Tootfinder

Linear Attention with Global Context: A Multipole Attention Mechanism for Vision and Physics
Alex Colagrande, Paul Caillon, Eva Feillet, Alexandre Allauzen
https://arxiv.org/abs/2507.02748

Linear Attention with Global Context: A Multipole Attention Mechanism for Vision and Physics
Transformers have become the de facto standard for a wide range of tasks, from image classification to physics simulations. Despite their impressive performance, the quadratic complexity of standard Transformers in both memory and time with respect to the input length makes them impractical for processing high-resolution inputs. Therefore, several variants have been proposed, the most successful relying on patchification, downsampling, or coarsening techniques, often at the cost of losing the f…

The Local Structure Theorem for Graph Minors with Finite Index
Christophe Paul, Evangelos Protopapas, Dimitrios M. Thilikos, Sebastian Wiederrecht
https://arxiv.org/abs/2507.02769

The Local Structure Theorem for Graph Minors with Finite Index
The Local Structure Theorem (LST) for graph minors roughly states that every $H$-minor free graph $G$ that contains a sufficiently large wall $W$, there is a set of few vertices $A$ such that, upon removing $A$, the resulting graph $G':=G - A$ admits an "almost embedding" $δ$ into a surface $Σ$ in which $H$ does not embed. By almost embedding, we mean that there exists a hypergraph $\mathcal{H}$ whose vertex set is a subset of the vertex set of $G$ and an embedding of $\mathcal{H}$ in $Σ$ su…

Energy-Aware Workflow Execution: An Overview of Techniques for Saving Energy and Emissions in Scientific Compute Clusters
Lauritz Thamsen, Yehia Elkhatib, Paul Harvey, Syed Waqar Nabi, Jeremy Singer, Wim Vanderbauwhede
https://arxiv.org/abs/2506.04062

Energy-Aware Workflow Execution: An Overview of Techniques for Saving Energy and Emissions in Scientific Compute Clusters
Scientific research in many fields routinely requires the analysis of large datasets, and scientists often employ workflow systems to leverage clusters of computers for their data analysis. However, due to their size and scale, these workflow applications can have a considerable environmental footprint in terms of compute resource use, energy consumption, and carbon emissions. Mitigating this is critical in light of climate change and the urgent need to reduce carbon emissions. In this chapte…

On the number of divisors of Mersenne numbers
Vjekoslav Kova\v{c}, Florian Luca
https://arxiv.org/abs/2506.04883 https://arxiv.org/pd…

On the number of divisors of Mersenne numbers
Denote $f(n):=\sum_{1\le k\le n} τ(2^k-1)$, where $τ$ is the number of divisors function. Motivated by a question of Paul Erdős, we show that the sequence of ratios $f(2n)/f(n)$ is unbounded. We also present conditional results on the divergence of this sequence to infinity. Finally, we test numerically both the conjecture $f(2n)/f(n)\to\infty$ and our sufficient conditions for it to hold.

Novel Experimental Platform to realize One-dimensional Quantum Fluids
Stephanie McNamara, Prabin Parajuli, Sutirtha Paul, Garfield Warren, Adrian Del Maestro, Paul E. Sokol
https://arxiv.org/abs/2506.03200

Novel Experimental Platform to realize One-dimensional Quantum Fluids
Templated porous materials, such as MCM-41, due to the uniformity of their onedimensional structure and scalability in synthesis, have emerged as an attractive medium for studying one-dimensional quantum fluids. However, the experimental challenge of synthesizing these materials with pore radii smaller than 15 Angstroms hinders the realization of a one-dimensional quantum liquid of helium within such systems, as the coherence length of helium is shorter than the pore radius. Recently, DelMaestr…

A search for extra polarisations using a Gaussian process in Gravitational-Wave Transient Catalogue 3
Shun Yin Cheung, Lachlan Passenger, Paul D. Lasky, Eric Thrane
https://arxiv.org/abs/2507.02335

A search for extra polarisations using a Gaussian process in Gravitational-Wave Transient Catalogue 3
General relativity predicts that gravitational waves are described by two polarisation states: the plus $+$ state and cross $\times$ state. However, alternate theories of gravity allow up to six polarisations. We employ the gravitational-wave null stream, a linear combination of three or more detectors where the $+$ and $\times$ signals add to zero, leaving behind noise and potentially gravitational waves in non-standard polarisation states. We develop a Gaussian process model to search for ext…

Prospects for PBR detection of KM3-230213A-like events
Angela V. Olinto (for the JEM-EUSO collaboration), Luis A. Anchordoqui (for the JEM-EUSO collaboration), Austin Cummings (for the JEM-EUSO collaboration), Johannes Eser (for the JEM-EUSO collaboration), Diksha Garg (for the JEM-EUSO collaboration), Claire Gu\'epin (for the JEM-EUSO collaboration), Tobias Heibges (for the JEM-EUSO collaboration), John F. Krizmanic (for the JEM-EUSO collaboration), Thomas C. Paul (for the JEM-EUS…

Prospects for PBR detection of KM3-230213A-like events
POEMMA-Balloon with Radio (PBR) is a scaled-down version of the Probe Of Extreme Multi-Messenger Astrophysics (POEMMA) design, optimized to be flown as a payload on one of NASA's sub-orbital super pressure balloons circling the Earth above the southern oceans for a mission duration of more than 20 days. One of the main science objectives of PBR is to follow up astrophysical event alerts in search of neutrinos with very high energy ($10^8 \lesssim E_ν/{\rm GeV} \lesssim 10^{10}$). Of particular…

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems
Prithvish V Nembhani, Oliver Rhodes, Guangzhi Tang, Alexandra F Dobrita, Yingfu Xu, Kanishkan Vadivel, Kevin Shidqi, Paul Detterer Mario Konijnenburg, Gert-Jan van Schaik, Manolis Sifalakis, Zaid Al-Ars, Amirreza Yousefzadeh
https://…

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems
This paper introduces SENMap, a mapping and synthesis tool for scalable, energy-efficient neuromorphic computing architecture frameworks. SENECA is a flexible architectural design optimized for executing edge AI SNN/ANN inference applications efficiently. To speed up the silicon tape-out and chip design for SENECA, an accurate emulator, SENSIM, was designed. While SENSIM supports direct mapping of SNNs on neuromorphic architectures, as the SNN and ANNs grow in size, achieving optimal mapping fo…

Probability of Collision with Tethered Spacecraft
Yema Paul, Emmanuel Delande, Francois Vinet, Francois Laporte, Manuel Sanjurjo-Rivo, Aldo Tonnini, Joan-Pau Sanchez
https://arxiv.org/abs/2506.04969

Probability of Collision with Tethered Spacecraft
This Engineering Note addresses the challenge of estimating the probability of collision for tethered spacecraft during close encounters with other space objects. Standard probability of collision methods, based on spherical hard-body assumptions, tend to be overly conservative when applied to long tether systems. We introduce a method that accounts for the tether's spatial extent and configuration uncertainty by maximizing the probability of collision over all physically admissible tether shap…

A limit on the mass of the Taurid Resonant Swarm at sub-100 meter sizes
Paul Wiegert, Denis Vida, David L. Clark, Auriane Egal, Richard Wainscoat, Robert Weryk
https://arxiv.org/abs/2506.03327

A limit on the mass of the Taurid Resonant Swarm at sub-100 meter sizes
We report on a pencil-beam survey of the Taurid Swarm, a possible concentration of bodies in the Taurid meteoroid stream associated with the 7:2 mean-motion resonance with Jupiter. Canada-France-Hawaii Telescope MegaCam observations reaching apparent magnitudes of 24.5 in the gri filter were taken over three nights. Rates of motion on the sky allowed for the quick elimination of main-belt objects from the over 1000 moving sources seen. Eight candidates with on-sky rates of motion consistent wit…

A statistical theory for polymer elasticity: from molecular kinematics to continuum behavior
Lin Zhan, Siyu Wang, Rui Xiao, Shaoxing Qu, Paul Steinmann
https://arxiv.org/abs/2507.02361

A statistical theory for polymer elasticity: from molecular kinematics to continuum behavior
Predicting the macroscopic mechanical behavior of polymeric materials from the micro-structural features has remained a challenge for decades. Existing theoretical models often fail to accurately capture the experimental data, due to non-physical assumptions that link the molecule kinematics with the macroscopic deformation. In this work, we construct a novel Hamiltonian for chain segments enabling a unified statistical description of both individual macromolecular chains and continuum polymer …

Warm Vapor Rydberg EIT spectra in Doppler-free configurations
Jeremy Glick, Brielle E. Anderson, T. Nathan Nunley, Josiah Bingaman, Jian Jun Liu, David H. Meyer, Paul D. Kunz
https://arxiv.org/abs/2506.04504

The Impact of Cluster Mergers on Galaxy Properties
O\u{g}uzhan \c{C}ak{\i}r, Matt S. Owers, Lucas C. Kimmig, Paul Nulsen, Mina Pak, Gabriella Quattropani, Warrick J. Couch
https://arxiv.org/abs/2506.04799

The Impact of Cluster Mergers on Galaxy Properties
Being the most energetic events in the known universe, the impact of galaxy cluster mergers on the properties of the resident galaxies has yet to be well-understood. In this paper, we investigate the effects of merging environments on star formation in nearby clusters ($0.04

Detecting and characterising the magnetic field of exoplanets
A. Strugarek, S. V. Berdyugina, V. Bourrier, J. A. Caballero, J. J. Chebly, R. Fares, A. Fludra, L. Fossati, A. Garc\'ia Mu\~noz, L. Gkouvelis, C. Gourv\`es, J. L. Grenfell, R. D. Kavanagh, K. G. Kislyakova, L. Lamy, A. F. Lanza, C. Moutou, D. Nandy, C. Neiner, A. Oklop\v{c}i\'c, A. Paul, V. R\'eville, D. Rodgers-Lee, E. L. Shkolnik, J. D. Turner, A. A. Vidotto, F. Yang, P. Zarka

Detecting and characterising the magnetic field of exoplanets
Magnetic fields play a crucial role in planetary evolution and habitability. While the intrinsic magnetic fields of solar system planets are relatively well understood, the magnetic properties of exoplanets remain largely unconstrained, despite their potential ubiquity. Detecting exoplanetary magnetic fields is essential to advancing our understanding of planetary habitability beyond the solar system. This paper focuses on two promising spectropolarimetric techniques for detecting magnetic fiel…

Exciton-polaritons in a monolayer semiconductor coupled to van der Waals dielectric nanoantennas on a metallic mirror
Yadong Wang, Charalambos Louca, Sam Randerson, Xuerong Hu, Panaiot G. Zotev, Oscar Palma Chaundler, Paul Bouteyre, Casey K. Cheung, Roman Gorbachev, Yue Wang, Alexander I. Tartakovskii
https://arxiv.org/abs/2506.…

Exciton-polaritons in a monolayer semiconductor coupled to van der Waals dielectric nanoantennas on a metallic mirror
Polaritons in nanophotonic structures have attracted long-standing interest owing to their fundamental importance and potential for applications in nonlinear and quantum optics. Nanoantennas (NAs) made from high refractive index dielectrics offer a suitable platform for polariton physics thanks to the strongly confined optical Mie resonances and low optical losses in contrast to metallic NAs. However, Mie modes are mainly confined within the NA, making inefficient their coupling with excitons i…

Fractional order entropy-based decision-making models under risk
Poulami Paul, Chanchal Kundu
https://arxiv.org/abs/2507.02683 https://

Fractional order entropy-based decision-making models under risk
The construction of an efficient portfolio with a good level of return and minimal risk depends on selecting the optimal combination of stocks. This paper introduces a novel decision-making framework for stock selection based on fractional order entropy due to Ubriaco. By tuning the fractional parameter, the model captures varying attitudes of individuals toward risk. Values of fractional parameter near one indicate high risk tolerance (adventurous attitude), while those near zero reflect risk …

Emergent gravity and gravitational lensing in quantum materials
Yugo Onishi, Nisarga Paul, Liang Fu
https://arxiv.org/abs/2506.04335 https://

Emergent gravity and gravitational lensing in quantum materials
We show that an effective gravitational field naturally emerges in quantum materials with long-wavelength spin (or pseudospin) textures. When the itinerant electrons' spin strongly couples to the background spin texture, it effectively behaves as a spinless particle in a curved space, with the curvature arising from quantum corrections to the electron's spin orientation. The emergent gravity gives rise to the electron lensing effect, an analog of the gravitational lensing. Our work shows that n…

On the Berezin range of Toeplitz and weighted composition operators on weighted Bergman spaces
Anirban Sen, Somdatta Barik, Kallol Paul
https://arxiv.org/abs/2506.04052

On the Berezin range of Toeplitz and weighted composition operators on weighted Bergman spaces
In this article, we completely characterize the Berezin range of Toeplitz operators with harmonic symbols acting on weighted Bergman spaces, illustrating the necessity of the harmonicity condition through examples. We then introduce a new class of weighted composition operators on these spaces, investigating their fundamental properties and determining their Berezin range and Berezin number. Finally, we study the convexity of the Berezin range of composition operators on weighted Bergman spaces…

chemtrain-deploy: A parallel and scalable framework for machine learning potentials in million-atom MD simulations
Paul Fuchs, Weilong Chen, Stephan Thaler, Julija Zavadlav
https://arxiv.org/abs/2506.04055

chemtrain-deploy: A parallel and scalable framework for machine learning potentials in million-atom MD simulations
Machine learning potentials (MLPs) have advanced rapidly and show great promise to transform molecular dynamics (MD) simulations. However, most existing software tools are tied to specific MLP architectures, lack integration with standard MD packages, or are not parallelizable across GPUs. To address these challenges, we present chemtrain-deploy, a framework that enables model-agnostic deployment of MLPs in LAMMPS. chemtrain-deploy supports any JAX-defined semi-local potential, allowing users t…

Towards Better Attribute Inference Vulnerability Measures
Paul Francis, David Wagner
https://arxiv.org/abs/2507.01710 https://arxiv.o…

Towards Better Attribute Inference Vulnerability Measures
The purpose of anonymizing structured data is to protect the privacy of individuals in the data while retaining the statistical properties of the data. An important class of attack on anonymized data is attribute inference, where an attacker infers the value of an unknown attribute of a target individual given knowledge of one or more known attributes. A major limitation of recent attribute inference measures is that they do not take recall into account, only precision. It is often the case tha…

Judgment as Coordination: A Joint Systems View of Visualization Design Practice
Paul C. Parsons, Arran Ridley
https://arxiv.org/abs/2507.01209 https://

Judgment as Coordination: A Joint Systems View of Visualization Design Practice
Professional visualization design has become an increasingly important area of inquiry, yet much of the field's discourse remains anchored in researcher-centered contexts. Studies of design practice often focus on individual designers' decisions and reflections, offering limited insight into the collaborative and systemic dimensions of professional work. In this paper, we propose a systems-level reframing of design judgment grounded in the coordination and adaptation that sustain progress amid …

Reproducing kernel Hilbert space methods for modelling the discount curve
Andreas Celary, Paul Kr\"uhner, Zehra Eksi
https://arxiv.org/abs/2506.03342 …

Reproducing kernel Hilbert space methods for modelling the discount curve
We consider the theory of bond discounts, defined as the difference between the terminal payoff of the contract and its current price. Working in the setting of finite-dimensional realizations in the HJM framework, under suitable notions of no-arbitrage, the admissible discount curves take the form of polynomial, exponential functions. We introduce reproducing kernels that are admissible under no-arbitrage as a tractable regression basis for the estimation problem in calibrating the model to ma…

Towards Perception-Informed Latent HRTF Representations
You Zhang, Andrew Francl, Ruohan Gao, Paul Calamia, Zhiyao Duan, Ishwarya Ananthabhotla
https://arxiv.org/abs/2507.02815

Towards Perception-Informed Latent HRTF Representations
Personalized head-related transfer functions (HRTFs) are essential for ensuring a realistic auditory experience over headphones, because they take into account individual anatomical differences that affect listening. Most machine learning approaches to HRTF personalization rely on a learned low-dimensional latent space to generate or select custom HRTFs for a listener. However, these latent representations are typically learned in a manner that optimizes for spectral reconstruction but not for …

A computationally frugal open-source foundation model for thoracic disease detection in lung cancer screening programs
Niccol\`o McConnell, Pardeep Vasudev, Daisuke Yamada, Daryl Cheng, Mehran Azimbagirad, John McCabe, Shahab Aslani, Ahmed H. Shahin, Yukun Zhou, The SUMMIT Consortium, Andre Altmann, Yipeng Hu, Paul Taylor, Sam M. Janes, Daniel C. Alexander, Joseph Jacob

A computationally frugal open-source foundation model for thoracic disease detection in lung cancer screening programs
Low-dose computed tomography (LDCT) imaging employed in lung cancer screening (LCS) programs is increasing in uptake worldwide. LCS programs herald a generational opportunity to simultaneously detect cancer and non-cancer-related early-stage lung disease. Yet these efforts are hampered by a shortage of radiologists to interpret scans at scale. Here, we present TANGERINE, a computationally frugal, open-source vision foundation model for volumetric LDCT analysis. Designed for broad accessibility …

Replaced article(s) found for hep-th. https://arxiv.org/list/hep-th/new
[2/2]:
- Quantum correlations in a gravitational collapse simulation with SpheriCo.jl
Benjamin Berczi, Magdalena Eriksson, Thanasis Giannakopoulos, Paul M. Saffin

DGMO: Training-Free Audio Source Separation through Diffusion-Guided Mask Optimization
Geonyoung Lee, Geonhee Han, Paul Hongsuck Seo
https://arxiv.org/abs/2506.02858

DGMO: Training-Free Audio Source Separation through Diffusion-Guided Mask Optimization
Language-queried Audio Source Separation (LASS) enables open-vocabulary sound separation via natural language queries. While existing methods rely on task-specific training, we explore whether pretrained diffusion models, originally designed for audio generation, can inherently perform separation without further training. In this study, we introduce a training-free framework leveraging generative priors for zero-shot LASS. Analyzing naïve adaptations, we identify key limitations arising from m…

SMELLNET: A Large-scale Dataset for Real-world Smell Recognition
Dewei Feng, Carol Li, Wei Dai, Paul Pu Liang
https://arxiv.org/abs/2506.00239 https://

SMELLNET: A Large-scale Dataset for Real-world Smell Recognition
The ability of AI to sense and identify various substances based on their smell alone can have profound impacts on allergen detection (e.g., smelling gluten or peanuts in a cake), monitoring the manufacturing process, and sensing hormones that indicate emotional states, stress levels, and diseases. Despite these broad impacts, there are virtually no large scale benchmarks, and therefore little progress, for training and evaluating AI systems' ability to smell in the real world. In this paper, w…

Mixtures of Neural Network Experts with Application to Phytoplankton Flow Cytometry Data
Ethan Pawl, Fran\c{c}ois Ribalet, Paul A. Parker, Sangwon Hyun
https://arxiv.org/abs/2507.01375

Mixtures of Neural Network Experts with Application to Phytoplankton Flow Cytometry Data
Flow cytometry is a valuable technique that measures the optical properties of particles at a single-cell resolution. When deployed in the ocean, flow cytometry allows oceanographers to study different types of photosynthetic microbes called phytoplankton. It is of great interest to study how phytoplankton properties change in response to environmental conditions. In our work, we develop a nonlinear mixture of experts model for simultaneous clustering and regression utilizing random-weight neur…

Replaced article(s) found for cs.DS. https://arxiv.org/list/cs.DS/new
[1/1]:
- Collision-Free Robot Scheduling
Duncan Adamson, Nathan Flaherty, Igor Potapov, Paul Spirakis

Question Decomposition for Retrieval-Augmented Generation
Paul J. L. Ammann, Jonas Golde, Alan Akbik
https://arxiv.org/abs/2507.00355 https://

Question Decomposition for Retrieval-Augmented Generation
Grounding large language models (LLMs) in verifiable external sources is a well-established strategy for generating reliable answers. Retrieval-augmented generation (RAG) is one such approach, particularly effective for tasks like question answering: it retrieves passages that are semantically related to the question and then conditions the model on this evidence. However, multi-hop questions, such as "Which company among NVIDIA, Apple, and Google made the biggest profit in 2023?," challenge RA…

Navigating Phase Transitions with Path-Finding Algorithms: A Strategic Approach to Replica Exchange Monte Carlo
Akie Kowaguchi, Katsuhiro Endo, Kentaro Nomura, Shuichi Kurabayashi, Paul E. Brumby, Kenji Yasuoka
https://arxiv.org/abs/2506.02549

Navigating Phase Transitions with Path-Finding Algorithms: A Strategic Approach to Replica Exchange Monte Carlo
The replica exchange method is a powerful tool for overcoming slow relaxation in molecular simulations, but its efficiency depends strongly on the choice of the number and interval of replicas and their exchange probabilities. Here, we propose a new optimization scheme based on the Dijkstra algorithm that constructs an optimal exchange path by representing replicas and their exchange probabilities as a graph. Inspired by path-finding techniques widely used in computer science, including applica…

Late gas released in the young Kuiper belt could have significantly contributed to the carbon enrichment of the atmospheres of Neptune and Uranus
Paul Huet, Quentin Kral, Tristan Guillot
https://arxiv.org/abs/2506.03412

Late gas released in the young Kuiper belt could have significantly contributed to the carbon enrichment of the atmospheres of Neptune and Uranus
Exo-Kuiper belts have been observed for decades, but the recent detection of gas in some of them may change our view of the Solar System's youth. Late gas produced by the sublimation of CO (or CO$_2$) ices after the dissipation of the primordial gas could be the norm in young planetesimal belts. Hence, a gas-rich Kuiper belt could have been present in the Solar System. The high C/H ratios observed on Uranus and Neptune could be a clue to the existence of such late gas that could have been accre…

Dynamics of Wound Closure in Living Nematic Epithelia
Henry Andralojc, Jake Turley, Helen Weavers, Paul Martin, Isaac V. Chenchiah, Rachel R. Bennett, Tanniemola B. Liverpool
https://arxiv.org/abs/2506.04922

Dynamics of Wound Closure in Living Nematic Epithelia
We study theoretically the closure of a wound in a layer of epithelial cells in a living tissue after damage. Our analysis is informed by our recent experiments observing re-epithelialisation in vivo of Drosophila pupae. On time and length-scales such that the evolution of the epithelial tissue near the wound is well captured by that of a 2D active fluid with local nematic order, we consider the free-surface problem of a hole in a bounded region of tissue, and study the role that active stresse…

Nuclear Physics Confronts Relativistic Collisions Of Isobars
Giuliano Giacalone, Jiangyong Jia, Vittorio Som\`a, You Zhou, Anatoli Afanasjev, Massimiliano Alvioli, Benjamin Bally, Federica Capellino, Jean-Paul Ebran, Hannah Elfner, Fernando G. Gardim, Andr\'e V. Giannini, Fr\'ed\'erique Grassi, Eduardo Grossi, Jan Hammelmann, Andreas Kirchner, Dean Lee, Matthew Luzum, Hadi Mehrabpour, Emil G. Nielsen, Govert Nijs, Tamara Nik\v{s}i\'c, Jacquelyn Noronha-Hostler, Jean-Yve…

Nuclear Physics Confronts Relativistic Collisions Of Isobars
High-energy collisions involving the $A=96$ isobars $^{96}$Zr and $^{96}$Ru have been performed in 2018 at Brookhaven National Laboratory's Relativistic Heavy Ion Collider (RHIC) as a means to search for the chiral magnetic effect in QCD. This would manifest itself as specific deviations from unity in the ratio of observables taken between $^{96}$Zr+$^{96}$Zr and $^{96}$Ru+$^{96}$Ru collisions. Measurements of such ratios (released at the end of 2021) indeed reveal deviations from unity, but th…

A gradient-enhanced approach for stable finite element approximations of reaction-convection-diffusion problems
Soheil Firooz, B. Daya Reddy, Paul Steinmann
https://arxiv.org/abs/2506.01873

A gradient-enhanced approach for stable finite element approximations of reaction-convection-diffusion problems
We develop a micromorphic-based approach for finite element stabilization of reaction-convection-diffusion equations, by gradient enhancement of the field of interest via introducing an auxiliary variable. The well-posedness of the coupled-field approach is established, together with an error estimate. Through a set of 1D and 2D numerical examples the high accuracy and enhanced stability of the approach in approximating solutions associated with complex problems is demonstrated, for situations …

Binarity at LOw Metallicity (BLOeM): Pipeline-Determined Physical Properties of OB Stars
J. M. Bestenlehner, Paul A. Crowther, V. A. Bronner, S. Simon-Diaz, D. J. Lennon, J. Bodensteiner, N. Langer, P. Marchant, H. Sana, F. R. N. Schneider, T. Shenar
https://arxiv.org/abs/2506.00117

Binarity at LOw Metallicity (BLOeM): Pipeline-Determined Physical Properties of OB Stars
We aim to determine the physical properties of OB stars from the multi-epoch VLT/FLAMES BLOeM spectroscopic survey of the Small Magellanic Cloud. We apply a pipeline designed to analyse large spectroscopic samples of OB stars to the co-added, initial 9 epochs of the BLOeM survey, utilising grids of synthetic model spectra computed with the stellar atmosphere code FASTWIND. 69 OB stars are excluded from the analysis owing to disk emission or significant contamination by secondaries in SB2 binari…

Replaced article(s) found for math.KT. https://arxiv.org/list/math.KT/new
[1/1]:
- Logarithmic motivic homotopy theory
Federico Binda, Doosung Park, Paul Arne {\O}stv{\ae}r

Replaced article(s) found for cs.CR. https://arxiv.org/list/cs.CR/new
[1/1]:
- Learned-Database Systems Security
Roei Schuster, Jin Peng Zhou, Thorsten Eisenhofer, Paul Grubbs, Nicolas Papernot

Dark from light (DfL): Inferring halo properties from luminous tracers with machine learning trained on cosmological simulations. I. Method, proof of concept & preliminary testing
Asa F. L. Bluck, Joanna M. Piotrowska, Paul Goubert, Roberto Maiolino, Camilo Casimiro, Thomas Pinto Franco, Nicolas Cea
https://arxiv.org/abs/250…

Dark from light (DfL): Inferring halo properties from luminous tracers with machine learning trained on cosmological simulations. I. Method, proof of concept & preliminary testing
We present Dark from Light (DfL) - a novel method to infer the dark sector in wide-field galaxy surveys, leveraging a machine learning approach trained on contemporary cosmological simulations. The aim of this algorithm is to provide a fast, straightforward, and accurate route to estimating dark matter halo masses and group membership in wide-field spectroscopic galaxy surveys. This approach requires a highly limited number of input parameters and yields full probability distribution functions …

Semi-analytical modeling of receive transfer function and thermal noise of integrated photonic ultrasound transducers
Sabiju Valiya Valappil, Peter Harmsma, Maurits van der Heiden, Martin Verweij, Paul van Neer
https://arxiv.org/abs/2506.02817

Semi-analytical modeling of receive transfer function and thermal noise of integrated photonic ultrasound transducers
Ultrasound transducers (UTs) are extensively used in several applications across a multitude of disciplines. A new type of UTs namely integrated photonic ultrasound transducers (IPUTs) possess superior performance due to the presence of optical interrogation systems, avoiding electric crosstalk and thermal electronic noise of the sensor. However, a major component of the IPUT's noise floor is its thermal acoustic noise. Several studies have been proposed to characterize IPUTs' behavior; neverth…

2-Homogeneous bipartite distance-regular graphs and the quantum group $U^\prime_q(\mathfrak{so}_6)$
Paul Terwilliger
https://arxiv.org/abs/2506.02190 https…

2-Homogeneous bipartite distance-regular graphs and the quantum group $U^\prime_q(\mathfrak{so}_6)$
We consider a 2-homogeneous bipartite distance-regular graph $Γ$ with diameter $D \geq 3$. We assume that $Γ$ is not a hypercube nor a cycle. We fix a $Q$-polynomial ordering of the primitive idempotents of $Γ$. This $Q$-polynomial ordering is described using a nonzero parameter $q \in \mathbb C$ that is not a root of unity. We investigate $Γ$ using an $S_3$-symmetric approach. In this approach one considers $V^{\otimes 3} = V \otimes V \otimes V$ where $V$ is the standard module of $Γ$. W…

Replaced article(s) found for cs.CY. https://arxiv.org/list/cs.CY/new
[1/1]:
- Understanding and Reducing the Class-Dependent Effects of Data Augmentation with A Two-Player Gam...
Yunpeng Jiang, Yutong Ban, Paul Weng

Chirality Amplification and Deracemization in Liquid Crystals
Matthew J. Deutsch, Robin L. B. Selinger, Paul van der Schoot
https://arxiv.org/abs/2506.05053

Chirality Amplification and Deracemization in Liquid Crystals
Liquid crystal mesophases of achiral molecules are normally achiral, yet in a few materials they spontaneously deracemize and form right- and left-handed chiral domains. One mechanism that drives deracemization is molecular shape fluctuations between axial chiral conformations, where molecular interactions favor matching chirality and promote helical twist. Cooperative chiral ordering may also play a role in chirality amplification, as when a tiny fraction of chiral dopant drives a nematic phas…

Data-Driven Performance Guarantees for Parametric Optimization Problems
Jingyi Huang, Paul Goulart, Kostas Margellos
https://arxiv.org/abs/2506.23819 https…

Data-Driven Performance Guarantees for Parametric Optimization Problems
We propose a data-driven method to establish probabilistic performance guarantees for parametric optimization problems solved via iterative algorithms. Our approach addresses two key challenges: providing convergence guarantees to characterize the worst-case number of iterations required to achieve a predefined tolerance, and upper bounding a performance metric after a fixed number of iterations. These guarantees are particularly useful for online optimization problems with limited computationa…

Percolation on random 2-lifts
Paul Drouvill\'e
https://arxiv.org/abs/2506.01612 https://arxiv.org/pdf/2506.01612

Percolation on random 2-lifts
Given a graph $G$, we consider a model for a random cover of $G$ by taking two parallel copies of $G$ and crossing every pair of parallel edges randomly with probability $q$ independently of each other. The resulting graph $G_q$, is a random $2$-lift of $G$ that may not be transitive but still probabilistically exhibit many properties of transitive graphs. Studying percolation in this context can help us test the reliability and robustness of our proofs methods in percolation theory. Our three …

PromptVFX: Text-Driven Fields for Open-World 3D Gaussian Animation
Mert Kiray, Paul Uhlenbruck, Nassir Navab, Benjamin Busam
https://arxiv.org/abs/2506.01091

PromptVFX: Text-Driven Fields for Open-World 3D Gaussian Animation
Visual effects (VFX) are key to immersion in modern films, games, and AR/VR. Creating 3D effects requires specialized expertise and training in 3D animation software and can be time consuming. Generative solutions typically rely on computationally intense methods such as diffusion models which can be slow at 4D inference. We reformulate 3D animation as a field prediction task and introduce a text-driven framework that infers a time-varying 4D flow field acting on 3D Gaussians. By leveraging lar…

QuKAN: A Quantum Circuit Born Machine approach to Quantum Kolmogorov Arnold Networks
Yannick Werner, Akash Malemath, Mengxi Liu, Vitor Fortes Rey, Nikolaos Palaiodimopoulos, Paul Lukowicz, Maximilian Kiefer-Emmanouilidis
https://arxiv.org/abs/2506.22340

QuKAN: A Quantum Circuit Born Machine approach to Quantum Kolmogorov Arnold Networks
Kolmogorov Arnold Networks (KANs), built upon the Kolmogorov Arnold representation theorem (KAR), have demonstrated promising capabilities in expressing complex functions with fewer neurons. This is achieved by implementing learnable parameters on the edges instead of on the nodes, unlike traditional networks such as Multi-Layer Perceptrons (MLPs). However, KANs potential in quantum machine learning has not yet been well explored. In this work, we present an implementation of these KAN architec…

Adaptive Traffic-Following Scheme for Orderly Distributed Control of Multi-Vehicle Systems
Anahita Jain, Husni Idris, John-Paul Clarke, Daniel Delahaye
https://arxiv.org/abs/2506.00703

Adaptive Traffic-Following Scheme for Orderly Distributed Control of Multi-Vehicle Systems
We present an adaptive control scheme to enable the emergence of order within distributed, autonomous multi-agent systems. Past studies showed that under high-density conditions, order generated from traffic-following behavior reduces travel times, while under low densities, choosing direct paths is more beneficial. In this paper, we leveraged those findings to allow aircraft to independently and dynamically adjust their degree of traffic-following behavior based on the current state of the air…

Ensemble Kalman Filter for Data Assimilation coupled with low-resolution computations techniques applied in Fluid Dynamics
Paul Jeanney, Ashton Hetherington, Shady E. Ahmed, David Lanceta, Susana Saiz, Jos\'e Miguel Perez, Soledad Le CLainche
https://arxiv.org/abs/2507.00539

Ensemble Kalman Filter for Data Assimilation coupled with low-resolution computations techniques applied in Fluid Dynamics
This paper presents an innovative Reduced-Order Model (ROM) for merging experimental and simulation data using Data Assimilation (DA) to estimate the "True" state of a fluid dynamics system, leading to more accurate predictions. Our methodology introduces a novel approach implementing the Ensemble Kalman Filter (EnKF) within a reduced-dimensional framework, grounded in a robust theoretical foundation and applied to fluid dynamics. To address the substantial computational demands of DA, the prop…

Dark Matter Haloscope with a Disordered Dielectric Absorber
Stewart Koppell, Otavio D. A. R. Bittencourt, Dip Joti Paul, Junwu Huang, Masha Baryakhtar, Karl K. Berggren
https://arxiv.org/abs/2506.00115

Dark Matter Haloscope with a Disordered Dielectric Absorber
Light dark matter candidates such as axions and dark photons generically couple to electromagnetism, yielding dark-matter-to-photon conversion as a key search strategy. In addition to resonant conversion in cavities and circuits, light dark matter bosons efficiently convert to photons on material interfaces, with a broadband power proportional to the total area of these interfaces. In this work, we make use of interface conversion to develop a new experimental dark matter detector design: the d…

A Gaussian process framework for testing general relativity with gravitational waves
Lachlan Passenger, Shun Yin Cheung, Nir Guttman, Nikhil Kannachel, Paul D. Lasky, Eric Thrane
https://arxiv.org/abs/2507.01294

A Gaussian process framework for testing general relativity with gravitational waves
Gravitational-wave astronomy provides a promising avenue for the discovery of new physics beyond general relativity as it probes extreme curvature and ultra-relativistic dynamics. However, in the absence of a compelling alternative to general relativity, it is difficult to carry out an analysis that allows for a wide range of deviations. To that end, we introduce a Gaussian process framework to search for deviations from general relativity in gravitational-wave signals from binary black hole me…

Kolmogorov-Arnold Wavefunctions
Paulo F. Bedaque, Jacob Cigliano, Hersh Kumar, Srijit Paul, Suryansh Rajawat
https://arxiv.org/abs/2506.02171 https://

Kolmogorov-Arnold Wavefunctions
This work investigates Kolmogorov-Arnold network-based wavefunction ansatz as viable representations for quantum Monte Carlo simulations. Through systematic analysis of one-dimensional model systems, we evaluate their computational efficiency and representational power against established methods. Our numerical experiments suggest some efficient training methods and we explore how the computational cost scales with desired precision, particle number, and system parameters. Roughly speaking, KAN…

Long-Term Astrometric Monitoring of the Galactic Center Magnetar PSR J1745--2900
Geoffrey C. Bower, Adam T. Deller, Paul B. Demorest, Jason Dexter, Andreas Brunthaler, Gregory Desvignes, Ralph P. Eatough, Heino Falcke, Ciriaco Goddi, Michael Kramer, F. Yusef-Zadeh
https://arxiv.org/abs/2506.02348…

Long-Term Astrometric Monitoring of the Galactic Center Magnetar PSR J1745--2900
We present new astrometric observations of the Galactic Center magnetar, PSR J1745-2900, with the Very Long Baseline Array (VLBA). Combined with previously published measurements in 10 epochs that spanned 477 days, the complete data set consists of 25 epochs and 41 independent measurements that span 1984 days. These data constrain the proper motion to an accuracy of $\lesssim 2\%$ and set an upper limit on the absolute value of the magnetar's acceleration of $\lesssim (0.4, 0.2)\, {\rm mas\,y^{…

Replaced article(s) found for physics.ed-ph. https://arxiv.org/list/physics.ed-ph/new
[1/1]:
- Evaluating GPT- and Reasoning-based Large Language Models on Physics Olympiad Problems: Surpassin...
Paul Tschisgale, Holger Maus, Fabian Kieser, Ben Kroehs, Stefan Pete…

XMAD-Bench: Cross-Domain Multilingual Audio Deepfake Benchmark
Ioan-Paul Ciobanu, Andrei-Iulian Hiji, Nicolae-Catalin Ristea, Paul Irofti, Cristian Rusu, Radu Tudor Ionescu
https://arxiv.org/abs/2506.00462

XMAD-Bench: Cross-Domain Multilingual Audio Deepfake Benchmark
Recent advances in audio generation led to an increasing number of deepfakes, making the general public more vulnerable to financial scams, identity theft, and misinformation. Audio deepfake detectors promise to alleviate this issue, with many recent studies reporting accuracy rates close to 99%. However, these methods are typically tested in an in-domain setup, where the deepfake samples from the training and test sets are produced by the same generative models. To this end, we introduce XMAD-…

Entropic optimal transport beyond product reference couplings: the Gaussian case on Euclidean space
Paul Freulon, Nikitas Georgakis, Victor Panaretos
https://arxiv.org/abs/2507.01709

Entropic optimal transport beyond product reference couplings: the Gaussian case on Euclidean space
The optimal transport problem with squared Euclidean cost consists in finding a coupling between two input measures that maximizes correlation. Consequently, the optimal coupling is often singular with respect to Lebesgue measure. Regularizing the optimal transport problem with an entropy term yields an approximation called entropic optimal transport. Entropic penalties steer the induced coupling toward a reference measure with desired properties. For instance, when seeking a diffuse coupling, …

The independence and clique cover numbers of the squarefree graph
Boris Alexeev, Dustin G. Mixon, Will Sawin
https://arxiv.org/abs/2507.01928 https://

The independence and clique cover numbers of the squarefree graph
We determine the largest subset $A\subseteq \{1,\dotsc,n\}$ such that for all $a,b\in A$, the product $ab$ is not squarefree. Specifically, the maximum size is achieved by the \emph{complement} of the odd squarefree numbers. This resolves a problem of Paul Erdős and András Sárközy from 1992.

Shape Preserving Tree Transducers
Paul Gallot, Sebastian Maneth
https://arxiv.org/abs/2506.22047 https://arxiv.org/pdf/2506.22047

Shape Preserving Tree Transducers
It is shown that shape preservation is decidable for top-down tree transducers, bottom-up tree transducers, and for compositions of total deterministic macro tree transducers. Moreover, if a transducer is shape preserving, then it can be brought into a particular normal form, where every input node creates exactly one output node.

The CASE Framework -- A New Architecture for Participatory Research and Digital Health Surveillance
Marco Hirsch, Peter Hevesi, Paul Lukowicz
https://arxiv.org/abs/2505.23516

The CASE Framework -- A New Architecture for Participatory Research and Digital Health Surveillance
We present the CASE framework, an open-source platform for adaptive, context-aware participatory research, and pandemic preparedness. CASE implements an event-driven architecture that enables dynamic survey workflows, allowing real-time adaptation based on participant responses, external data, temporal conditions, and evolving user states. The framework supports a broad range of research needs, from simple one-time questionnaires to complex longitudinal studies with advanced conditional logic. …

Asteroseismology of the G8 subgiant beta Aquilae with SONG-Tenerife, SONG-Australia and TESS
Hans Kjeldsen, Timothy R. Bedding, Yaguang Li, Frank Grundahl, Mads Fredslund Andersen, Duncan J. Wright, Jack Soutter, Robert Wittenmyer, Claudia Reyes, Dennis Stello, Courtney Crawford, Yixiao Zhou, Mathieu Clerte, Pere L. Palle, Sergio Simon-Diaz, Joergen Christensen-Dalsgaard, Rasmus Handberg, Hasse Hansen, Paul Heeren, Jens Jessen-Hansen, Mikkel Lund, Mia S. Lundkvist, Karsten Brogaard, Re…

Asteroseismology of the G8 subgiant beta Aquilae with SONG-Tenerife, SONG-Australia and TESS
We present radial velocities of the G8 subgiant star beta Aql obtained in 2022 and 2023 using SONG-Tenerife and SONG-Australia. We also analysed a sector of TESS photometry that overlapped with the 2022 SONG data. We processed the time series to assign weights and to remove bad data points. The power spectrum clearly shows solar-like oscillations centred at 430 muHz. The TESS data show the oscillations at lower signal-to-noise because photometric measurements are much more affected by the granu…

Replaced article(s) found for q-fin.CP. https://arxiv.org/list/q-fin.CP/new
[1/1]:
- Hybrid Quantum Neural Networks with Amplitude Encoding: Advancing Recovery Rate Predictions
Ying Chen, Paul Griffin, Paolo Recchia, Lei Zhou, Hongrui Zhang

Early warning skill, extrapolation and tipping for accelerating cascades
Peter Ashwin, Robbin Bastiaansen, Anna S. von der Heydt, Paul Ritchie
https://arxiv.org/abs/2506.01981

Early warning skill, extrapolation and tipping for accelerating cascades
We investigate how nonlinear behaviour (both of forcing in time and of the system itself) can affect the skill of early warning signals to predict tipping in (directionally) coupled bistable systems when using measures based on critical slowing down due to the breakdown of extrapolation. We quantify the skill of early warnings with a time horizon using a receiver-operator methodology for ensembles where noise realisations and parameters are varied to explore the role of extrapolation and how it…

Replaced article(s) found for q-fin.RM. https://arxiv.org/list/q-fin.RM/new
[1/1]:
- Risk exchange under infinite-mean Pareto models
Yuyu Chen, Paul Embrechts, Ruodu Wang

Multi-goal-oriented anisotropic error control and mesh adaptivity for time-dependent convection-dominated problems
Markus Bause, Marius Paul Bruchh\"auser, Bernhard Endtmayer, Nils Margenberg, Ioannis Toulopoulos, Thomas Wick
https://arxiv.org/abs/2507.00723

Multi-goal-oriented anisotropic error control and mesh adaptivity for time-dependent convection-dominated problems
In this work, we present an anisotropic multi-goal error control based on the Dual Weighted Residual (DWR) method for time-dependent convection-diffusion-reaction (CDR) equations. This multi-goal oriented approach allows for an accurate and efficient error control with regard to several quantities of interest simultaneously. Using anisotropic interpolation and restriction operators, we obtain elementwise error indicators in space and time, where the spatial indicators are additionally separated…

On the influence of language similarity in non-target speaker verification trials
Paul M. Reuter, Michael Jessen
https://arxiv.org/abs/2506.02777 https://

On the influence of language similarity in non-target speaker verification trials
In this paper, we investigate the influence of language similarity in cross-lingual non-target speaker verification trials using a state-of-the-art speaker verification system, ECAPA-TDNN, trained on multilingual and monolingual variants of the VoxCeleb dataset. Our analysis of the score distribution patterns on multilingual Globalphone and LDC CTS reveals a clustering effect in speaker comparisons involving a training language, whereby the choice of comparison language only minimally impacts s…

Improved Accuracy in Pelvic Tumor Resections Using a Real-Time Vision-Guided Surgical System
Vahid Danesh, Paul Arauz, Maede Boroji, Andrew Zhu, Mia Cottone, Elaine Gould, Fazel A. Khan, Imin Kao
https://arxiv.org/abs/2505.23984

Improved Accuracy in Pelvic Tumor Resections Using a Real-Time Vision-Guided Surgical System
Pelvic bone tumor resections remain significantly challenging due to complex three-dimensional anatomy and limited surgical visualization. Current navigation systems and patient-specific instruments, while accurate, present limitations including high costs, radiation exposure, workflow disruption, long production time, and lack of reusability. This study evaluates a real-time vision-guided surgical system combined with modular jigs to improve accuracy in pelvic bone tumor resections. A vision-g…

Latent Representations for Control Design with Provable Stability and Safety Guarantees
Paul Lutkus, Kaiyuan Wang, Lars Lindemann, Stephen Tu
https://arxiv.org/abs/2505.23210

Latent Representations for Control Design with Provable Stability and Safety Guarantees
We initiate a formal study on the use of low-dimensional latent representations of dynamical systems for verifiable control synthesis. Our main goal is to enable the application of verification techniques -- such as Lyapunov or barrier functions -- that might otherwise be computationally prohibitive when applied directly to the full state representation. Towards this goal, we first provide dynamics-aware approximate conjugacy conditions which formalize the notion of reconstruction error necessa…

High-precision light curves of geostationary objects: The PHANTOM ECHOES 2 RPO campaign
Paul Chote, Robert Airey, James McCormac, Don Pollacco, Richard West, Krzysztof Ulaczyk, Martin J. Dyer, Alexander Agathanggelou, William Feline, Simon George, Calum Meredith, Grant Privett
https://arxiv.org/abs/2506.01549

High-precision light curves of geostationary objects: The PHANTOM ECHOES 2 RPO campaign
We present results from an extensive optical observation campaign that monitored the Geostationary satellites Intelsat 10-02, Mission Extension Vehicle 2, Thor 5, Thor 6, Thor 7, and Meteosat 11 over a 14 week period that covered the proximity operations and docking of Mission Extension Vehicle 2 with Intelsat 10-02. High-cadence single-color photometric observations are supplemented with targeted multi-color observations, high resolution imaging, and passive radio frequency positioning obtaine…

Replaced article(s) found for physics.chem-ph. https://arxiv.org/list/physics.chem-ph/new
[1/1]:
- Learning Non-Local Molecular Interactions via Equivariant Local Representations and Charge Equili...
Paul Fuchs, Micha{\l} Sanocki, Julija Zavadlav

Fractional differential entropy and its application in modeling one-dimensional flow velocity
Poulami Paul, Chancal Kundu
https://arxiv.org/abs/2507.02323 …

Fractional differential entropy and its application in modeling one-dimensional flow velocity
The fractional order generalization of Shannon entropy proposed by Ubriaco has been studied for discrete distributions. In the current paper, we conduct a detailed study of the continuous analogue of this entropy termed as fractional differential entropy and find some interesting properties which makes it stand out among the existing entropies in literature. The studied entropy measure is evaluated analytically and numerically for some well-known continuous distributions, which will be quite us…

Near-optimal estimates for the $\ell^p$-Lipschitz constants of deep random ReLU neural networks
Sjoerd Dirksen, Patrick Finke, Paul Geuchen, Dominik St\"oger, Felix Voigtlaender
https://arxiv.org/abs/2506.19695

Near-optimal estimates for the $\ell^p$-Lipschitz constants of deep random ReLU neural networks
This paper studies the $\ell^p$-Lipschitz constants of ReLU neural networks $Φ: \mathbb{R}^d \to \mathbb{R}$ with random parameters for $p \in [1,\infty]$. The distribution of the weights follows a variant of the He initialization and the biases are drawn from symmetric distributions. We derive high probability upper and lower bounds for wide networks that differ at most by a factor that is logarithmic in the network's width and linear in its depth. In the special case of shallow networks, we …

Semi-tail Units: A Universal Scale for Test Statistics and Efficiency
Paul W. Vos
https://arxiv.org/abs/2506.22910 https://arxiv.org/…

Semi-tail Units: A Universal Scale for Test Statistics and Efficiency
We introduce $ζ$- and $s$-values as quantile-based standardizations that are particularly suited for hypothesis testing. Unlike p-values, which express tail probabilities, $s$-values measure the number of semi-tail units into a distribution's tail, where each unit represents a halving of the tail area. This logarithmic scale provides intuitive interpretation: $s=3.3$ corresponds to the 10th percentile, $s=4.3$ to the 5th percentile, and $s=5.3$ to the 2.5th percentile. For two-tailed tests, $Î…

Dark Matter Haloscope with a Disordered Dielectric Absorber
Stewart Koppell, Otavio D. A. R. Bittencourt, Dip Joti Paul, Junwu Huang, Masha Baryakhtar, Karl K. Berggren
https://arxiv.org/abs/2506.00115

Dark Matter Haloscope with a Disordered Dielectric Absorber
Light dark matter candidates such as axions and dark photons generically couple to electromagnetism, yielding dark-matter-to-photon conversion as a key search strategy. In addition to resonant conversion in cavities and circuits, light dark matter bosons efficiently convert to photons on material interfaces, with a broadband power proportional to the total area of these interfaces. In this work, we make use of interface conversion to develop a new experimental dark matter detector design: the d…

traccc: GPU track reconstruction library for HEP experiments
Paul Gessinger, Heather M. Gray, Attila Krasznahorkay, Charles Leggett, Joana Niermann, Andreas Salzburger, Stephen Nicholas Swatman, Beomki Yeo
https://arxiv.org/abs/2505.22822

traccc: GPU track reconstruction library for HEP experiments
We present the current development status and progress of traccc, a GPU track reconstruction library developed in the context of the A Common Tracking Software (ACTS) project. traccc implements tracking algorithms used in high energy physics (HEP) experiments, including the Kalman filter based track finding and fitting. We benchmark the software with data simulated by Geant4 to measure the physics and computing performance. We show that the physics performance for GPU and CPU are very close. We…

Interacting Barrow holographic dark energy model in the presence of radiation and matter
Gopinath Guin, Souvik Paul, Sunandan Gangopadhyay
https://arxiv.org/abs/2507.01070

Interacting Barrow holographic dark energy model in the presence of radiation and matter
We have studied the effect of radiation in the interacting barrow holographic dark energy model for a non-flat universe. For both open and closed universes, we have obtained the evolution equation for the density parameters for dark energy, dark matter and radiation for a specific kind of interaction among the seven possible linear interactions; the analysis with the remaining six interactions will be updated soon in this manuscript. We have then numerically solved those coupled differential eq…

Enhancement of hydrogen absorption and hypervalent metal hydride formation in lanthanum using cryogenic ball milling
Sakun Duwal, Vitalie Stavila, Catalin Spataru, Mohana Shivanna, Portia Allen, Timothy Elmslie, Christopher T. Seagle, Jason Jeffries, Nenad Velisavljevic, Jesse Smith, Paul Chow, Yuming Xiao, Maddury Somayazulu, Peter A. Sharma
https:/…

Enhancement of hydrogen absorption and hypervalent metal hydride formation in lanthanum using cryogenic ball milling
Rare earth superhydrides exhibit high temperature superconductivity but are difficult to characterize and use in applications due to their high formation and stability pressures, which are typically in excess of 100 GPa. We studied how modification of the rare earth precursor improves hydrogen reactivity and hydrogen uptake for forming such metal hydrides at lower pressures. An elemental lanthanum precursor was milled at liquid nitrogen temperatures for different time intervals. After exposure …

Fast-Converging Distributed Signal Estimation in Topology-Unconstrained Wireless Acoustic Sensor Networks
Paul Didier, Toon van Waterschoot, Simon Doclo, J\"org Bitzer, Marc Moonen
https://arxiv.org/abs/2506.02797

Fast-Converging Distributed Signal Estimation in Topology-Unconstrained Wireless Acoustic Sensor Networks
This paper focuses on distributed signal estimation in topology-unconstrained wireless acoustic sensor networks (WASNs) where sensor nodes only transmit fused versions of their local sensor signals. For this task, the topology-independent (TI) distributed adaptive node-specific signal estimation (DANSE) algorithm (TI-DANSE) has previously been proposed. It converges towards the centralized signal estimation solution in non-fully connected and time-varying network topologies. However, the applic…

LLM-based Property-based Test Generation for Guardrailing Cyber-Physical Systems
Khashayar Etemadi, Marjan Sirjani, Mahshid Helali Moghadam, Per Strandberg, Paul Pettersson
https://arxiv.org/abs/2505.23549

LLM-based Property-based Test Generation for Guardrailing Cyber-Physical Systems
Cyber-physical systems (CPSs) are complex systems that integrate physical, computational, and communication subsystems. The heterogeneous nature of these systems makes their safety assurance challenging. In this paper, we propose a novel automated approach for guardrailing cyber-physical systems using property-based tests (PBTs) generated by Large Language Models (LLMs). Our approach employs an LLM to extract properties from the code and documentation of CPSs. Next, we use the LLM to generate P…

Replaced article(s) found for cond-mat.stat-mech. https://arxiv.org/list/cond-mat.stat-mech/new
[1/1]:
- Thermodynamic Circuits: Association of thermoelectric converters in stationary non-equilibrium
Paul Raux, Christophe Goupil, Gatien Verley

Avalanching together: A model for sympathetic flaring
Louis-Simon Guit\'e, Paul Charbonneau, Antoine Strugarek
https://arxiv.org/abs/2506.23889 https:/…

Avalanching together: A model for sympathetic flaring
Avalanche models running in a self-organized critical regime have proven powerful in reproducing the power-law distributions and scale invariance that characterize the statistical properties of solar flares. They are often interpreted as representing an individual active region of the Sun. As a result, this class of models has rarely been applied to describe sympathetic flares $\unicode{x2014}$ solar eruptions that occur in close spatial and temporal proximity, seemingly driven by their mutual …

Imputing With Predictive Mean Matching Can Be Severely Biased When Values Are Missing At Random
Paul T. von Hippel
https://arxiv.org/abs/2506.22981 https:/…

Imputing With Predictive Mean Matching Can Be Severely Biased When Values Are Missing At Random
Predictive mean matching (PMM) is a popular imputation strategy that imputes missing values by borrowing observed values from other cases with similar expectations. We show that, unlike other imputation strategies, PMM is not guaranteed to be consistent -- and in fact can be severely biased -- when values are missing at random (when the probability a value is missing depends only on values that are observed). We demonstrate the bias in a simple situation where a complete variable $X$ is both …

Cool Gas in the Circumgalactic Medium of Massive Post Starburst Galaxies
Zoe Harvey, Sahyadri Krishna, Vivienne Wild, Rita Tojeiro, Paul Hewett
https://arxiv.org/abs/2506.22287

Cool Gas in the Circumgalactic Medium of Massive Post Starburst Galaxies
Observing the interplay between galaxies and their gaseous surroundings is crucial for understanding how galaxies form and evolve, including the roles of long-lived cool gas reservoirs, starburst and AGN driven outflows. We use stacked Mg II absorption lines in the spectra of background quasars to study the cool gas out to 9Mpc from massive quiescent, star-forming and post-starburst galaxies with stellar masses $\log_{10}(M_{\mathrm{gal}}/M_\odot) \gtrsim 11.4$ and $0.4 \lesssim z \lesssim 0.8$…

The NEID Earth Twin Survey. III. Survey Performance After Three Years on Sky
Arvind F. Gupta, Evan Fitzmaurice, Suvrath Mahadevan, Paul Robertson, Jacob K. Luhn, Jason T. Wright, Sarah E. Logsdon, Daniel M. Krolikowski, Leonardo A. Paredes, Chad F. Bender, Mark R. Giovinazzi, Andrea S. Lin, Cullen H. Blake, Caleb I. Ca\~nas, Eric B. Ford, Samuel P. Halverson, Shubham Kanodia, Michael W. McElwain, Joe P. Ninan, Jayadev Rajagopal, Arpita Roy, Christian Schwab, Gu{\dh}mundur Stef\'ans…

The NEID Earth Twin Survey. III. Survey Performance After Three Years on Sky
The NEID Earth Twin Survey (NETS) has been delivering a rich set of precise radial velocity (RV) measurements for 41 bright, nearby main sequence stars. Here, we describe the status of the survey after three years on sky and we present the full set of RV measurements and accompanying stellar activity indicators. We discuss intermediate survey diagnostics, including calibration of the known RV zero point offset introduced following the Contreras fire in 2022 and the identification of an undiagno…

Super-resolving frequency measurement with mode-selective quantum memory
Shicheng Zhang, Aonan Zhang, Ilse Maillette de Buy Wenniger, Paul M. Burdekin, Steven Sagona-Stophel, Anindya Rastogi, Sarah E. Thomas, Ian A. Walmsley
https://arxiv.org/abs/2506.20514

Super-resolving frequency measurement with mode-selective quantum memory
High-precision optical frequency measurement is indispensable to modern science and technology, yet conventional spectroscopic techniques struggle to resolve spectral features narrower than their bandwidth. Here, we introduce a unique platform for super-resolving frequency estimation utilizing a mode-selective atomic Raman quantum memory implemented in warm cesium vapor. By precisely engineering the light-matter interaction, our memory coherently stores the optimal temporal mode with high fidel…

Inference Scaled GraphRAG: Improving Multi Hop Question Answering on Knowledge Graphs
Travis Thompson, Seung-Hwan Lim, Paul Liu, Ruoying He, Dongkuan Xu
https://arxiv.org/abs/2506.19967

Inference Scaled GraphRAG: Improving Multi Hop Question Answering on Knowledge Graphs
Large Language Models (LLMs) have achieved impressive capabilities in language understanding and generation, yet they continue to underperform on knowledge-intensive reasoning tasks due to limited access to structured context and multi-hop information. Retrieval-Augmented Generation (RAG) partially mitigates this by grounding generation in retrieved context, but conventional RAG and GraphRAG methods often fail to capture relational structure across nodes in knowledge graphs. We introduce Infere…

Beyond von Mises Truss Models: Emergent Bistability in Mechanical Metamaterials
Md Nahid Hasan, Taylor E. Greenwood, Sharat Paul, Bolei Deng, Qihan Liu, Yong Lin Kong, Pai Wang
https://arxiv.org/abs/2507.00996

Beyond von Mises Truss Models: Emergent Bistability in Mechanical Metamaterials
We observe and analyze the phenomenon of bistability emergent from cooperative stiffening in hyper-elastic metamaterials. Using experimental and numerical results of identical geometric designs, we show evidence that a single unit is unistable while combining two units can result in bistability. Our study demonstrates that the von Mises truss model cannot describe such emergent behavior. Hence, we construct a novel and simple analytical model to explain this phenomenon.

Canary in the Mine: An LLM Augmented Survey of Disciplinary Complaints to the Ordre des ing\'enieurs du Qu\'ebec (OIQ)
Tammy Mackenzie, Varsha Kesavan, Thomas Mekhael, Animesh Paul, Branislav Radeljic, Sara Kodeiri, Sreyoshi Bhaduri
https://arxiv.org/abs/2506.19775

Canary in the Mine: An LLM Augmented Survey of Disciplinary Complaints to the Ordre des ingénieurs du Québec (OIQ)
This study uses pre-trained LLMs to conduct thematic analysis to investigate disciplinary incidents involving engineers in Quebec, shedding light on critical gaps in engineering education. Through a comprehensive review of the disciplinary register of the Ordre des ingénieurs du Québec (OIQ)'s disciplinary register for 2010 to 2024, researchers from engineering education and human resources management in technological development laboratories conducted a thematic analysis of reported incident…

Replaced article(s) found for math.NT. https://arxiv.org/list/math.NT/new
[1/1]:
- Quantum variance on quaternion algebras, III
Paul D. Nelson

Controlled Spherulitic Crystal Growth from Salt Mixtures: A Universal Mechanism for Complex Crystal Self-Assembly
Tess Heeremans, Simon L\'epinay, Romane Le Diz\`es Castell, Isa Yusuf, Paul Kolpakov, Daniel Bonn, Michael Steiger, Noushine Shahidzadeh
https://arxiv.org/abs/2506.01163 …

Controlled Spherulitic Crystal Growth from Salt Mixtures: A Universal Mechanism for Complex Crystal Self-Assembly
Spherulites are complex polycrystalline structures that form through the self-assembly of small aggregated nanocrystals starting from a central point and growing radially outward. Despite their wide prevalence and relevance to fields ranging from geology to medicine, the dynamics of spherulitic crystallization and the conditions required for such growth remain ill-understood. Here, we report on the conditions to induce controlled spherulitic growth of sodium sulfate from evaporating aqueous sol…

On inertial forces (indirect terms) in problems with a central body
Aur\'elien Crida, Cl\'ement Baruteau, Philippine Griveaud, Elena Lega, Fr\'ed\'eric Masset, William B\'ethune, David Fang, Jean-Fran\c{c}ois Gonzalez, H\'elo\"ise M\'eheut, Alessandro Morbidelli, Fabiola Gerosa, Dylan Kloster, L\'ea Marques, Alain Miniussi, Kate Minker, Gabriele Pichierri, Paul Segretain

On inertial forces (indirect terms) in problems with a central body
Gravitational systems in astrophysics often comprise a body -- the primary -- that far outweights the others, and which is taken as the centre of the reference frame. A fictitious acceleration, also known as the indirect term, must therefore be added to all other bodies in the system to compensate for the absence of motion of the primary. In this paper, we first stress that there is not one indirect term but as many indirect terms as there are bodies in the system that exert a gravitational pul…

Stop Lying to Me: New Visual Tools to Choose the Most Honest Nonlinear Dimension Reduction
Jayani P. Gamage, Dianne Cook, Paul Harrison, Michael Lydeamore
https://arxiv.org/abs/2506.22051

Stop Lying to Me: New Visual Tools to Choose the Most Honest Nonlinear Dimension Reduction
Nonlinear dimension reduction (NLDR) techniques such as tSNE, and UMAP provide a low-dimensional representation of high-dimensional data (\pD{}) by applying a nonlinear transformation. NLDR often exaggerates random patterns. But NLDR views have an important role in data analysis because, if done well, they provide a concise visual (and conceptual) summary of \pD{} distributions. The NLDR methods and hyper-parameter choices can create wildly different representations, making it difficult to deci…

Trustworthy Artificial Intelligence for Cyber Threat Analysis
Shuangbao Paul Wang, Paul Mullin
https://arxiv.org/abs/2506.19052 https://

Trustworthy Artificial Intelligence for Cyber Threat Analysis
Artificial Intelligence brings innovations into the society. However, bias and unethical exist in many algorithms that make the applications less trustworthy. Threats hunting algorithms based on machine learning have shown great advantage over classical methods. Reinforcement learning models are getting more accurate for identifying not only signature-based but also behavior-based threats. Quantum mechanics brings a new dimension in improving classification speed with exponential advantage. In …

Investigating Stochastic Methods for Prosody Modeling in Speech Synthesis
Paul Mayer, Florian Lux, Alejandro P\'erez-Gonz\'alez-de-Martos, Angelina Elizarova, Lindsey Vanderlyn, Dirk V\"ath, Ngoc Thang Vu
https://arxiv.org/abs/2507.00227

Investigating Stochastic Methods for Prosody Modeling in Speech Synthesis
While generative methods have progressed rapidly in recent years, generating expressive prosody for an utterance remains a challenging task in text-to-speech synthesis. This is particularly true for systems that model prosody explicitly through parameters such as pitch, energy, and duration, which is commonly done for the sake of interpretability and controllability. In this work, we investigate the effectiveness of stochastic methods for this task, including Normalizing Flows, Conditional Flow…

Quantifying Spin Defect Density in hBN via Raman and Photoluminescence Analysis
Atanu Patra, Paul Konrad, Andreas Sperlich, Timur Biktagirov, Wolf Gero Schmidt, Lesley Spencer, Igor Aharonovich, Sven H\"ofling, Vladimir Dyakonov
https://arxiv.org/abs/2506.19803

Quantifying Spin Defect Density in hBN via Raman and Photoluminescence Analysis
Negatively charged boron vacancies ($\mathrm{V_B^-}$) in hexagonal boron nitride (hBN) are emerging as promising solid-state spin qubits due to their optical accessibility, structural simplicity, and compatibility with photonic platforms. However, quantifying the density of such defects in thin hBN flakes has remained elusive, limiting progress in device integration and reproducibility. Here, we present an all-optical method to quantify $\mathrm{V_B^-}$ defect density in hBN by correlating Rama…

MEM1: Learning to Synergize Memory and Reasoning for Efficient Long-Horizon Agents
Zijian Zhou, Ao Qu, Zhaoxuan Wu, Sunghwan Kim, Alok Prakash, Daniela Rus, Jinhua Zhao, Bryan Kian Hsiang Low, Paul Pu Liang
https://arxiv.org/abs/2506.15841

MEM1: Learning to Synergize Memory and Reasoning for Efficient Long-Horizon Agents
Modern language agents must operate over long-horizon, multi-turn interactions, where they retrieve external information, adapt to observations, and answer interdependent queries. Yet, most LLM systems rely on full-context prompting, appending all past turns regardless of their relevance. This leads to unbounded memory growth, increased computational costs, and degraded reasoning performance on out-of-distribution input lengths. We introduce MEM1, an end-to-end reinforcement learning framework …

General measures of effect size to calculate power and sample size for Wald tests with generalized linear models
Amy L Cochran, Shijie Yuan, Paul J Rathouz
https://arxiv.org/abs/2506.22324

General measures of effect size to calculate power and sample size for Wald tests with generalized linear models
Power and sample size calculations for Wald tests in generalized linear models (GLMs) are often limited to specific cases like logistic regression. More general methods typically require detailed study parameters that are difficult to obtain during planning. We introduce two new effect size measures for estimating power, sample size, or the minimally detectable effect size in studies using Wald tests across any GLM. These measures accommodate any number of predictors or adjusters and require on…

Measuring Modern Phishing Tactics: A Quantitative Study of Body Obfuscation Prevalence, Co-occurrence, and Filter Impact
Antony Dalmiere (LAAS), Zheng Zhou (LAAS), Guillaume Auriol (LAAS-TRUST, INSA Toulouse), Vincent Nicomette (LAAS-TSF, LAAS-TRUST), Pascal Marchand (LERASS, IUT Paul Sabatier)
https://arxiv.org/abs/2506.20228…

Measuring Modern Phishing Tactics: A Quantitative Study of Body Obfuscation Prevalence, Co-occurrence, and Filter Impact
Phishing attacks frequently use email body obfuscation to bypass detection filters, but quantitative insights into how techniques are combined and their impact on filter scores remain limited. This paper addresses this gap by empirically investigating the prevalence, co-occurrence patterns, and spam score associations of body obfuscation techniques. Analysing 386 verified phishing emails, we quantified ten techniques, identified significant pairwise co-occurrences revealing strategic layering l…

The stellar population in the SARAO MeerKAT Galactic Plane Survey
Okwudili D. Egbo, David A. H. Buckley, Paul J. Groot, Francesco Cavallaro, Patrick A. Woudt, Mark A. Thompson, Mubela Mutale, Michael Bietenholz
https://arxiv.org/abs/2505.22139

The stellar population in the SARAO MeerKAT Galactic Plane Survey
We report on optically selected stellar candidates of SARAO MeerKAT 1.3 GHz radio continuum survey sources of the Galactic plane. Stellar counterparts to radio sources are selected by cross-matching the MeerKAT source positions with \textit{Gaia} DR3, using two approaches. The first approach evaluated the probability of chance alignments between the radio survey and \textit{Gaia} sources and used AllWISE infrared colour-colour information to select potential stellar candidates. The second appro…

Design high-confidence computers using trusted instructional set architecture and emulators
Shuangbao Paul Wang
https://arxiv.org/abs/2506.18780 https://…

Design high-confidence computers using trusted instructional set architecture and emulators
High-confidence computing relies on trusted instructional set architecture, sealed kernels, and secure operating systems. Cloud computing depends on trusted systems for virtualization tasks. Branch predictions and pipelines are essential in improving performance of a CPU/GPU. But Spectre and Meltdown make modern processors vulnerable to be exploited. Disabling the prediction and pipeline is definitely not a good solution. On the other hand, current software patches can only address non-essentia…

Leveraging Relational Evidence: Population Size Estimation on Tree-Structured Data with the Weighted Multiplier Method
Mallory J Flynn, Paul Gustafson
https://arxiv.org/abs/2506.21020

Leveraging Relational Evidence: Population Size Estimation on Tree-Structured Data with the Weighted Multiplier Method
Populations of interest are often hidden from data for a variety of reasons, though their magnitude remains important in determining resource allocation and appropriate policy. One popular approach to population size estimation, the multiplier method, is a back-calculation tool requiring only a marginal subpopulation size and an estimate of the proportion belonging to this subgroup. Another approach is to use Bayesian methods, which are inherently well-suited to incorporating multiple data sour…