Tootfinder

Metallicity differences between Type IIP and stripped-envelope supernova environments
R. Ganss, J. L. Pledger, A. E. Sansom, P. A. James, J. Puls, S. M. Habergham-Mawson
https://arxiv.org/abs/2509.06526

Metallicity differences between Type IIP and stripped-envelope supernova environments
This work presents measurements of local HII environment metallicities of core-collapse supernovae (SNe) in hosts with redshifts up to z$\sim$0.025. 139 SNe environments were observed at the Isaac Newton Telescope and data of an additional 268 SNe environments were found in archival data of MUSE, MaNGA and PISCO. The project focuses on SNe with clean Type IIP, Type Ib and Type Ic classifications. We present the largest spectroscopic sample to date, evaluating environment metallicities of 79 Typ…

Explaining 650 GeV and 95 GeV Anomalies in the 2-Higgs Doublet Model Type-I
Akshat Khanna, Stefano Moretti, Agnivo Sarkar
https://arxiv.org/abs/2509.06017 https://

Explaining 650 GeV and 95 GeV Anomalies in the 2-Higgs Doublet Model Type-I
We propose an interpretation of a rather significant 650 GeV excess emerged at the Large Hadron Collider (LHC) from CMS Collaboration data in the $γγb\bar b$ final state, accompanied by further clusters at 125(90-100) GeV in the $γγ(b\bar b)$ system, within the 2-Higgs Doublet Model Type-I (2HDM-I) in presence of a softly broken $\mathcal{Z}_{2}$ symmetry. The underlying process that we probe is $gg$-initiated production of a CP-odd (or pseudoscalar) Higgs boson $A$, with mass around 650 Ge…

Cumulative/Dynamic Time-Dependent ROC Analysis for Left-Truncated and Right-Censored Data: Estimators and Comparison
Kendrick Li, Mithun Kumar Acharjee
https://arxiv.org/abs/2509.05693

Cumulative/Dynamic Time-Dependent ROC Analysis for Left-Truncated and Right-Censored Data: Estimators and Comparison
Time-dependent Receiver Operating Characteristics (ROC) analysis is a standard method to evaluate the discriminative performance of biomarkers or risk scores for time-to-event outcomes. Extensions of this useful method to left-truncated right-censored data have been understudied, with the exception of Li 2017. In this paper, we first extended the estimators in Li 2017 to several regression-type estimators that account for independent or covariate-induced dependent left truncation and right cens…

Too many keep using WhatsApp while the company, Meta can not be trusted with your data.
https://arstechnica.com/security/2025/09/…

Former WhatsApp security boss in lawsuit likens Meta’s culture to a “cult”
Meta allegedly prioritized user growth over security, lawsuit said.

Automorphism groups of Inoue surfaces $S^{( )}/S^{(-)}$
David Petcu
https://arxiv.org/abs/2509.06860 https://arxiv.org/pdf/2509.06860

Automorphism groups of Inoue surfaces $S^{(+)}/S^{(-)}$
We present the construction of Inoue surfaces of type $S^{(+)}/S^{(-)}$ in terms of data arising from real quadratic number fields. We then describe the automorphism group of such surfaces in terms of this data.

Global strong solutions to the $3$D rotating compressible Navier--Stokes--Korteweg system for large data in the critical $\widehat{L^p}$ framework
Mikihiro Fujii, Shunhang Zhang
https://arxiv.org/abs/2509.06078

Global strong solutions to the $3$D rotating compressible Navier--Stokes--Korteweg system for large data in the critical $\widehat{L^p}$ framework
Let us consider the $3$D compressible Navier--Stokes--Korteweg system in the rotational framework. Although there is a wealth of literature on the weak solutions to this system, there seem to be no results on the strong solutions. In this paper, we show the unique existence of global solutions for {\it large} initial data in the critical Besov-type spaces based on the Fourier--Lebesgue spaces $\widehat{L^p}(\mathbb{R}^3)$ with $2 \leq p < 3$, provided that the rotation speed and the Mach number…

Feature Understanding and Sparsity Enhancement via 2-Layered kernel machines (2L-FUSE)
Fabiana Camattari, Sabrina Guastavino, Francesco Marchetti, Emma Perracchione
https://arxiv.org/abs/2509.07806

Feature Understanding and Sparsity Enhancement via 2-Layered kernel machines (2L-FUSE)
We propose a novel sparsity enhancement strategy for regression tasks, based on learning a data-adaptive kernel metric, i.e., a shape matrix, through 2-Layered kernel machines. The resulting shape matrix, which defines a Mahalanobis-type deformation of the input space, is then factorized via an eigen-decomposition, allowing us to identify the most informative directions in the space of features. This data-driven approach provides a flexible, interpretable and accurate feature reduction scheme. …

Gaussian process analysis of type-B quasiperiodic oscillations in the black hole X-ray binary MAXI J1348-630
Yiran Wang, Ruican Ma, Haiyun Zhang, Dahai Yan
https://arxiv.org/abs/2510.05587

Gaussian process analysis of type-B quasiperiodic oscillations in the black hole X-ray binary MAXI J1348-630
We analyzed Insight-HXMT data of the black hole X-ray binary MAXI J1348-630 during the type-B QPO phase of its 2019 outburst. Using the Gaussian process method, we applied an additive composite kernel model consisting of an SHO, a DRW, and an additional white noise (AWN) to data from three energy bands: LE (1-10 keV), ME (10-30 keV), and HE (30-150 keV). We find that for the DRW component, correlations on the timescale of $τ_{\rm DRW}\sim10$ s are absent in the LE band, while they persist in t…

Time-resolved measurement of Seebeck effect for superionic metals during structural phase transition
Shilin Li (Beijing Academy of Quantum Information Sciences), Hailiang Xia (Beijing Huihaoyu Intelligent Technology Co., Ltd), Takuma Ogasawara (Beijing Academy of Quantum Information Sciences), Liguo Zhang (Beijing Academy of Quantum Information Sciences), Katsumi Tanigaki (Beijing Academy of Quantum Information Sciences)

Time-resolved measurement of Seebeck effect for superionic metals during structural phase transition
We propose a new time (t)-resolved method of both vertical- and horizontal-temperature gradients in an orthogonal configuration (t-resolved T(t)-HVOT) to have real interpretations of the enhancement in thermoelectric Seebeck effect (SE) observed during the structural phase transition. We apply our new method to superionic-state semiconductors of p-type Cu2Se and n-type Ag2S. The experimental data differentiate the two types of enhancements during the phase transition: a colossal SE (Scolossal),…

> It is unexpected that this type of political content not just made it into the tokenizer training data, but was even overrepresented
https://fi-le.net/oss/

Heavy Field Effects on Inflationary Models in Light of ACT Data
Shuntaro Aoki, Hajime Otsuka, Ryota Yanagita
https://arxiv.org/abs/2509.06739 https://arxiv…

Heavy Field Effects on Inflationary Models in Light of ACT Data
Recent results from the Atacama Cosmology Telescope (ACT), when combined with Planck and DESI datasets, indicate a scalar spectral index $n_s$ larger than that reported in the Planck 2018 baseline, thereby challenging conventional Starobinsky-type ($α$-attractor) inflationary scenarios at the $2σ$ level. In addition, the positive running of the spectral index $α_s$ implied by the data provides strong constraints on these models. In this paper, we explore the possibility that the presence of …

from my link log —
Type inference for plain data.
https://www.haskellforall.com/2025/08/type-inference-for-plain-data.html
saved 2025-08-13

Probing departures from $\Lambda$CDM by late-time datasets
Himanshu Chaudhary, Vipin Kumar Sharma, Salvatore Capozziello, G. Mustafa
https://arxiv.org/abs/2510.08339 https://

Probing departures from $Λ$CDM by late-time datasets
Observational data play a pivotal role in identifying cosmological models that are both theoretically consistent and empirically viable. In this work, we investigate whether the standard $Λ$CDM model exhibits significant departure with current late time datasets, including Cosmic Chronometers, Baryon Acoustic Oscillations from DESI DR2, and various Type Ia supernova compilations (Pantheon$^+$, DES-SN5Y, Union3). We analyze several dynamical dark energy models, including $ω$CDM, o$ω$CDM, $ω_…

AP2O: Correcting LLM-Generated Code Errors Type by Type Like Humans via Adaptive Progressive Preference Optimization
Jianqing Zhang, Wei Xia, Hande Dong, Qiang Lin, Jian Cao
https://arxiv.org/abs/2510.02393

AP2O: Correcting LLM-Generated Code Errors Type by Type Like Humans via Adaptive Progressive Preference Optimization
LLMs' code generation capabilities have yielded substantial improvements in the effectiveness of programming tasks. However, LLM-generated code still suffers from compilation and runtime errors. Existing offline preference optimization methods primarily focus on enhancing LLMs' coding abilities using pass/fail signals in the preference data, overlooking the deep-level error types in the failed codes. To address this, we propose Adaptively Progressive Preference Optimization (AP2O) for coding (i…

On the equivariant cohomological rigidity of semi-free Hamiltonian circle actions
Liat Kessler, Nikolas Wardenski
https://arxiv.org/abs/2509.04890 https://…

On the equivariant cohomological rigidity of semi-free Hamiltonian circle actions
We consider semi-free Hamiltonian $S^1$-manifolds of dimension six and establish when the equivariant cohomology and data on the fixed point set determine the isomorphism type. Gonzales listed conditions under which the isomorphism type of such spaces is determined by fixed point data. We pointed out in an earlier paper that this result as stated is erroneous, and proved a corrected version. However, that version relied on a certain distribution of fixed points that is not at all necessary. In …

Dynamic Prediction of Joint Longitudinal-Survival Models Using a Similarity-Based Approach
Minzee Kim, Joel A. Dubin
https://arxiv.org/abs/2509.05476 https://

Dynamic Prediction of Joint Longitudinal-Survival Models Using a Similarity-Based Approach
Longitudinal and time-to-event data are often analyzed in biomarker research to study the association between the longitudinal biomarker measurements and the event-time outcome, in which the longitudinal information contributes to the probability of the outcome of interest. An attractive nature of fitting a joint model on this type of data is that we can dynamically predict the survival probability as additional longitudinal information becomes available. We propose a new similarity-based metho…

Efficient Contractions of Dynamic Graphs -- with Applications
Monika Henzinger, Evangelos Kosinas, Robin M\"unk, Harald R\"acke
https://arxiv.org/abs/2509.05157 https:…

Efficient Contractions of Dynamic Graphs -- with Applications
A non-trivial minimum cut (NMC) sparsifier is a multigraph $\hat{G}$ that preserves all non-trivial minimum cuts of a given undirected graph $G$. We introduce a flexible data structure for fully dynamic graphs that can efficiently provide an NMC sparsifier upon request at any point during the sequence of updates. We employ simple dynamic forest data structures to achieve a fast from-scratch construction of the sparsifier at query time. Based on the strength of the adversary and desired type of …

The analogy theorem in Hoare logic
Nikitin Nikita
https://arxiv.org/abs/2510.03685 https://arxiv.org/pdf/2510.03685…

The analogy theorem in Hoare logic
The introduction of machine learning methods has led to significant advances in automation, optimization, and discoveries in various fields of science and technology. However, their widespread application faces a fundamental limitation: the transfer of models between data domains generally lacks a rigorous mathematical justification. The key problem is the lack of formal criteria to guarantee that a model trained on one type of data will retain its properties on another.This paper proposes a so…

From Traces to Program Incorrectness: A Type-Theoretic Approach
Yongwei Yuan, Zhe Zhou, Julia Belyakova, Benjamin Delaware, Suresh Jagannathan
https://arxiv.org/abs/2509.02428 h…

From Traces to Program Incorrectness: A Type-Theoretic Approach
We present a type-theoretic framework for reasoning about incorrectness in functional programs that interact with effectful, opaque library APIs. Our approach centers on traces -- temporally-ordered sequences of library API invocations -- which naturally characterize both the preconditions of individual APIs and their composite behavior. We represent these traces using symbolic regular expressions (SREs), enabling formal specification of incorrect abstract data type (ADT) behaviors across funct…

The UK's obligatory inshore fishing vessel position reporting system (I-VMS) appears to have launched without one of the suppliers having a finalised contract. So they just stopped relaying the data.
(It's not like AIS - it batches up positional data and relays via cell-towers when in range.)
https://www.

I-VMS Urgent Update
The Marine Management Organisation (MMO) is aware that Succorfish is no longer transmitting I-VMS data to the UK VMS Hub. This is preventing MMO from receiving positional data from under-12m vessels using Succorfish type-approved devices.

Probing the Cosmic Distance Duality Relation via Non-Parametric Reconstruction for High Redshifts
Felipe Avila, Fernanda Oliveira, Camila Franco, Maria Lopes, Rodrigo Holanda, Rafael C. Nunes, Armando Bernui
https://arxiv.org/abs/2509.07848

Probing the Cosmic Distance Duality Relation via Non-Parametric Reconstruction for High Redshifts
We test the validity of the cosmic distance duality relation (CDDR) by combining angular diameter distance and luminosity distance measurements from recent cosmological observations. For the angular diameter distance, we use data from transverse baryon acoustic oscillations and galaxy clusters. On the other hand, the luminosity distance is obtained from Type Ia supernovae in the Pantheon+ sample and from quasar catalogs. To reduce the large dispersion in quasar luminosity distances, we apply a …

On Morawetz estimates for the elastic wave equation
Seongyeon Kim, Ihyeok Seo
https://arxiv.org/abs/2510.06958 https://arxiv.org/pdf/2510.06958

On Morawetz estimates for the elastic wave equation
We establish Morawetz-type estimates for solutions to the elastic wave equation with singular weights of the form $|x|^{-α}$ or $|(x,t)|^{-α}$. In particular, we show that space-time weights $|(x,t)|^{-α}$ admit stronger singularities and require weaker regularity assumptions on the initial data compared to purely spatial weights $|x|^{-α}$.

Do you have any projects that have stalled out? Could you use some prompts to help break them down into smaller pieces?
Now in TestFlight, OmniFocus 4.8 plug-ins can consult Apple's new on-device Foundation Models. These AI models are built into your device, so you’re not sending any data to any other systems, nor are you using any expensive outside resources—you’re just using more capabilities of the device that’s already at your fingertips.

Illuminating Patterns of Divergence: DataDios SmartDiff for Large-Scale Data Difference Analysis
Aryan Poduri, Yashwant Tailor
https://arxiv.org/abs/2509.00293 https://

Illuminating Patterns of Divergence: DataDios SmartDiff for Large-Scale Data Difference Analysis
Data engineering workflows require reliable differencing across files, databases, and query outputs, yet existing tools falter under schema drift, heterogeneous types, and limited explainability. SmartDiff is a unified system that combines schema-aware mapping, type-specific comparators, and parallel execution. It aligns evolving schemas, compares structured and semi-structured data (strings, numbers, dates, JSON/XML), and clusters results with labels that explain how and why differences occur.…

Investigating Document Type, Language, Publication Year, and Author Count Discrepancies Between OpenAlex and Web of Science
#OpenAccess

Investigating Document Type, Language, Publication Year, and Author Count Discrepancies Between OpenAlex and Web of Science
Bibliometrics, whether used for research or research evaluation, relies on large multidisciplinary databases of research outputs and citation indices. The Web of Science (WoS) was the main supporting infrastructure of the field for more than 30 years until several new competitors emerged. OpenAlex, a bibliographic database launched in 2022, has distinguished itself for its openness and extensive coverage. While OpenAlex may reduce or eliminate barriers to accessing bibliometric data, one of the…

The {esquisse} package makes it easy to plot your data in different ways with a drag and drop interface: #rstats

Explore and Visualize Your Data Interactively
A shiny gadget to create ggplot2 figures interactively with drag-and-drop to map your variables to different aesthetics. You can quickly visualize your data accordingly to their type, export in various formats, and retrieve the code to reproduce the plot.

Data driven modeling of multiple interest rates with generalized Vasicek-type models
Pauliina Ilmonen, Milla Laurikkala, Kostiantyn Ralchenko, Tommi Sottinen, Lauri Viitasaari
https://arxiv.org/abs/2509.03208

Data driven modeling of multiple interest rates with generalized Vasicek-type models
The Vasicek model is a commonly used interest rate model, and there exist many extensions and generalizations of it. However, most generalizations of the model are either univariate or assume the noise process to be Gaussian, or both. In this article, we study a generalized multivariate Vasicek model that allows simultaneous modeling of multiple interest rates while making minimal assumptions. In the model, we only assume that the noise process has stationary increments with a suitably decaying…

Constraining the new contributions to electron $g-2$ in a radiative neutrino mass model
Bayu Dirgantara, J. Julio
https://arxiv.org/abs/2510.08504 https://…

Constraining the new contributions to electron $g-2$ in a radiative neutrino mass model
We examine electron and muon anomalous magnetic dipole moments within a radiative neutrino mass model featuring TeV-scale scalar leptoquarks $S(3,1,-1/3)$ and $R(3,2,1/6)$. We utilize textures with decoupling electron and muon sectors, so that both electron and muon anomalous magnetic dipole moments could receive internal chiral enhancements from different heavy up-type quarks while in the same time evading the stringent $μ\to eγ$ constraint. A successful fit to neutrino oscillation data requ…

Detection of supernova magnitude fluctuations induced by large-scale structure
A. Nguyen, C. Blake, R. J. Turner, V. Aronica, J. Bautista, J. Aguilar, S. Ahlen, S. BenZvi, D. Bianchi, D. Brooks, A. Carr, T. Claybaugh, A. Cuceu, A. de la Macorra, B. Dey, P. Doel, K. Douglass, S. Ferraro, J. E. Forero-Romero, E. Gazta\~naga, S. Gontcho A Gontcho, G. Gutierrez, J. Guy, K. Honscheid, C. Howlett, D. Huterer, M. Ishak, R. Joyce, R. Kehoe, A. G. Kim, A. Kremin, O. Lahav, M. Landriau, L. Le Gu…

Detection of supernova magnitude fluctuations induced by large-scale structure
The peculiar velocities of supernovae and their host galaxies are correlated with the large-scale structure of the Universe, and can be used to constrain the growth rate of structure and test the cosmological model. In this work, we measure the correlation statistics of the large-scale structure traced by the Dark Energy Spectroscopic Instrument Bright Galaxy Survey Data Release 1 sample, and magnitude fluctuations of type Ia supernova from the Pantheon+ compilation across redshifts z < 0.1. We…

A Recursive Algorithm for Multi-Coefficient Inversion in Nonlinear Helmholtz Equations
Shuai LU, Boxi XU
https://arxiv.org/abs/2509.06008 https://arxiv.org…

A Recursive Algorithm for Multi-Coefficient Inversion in Nonlinear Helmholtz Equations
We present a recursive algorithm for multi-coefficient inversion in nonlinear Helmholtz equations with polynomial-type nonlinearities, utilizing the linearized Dirichlet-to-Neumann map as measurement data. To achieve effective recursive decoupling and simultaneous recovery of multiple coefficients, we develop a novel Fourier-based approach that combines the principle of inclusion-exclusion with carefully constructed complex exponential solutions. This methodology not only ensures unique identif…

Revisiting the Radius Valley Across Stellar Types: A Transit-Only Analysis of M, K, G, and F Stars with Updated NASA Exoplanet Archive Data
Sukdev Mahapatra
https://arxiv.org/abs/2509.03549

Revisiting the Radius Valley Across Stellar Types: A Transit-Only Analysis of M, K, G, and F Stars with Updated NASA Exoplanet Archive Data
The radius valley -- a deficit of exoplanets between super-Earths and sub-Neptunes -- is a key diagnostic of planet formation and atmospheric evolution. We investigate how the radius valley depends on stellar type by analyzing an updated, transit-only sample of exoplanets from the NASA Exoplanet Archive. Planets are selected with $P < 100$ days and divided by host spectral class (M, K, G, F). We construct weighted radius distributions and apply statistical tests to quantify the valley depth. We…

Type-Compliant Adaptation Cascades: Adapting Programmatic LM Workflows to Data
Chu-Cheng Lin, Daiyi Peng, Yifeng Lu, Ming Zhang, Eugene Ie
https://arxiv.org/abs/2508.18244 https…

Type-Compliant Adaptation Cascades: Adapting Programmatic LM Workflows to Data
Reliably composing Large Language Models (LLMs) for complex, multi-step workflows remains a significant challenge. The dominant paradigm-optimizing discrete prompts in a pipeline-is notoriously brittle and struggles to enforce the formal compliance required for structured tasks. We introduce Type-Compliant Adaptation Cascades (TACs), a framework that recasts workflow adaptation as learning typed probabilistic programs. TACs treats the entire workflow, which is composed of parameter-efficiently …

Transduction is All You Need for Structured Data Workflows
Alfio Gliozzo, Naweed Khan, Christodoulos Constantinides, Nandana Mihindukulasooriya, Nahuel Defosse, Junkyu Lee
https://arxiv.org/abs/2508.15610

Transduction is All You Need for Structured Data Workflows
This paper introduces Agentics, a modular framework for building agent-based systems capable of structured reasoning and compositional generalization over complex data. Designed with research and practical applications in mind, Agentics offers a novel perspective on working with data and AI workflows. In this framework, agents are abstracted from the logical flow and they are used internally to the data type to enable logical transduction among data. Agentics encourages AI developers to focus o…

Selection Bias in Hybrid Randomized Controlled Trials using External Controls: A Simulation Study
Han Chang Chiam, Franz K\"onig, Martin Posch
https://arxiv.org/abs/2510.04829

Selection Bias in Hybrid Randomized Controlled Trials using External Controls: A Simulation Study
Hybrid randomized controlled trials (hybrid RCTs) integrate external control data, such as historical or concurrent data, with data from randomized trials. While numerous frequentist and Bayesian methods, such as the test-then-pool and Meta-Analytic-Predictive prior, have been developed to account for potential disagreement between the external control and randomized data, they cannot ensure strict type I error rate control. However, these methods can reduce biases stemming from systematic diff…

Machine learning-accelerated search of superconductors in B-C-N based compounds and R3Ni2O7-type nickelates
Xiaoying Li, Wenqian Tu, Run Lv, Li'e Liu, Dingfu Shao, Yuping Sun, Wenjian Lu
https://arxiv.org/abs/2509.03081

Machine learning-accelerated search of superconductors in B-C-N based compounds and R3Ni2O7-type nickelates
Superconductor research has traditionally depended on experiments and theoretical approaches. However, the rapid advancement of data-driven methods and machine learning (ML) has opened avenues for accelerating superconductor discovery. Here, we integrated ML with density functional theory (DFT) calculations to efficiently screen conventional B-C-N based superconductors and identify potential high-TC candidates among R3Ni2O7-type bilayer nickelates. We identified 12 new binary and ternary B-C-N …

from my link log —
Byte type: supporting raw data copies in LLVM IR.
https://blog.llvm.org/posts/2025-08-29-gsoc-byte-type/
saved 2025-09-09

Machine-interpretable Engineering Design Standards for Valve Specification
Anders Gjerver, Rune Frostad, Vedrana Barisic, Melinda Hodkiewicz, Caitlin Woods, Mihaly Fekete, Arild Braathen Torjusen, Johan Wilhelm Kluwer
https://arxiv.org/abs/2510.01736

Machine-interpretable Engineering Design Standards for Valve Specification
Engineering design processes use technical specifications and must comply with standards. Product specifications, product type data sheets, and design standards are still mainly document-centric despite the ambition to digitalize industrial work. In this paper, we demonstrate how to transform information held in engineering design standards into modular, reusable, machine-interpretable ontologies and use the ontologies in quality assurance of the plant design and equipment selection process. We…

Replaced article(s) found for stat.ML. https://arxiv.org/list/stat.ML/new
[2/2]:
- A Deterministic Information Bottleneck Method for Clustering Mixed-Type Data
Efthymios Costa, Ioanna Papatsouma, Angelos Markos

Non-Existence of Solutions for a Fourth-Order Structurally Damped Equation Under Nonlinear Memory Effect
Luis Gustavo Longen
https://arxiv.org/abs/2509.06671 https://

Non-Existence of Solutions for a Fourth-Order Structurally Damped Equation Under Nonlinear Memory Effect
In this paper, we study a mixed wave-plate equation with rotational inertia, fractional damping and memory non-linearity. This research is a non-existence counterpart to a paper by D'Abbicco and Longen, in search of the critical exponent for the global in-time existence of small data solutions to the Cauchy problem for a mixed wave-plate equation, with a rotational inertia and a non-integer dissipation term and a memory-type non-linearity. We employ a modified test function argument to show tha…

Pure Data Spaces
Saul Youssef
https://arxiv.org/abs/2508.14271 https://arxiv.org/pdf/2508.14271

Pure Data Spaces
In a previous work, "pure data" is proposed as an axiomatic foundation for mathematics and computing, based on "finite sequence" as the foundational concept rather than based on logic or type. Within this framework, objects with mathematical meaning are "data" and collections of mathematical objects must then be associative data, called a "space." A space is then the basic collection in this framework analogous to sets in Set Theory or objects in Category Theory. A theory of spaces is developed…

Fast and Accurate SVD-Type Updating in Streaming Data
Johannes J. Brust, Michael A. Saunders
https://arxiv.org/abs/2509.02840 https://arxiv.org/pdf/2509.02…

Fast and Accurate SVD-Type Updating in Streaming Data
For a datastream, the change over a short interval is often of low rank. For high throughput information arranged in matrix format, recomputing an optimal SVD approximation after each step is typically prohibitive. Instead, incremental and truncated updating strategies are used, which may not scale for large truncation ranks. Therefore, we propose a set of efficient new algorithms that update a bidiagonal factorization, and which are similarly accurate as the SVD methods. In particular, we deve…

Exploration of Parameters in f(R,T) Gravity and Comparison with Type Ia Supernovae Data
Vincent R. Siggia, Eric D. Carlson, P. Lee Pryor
https://arxiv.org/abs/2508.15014 https:/…

Exploration of Parameters in f(R,T) Gravity and Comparison with Type Ia Supernovae Data
The expansion of the Universe in $f(R,T)$ gravity is studied. We consider functions of the form $f(R,T)=R+λT^ε$ where $ε<1$. We find that for all models with $ε<0$, the Universe transitions to exponential growth at late times, just as it does in the standard cosmological model, which corresponds to $ε=0$. It also fits the type Ia supernova data slightly better than the standard cosmological model, without increasing the number of parameters of the theory. In contrast, the fits for $ε>0$ r…

Speaking of new tools: Here's some other open-ended and work-in-progress tooling I published recently:
Assorted CLI utilities for data wrangling & media conversion
https://codeberg.org/thi.ng/thing-tools
This is (will be) a Swiss-army knife type multi-tool for frequent little t…

thing-tools
Assorted CLI utilities for data wrangling, dataviz & media conversion

Decision Procedure for A Theory of String Sequences
Denghang Hu, Taolue Chen, Philipp R\"ummer, Fu Song, Zhilin Wu
https://arxiv.org/abs/2509.00948 https://

Decision Procedure for A Theory of String Sequences
The theory of sequences, supported by many SMT solvers, can model program data types including bounded arrays and lists. Sequences are parameterized by the element data type and provide operations such as accessing elements, concatenation, forming sub-sequences and updating elements. Strings and sequences are intimately related; many operations, e.g., matching a string according to a regular expression, splitting strings, or joining strings in a sequence, are frequently used in string-manipulat…

Playing CHESS with stars. I. Search for similar stars in large spectroscopic data sets
J. E. Mart\'inez Fern\'andez, S. \"Ozdemir, R. Smiljanic, M. L. L. Dantas, A. R. da Silva
https://arxiv.org/abs/2509.19443

Playing CHESS with stars. I. Search for similar stars in large spectroscopic data sets
Context: Massive amounts of spectroscopic data obtained by stellar surveys are feeding an ongoing revolution in our knowledge of stellar and Galactic astrophysics. Analysing these data sets to extract the best possible astrophysical parameters on short time scales represents a considerable challenge. Aims: The differential analysis method is known to return the most precise results in the spectroscopic analyses of F-, G-, and K-type stars. However, it can only be applied to stars with similar p…

Generalized Encrypted Traffic Classification Using Inter-Flow Signals
Federica Bianchi, Edoardo Di Paolo, Angelo Spognardi
https://arxiv.org/abs/2508.21558 https://

Generalized Encrypted Traffic Classification Using Inter-Flow Signals
In this paper, we present a novel encrypted traffic classification model that operates directly on raw PCAP data without requiring prior assumptions about traffic type. Unlike existing methods, it is generalizable across multiple classification tasks and leverages inter-flow signals - an innovative representation that captures temporal correlations and packet volume distributions across flows. Experimental results show that our model outperforms well-established methods in nearly every classifi…

Hidden massive eclipsing binaries in red supergiant systems: The hierarchical triple system KQ Puppis and other candidates
D. Jadlovsk\'y, L. Moln\'ar, A. Ercolino, M. Bernini-Peron, A. M\'erand, J. Krti\v{c}ka, L. Wang, R. Z. \'Ad\'am, D. Baade, G. Gonz\'alez-Tor\`a, T. Granzer, J. Jan\'ik, J. Kol\'a\v{r}, K. Kravchenko, N. Langer, L. M. Oskinova, D. Pauli, V. Ramachandran, A. C. Rubio, A. A. C. Sander, K. G. Strassmeier, M. Weber, M. Wittkowski, R. Bra…

Hidden massive eclipsing binaries in red supergiant systems: The hierarchical triple system KQ Puppis and other candidates
The majority of massive stars are part of binary systems that may interact during their evolution. This has important consequences for systems in which one star develops into a Red supergiant (RSG); however, not many RSGs are known binaries. We aim to better constrain the properties of some of the known RSGs in binaries. We first focus on the VV Cephei type RSG KQ Pup (RSG+B-type companion, orbital period of 26 yr), where we have enough data to constrain the system's properties. We use archiv…

Crosslisted article(s) found for cs.MS. https://arxiv.org/list/cs.MS/new
[1/1]:
- Fast and Accurate SVD-Type Updating in Streaming Data
Johannes J. Brust, Michael A. Saunders

FreqDebias: Towards Generalizable Deepfake Detection via Consistency-Driven Frequency Debiasing
Hossein Kashiani, Niloufar Alipour Talemi, Fatemeh Afghah
https://arxiv.org/abs/2509.22412

FreqDebias: Towards Generalizable Deepfake Detection via Consistency-Driven Frequency Debiasing
Deepfake detectors often struggle to generalize to novel forgery types due to biases learned from limited training data. In this paper, we identify a new type of model bias in the frequency domain, termed spectral bias, where detectors overly rely on specific frequency bands, restricting their ability to generalize across unseen forgeries. To address this, we propose FreqDebias, a frequency debiasing framework that mitigates spectral bias through two complementary strategies. First, we introduc…

Characterizing the host galaxies and delay times of Ca-rich gap transients vs 91bg-like SNe and normal Type Ia SNe
Peter Scherbak, Abigail Polin, Mansi Kasliwal, Kishaley De, Peter Behroozi, Dave Cook, Wynn Jacobson-Gal\'an
https://arxiv.org/abs/2509.25577

Characterizing the host galaxies and delay times of Ca-rich gap transients vs 91bg-like SNe and normal Type Ia SNe
Calcium-rich gap transients are a faint, fast-evolving class of supernovae that show strong nebular Ca emission lines. Their progenitor systems are uncertain, but they are often associated with old and quiescent host galaxies. In this work, we compare the properties of the hosts of hydrogen-poor Ca-rich gap transients to the hosts of 3 other classes of supernova (SNe): normal Type Ia, 91bg-like, and Type II. We use data from the Zwicky Transient Facility (ZTF) Census of the Local Universe (CLU)…

The Impact of Device Type, Data Practices, and Use Case Scenarios on Privacy Concerns about Eye-tracked Augmented Reality in the United States and Germany
Efe Bozkir, Babette B\"uhler, Xiaoyuan Wu, Enkelejda Kasneci, Lujo Bauer, Lorrie Faith Cranor
https://arxiv.org/abs/2509.09285

The Impact of Device Type, Data Practices, and Use Case Scenarios on Privacy Concerns about Eye-tracked Augmented Reality in the United States and Germany
Augmented reality technology will likely be prevalent with more affordable head-mounted displays. Integrating novel interaction modalities such as eye trackers into head-mounted displays could lead to collecting vast amounts of biometric data, which may allow inference of sensitive user attributes like health status or sexual preference, posing privacy issues. While previous works broadly examined privacy concerns about augmented reality, ours is the first to extensively explore privacy concern…

Early warning of critical transitions: distinguishing tipping points from Turing destabilizations
Paul A. Sanders, Robbin Bastiaansen
https://arxiv.org/abs/2510.01959 https://…

Early warning of critical transitions: distinguishing tipping points from Turing destabilizations
Current early warning signs for tipping points often fail to distinguish between catastrophic shifts and less dramatic state changes, such as spatial pattern formation. This paper introduces a novel method that addresses this limitation by providing more information about the type of bifurcation being approached starting from a spatially homogeneous system state. This method relies on estimates of the dispersion relation from noisy spatio-temporal data, which reveals whether the system is appro…

So #Vanguard tries really hard to _disable_ any form of using a password manager to log into their site. Do they really believe that it is more secure for people to choose passwords that they can type?
I hate gut-feeling based security methods. Show me the data that this usability blocker has a measurable effect on security and that there aren't other options that don't have thes…

from my link log —
Row polymorphic programming.
https://www.stranger.systems/posts/by-slug/row-polymorphic-programming.html
saved 2025-07-14

Row Polymorphic Programming
Sometimes, especially when dealing with business logic, we have to deal with data that comes in from the real world, or elsewhere, naturally very messily typed, leading to nasty type signatures and messes of macros or code generation to build data structures from a schema. Row polymorphism can help us by abstracting over the fields contained in a record type in the type signature, letting us define records based on data, concatenate records together, and define functions that are generic across…

AI – I am here to help; would you like to chat?
 
 
Artificial Intelligence (AI) of one type of another is now a part of most of the applications and services we use on the Internet. In spite of AI’s helpful features, there are hidden dangers in most of the common AI applications and services. Most people are not aware that AI is not just being helpful – it is recording, storing and sharing information about our activities. This information can be helpful to autocrats in their…

Unsourced Random Access
Kirill Andreev, Pavel Rybin, Alexey Frolov
https://arxiv.org/abs/2509.25074 https://arxiv.org/pdf/2509.25074

Unsourced Random Access
Current wireless networks are designed to optimize spectral efficiency for human users, who typically require sustained connections for high-data-rate applications like file transfers and video streaming. However, these networks are increasingly inadequate for the emerging era of machine-type communications (MTC). With a vast number of devices exhibiting sporadic traffic patterns consisting of short packets, the grant-based multiple access procedures utilized by existing networks lead to signif…

Generalized promotion time cure model: A new modeling framework to identify cell-type-specific genes and improve survival prognosis
Zhi Zhao, Fatih Kizilaslan, Shixiong Wang, Manuela Zucknick
https://arxiv.org/abs/2509.01001

Generalized promotion time cure model: A new modeling framework to identify cell-type-specific genes and improve survival prognosis
Single-cell technologies provide an unprecedented opportunity for dissecting the interplay between the cancer cells and the associated tumor microenvironment, and the produced high-dimensional omics data should also augment existing survival modeling approaches for identifying tumor cell type-specific genes predictive of cancer patient survival. However, there is no statistical model to integrate multiscale data including individual-level survival data, multicellular-level cell composition data…

Investigating Document Type, Language, Publication Year, and Author Count Discrepancies Between OpenAlex and Web of Science
Philippe Mongeon, Madelaine Hare, Poppy Riddle, Summer Wilson, Geoff Krause, Rebecca Marjoram, R\'emi Toupin
https://arxiv.org/abs/2508.18620

Investigating Document Type, Language, Publication Year, and Author Count Discrepancies Between OpenAlex and Web of Science
Bibliometrics, whether used for research or research evaluation, relies on large multidisciplinary databases of research outputs and citation indices. The Web of Science (WoS) was the main supporting infrastructure of the field for more than 30 years until several new competitors emerged. OpenAlex, a bibliographic database launched in 2022, has distinguished itself for its openness and extensive coverage. While OpenAlex may reduce or eliminate barriers to accessing bibliometric data, one of the…

Quantitative Stability and Contraction Principles for Mean-Field G-SDEs
Yunfan Zhao, Xiaojing Chen, Wenwen Pan
https://arxiv.org/abs/2509.03439 https://arx…

Quantitative Stability and Contraction Principles for Mean-Field G-SDEs
We study mean-field stochastic differential equations (SDEs) driven by G-Brownian motion, extending recent work on existence and uniqueness by developing a full quantitative stability framework. Our main contribution is the construction of an intrinsic stability modulus that provides explicit bounds on the sensitivity of solutions with respect to perturbations in initial data (and, indirectly, coefficients). Using Bihari-Osgood type inequalities under G-expectation, we establish sharp continuit…

Sampling String Vacua Using Generative Models
Moritz Walden, Magdalena Larfors
https://arxiv.org/abs/2509.16029 https://arxiv.org/pdf/2509.16029

Sampling String Vacua Using Generative Models
We apply generative models to a key problem in the string compactification program, namely construction of type IIB string vacua. To this end, we make use of a Bayesian Flow Network, a generative model capable of handling discrete data, to generate flux vectors that give rise to type IIB vacua. Furthermore, we sample flux vacua that have certain desirable properties by employing a Transformer as a conditional generative model. Both models demonstrate good performance in finding flux vacua and t…

Synthetic Data Generation for Classifying Electrophysiological and Morpho-Electrophysiological Neurons from Mouse Visual Cortex
Xavier Vasques, Laura Cif
https://arxiv.org/abs/2508.06514

Synthetic Data Generation for Classifying Electrophysiological and Morpho-Electrophysiological Neurons from Mouse Visual Cortex
The accurate classification of neuronal cell types is central to decoding brain function, yet remains hindered by data scarcity and cellular heterogeneity. Here, we benchmarked classical and deep generative synthetic data augmentation strategies -- including SMOTE, GANs, VAEs, Normalizing Flows, and DDPMs -- for supervised classification of both electrophysiological (e-type) and morpho-electrophysiological (mee-type) neuron types from the mouse visual cortex. Using a curated dataset annotated w…

Currently listening to Marcos Viera at TyDe 2025:
Representing Data Structures with Invariants in Haskell: the cases of BST and AVL
https://conf.researchr.org/details/icfp-splash-20…

From Stoplights to On-Ramps: A Comprehensive Set of Crash Rate Benchmarks for Freeway and Surface Street ADS Evaluation
John M. Scanlon, Timothy L McMurry, Yin-Hsiu Chen, Kristofer D. Kusano, Trent Victor
https://arxiv.org/abs/2508.19425

From Stoplights to On-Ramps: A Comprehensive Set of Crash Rate Benchmarks for Freeway and Surface Street ADS Evaluation
This paper presents crash rate benchmarks for evaluating US-based Automated Driving Systems (ADS) for multiple urban areas. The purpose of this study was to extend prior benchmarks focused only on surface streets to additionally capture freeway crash risk for future ADS safety performance assessments. Using publicly available police-reported crash and vehicle miles traveled (VMT) data, the methodology details the isolation of in-transport passenger vehicles, road type classification, and crash …

🧩 Works beautifully with immutability (readonly) and plays nice with DTOs or Spatie Data objects if you want extra transformations.
🔥 Clean configs = less debugging, fewer typos, more joy.
👉 Read the full write-up here:
https://cosmastech.com/2025/08/23/crea

MMM: Clustering Multivariate Longitudinal Mixed-type Data
Francesco Amato, Julien Jacques
https://arxiv.org/abs/2509.12166 https://arxiv.org/pdf/2509.12166…

MMM: Clustering Multivariate Longitudinal Mixed-type Data
Multivariate longitudinal data of mixed-type are increasingly collected in many science domains. However, algorithms to cluster this kind of data remain scarce, due to the challenge to simultaneously model the within- and between-time dependence structures for multivariate data of mixed kind. We introduce the Mixture of Mixed-Matrices (MMM) model: reorganizing the data in a three-way structure and assuming that the non-continuous variables are observations of underlying latent continuous variab…

Blowup of solutions for compressible viscoelastic fluid
S\'ebastien Boyaval (MATHERIALS, LHSV), Na Wang (BITSU), Yuxi Hu (CUMT)
https://arxiv.org/abs/2509.04924 https://

Blowup of solutions for compressible viscoelastic fluid
We prove finite-time blowup of classical solutions for the compressible Upper Convective Maxwell (UCM) viscoelastic fluid system. By establishing a key energy identity and adapting Sideris' method for compressible flows, we derive a Riccati-type inequality for a momentum functional. For initial data with compactly supported perturbations satisfying a sufficiently large condition, all classical solutions lose regularity in finite time. This constitutes the first rigorous blowup result for multid…

Machine-Learning Driven Load Shedding to Mitigate Instability Attacks in Power Grids
Justin Tackett, Benjamin Francis, Luis Garcia, David Grimsman, Sean Warnick
https://arxiv.org/abs/2509.26532

Machine-Learning Driven Load Shedding to Mitigate Instability Attacks in Power Grids
Every year critical infrastructure becomes more complex and we grow to rely on it more and more. With this reliance, it becomes an attractive target for cyberattacks from sophisticated actors, with one of the most attractive targets being the power grid. One class of attacks, instability attacks, is a newer type of attack that has relatively few protections developed. We present a cost effective, data-driven approach to training a supervised machine learning model to retrofit load shedding deci…

An invariant measure of deviation from Petrov type D at the level of initial data
Edgar Gasperin, Jarrod L. Williams
https://arxiv.org/abs/2509.08021 https://

An invariant measure of deviation from Petrov type D at the level of initial data
In this article, we describe a simple covariant characterisation of initial data sets which give rise to Petrov type D vacuum spacetime developments. As an application, we derive an integral invariant which, when restricted to the appropriate class of asymptotically Euclidean initial data sets, vanishes if and only if the initial dataset is isometric to initial data for the Kerr spacetime. As such, the invariant can be considered a measure of non-Kerrness on such initial data sets. In contrast …

ALMA Reveals an Eccentricity Gradient in the Fomalhaut Debris Disk
Joshua B. Lovell, Elliot M. Lynch, Jay Chittidi, Antranik A. Sefilian, Sean M. Andrews, Grant M. Kennedy, Meredith MacGregor, David J. Wilner, Mark C. Wyatt
https://arxiv.org/abs/2509.02884

ALMA Reveals an Eccentricity Gradient in the Fomalhaut Debris Disk
We present evidence of a negative eccentricity gradient in the debris disk of the nearby A-type main sequence star, Fomalhaut. Fitting to the high-resolution, archival ALMA 1.32 mm continuum data for Fomalhaut (with a synthesised angular resolution of $0.76{\times}0.55''$; 4-6\,au), we present a model that describes the bulk properties of the disk (semi-major axis, width, and geometry) and its asymmetric morphology. The best-fit model incorporates a forced eccentricity gradient that varies with…

The Eclipsing $\gamma$ Doradus Star V421 Pegasi
Jae Woo Lee
https://arxiv.org/abs/2510.00337 https://arxiv.org/pdf/2510.00337

The Eclipsing $γ$ Doradus Star V421 Pegasi
We present high-precision TESS photometry of V421 Peg (TIC 301747091), an early F-type eclipsing binary containing a candidate $γ$ Dor component. The observed short-cadence data allow the detection of pulsation signals, along with revision of the fundamental properties of the component stars. Detailed binary modeling indicated that the program target is a partially-eclipsing detached system in a circular orbit and that both components are currently in super-synchronous states. The radii of eac…

SNELLS-HD I: a first look at the stellar properties of the massive strong-lens galaxy SNL-1 with 50 pc resolution
Adriano Poci, Russell J. Smith
https://arxiv.org/abs/2509.01732

SNELLS-HD I: a first look at the stellar properties of the massive strong-lens galaxy SNL-1 with 50 pc resolution
We present a dynamical and chemical study of the centre of a massive early-type strong-lens galaxy ESO286-G022 (SNL-1). Analysing new data obtained through the adaptive-optics-assisted Narrow-Field Mode of VLT/MUSE, we aim to measure the mass distribution and internal properties of SNL-1 at $\sim 50\ {\rm pc}$ resolution. In particular, we aim to address the tension in the reported IMF measurements of SNL-1 between strong-lens/dynamical and spectral-fitting techniques. We fit a triaxial orbital…

Energy critical fourth-order Schr\"odinger equation system with power-type nonlinearities in the radial case
Maicon Hespanha, Renzo Scarpelli
https://arxiv.org/abs/2509.04428

Energy critical fourth-order Schrödinger equation system with power-type nonlinearities in the radial case
In this paper, we study a system of focusing fourth-order Schrödinger equations in the energy-critical setting with radial initial data and general power-type nonlinearities. The main idea is to generalize the analysis of such systems: we first establish several hypotheses on the nonlinearities and prove their implications. These implications are then used to establish a local well-posedness result in $H^2(\mathbb{R}^d)$ and and to prove the existence of ground state solutions. Using a virial …

Large Language Model Hacking: Quantifying the Hidden Risks of Using LLMs for Text Annotation
Joachim Baumann, Paul R\"ottger, Aleksandra Urman, Albert Wendsj\"o, Flor Miriam Plaza-del-Arco, Johannes B. Gruber, Dirk Hovy
https://arxiv.org/abs/2509.08825

Large Language Model Hacking: Quantifying the Hidden Risks of Using LLMs for Text Annotation
Large language models (LLMs) are rapidly transforming social science research by enabling the automation of labor-intensive tasks like data annotation and text analysis. However, LLM outputs vary significantly depending on the implementation choices made by researchers (e.g., model selection, prompting strategy, or temperature settings). Such variation can introduce systematic biases and random errors, which propagate to downstream analyses and cause Type I, Type II, Type S, or Type M errors. W…

Type I II Seesaw Model in light of the New Neutrino Oscillation Measurements
Maria Aguilar, Juan Carlos Helo, Toshihiko Ota, Farinaldo S. Queiroz, David Suarez, Amanda Rodr\'iguez
https://arxiv.org/abs/2509.23508

Type I + II Seesaw Model in light of the New Neutrino Oscillation Measurements
Global analysis of neutrino oscillation data slightly favors normal mass ordering. In this work, we investigate an extended scalar sector that naturally gives rise to a type I + II seesaw mechanism after spontaneous symmetry breaking and explore the interplay between collider physics and lepton flavor violation, adopting normal ordering. In particular, we focus on the rare muon decays $μ\rightarrow e γ$ and $μ\rightarrow 3e$ and the same-sign dilepton searches at LHC, a canonical signature o…

MoPE: A Mixture of Password Experts for Improving Password Guessing
Mingjian Duan, Ming Xu, Shenghao Zhang, Jiaheng Zhang, Weili Han
https://arxiv.org/abs/2509.16558 https://

MoPE: A Mixture of Password Experts for Improving Password Guessing
Textual passwords remain a predominant authentication mechanism in web security. To evaluate their strength, existing research has proposed several data-driven models across various scenarios. However, these models generally treat passwords uniformly, neglecting the structural differences among passwords. This typically results in biased training that favors frequent password structural patterns. To mitigate the biased training, we argue that passwords, as a type of complex short textual data, …

Bayesian Anomaly Detection for Ia Cosmology: Automating SALT3 Data Curation
S. A. K. Leeney, W. J. Handley, H. T. J. Bevins, E. de Lera Acedo
https://arxiv.org/abs/2509.13394 ht…

Bayesian Anomaly Detection for Ia Cosmology: Automating SALT3 Data Curation
Precision cosmology with Type Ia supernovae (SNe Ia) requires robust quality control of large, heterogeneous datasets. Current data processing often relies on manual, subjective rejection of photometric data, a practice that is not scalable for forthcoming surveys like the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST). We present a Bayesian framework that automates this step by integrating anomaly detection directly into the light curve fitting process. While the framework …

Global-Local Dirichlet Processes for Identifying Pan-Cancer Subpopulations Using Both Shared and Cancer-Specific Data
Arhit Chakrabarti, Yang Ni, Debdeep Pati, Bani K. Mallick
https://arxiv.org/abs/2509.22884

Global-Local Dirichlet Processes for Identifying Pan-Cancer Subpopulations Using Both Shared and Cancer-Specific Data
We consider the problem of clustering grouped data for which the observations may include group-specific variables in addition to the variables that are shared across groups. This type of data is common in cancer genomics where the molecular information is usually accompanied by cancer-specific clinical information. Existing grouped clustering methods only consider the shared variables, thereby ignoring valuable information from the cancer-specific variables. To allow for these cancer-specific …

Retrieve-and-Verify: A Table Context Selection Framework for Accurate Column Annotations
Zhihao Ding, Yongkang Sun, Jieming Shi
https://arxiv.org/abs/2508.17203 https://

Retrieve-and-Verify: A Table Context Selection Framework for Accurate Column Annotations
Tables are a prevalent format for structured data, yet their metadata, such as semantic types and column relationships, is often incomplete or ambiguous. Column annotation tasks, including Column Type Annotation (CTA) and Column Property Annotation (CPA), address this by leveraging table context, which are critical for data management. Existing methods typically serialize all columns in a table into pretrained language models to incorporate context, but this coarse-grained approach often degrad…

Benchmarking foundation models for hyperspectral image classification: Application to cereal crop type mapping
Walid Elbarz, Mohamed Bourriz, Hicham Hajji, Hamd Ait Abdelali, Fran\c{c}ois Bourzeix
https://arxiv.org/abs/2510.11576

Benchmarking foundation models for hyperspectral image classification: Application to cereal crop type mapping
Foundation models are transforming Earth observation, but their potential for hyperspectral crop mapping remains underexplored. This study benchmarks three foundation models for cereal crop mapping using hyperspectral imagery: HyperSigma, DOFA, and Vision Transformers pre-trained on the SpectralEarth dataset (a large multitemporal hyperspectral archive). Models were fine-tuned on manually labeled data from a training region and evaluated on an independent test region. Performance was measured w…

LAMOST J064137.77 045743.8: A New Binary of an A7-type Pulsating Subgiant and an M-type Red Dwarf
Yanhui Chen, Chaomi Duan, Baokun Sun
https://arxiv.org/abs/2510.10164 https://

LAMOST J064137.77+045743.8: A New Binary of an A7-type Pulsating Subgiant and an M-type Red Dwarf
With the progressive release of data from numerous sky surveys, humanity has entered the era of astronomical big data. Multi-wavelength, multi-method research is playing an increasingly crucial role. Binaries account for a substantial fraction of all stellar systems and research into binaries is of fundamental importance. LAMOST J064137.77+045743.8 has not yet been recorded in the SIMBAD astronomical database. We conducted a comprehensive analysis of LAMOST J064137.77+045743.8 using multi-band …

An ancient L- type family associated to (460) Scania in the Middle Main Belt as revealed by Gaia DR3 spectra
Roberto Balossi, Paolo Tanga, Marco Delbo, Alberto Cellino, Federica Spoto
https://arxiv.org/abs/2509.17642

An ancient L- type family associated to (460) Scania in the Middle Main Belt as revealed by Gaia DR3 spectra
Asteroid families are typically identified using hierarchical clustering methods (HCM) in the proper element phase space. However, these methods struggle with overlapping families, interlopers, and the detection of older structures. Spectroscopic data can help overcome these limitations. The Gaia Data Release 3 (DR3) contains reflectance spectra at visible wavelengths for 60,518 asteroids over the range between 374-1034 nm, representing a large sample that is well suited to studies of asteroid …

Generalization Bound for a General Class of Neural Ordinary Differential Equations
Madhusudan Verma, Manoj Kumar
https://arxiv.org/abs/2508.18920 https://a…

Generalization Bound for a General Class of Neural Ordinary Differential Equations
Neural ordinary differential equations (neural ODEs) are a popular type of deep learning model that operate with continuous-depth architectures. To assess how well such models perform on unseen data, it is crucial to understand their generalization error bounds. Previous research primarily focused on the linear case for the dynamics function in neural ODEs - Marion, P. (2023), or provided bounds for Neural Controlled ODEs that depend on the sampling interval Bleistein et al. (2023). In this wor…

A statistical study of type II outbursts of XRPs: Brighter accreting pulsars rotate faster
Shan-Shan Weng, Xiao-Tian Xu, Han-Long Peng, Yu-Jing Xu, Yan Zhang, Ying-Han Mao, Xiang-Dong Li, Jing-Zhi Yan, Qing-Zhong Liu
https://arxiv.org/abs/2509.21103

A statistical study of type II outbursts of XRPs: Brighter accreting pulsars rotate faster
X-ray pulsars (XRPs) consist of a magnetized neutron star (NS) and an optical donor star. The NS accretes matter from the donor star producing pulsed X-ray emission. In most cases the donor stars are Be stars, and accretion is episodic, that is, the NSs are generally X-ray dim, but occasionally experience outbursts. Here, we carry out a statistical study with the X-ray monitoring data, and obtain strong correlations between the spin periods of the NSs and the outburst parameters for the first t…

Sign and signed rank tests for paired functions
Mark J. Meyer
https://arxiv.org/abs/2509.24170 https://arxiv.org/pdf/2509.24170

Sign and signed rank tests for paired functions
Simple nonparametric tests for paired functional data are an understudied area, despite recent advances in similar tests for other types of functional data. While the sign test has received limited treatment, the signed rank-type test has not previously been examined. The aim of the present work is to develop and evaluate these types of tests for functional data. We derive a simple, theoretical framework for both sign and signed rank tests for pairs of functions. In particular, we demonstrate t…

Testing the Constancy of Type Ia Supernova Luminosities with Gaussian Process
Akshay Rana
https://arxiv.org/abs/2509.19494 https://arxiv.org/pdf/2509.19494…

Testing the Constancy of Type Ia Supernova Luminosities with Gaussian Process
Type Ia supernovae (SNe~Ia) are central to studies of cosmic expansion, under the assumption that their absolute magnitude $M_B$ does not evolve with redshift. Even small drifts in brightness can bias cosmological parameters such as $H_0$ and $w$. Here we test this assumption using a non-parametric Gaussian Process (GP) reconstruction of the expansion history from cosmic chronometer $H(z)$ data, which provides a model-independent baseline distance modulus, $μ_{\rm GP}(z)$. To propagate uncerta…

An efficient splitting iteration for a CDA-accelerated solver for incompressible flow problems
Victoria L. Fisher, Leo G. Rebholz, Duygu Vargun
https://arxiv.org/abs/2509.12547 …

An efficient splitting iteration for a CDA-accelerated solver for incompressible flow problems
We propose, analyze, and test an efficient splitting iteration for solving the incompressible, steady Navier-Stokes equations in the setting where partial solution data is known. The (possibly noisy) solution data is incorporated into a Picard-type solver via continuous data assimilation (CDA). Efficiency is gained over the usual Picard iteration through an algebraic splitting of Yosida-type that produces easier linear solves, and accuracy/consistency is shown to be maintained through the use o…

Neutrino phenomenology and Dark matter in a left-right asymmetric model with non-holomorphic modular $A_{4}$ group
Bhabana Kumar, Mrinal Kumar Das
https://arxiv.org/abs/2509.01205

Neutrino phenomenology and Dark matter in a left-right asymmetric model with non-holomorphic modular $A_{4}$ group
We present a model constructed within a non-supersymmetric framework capable of explaining both current neutrino oscillation data and the observed dark matter relic abundance. In this study, the Yukawa couplings are expressed as polyharmonic Maaß forms, and the non-supersymmetric left-right symmetric model is realized through the $Γ_{3}$ modular group, with neutrino masses generated via the Type II seesaw dominance mechanism. The analysis focuses on determining the neutrino oscillation parame…

Probing redshift-dependent systematics in the Hubble tension: Model-independent $H_0$ constraints from DESI R2
Tonghua Liu, Shuo Cao, Jieci Wang
https://arxiv.org/abs/2509.20898

Probing redshift-dependent systematics in the Hubble tension: Model-independent $H_0$ constraints from DESI R2
We present a model-independent determination of the Hubble constant ($H_0$) using the latest observational data from multiple cosmological probes. By combining baryon acoustic oscillation (BAO) measurements from the second data release of the Dark Energy Spectroscopic Instrument (DESI DR2), cosmic chronometer $H(z)$ data, and the Pantheon Plus Type Ia supernova (SN Ia) sample, we reconstruct the cosmic expansion history through Gaussian process regression without assuming a specific cosmologica…

Defending Diffusion Models Against Membership Inference Attacks via Higher-Order Langevin Dynamics
Benjamin Sterling, Yousef El-Laham, M\'onica F. Bugallo
https://arxiv.org/abs/2509.14225

Defending Diffusion Models Against Membership Inference Attacks via Higher-Order Langevin Dynamics
Recent advances in generative artificial intelligence applications have raised new data security concerns. This paper focuses on defending diffusion models against membership inference attacks. This type of attack occurs when the attacker can determine if a certain data point was used to train the model. Although diffusion models are intrinsically more resistant to membership inference attacks than other generative models, they are still susceptible. The defense proposed here utilizes criticall…

High Proper Motion Discoveries from the UKIRT Hemisphere Survey
Wings Zhang, Adam C. Schneider, Thomas P. Bickle, Adam J. Burgasser, Emma Softich, Federico Marocco, Daniella Bardalez Gagliuffi, Jacqueline K. Faherty, Aaron M. Meisner, J. Davy Kirkpatrick, Marc J. Kuchner, Martin Kabatnik, Frank Kiwy, Arttu Sainio, J\"org Sch\"umann, Karl Selg-Mann, Nikolaj Stevnbak Andersen, Bruce Baller, Paul Beaulieu, John Bell, Dan Caselden, Guillaume Colin, Alexandru Dereveanco, Christoph…

High Proper Motion Discoveries from the UKIRT Hemisphere Survey
We used the third data release of the UKIRT Hemisphere Survey to locate previously unrecognized high proper motion objects. We identify a total of 127 new discoveries with total proper motions $\gtrsim$300 mas yr$^{-1}$. A significant fraction of these sources with counterparts in the Gaia DR3 catalog are found to be distant ($>$100 pc) low-mass stars, where their large tangential velocities and placement on color-magnitude diagrams suggest that they are likely low-metallicity M-type subdwarfs.…

Learning to Detect Label Errors by Making Them: A Method for Segmentation and Object Detection Datasets
Sarina Penquitt, Tobias Riedlinger, Timo Heller, Markus Reischl, Matthias Rottmann
https://arxiv.org/abs/2508.17930

Learning to Detect Label Errors by Making Them: A Method for Segmentation and Object Detection Datasets
Recently, detection of label errors and improvement of label quality in datasets for supervised learning tasks has become an increasingly important goal in both research and industry. The consequences of incorrectly annotated data include reduced model performance, biased benchmark results, and lower overall accuracy. Current state-of-the-art label error detection methods often focus on a single computer vision task and, consequently, a specific type of dataset, containing, for example, either …

Stable and practical semi-Markov modelling of intermittently-observed data
Christopher Jackson
https://arxiv.org/abs/2508.20949 https://arxiv.org/pdf/2508.…

Stable and practical semi-Markov modelling of intermittently-observed data
Multi-state models are commonly used for intermittent observations of a state over time, but these are generally based on the Markov assumption, that transition rates are independent of the time spent in current and previous states. In a semi-Markov model, the rates can depend on the time spent in the current state, though available methods for this are either restricted to specific state structures or lack general software. This paper develops the approach of using a "phase-type" distribution …

Data Assimilation in Large Eddy Simulation: Addressing Model-Observation Mismatch from Navier-Stokes Data
Adam Larios, Ali Pakzad, Nicholas White
https://arxiv.org/abs/2508.07492

Data Assimilation in Large Eddy Simulation: Addressing Model-Observation Mismatch from Navier-Stokes Data
In atmospheric and turbulent flow modeling, Large Eddy Simulation (LES) is often used to reduce computational cost, while observational data typically originates from the underlying physical system. Motivated by this setting, we study a continuous data assimilation (CDA) algorithm applied to a Smagorinsky/Ladyzhenskaya-type LES model, in which the observational data is generated from the full Navier--Stokes equations (NSE). In the two-dimensional setting, we establish global well-posedness of t…

Updated observational constraints on $\phi$CDM dynamical dark energy cosmological models
Chan-Gyung Park, Bharat Ratra
https://arxiv.org/abs/2509.25812 https://

Updated observational constraints on $ϕ$CDM dynamical dark energy cosmological models
We present updated observational constraints on the spatially flat $ϕ$CDM model, where dark energy is described by a minimally coupled scalar field $ϕ$ with an inverse power-law potential $V=V_0 ϕ^{-α}$. Using Planck 2018 CMB temperature, polarization (P18), and lensing power spectra (lensing), along with a compilation of non-CMB data including baryon acoustic oscillation, type Ia supernova, Hubble parameter, and growth rate measurements, we constrain $ϕ$CDM and $ϕ$CDM+$A_L$ models where …

Strichartz estimates for higher order Schr\"odinger equations with Partial regular initial data
Vishvesh Kumar, Shyam Swarup Mondal, Iswarya Sitiraju, Manli Song
https://arxiv.org/abs/2508.15670

Strichartz estimates for higher order Schrödinger equations with Partial regular initial data
In this paper, we establish refined Strichartz estimates for higher-order Schrödinger equations with initial data exhibiting partial regularity. By partial regularity, we mean that the initial data are not required to have full Sobolev regularity but only regularity with respect to a subset of the spatial variables. As an application of these estimates, we investigate the well-posedness of nonlinear Schrödinger equations with power-type nonlinearities. In addition, we extend our analysis to t…

Updated constraints on interacting dark energy: A comprehensive analysis using multiple CMB probes, DESI DR2, and supernovae observations
Tian-Nuo Li, Guo-Hong Du, Yun-He Li, Yichao Li, Jia-Le Ling, Jing-Fei Zhang, Xin Zhang
https://arxiv.org/abs/2510.11363

Updated constraints on interacting dark energy: A comprehensive analysis using multiple CMB probes, DESI DR2, and supernovae observations
Recent DESI baryon acoustic oscillation (BAO) measurements, combined with Planck cosmic microwave background (CMB) data and DESY5 type Ia supernova (SN) data, indicate a significant deviation from $Λ$CDM, which seems to suggest that this deviation can be explained by an interaction between dark energy and dark matter. In this work, we perform a comprehensive analysis by utilizing the latest DESI DR2 BAO data in conjunction with CMB data from ACT, SPT, Planck, and WMAP, along with SN data from …

Probing the H0 Tension with Holographic Dark Energy in Unimodular Gravity: Insights from DESI DR2
Francisco Plaza, Gabriel Le\'on, Lucila Kraiselburd
https://arxiv.org/abs/2508.21175

Probing the H0 Tension with Holographic Dark Energy in Unimodular Gravity: Insights from DESI DR2
Motivated by the recent baryon acoustic oscillation measurements of DESI DR2 collaboration, this works presents an extended analysis of a cosmological model based on holographic dark energy within the framework of Unimodular Gravity. We probe the model with an extensive set of observations: cosmic chronometers, Pantheon Plus$+$SH0ES Type Ia supernovae, DESI DR2 BAO distances, quasar X-ray/UV fluxes (two independent calibrations), and Planck 2018 CMB data. The results are analyzed to assess the …

Comparison Principle, A.B.P.-type estimates for solutions of quasi-linear elliptic equations in non-divergence form and some implications
Junior da S. Bessa, Reshmi Biswas, Jo\~ao Vitor da Silva, Ginaldo S\'a, Makson Santos
https://arxiv.org/abs/2508.18495

Comparison Principle, A.B.P.-type estimates for solutions of quasi-linear elliptic equations in non-divergence form and some implications
In this work, we establish global gradient estimates to solutions of quasilinear elliptic models in non-divergence form with general degeneracy law and a Hamiltonian term, given by $$ -Ψ(x, |\nabla u|)Δ_p^{\mathrm{N}}u(x)+\mathscr{H}(x,\nabla u)=f(x) \quad \mathrm{in} \quad Ω, \quad \mathrm{for} \,\,\,1

On the Fermi-Dirac-type Fisher information
Yuzhe Zhu
https://arxiv.org/abs/2508.15054 https://arxiv.org/pdf/2508.15054

On the Fermi-Dirac-type Fisher information
We consider kinetic models for Fermi-Dirac-like particles obeying the exclusion principle. A generalized notion of Fisher information, tailored to kinetic equations of Fermi-Dirac-Fokker-Planck type, is introduced via the associated entropy dissipation identity. We show that, subject to a suitable upper bound on the initial data, this quantity decreases along solutions of the Fermi-Dirac-Fokker-Planck equation, while monotonicity can fail in the absence of such a bound. We also discuss the time…