaghani

This study investigates the probability of threading in star catenanes under good solvent conditions using molecular dynamics simulations, emphasizing the influence of ring rigidity. Threading in these systems arises from the interplay between the intrinsic topology of and within the star-shaped structure and the bending rigidity of individual rings. It is d

Jonathan Fried, Santiago Paternain

In this work, we present an approach to minimizing the time necessary for the end-effector of a redundant robot manipulator to traverse a Cartesian path by optimizing the trajectory of its joints. Each joint has limits in the ranges of position, velocity and acceleration, the latter making jerks in joint space undesirable. The proposed approach takes this no

Maayane T. Soumagnac, Eran O. Ofek, Shachar S. Israeli, Guy Nir

We present X-sifter, a software package designed for near-optimal detection of sources in X-ray images and other forms of photon images in the Poisson-noise regime. The code is based on the Poisson-noise-matched filter (Ofek & Zackay), which provides an efficient method for calculating the delta log-likelihood function for source detection. The software acco

Christopher A. Mizzi, W. Adam Phelan, Matthew S. Cook, Greta L. Chappell

The quasiharmonic approximation is the most common method for modeling the specific heat of solids; however, it fails to capture the effects of intrinsic anharmonicity. In this study, we introduce the "elastic softening approximation," an alternative approach to modeling intrinsic anharmonic effects on thermodynamic quantities, which is grounded in Wallace's

Pierre A. Burger, Darshak A. Patel, Michael J. Hudson

In this work, we develop a simulation-based model to predict the excess surface mass density (ESD) depending on the local density environment. Using a conditional stellar mass function, our foreground galaxies are tailored toward the bright galaxy sample of the early data release of the Dark Energy Spectroscopic Instrument (DESI). Due to the nature of the ES

Min Li, Andrey Polyakov, Siyuan Wang, Gang Zheng

This paper addresses the finite-time non-overshooting leader-following consensus problem for multi-agent systems, whose agents are modeled by a dynamical system topologically equivalent to the integrator chain. Based on the weighted homogeneity, a nonlinear consensus control protocol is designed. A tuning scheme ensures the finite-time stability of the conse

Dario Sauro

We study the possible affine gauge transformations of the torsion tensor that make up Lie algebras. We find two such non-trivial structures, in which the gauge parameters are a $2$-form and a scalar. The first one gives rise to a non-abelian Lie algebra that is isomorphic to the Lorentz algebra, and which commutes with the latter. By linearizing this new gau

E. F. van Dishoeck, the MINDS team

Infrared observations with JWST open up a new window into the chemical composition of the gas in the inner disk (<few au) where planets are built. Results from the MIRI GTO program MINDS (PI: Th. Henning, co-PI: I. Kamp) are presented for several disks around T Tauri and lower-mass stars. A large diversity in spectra is found. Some disks are very rich in H2O

Gwenllian M. Williams, Mark A. Thompson, Mubela Mutale, Andrew J. Rigby

We present a catalogue of filamentary structures identified in the SARAO (South African Radio Astronomy Observatory) MeerKAT 1.3 GHz Galactic Plane Survey (SMGPS). We extract 933 filaments across the survey area, 803 of which (~86%) are associated with extended radio structures (e.g. supernova remnants and HII regions), whilst 130 (~14%) are largely isolated

Jessica Metzger, Sunghan Ro, Julien Tailleur

The "ratchet principle", which states that non-equilibrium systems violating parity symmetry generically exhibit steady-state currents, is one of the few generic results outside thermal equilibrium. We study exceptions to this principle observed in active and passive systems with spatially varying fluctuations sources. For dilute systems, we show that a hidd

Hyun Min Lee, Myeonghun Park, Veronica Sanz

We present a new study on the Gravity-Mediated Dark Matter (GMDM) scenario, where interactions between dark matter (DM) and the Standard Model are mediated by spin-two particles. Expanding on this established framework, we explore a novel regime characterized by a low reheating temperature that offers an alternative to the conventional thermal relic paradigm

Ufuk Aydemir, Mahmut Elbistan

Diffeomorphism invariance breaking has been investigated in the literature in several contexts, including emergent General Relativity (GR). If GR emerges from an underlying theory without diffeomorphism invariance, there may be small violations of this symmetry at low energies. Since such small violations should not cause instabilities in cosmological evolut

Steffen Gielen

Group field theory is a background-independent approach to quantum gravity whose starting point is the definition of a quantum field theory on an auxiliary group manifold (not interpreted as spacetime, but rather as the finite-dimensional configuration space of a single "atom" of geometry). Group field theory models can be seen as an extension of matrix and

Rosalba Perna, Ore Gottlieb, Estuti Shukla, David Radice

The fate of the binary neutron star (NS) merger remnants hinges sensitively upon the NS equation of state and the threshold mass, $M_{\rm ls}$, that separates a long-lived from a short-lived NS remnant. The nature of the electromagnetic counterparts is also influenced by the remnant type, particularly in determining whether a gamma-ray burst from a compact b

E. Pepe, M. Palla, F. Matteucci, E. Spitoni

A large fraction of massive stars in the Galaxy reside in binary systems and their evolution is different from that of single stars. The yields of massive stars, which are the main responsible for the production of metals, can be therefore affected by the binary nature of the systems. Recently, Farmer et al. (2023) computed new grids of yields for single and

Edoardo Ballini, Julius Mildenberger, Matteo M. Wauters, Philipp Hauke

Non-Abelian gauge theories underlie our understanding of fundamental forces of modern physics. Simulating them on quantum hardware is an outstanding challenge in the rapidly evolving field of quantum simulation. A key prerequisite is the protection of local gauge symmetries against errors that, if unchecked, would lead to unphysical results. While an extensi

Haoyuan Liu, Zhong-Zhi Xianyu

We construct and solve a complete system of differential equations for general tree-level inflation correlators with an arbitrary number of massive scalar exchanges and time-dependent couplings. Any massive tree correlators can be uniquely fixed by solving this system of equations with appropriate boundary conditions. We take a hybrid approach to solve this

Federico Bonetti, Michele Del Zotto, Ruben Minasian

We revisit 6d (2,0) SCFTs of type $D_N$ and their realization in M-theory, focusing on absolute variants of these theories and on their global finite 0- and 2-form symmetries. We derive the 7d SymTFT capturing these global symmetries from M-theory, both from the point of view of the low-energy supergravity action on $AdS_7\times \mathbb{RP}^4$ and from M2- a

Hugo Perrin, Sven Jandura, Guido Pupillo

We investigate quantum error correction protocols for neutral atoms quantum processors in the presence of atom loss. We complement the surface code with loss detection units (LDU) and analyze its performances by means of circuit-level simulations for two distinct protocols -- the standard LDU and a teleportation-based LDU --, focussing on the impact of both

Marcus Högås, Edvard Mörtsell

The Hubble constant ($H_0$) is a key parameter in cosmology, yet its precise value remains contentious due to discrepancies between early- and late-universe measurement methods, a problem known as the "Hubble tension." In this study, we revisit the Cepheid-based distance ladder calibration, focusing on two potential sources of bias in the period-luminosity r

Manuel Morales-Alvarado, Daniel Conde, Josh Bendavid, Veronica Sanz

We study the potential of symbolic regression (SR) to derive compact and precise analytic expressions that can improve the accuracy and simplicity of phenomenological analyses at the Large Hadron Collider (LHC). As a benchmark, we apply SR to equation recovery in quantum electrodynamics (QED), where established analytical results from quantum field theory pr

Minjae Cho, Colin Oscar Nancarrow, Petar Tadić, Yuan Xin

We present a new computational framework combining coarse-graining techniques with bootstrap methods to study quantum many-body systems. The method efficiently computes rigorous upper and lower bounds on both zero- and finite-temperature expectation values of any local observables of infinite quantum spin chains. This is achieved by using tensor networks to

Semih Kacmaz, Roland Haas, E. A. Huerta

We present a novel machine learning (ML) method to accelerate conservative-to-primitive inversion, focusing on hybrid piecewise polytropic and tabulated equations of state. Traditional root-finding techniques are computationally expensive, particularly for large-scale relativistic hydrodynamics simulations. To address this, we employ feedforward neural netwo

Ravi Joshi, Sarbeswar Das, Michele Fumagalli, Matteo Fossati

We study the galaxies hosting ultra-strong MgII (USMgII) absorbers at small impact parameters of $\sim$2" (5 - 20 kpc), spanning a redshift range of $0.4 \le z \le 1.7$, using deep, high-resolution images from Hyper Suprime-Cam Subaru Strategic Survey and spectra from SDSS survey. From a total of 418 USMgII absorbers with $W_{2796}\ \ge 3 \mathring{A}$, alon

Harry Stephenson, John Stott, Joseph Butler, Molly Webster

We use a sample of 11 $z\approx0.2-0.5$ ($z_{\text{med.}} = 0.36$) galaxy clusters from the Cluster Lensing And Supernovae survey with Hubble (CLASH) to analyse the angular dependence of satellite galaxy colour $(B-R)$ and passive galaxy fraction ($f_{\text{pass.}}$) with respect to the major axis of the brightest cluster galaxy (BCG). This phenomenon has be

S. Zarattini, J. M. Rodríguez Espinosa, C. Muñoz-Tuñon, J. M. Mas-Hesse

We report the discovery and characterisation of a Lya blob close to a galaxy at redshift z=3.49. We present our analysis to check whether the companion galaxy could be the source of the ionised photons responsible for the Lya emission from the blob. We use images obtained from the 10.4 m GTC telescope that are part of the SHARDS project. The blob is only vis