Tootfinder

This https://arxiv.org/abs/2504.20369 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

Perception-aware Sampling for Scatterplot Visualizations
Visualizing data is often a crucial first step in data analytics workflows, but growing data sizes pose challenges due to computational and visual perception limitations. As a result, data analysts commonly down-sample their data and work with subsets. Deriving representative samples, however, remains a challenge. This paper focuses on scatterplots, a widely-used visualization type, and introduces a novel sampling objective -- perception-awareness -- aiming to improve sample efficacy by targeti…

Optimal protocol for collisional Brownian engines
Gustavo A. L. For\~ao
https://arxiv.org/abs/2506.05078 https://arxiv.org/pdf/2506.0…

Optimal protocol for collisional Brownian engines
Collisional Brownian engines have recently gained attention as alternatives to conventional nanoscale engines. However, a comprehensive optimization of their performance, which could serve as a benchmark for future engine designs, is still lacking. In this work, we address this gap by deriving and analyzing the optimal driving protocol for a collisional Brownian engine. By maximizing the average output work, we show that the optimal protocol consists of linear force segments separated by impuls…

This https://arxiv.org/abs/2505.20514 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hept…

Spontaneous quantization of the Yang-Mills gradient flow
We apply loop calculus in momentum loop space to the Yang-Mills gradient flow, deriving momentum loop equations for the Wilson loop. These equations possess fixed points corresponding to superpositions of Wilson loops associated with classical Yang-Mills solutions. We identify two distinct classes of solutions: one converging toward a trivial free-field configuration (vanishing field strength) and another converging toward configurations characterized by self-dual field strengths. Both solution…

Coherent electrically-charged quantum black holes
Tommaso Antonelli, Marco Sebastianutti, Andrea Giusti
https://arxiv.org/abs/2506.02231 https://

Coherent electrically-charged quantum black holes
We improve upon the results presented in [R. Casadio, et al., Phys. Rev. D 105 (2022) 124026] deriving a quantum-corrected Reissner-Nordström geometry containing an integrable singularity at its center while being devoid of spurious oscillations around the classical configuration. We further investigate some relevant physical observables, related to geodesics and quasinormal modes of scalar perturbations, associated with this geometry to complement our theoretical analysis.

Reappraising the Elatina series: Solar dynamo clocking and inference of orbital periods
F. Stefani, T. Weier, G. M. Horstmann, G. Mamatsashvili
https://arxiv.org/abs/2506.02628

Reappraising the Elatina series: Solar dynamo clocking and inference of orbital periods
We reconsider the 680 million year old Elatina series of sedimentary laminae from South Australia that show a remarkably stable periodicity with a main period of around 12 years, which is close to the Schwabe cycle, and a second period of 314 years that has been coined Elatina cycle. By analyzing the residuals of the series' minima from a linear trend, and deriving Dicke's ratio, we first show that the series exhibits a high degree of phase stability, except one single break point which may ind…

This https://arxiv.org/abs/2505.22205 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

The Gaia spectroscopic catalogue of exoplanets and host stars
Complete, accurate, and precise catalogues of exoplanet host star (EHS) properties are essential to deriving high-quality exoplanet parameters. This paper aims at homogeneously parameterising EHS and their exoplanets, using Gaia and GSP-spec data. For 2573 EHS, we computed their L*, R*, and M*, with no prior assumption from stellar evolution models. Their Galactic positions, kinematic and orbital properties were derived. We re-scaled Mp and Rp of 3556 exoplanets, fully consistently with the ste…

This https://arxiv.org/abs/2505.23638 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Visualizing Three-Qubit Entanglement
We present a graphical framework to represent entanglement in three-qubit states. The geometry associated with each entanglement class and type is analyzed, revealing distinct structural features. We explore the connection between this geometric perspective and the tangle, deriving bounds that depend on the entanglement class. Based on these insights, we conjecture a purely geometric expression for both the tangle and Cayley's hyperdeterminant for non-generic states. As an application, we analy…

This https://arxiv.org/abs/2504.13703 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

Consensus-aware Contrastive Learning for Group Recommendation
Group recommendation aims to provide personalized item suggestions to a group of users by reflecting their collective preferences. A fundamental challenge in this task is deriving a consensus that adequately represents the diverse interests of individual group members. Despite advancements made by deep learning-based models, existing approaches still struggle in two main areas: (1) Capturing consensus in small-group settings, which are more prevalent in real-world applications, and (2) Balancin…

Practical Short-Length Coding Schemes for Binary Distributed Hypothesis Testing
Ismaila Salihou Adamou, Elsa Dupraz, Reza Asvadi, Tad Matsumoto
https://arxiv.org/abs/2506.01747

Practical Short-Length Coding Schemes for Binary Distributed Hypothesis Testing
This paper addresses the design of practical shortlength coding schemes for Distributed Hypothesis Testing (DHT). While most prior work on DHT has focused on informationtheoretic analyses, deriving bounds on Type-II error exponents via achievability schemes based on quantization and quantizebinning, the practical implementation of DHT coding schemes has remained largely unexplored. Moreover, existing practical coding solutions for quantization and quantize-binning approaches were developed for …

Using Machine Learning to Compute Constrained Optimal Carbon Tax Rules
Felix K\"ubler, Simon Scheidegger, Oliver Surbek
https://arxiv.org/abs/2507.01704

Using Machine Learning to Compute Constrained Optimal Carbon Tax Rules
We develop a computational framework for deriving Pareto-improving and constrained optimal carbon tax rules in a stochastic overlapping generations (OLG) model with climate change. By integrating Deep Equilibrium Networks for fast policy evaluation and Gaussian process surrogate modeling with Bayesian active learning, the framework systematically locates optimal carbon tax schedules for heterogeneous agents exposed to climate risk. We apply our method to a 12-period OLG model in which exogenous…

Performance of the image persistence model for Euclid infrared detectors
B. Kubik, R. Barbier, G. Smadja, S. Ferriol, Y. Conseil, Y. Copin, W. Gillard, S. Dusini, K. Jahnke, E. Prieto, N. Auricchio, E. Balbi, A. Balestra, P. Battaglia, V. Capobianco, R. Chary, L. Corcione, F. Cogato, G. Delucchi, E. Franceschi, L. Gabarra, F. Gianotti, F. Grupp, E. Lentini, S. Ligori, E. Medinaceli, G. Morgante, K. Paterson, E. Romelli, L. Sauniere, M. Schirmer, C. Sirignano G. Testera, M. Trifoglio, A. Troja, L. Valenziano, M. Frailis, M. Scodeggio, J. -C. Barriere, M. Berthe, C. Bodendorf, A. Caillat, M. Carle, R. Casas, H. Cho, A. Costille, F. Ducret, B. Garilli, W. Holmes, F. Hormuth, A. Hornstrup, M. Jhabvala, R. Kohley, D. Le Mignant, P. B. Lilje, I. Lloro, C. Padilla, G. Polenta, J. -C. Salvignol, G. Seidel, B. Serra, A. Secroun, L. Stanco, R. Toledo-Moreo, S. Anselmi, E. Borsato, L. Caillat, C. Colodro-Conde, V. Conforti, J. E. Davies, A. Renzi, F. Dal Corso, S. Davini, A. Derosa, J. J. Diaz, S. Di Domizio, D. Di Ferdinando, R. Farinelli, A. G. Ferrari, F. Fornari, F. Giacomini, O. Krause, F. Laudisio, J. Macias-Perez, J. Marpaud, N. Mauri, R. da Silva, M. Niclas, F. Passalacqua, I. Risso, P. Lagier, A. N. Sorensen, P. Stassi, J. Steinwagner, M. Tenti, C. Thizy, S. Tosi, R. Travaglini, O. Tubio, C. Valieri, S. Ventura, C. Vescovi, J. Zoubian
#toXiv_bot_toot

Tolerants
Swechchha Adhikari, Brent Hall, Stephen McKean
https://arxiv.org/abs/2506.22897 https://arxiv.org/pdf/2506.22897

Tolerants
We study a generalization of the discriminant of a polynomial, which we call the tolerant. The tolerant differs by a square from the duplicant, which was discovered in recent work on $\mathbb{P}^1$-loop spaces in motivic homotopy theory. We show that the tolerant is rational by deriving a formula in terms of discriminants. We also show that the tolerant satisfies many of the same properties as the discriminant. A notable difference between the two is that the discriminant is inversion invariant…

A Compartmental Model for Epidemiology with Human Behavior and Stochastic Effects
Christian Parkinson, Weinan Wang
https://arxiv.org/abs/2507.01046 https:/…

A Compartmental Model for Epidemiology with Human Behavior and Stochastic Effects
We propose a compartmental model for epidemiology wherein the population is split into groups with either comply or refuse to comply with protocols designed to slow the spread of a disease. Parallel to the disease spread, we assume that noncompliance with protocols spreads as a social contagion. We begin by deriving the reproductive ratio for a deterministic version of the model, and use this to fully characterize the local stability of disease free equilibrium points. We then append the determ…

Classification with Reject Option: Distribution-free Error Guarantees via Conformal Prediction
Johan Hallberg Szabadv\'ary, Tuwe L\"ofstr\"om, Ulf Johansson, Cecilia S\"onstr\"od, Ernst Ahlberg, Lars Carlsson
https://arxiv.org/abs/2506.21802

Classification with Reject Option: Distribution-free Error Guarantees via Conformal Prediction
Machine learning (ML) models always make a prediction, even when they are likely to be wrong. This causes problems in practical applications, as we do not know if we should trust a prediction. ML with reject option addresses this issue by abstaining from making a prediction if it is likely to be incorrect. In this work, we formalise the approach to ML with reject option in binary classification, deriving theoretical guarantees on the resulting error rate. This is achieved through conformal pred…

Sampling of Graph Signals Based on Joint Time-Vertex Fractional Fourier Transform
Yu Zhang, Bing-Zhao Li
https://arxiv.org/abs/2506.00023 https://

Sampling of Graph Signals Based on Joint Time-Vertex Fractional Fourier Transform
With the growing demand for non-Euclidean data analysis, graph signal processing (GSP) has gained significant attention for its capability to handle complex time-varying data. This paper introduces a novel sampling method based on the joint time-vertex fractional Fourier transform (JFRFT), enhancing signal representation in time-frequency analysis and GSP. The JFRFT sampling theory is established by deriving conditions for the perfect recovery of jointly bandlimited signals, along with an optim…

This https://arxiv.org/abs/2411.09088 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Precision bounds for multiple currents in open quantum systems
Thermodynamic (TUR) and kinetic (KUR) uncertainty relations are fundamental bounds constraining the fluctuations of current observables in classical, non-equilibrium systems. Several works have verified, however, violations of these classical bounds in open quantum systems, motivating the derivation of new quantum TURs and KURs that account for the role of quantum coherence. Here, we go one step further by deriving multidimensional KUR and TUR for multiple observables in open quantum systems un…

Soft theorems of tree-level ${\rm Tr}(\phi^3)$, YM and NLSM amplitudes from $2$-splits
Kang Zhou
https://arxiv.org/abs/2506.00747 https://

Soft theorems of tree-level ${\rm Tr}(ϕ^3)$, YM and NLSM amplitudes from $2$-splits
In this paper, we extend the method proposed in \cite{Arkani-Hamed:2024fyd} for deriving soft theorems of amplitudes, which relies exclusively on factorization properties including conventional factorizations on physical poles, as well as newly discovered $2$-splits on special loci in kinematic space. Using the extended approach, we fully reproduce the leading and sub-leading single-soft theorems for tree-level ${\rm Tr}(ϕ^3)$ and Yang-Mills (YM) amplitudes, along with the leading and sub-lead…

Gigantic Harmonic Generation in N\'eel-Torque Antiferromagnetic Resonance
Kuangyin Deng, Ran Cheng
https://arxiv.org/abs/2506.22974 https://

Gigantic Harmonic Generation in Néel-Torque Antiferromagnetic Resonance
We theoretically investigate the resonant and higher-harmonic magnetic responses of a collinear antiferromagnet induced by Néel spin-orbit torques (NSOTs). By deriving the dynamical susceptibilities up to the third harmonic, we find remarkable NSOT-induced amplifications of the linear and nonlinear magnetic dynamics by orders of magnitude compared to conventional spin-orbit torques, enabling highly-efficient frequency conversion in the sub-terahertz frequency range. We then propose a multilaye…

Confidence intervals for forced alignment boundaries using model ensembles
Matthew C. Kelley
https://arxiv.org/abs/2506.01256 https://

Confidence intervals for forced alignment boundaries using model ensembles
Forced alignment is a common tool to align audio with orthographic and phonetic transcriptions. Most forced alignment tools provide only a single estimate of a boundary. The present project introduces a method of deriving confidence intervals for these boundaries using a neural network ensemble technique. Ten different segment classifier neural networks were previously trained, and the alignment process is repeated with each model. The alignment ensemble is then used to place the boundary at th…

Kapitza's Pendulum as a Classical Prelude to Floquet-Magnus Theory
Johannes K. Krondorfer, Maria Kainz, Matthias Diez, Andreas W. Hauser
https://arxiv.org/abs/2507.02736

Kapitza's Pendulum as a Classical Prelude to Floquet-Magnus Theory
We present a pedagogical introduction to Floquet-Magnus theory through the classical example of Kapitza's pendulum \ -- a simple system exhibiting nontrivial dynamical stabilization under rapid periodic driving. By deriving the equations of motion and analyzing the system via Floquet theory and the Magnus expansion, we obtain analytical stability conditions and effective evolution equations. While grounded in classical mechanics, the techniques are directly applicable to periodically driven qua…

This https://arxiv.org/abs/2412.13727 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Open Superclusters II. Discovery of an Inactive Supercluster Including a New Star Cluster in the Solar Neighborhood
The number of known star clusters, associations, and moving groups in the vicinity of the Sun has increased significantly due to the use of Gaia data. We investigated the existence and properties of open superclusters (OSC) within 500 pc of the Sun, with a particular focus on a newly identified OSC, designated HC8. Using advanced Gaia-derived astrometric data and star cluster catalogs, we identify and analyze member stars of various clusters, deriving key parameters such as ages, distances, ext…

Direct approach to approximate conservation laws
M. Gorgone, G. Inferrera
https://arxiv.org/abs/2505.23390 https://arxiv.org/pdf/2505…

Direct approach to approximate conservation laws
In this paper, non-variational systems of differential equations containing small terms are considered, and a consistent approach for deriving approximate conservation laws through the introduction of approximate Lagrange multipliers is developed. The proposed formulation of the approximate direct method starts by assuming the Lagrange multipliers to be dependent on the small parameter; then, by expanding the dependent variables in power series of the small parameter, we consider the consistent…

This https://arxiv.org/abs/2501.05683 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Dark Energy Survey Year 6 Results: Synthetic-source Injection Across the Full Survey Using Balrog
Synthetic source injection (SSI), the insertion of sources into pixel-level on-sky images, is a powerful method for characterizing object detection and measurement in wide-field, astronomical imaging surveys. Within the Dark Energy Survey (DES), SSI plays a critical role in characterizing all necessary algorithms used in converting images to catalogs, and in deriving quantities needed for the cosmology analysis, such as object detection rates, galaxy redshift estimation, galaxy magnification, s…

Topological Adaptive Least Mean Squares Algorithms over Simplicial Complexes
Lorenzo Marinucci, Claudio Battiloro, Paolo Di Lorenzo
https://arxiv.org/abs/2505.23160

Topological Adaptive Least Mean Squares Algorithms over Simplicial Complexes
This paper introduces a novel adaptive framework for processing dynamic flow signals over simplicial complexes, extending classical least-mean-squares (LMS) methods to high-order topological domains. Building on discrete Hodge theory, we present a topological LMS algorithm that efficiently processes streaming signals observed over time-varying edge subsets. We provide a detailed stochastic analysis of the algorithm, deriving its stability conditions, steady-state mean-square-error, and converge…

Fusing Radiomic Features with Deep Representations for Gestational Age Estimation in Fetal Ultrasound Images
Fangyijie Wang, Yuan Liang, Sourav Bhattacharjee, Abey Campbell, Kathleen M. Curran, Gu\'enol\'e Silvestre
https://arxiv.org/abs/2506.20407

Fusing Radiomic Features with Deep Representations for Gestational Age Estimation in Fetal Ultrasound Images
Accurate gestational age (GA) estimation, ideally through fetal ultrasound measurement, is a crucial aspect of providing excellent antenatal care. However, deriving GA from manual fetal biometric measurements depends on the operator and is time-consuming. Hence, automatic computer-assisted methods are demanded in clinical practice. In this paper, we present a novel feature fusion framework to estimate GA using fetal ultrasound images without any measurement information. We adopt a deep learning…

Leveraging machine learning features for linear optical interferometer control
Sergei S. Kuzmin, Ivan V. Dyakonov, Stanislav S. Straupe
https://arxiv.org/abs/2505.24032

Leveraging machine learning features for linear optical interferometer control
We have developed an algorithm that constructs a model of a reconfigurable optical interferometer, independent of specific architectural constraints. The programming of unitary transformations on the interferometer's optical modes relies on either an analytical method for deriving the unitary matrix from a set of phase shifts or an optimization routine when such decomposition is not available. Our algorithm employs a supervised learning approach, aligning the interferometer model with a trainin…

Advanced Applications of Generative AI in Actuarial Science: Case Studies Beyond ChatGPT
Simon Hatzesberger, Iris Nonneman
https://arxiv.org/abs/2506.18942

Advanced Applications of Generative AI in Actuarial Science: Case Studies Beyond ChatGPT
This article demonstrates the transformative impact of Generative AI (GenAI) on actuarial science, illustrated by four implemented case studies. It begins with a historical overview of AI, tracing its evolution from early neural networks to modern GenAI technologies. The first case study shows how Large Language Models (LLMs) improve claims cost prediction by deriving significant features from unstructured textual data, significantly reducing prediction errors in the underlying machine learning…

IBIS: Inverse BInomial sum Solver
Paul A. J. W. van Hoegaerden, Coenraad B. Marinissen, Wouter J. Waalewijn
https://arxiv.org/abs/2506.19904 https://

IBIS: Inverse BInomial sum Solver
In higher-loop calculations, Mellin-Barnes representations are used to simplify the denominators encountered in Feynman parameter integrals. The contour integral of these representations yield sums over residues. We extend the classes of such sums that can be calculated, to include those involving inverse binomials. Our results are expressed in terms of so-called $S$-sums, where the dependence on the upper limit of the sum is analytic. This is accomplished by deriving several new recursion rela…

A uniform cut-elimination theorem for linear logics with fixed points and super exponentials
Esa\"ie Bauer, Alexis Saurin
https://arxiv.org/abs/2506.14327

A uniform cut-elimination theorem for linear logics with fixed points and super exponentials
In the realm of light logics deriving from linear logic, a number of variants of exponential rules have been investigated. The profusion of such proof systems induces the need for cut-elimination theorems for each logic, the proof of which may be redundant. A number of approaches in proof theory have been adopted to cope with this need. In the present paper, we consider this issue from the point of view of enhancing linear logic with least and greatest fixed-points and considering such a variet…

The Zeta Tail Distribution: A Novel Event-Count Model
Michael R. Powers
https://arxiv.org/abs/2506.17496 https://arxiv.org/pdf/2506.1…

The Zeta Tail Distribution: A Novel Event-Count Model
We introduce the Zeta Tail(a) probability distribution as a new model for random damage-event counts in risk analysis. Although readily motivated through a natural relationship with the Geometric(p) distribution, Zeta Tail(a) has received little attention in the scholarly literature. In the present work, we begin by deriving various fundamental properties of this novel distribution. We then assess its usefulness as an alternative to Geometric(p) for event-count data.

Pivot probabilities and norm effects in Gaussian elimination for $\beta$-ensembles
Kenji Gunawan, John Peca-Medlin
https://arxiv.org/abs/2506.20470 https:/…

Pivot probabilities and norm effects in Gaussian elimination for $β$-ensembles
We analyze pivot probabilities in Gaussian elimination with partial pivoting (GEPP) for $2 \times 2$ random matrix ensembles. For GUE matrices, we resolve a previously reported discrepancy between theoretical predictions and empirical observations by deriving the exact pivot probability under standard LAPACK-style implementations. We further show that Dumitriu-Edelman tridiagonal $β$-ensembles agree with the earlier theoretical expectations. Finally, we propose an open question on pivot behavi…

Deriving physical parameters of unresolved star clusters. IX. Sky background effects in the aperture photometry
Karolis Daugevi\v{c}ius, Rima Stonkut\.e, Eimantas Kri\v{s}\v{c}i\=unas, Erikas Cic\.enas, Vladas Vansevi\v{c}ius
https://arxiv.org/abs/2506.09622

Deriving physical parameters of unresolved star clusters. IX. Sky background effects in the aperture photometry
The aperture photometry method is a powerful tool that enables us to study large star cluster systems efficiently. However, its accuracy depends on various factors, including the stochasticity of the stellar initial mass function and variations in the sky background. Previously, in the eighth paper of this series, we established the best achievable limits of the aperture photometry method for star cluster studies in the local universe. The aim of this study is to determine how the sky backgroun…

Machine-Learning-Assisted Photonic Device Development: A Multiscale Approach from Theory to Characterization
Yuheng Chen, Alexander Montes McNeil, Taehyuk Park, Blake A. Wilson, Vaishnavi Iyer, Michael Bezick, Jae-Ik Choi, Rohan Ojha, Pravin Mahendran, Daksh Kumar Singh, Geetika Chitturi, Peigang Chen, Trang Do, Alexander V. Kildishev, Vladimir M. Shalaev, Michael Moebius, Wenshan Cai, Yongmin Liu, Alexandra Boltasseva

Machine-Learning-Assisted Photonic Device Development: A Multiscale Approach from Theory to Characterization
Photonic device development (PDD) has achieved remarkable success in designing and implementing new devices for controlling light across various wavelengths, scales, and applications, including telecommunications, imaging, sensing, and quantum information processing. PDD is an iterative, five-step process that consists of: i) deriving device behavior from design parameters, ii) simulating device performance, iii) finding the optimal candidate designs from simulations, iv) fabricating the optima…

Deriving Entangled Relativity
Olivier Minazzoli (ARTEMIS), Maxime Wavasseur (ARTEMIS), Thomas Chehab (ARTEMIS)
https://arxiv.org/abs/2506.15209 https://

Deriving Entangled Relativity
Entangled Relativity is a non-linear reformulation of Einstein's theory that cannot be defined in the absence of matter fields. It recovers General Relativity in the weak matter density limit or whenever $\mathcal{L}_m = T$ on-shell, and it is also more parsimonious in terms of fundamental constants and units. In this paper, we show that Entangled Relativity can be derived from a general $f(R,\mathcal{L}_m)$ theory by imposing a single requirement: the theory must admit all solutions of General…

STable AutoCorrelation Integral Estimator (STACIE): Robust and accurate transport properties from molecular dynamics simulations
G\"ozdenur Toraman, Dieter Fauconnier, Toon Verstraelen
https://arxiv.org/abs/2506.20438

STable AutoCorrelation Integral Estimator (STACIE): Robust and accurate transport properties from molecular dynamics simulations
STACIE (STable AutoCorrelation Integral Estimator) is a novel algorithm and Python package that delivers robust, uncertainty-aware estimates of autocorrelation integrals from time-correlated data. While its primary application is deriving transport properties from equilibrium molecular dynamics simulations, STACIE is equally applicable to time-correlated data in other scientific fields. A key feature of STACIE is its ability to provide robust and accurate estimates without requiring manual adju…

Generalized Multiple Operator Integrals for Operators with Finite Dimensions
Shih-Yu Chang
https://arxiv.org/abs/2506.19971 https://a…

Generalized Multiple Operator Integrals for Operators with Finite Dimensions
Multiple Operator Integrals (MOIs) have played a foundational role in operator theory and functional calculus, particularly for analyzing Hermitian matrices via spectral decomposition. Conventional MOIs rely on the assumption of self-adjointness, making them analytically tractable for computing Frechet derivatives, establishing trace formulas, and deriving commutator estimates. However, many problems in mathematics, science, and engineering involve matrices that are fundamentally non-Hermitian,…

Transformative or Conservative? Conservation laws for ResNets and Transformers
Sibylle Marcotte, R\'emi Gribonval, Gabriel Peyr\'e
https://arxiv.org/abs/2506.06194

Transformative or Conservative? Conservation laws for ResNets and Transformers
While conservation laws in gradient flow training dynamics are well understood for (mostly shallow) ReLU and linear networks, their study remains largely unexplored for more practical architectures. This paper bridges this gap by deriving and analyzing conservation laws for modern architectures, with a focus on convolutional ResNets and Transformer networks. For this, we first show that basic building blocks such as ReLU (or linear) shallow networks, with or without convolution, have easily exp…

The Gaia spectroscopic catalogue of exoplanets and host stars
Patrick de Laverny, Roxanne Ligi, Aur\'elien Crida, Alejandra Recio-Blanco, Pedro A. Palicio
https://arxiv.org/abs/2505.22205

The Gaia spectroscopic catalogue of exoplanets and host stars
Complete, accurate, and precise catalogues of exoplanet host star (EHS) properties are essential to deriving high-quality exoplanet parameters. This paper aims at homogeneously parameterising EHS and their exoplanets, using Gaia and GSP-spec data. For 2573 EHS, we computed their L*, R*, and M*, with no prior assumption from stellar evolution models. Their Galactic positions, kinematic and orbital properties were derived. We re-scaled Mp and Rp of 3556 exoplanets, fully consistently with the ste…

A High-Order, Pressure-Robust, and Decoupled Finite Difference Method for the Stokes Problem
Qiwei Feng, Bin Han, Michael Neilan
https://arxiv.org/abs/2506.13645

A High-Order, Pressure-Robust, and Decoupled Finite Difference Method for the Stokes Problem
In this paper, we consider the Stokes problem with Dirichlet boundary conditions and the constant kinematic viscosity $ν$ in an axis-aligned domain $Ω$. We decouple the velocity $\bm u$ and pressure $p$ by deriving a novel biharmonic equation in $Ω$ and third-order boundary conditions on $\partialΩ$. In contrast to the fourth-order streamfunction approach, our formulation does not require $Ω$ to be simply connected. For smooth velocity fields $\bm u$ in two dimensions, we explicitly constr…

Controllability and Stabilization of a Wave-Heat Cascade System
Hugo Lhachemi (L2S), Christophe Prieur (GIPSA-INFINITY), Emmanuel Tr\'elat (LJLL)
https://arxiv.org/abs/2506.10495

Controllability and Stabilization of a Wave-Heat Cascade System
Considering a wave-reaction-diffusion PDE cascade system with wave Neumann control, we first establish controllability properties in a suitable Hilbert space depending on the coupling cascade term. This is done by deriving an observability inequality for the dual problem by resorting to an Ingham-M{ü}ntz inequality. Second, we design an explicit output feedback control strategy for the actual stabilization of the PDE cascade. The key property is that the underlying operator is a Riesz-spectral…

A direct method in noncommutative integrable systems
Shi-Hao Li, Shou-Feng Shen, Guo-Fu Yu, Jun-Yang Zhang
https://arxiv.org/abs/2506.18661 https://…

A direct method in noncommutative integrable systems
We present a constructive framework for deriving noncommutative (NC) integrable equations directly from quasi-determinant solutions. Building upon the quasi-Wronskian structure, we extend the classical direct method to the NC setting, where standard determinant identities are replaced by algebraic relations intrinsic to quasi-determinants. By analyzing derivative identities satisfied by quasi-determinants, we recover the NC Kadomtsev-Petviashvili (ncKP) and Date-Jimbo-Kashiwara-Miwa (ncDJKM) eq…

The Gardner equation and acoustic solitary waves in plasmas
Frank Verheest, Willy A. Hereman
https://arxiv.org/abs/2506.15024 https://

The Gardner equation and acoustic solitary waves in plasmas
Ion-acoustic waves in a dusty plasma are investigated where it is assumed that the ions follow a Cairns distribution and the electrons are Boltzmann distributed. Two theoretical methods are applied: Sagdeev pseudopotential analysis (SPA) and reductive perturbation theory (RPT). Since SPA incorporates all nonlinearities of the model it is the most accurate but deriving soliton profiles requires numerical integration of Poisson's equation. By contrast, RPT is a perturbation method which at second…

Statistical Geometry and Information Dynamics on Hyperspherical Surfaces
Masoud Ataei
https://arxiv.org/abs/2506.19251 https://arxiv.…

Statistical Geometry and Information Dynamics on Hyperspherical Surfaces
We study the statistical geometry of random chords on n-dimensional spheres by deriving explicit analytical expressions for the chord length distribution and its associated structural properties. A critical threshold emerges at dimension 19, marking the transition from curvature-dominated variability to high-dimensional concentration, where interpoint distances become nearly deterministic and probabilistic diversity collapses into geometric uniformity. We further derive a closed-form expression…

Deriving physical parameters of unresolved star clusters. VIII. Limits of aperture photometry for star cluster studies
Karolis Daugevi\v{c}ius, Eimantas Kri\v{s}\v{c}i\=unas, Erikas Cic\.enas, Rima Stonkut\.e, Vladas Vansevi\v{c}ius
https://arxiv.org/abs/2506.08674

Deriving physical parameters of unresolved star clusters. VIII. Limits of aperture photometry for star cluster studies
Recently, it has been noticed that the discrepancies in the integrated colour indices (CIs) between star clusters and models are mostly due to the projection of bright stars in the apertures. In order to reduce this problem, the method of adaptive aperture photometry has been proposed. This method has been applied to star clusters from the M 31 Panchromatic Hubble Andromeda Treasury (PHAT) survey, and studies show that the adaptive aperture photometry performs better than the conventional appro…

This https://arxiv.org/abs/2502.19213 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qfi…

Framework for asset-liability management with fixed-term securities
We consider an optimal investment-consumption problem for a utility-maximizing investor who has access to assets with different liquidity and whose consumption rate as well as terminal wealth are subject to lower-bound constraints. Assuming utility functions that satisfy standard conditions, we develop a methodology for deriving the optimal strategies in semi-closed form. Our methodology is based on the generalized martingale approach and the decomposition of the problem into subproblems. We il…

Tight Success Probabilities for Quantum Period Finding and Phase Estimation
Malik Magdon-Ismail, Khai Dong
https://arxiv.org/abs/2506.20527 https://…

Tight Success Probabilities for Quantum Period Finding and Phase Estimation
Period finding and phase estimation are fundamental in quantum computing. Prior work has established lower bounds on their success probabilities. We improve these results by deriving tight upper and lower bounds on the success probability that converge to 1.

Normalized solutions for a Sobolev critical quasilinear Schr\"odinger equation
Yuxin Li, Meijie Yang, Xiaojun Chang
https://arxiv.org/abs/2506.10870 h…

Normalized solutions for a Sobolev critical quasilinear Schrödinger equation
In this paper, we study the existence of normalized solutions for the following quasilinear Schrödinger equation with critical exponent: \begin{equation*} -Δu-uΔ(u^2)+λu=τ|u|^{q-2}u+|u|^{2\cdot2^*-2}u,~~~~x\in\R^N, \end{equation*} under the mass constraint $\int_{\R^N}|u|^2dx=c$ for some prescribed $c>0$. Here $τ\in \mathbb{R}$ is a parameter, $λ\in\R$ appears as a Lagrange multiplier, $N\ge3$, $2^*:=\frac{2N}{N-2}$ and $2

Cancer model with moving extinction threshold reproduces real cancer data
Frank Bastian, Hassan Alkhayuon, Kieran Mulchrone, Micheal O'Riordain, Sebastian Wieczorek
https://arxiv.org/abs/2506.05992

Cancer model with moving extinction threshold reproduces real cancer data
We propose a simple dynamic model of cancer development that captures carcinogenesis and subsequent cancer progression. A central idea of the model is to include the immune system as an extinction threshold, similar to the strong Allee effect in population biology. We first identify the limitations of commonly used Allee effect models in reproducing typical cancer progression. We then address these limitations by deriving a new model that incorporates: (i) random mutations of stem cells at a ra…

Revised identification of strain gradient elastic parameters
Luca Placidi, Anil Misra, Gabriele La Valle, Casey Rodriguez
https://arxiv.org/abs/2506.14932 …

Revised identification of strain gradient elastic parameters
The work reported in ``Granular micromechanics-based identification of isotropic strain gradient parameters for elastic geometrically nonlinear deformations" misidentified key terms in the grain-pair objective relative displacement when accounting for the second gradient of placement. In this paper, we correct that oversight by deriving a revised expression for the grain-pair objective relative displacement within the granular micromechanics framework. The amended terms, which resemble Christof…

CALICO: Computing Annihilators from Linear Identities Constraining (differential) Operators
Giuseppe Bertolini, Gaia Fontana, Tiziano Peraro
https://arxiv.org/abs/2506.13653

CALICO: Computing Annihilators from Linear Identities Constraining (differential) Operators
We elaborate on the method of parametric annihilators for deriving integral relations. Parametric annihilators are differential operators that annihilate multivalued integration kernels appearing in suitable integral representations of special functions. We illustrate this approach in a way that applies to a broad variety of integral representations. We describe a method for computing parametric annihilators based on efficient linear solvers and use them to derive relations between a wide class…

Testing Quantum-Corrected Black Holes with QPOs Observations: A Study of Particle Dynamics and Accretion Flow
G. Mustafa, Sushant G. Ghosh, Orhan Donmez, S. K. Maurya, Shakhzod Orzuev, Farruh Atamurotov
https://arxiv.org/abs/2506.16405

Testing Quantum-Corrected Black Holes with QPOs Observations: A Study of Particle Dynamics and Accretion Flow
We study the epicyclic oscillations of test particles around rotating quantum-corrected black holes (QCBHs), characterized by mass $M$, spin $a$, and quantum deformation parameter $b$. By deriving the radial ($Ω_r$) and vertical ($Ω_θ$) oscillation frequencies, we explore their dependence on spacetime parameters and show that quantum corrections ($b \neq 0$) significantly modify the dynamics compared to the classical Kerr case. Through numerical modelling of accretion around QCBHs, we furthe…

From simulations to observations. Methodology and data release of mock TNG50 galaxies at 0.3 < z < 0.7 for WEAVE-StePS
A. Ikhsanova, L. Costantin, A. Pizzella, E. M. Corsini, L. Morelli, F. R. Ditrani, A. Ferr\'e-Mateu, L. Gabarra, M. Gullieuszik, C. P. Haines, A. Iovino, M. Longhetti, A. Mercurio, R. Ragusa, P. S\'anchez-Bl\'azquez, C. Tortora, B. Vulcani, S. Zhou, E. Gafton, F. Pistis

From simulations to observations. Methodology and data release of mock TNG50 galaxies at 0.3 < z < 0.7 for WEAVE-StePS
The new generation of optical spectrographs (i.e., WEAVE, 4MOST, DESI, and WST) offer unprecedented opportunities for statistically studying the star formation histories of galaxies. However, these observations are not easily comparable to predictions from cosmological simulations. Our goal is to build a reference framework for comparing spectroscopic observations with simulations and test tools for deriving stellar population properties of galaxies. We focus on the observational strategy of th…

This https://arxiv.org/abs/2409.05316 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Continuous Relaxation of Discontinuous Shrinkage Operator: Proximal Inclusion and Conversion
We present a principled way of deriving a continuous relaxation of a given discontinuous shrinkage operator, which is based on two fundamental results, proximal inclusion and conversion. Using our results, the discontinuous operator is converted, via double inversion, to a continuous operator; more precisely, the associated ``set-valued'' operator is converted to a ``single-valued'' Lipschitz continuous operator. The first illustrative example is the firm shrinkage operator which can be derived…

Normal forms of piecewise-smooth systems with a monodromic singular point
Jiahao Li, Xingwu Chen, Weinian Zhang
https://arxiv.org/abs/2506.13200 https://…

Normal forms of piecewise-smooth systems with a monodromic singular point
Normal form theory is developed deeply for planar smooth systems but has few results for piecewise-smooth systems because difficulties arise from continuity of the near-identity transformation, which is constructed piecewise. In this paper, we overcome the difficulties to study normal forms for piecewise-smooth systems with FF, FP, or PP equilibrium and obtain explicit any-order normal forms by finding piecewise-analytic homeomorphisms and deriving a new normal form for analytic syste…

Alternating steepest descent methods for tensor completion with applications to spectromicroscopy
Oliver Townsend, Sergey Dolgov, Silvia Gazzola, Misha Kilmer
https://arxiv.org/abs/2506.10661

Alternating steepest descent methods for tensor completion with applications to spectromicroscopy
In this paper we develop two new Tensor Alternating Steepest Descent algorithms for tensor completion in the low-rank $\star_{M}$-product format, whereby we aim to reconstruct an entire low-rank tensor from a small number of measurements thereof. Both algorithms are rooted in the Alternating Steepest Descent (ASD) method for matrix completion, first proposed in [J. Tanner and K. Wei, Appl. Comput. Harmon. Anal., 40 (2016), pp. 417-429]. In deriving the new methods we target the X-ray spectromic…

Nonequilibrium fluctuation-response relations for state-current correlations
Krzysztof Ptaszynski, Timur Aslyamov, Massimiliano Esposito
https://arxiv.org/abs/2506.08877

Nonequilibrium fluctuation-response relations for state-current correlations
Recently, novel exact identities known as Fluctuation-Response Relations (FRRs) have been derived for nonequilibrium steady states of Markov jump processes. These identities link the fluctuations of state or current observables to a combination of responses of these observables to perturbations of transition rates. Here, we complement these results by deriving analogous FRRs applicable to mixed covariances of one state and one current observable. We further derive novel Inverse FRRs expressing …

Indicator Functions: Distilling the Information from Gaussian Random Fields
Andrew Repp, Ravi K. Sheth, Istvan Szapudi, Yan-Chuan Cai
https://arxiv.org/abs/2506.06668

Indicator Functions: Distilling the Information from Gaussian Random Fields
A random Gaussian density field contains a fixed amount of Fisher information on the amplitude of its power spectrum. For a given smoothing scale, however, that information is not evenly distributed throughout the smoothed field. We investigate which parts of the field contain the most information by smoothing and splitting the field into different levels of density (using the formalism of indicator functions), deriving analytic expressions for the information content of each density bin in the…

Norm Inequality for Perturbed Quantum Evolutions and Its Application to Grover's Algorithm
Kohei Kobayashi
https://arxiv.org/abs/2506.14230 https://

Norm Inequality for Perturbed Quantum Evolutions and Its Application to Grover's Algorithm
We investigate the impact of coherent control errors on quantum state evolution by deriving a general norm inequality based on Gronwall's lemma. This inequality provides an explicit upper bound on the deviation between an ideal quantum state and one subject to arbitrary coherent perturbations, including both time-dependent and time-independent cases. The framework is broadly applicable, requiring no assumptions about the detailed structure of the perturbation and full dynamics of the quantum sy…

The circular disc made of linear elastic incompressible material and the 'bathyscaphe lesson'
D. Bigoni, S. G. Mogilevskaya, A. Piccolroaz, M. Gaibotti
https://arxiv.org/abs/2506.20247

The circular disc made of linear elastic incompressible material and the 'bathyscaphe lesson'
A linear elastic circular disc is analyzed under a self-equilibrated system of loads applied along its boundary. A distinctive feature of the investigation, conducted using complex variable analysis, is the assumption that the material is incompressible (in its linearized approximation), rendering the governing equations formally identical to those of Stokes flow in viscous fluids. After deriving a general solution to the problem, an isoperimetric constraint is introduced at the boundary to enf…

Stochastic maximum principle for optimal control problem of non exchangeable mean field systems
Idris Kharroubi, Samy Mekkaoui, Huy\^en Pham
https://arxiv.org/abs/2506.05595

Stochastic maximum principle for optimal control problem of non exchangeable mean field systems
We study the Pontryagin maximum principle by deriving necessary and sufficient conditions for a class of optimal control problems arising in non exchangeable mean field systems, where agents interact through heterogeneous and asymmetric couplings. Our analysis leads to a collection of forward-backward stochastic differential equations (FBSDE) of non exchangeable mean field type. Under suitable assumptions, we establish the solvability of this system. As an illustration, we consider the linear-q…

This https://arxiv.org/abs/2404.09284 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Deriving a GENERIC system from a Hamiltonian system
We reconsider the fundamental problem of coarse-graining infinite-dimensional Hamiltonian dynamics to obtain a macroscopic system which includes dissipative mechanisms. In particular, we study the thermodynamical implications concerning Hamiltonians, energy, and entropy and the induced geometric structures such as Poisson and Onsager brackets (symplectic and dissipative brackets). We start from a general finite-dimensional Hamiltonian system that is coupled linearly to an infinite-dimensional…

Entropy proxy inversions as tracers of the evolution of physical conditions at the base of the solar convective envelope
G. Buldgen, A. Noels, V. A. Baturin, J. Christensen-Dalsgaard, S. V. Ayukov, A. V. Oreshina, R. Scuflaire
https://arxiv.org/abs/2506.09503

Entropy proxy inversions as tracers of the evolution of physical conditions at the base of the solar convective envelope
The Sun is an important calibrator for the theory of stellar structure and evolution. However, the accuracy of our solar evolution models is tightly linked to the physical ingredients that enter their computations. This include, amongst other, the equation of state, the opacities, the transport of chemicals and the modelling of turbulent convection. Deriving model-independent probes of these ingredients is therefore crucial to further test the quality of these ingredients and potentially reveal…

This https://arxiv.org/abs/2312.03941 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Minimising Numbers of Losses and Abandonments in Small Call Centres Under a Transient Regime
We consider the problem of allocating customers to agents in small call centres so that transient performance indicators in terms of expected numbers of losses and abandonments are optimised. To gain insight into the general structure of optimal policies, we start by (i) using backward induction based upon Bellman's equation for a finite-horizon discrete-time model, and (ii) deriving stationary policies for an infinite-horizon continuous-time model with discounting. We then compare the performa…

SDSS-V Milky Way Mapper (MWM): ASPCAP Stellar Parameters and Abundances in SDSS-V Data Release 19
Szabolcs M\'esz\'aros, Paula Jofr\'e, Jennifer A. Johnson, Jonathan C. Bird, Andrew R. Casey, Katia Cunha, Nathan De Lee, Peter Frinchaboy, Guillaume Guiglion, Viola Heged\H{u}s, Alex P. Ji, Juna A. Kollmeier, Melissa K. Ness, Jonah Otto, Marc H. Pinsonneault, Alexandre Roman-Lopes, Amaya Sinha, Ying-Yi Song, Guy S. Stringfellow, Keivan G. Stassun, Jamie Tayar, Andrew Tkachenko…

SDSS-V Milky Way Mapper (MWM): ASPCAP Stellar Parameters and Abundances in SDSS-V Data Release 19
The goal of this paper is to describe the science verification of Milky Way Mapper (MWM) ASPCAP data products published in Data Release 19 (DR19) of the fifth phase of the Sloan Digital Sky Survey (SDSS-V). We compare MWM ASPCAP atmospheric parameters T$_{\rm eff}$, log g, 24 abundances of 21 elements (carbon, nitrogen, and oxygen have multiple sources for deriving their abundance values) and their uncertainties determined from APOGEE spectrograph spectra with those of the literature and evalua…

Limits of Classical correlations and Quantum advantages under (Anti-)Distinguishability constraints in Multipartite Communication
Ankush Pandit, Soumyabrata Hazra, Satyaki Manna, Anubhav Chaturvedi, Debashis Saha
https://arxiv.org/abs/2506.07699

Limits of Classical correlations and Quantum advantages under (Anti-)Distinguishability constraints in Multipartite Communication
We consider communication scenarios with multiple senders and a single receiver. Focusing on communication tasks where the distinguishability or anti-distinguishability of the sender's input is bounded, we show that quantum strategies without any shared entanglement can outperform the classical ones. We introduce a systematic technique for deriving the facet inequalities that delineate the polytope of classical correlations in such scenarios. As a proof of principle, we recover the complete set…