Tootfinder

PIC12F683 sample 2H6, after 14 HF etch cycles and a clean.
This sample has now been imaged 30 times, ranging from fresh after decap to the current state, after each etch, after cleaning passes to remove loose debris, and sometimes at both 20x and 100x in the same state.
This sample is now mostly at via1, but there's still upper layer visible in the seal ring and in the analog IPs.
It's now imaging at 100x. Things go slow because a full focus-stacked 100x image is 10…

Sample-Efficient Online Control Policy Learning with Real-Time Recursive Model Updates
Zixin Zhang, James Avtges, Todd D. Murphey
https://arxiv.org/abs/2509.08241 https://

Sample-Efficient Online Control Policy Learning with Real-Time Recursive Model Updates
Data-driven control methods need to be sample-efficient and lightweight, especially when data acquisition and computational resources are limited -- such as during learning on hardware. Most modern data-driven methods require large datasets and struggle with real-time updates of models, limiting their performance in dynamic environments. Koopman theory formally represents nonlinear systems as linear models over observables, and Koopman representations can be determined from data in an optimizat…

Uncertainty Estimation using Variance-Gated Distributions
H. Martin Gillis, Isaac Xu, Thomas Trappenberg
https://arxiv.org/abs/2509.08846 https://arxiv.org…

Uncertainty Estimation using Variance-Gated Distributions
Evaluation of per-sample uncertainty quantification from neural networks is essential for decision-making involving high-risk applications. A common approach is to use the predictive distribution from Bayesian or approximation models and decompose the corresponding predictive uncertainty into epistemic (model-related) and aleatoric (data-related) components. However, additive decomposition has recently been questioned. In this work, we propose an intuitive framework for uncertainty estimation a…

OSCAR: Orthogonal Stochastic Control for Alignment-Respecting Diversity in Flow Matching
Jingxuan Wu, Zhenglin Wan, Xingrui Yu, Yuzhe Yang, Bo An, Ivor Tsang
https://arxiv.org/abs/2510.09060

OSCAR: Orthogonal Stochastic Control for Alignment-Respecting Diversity in Flow Matching
Flow-based text-to-image models follow deterministic trajectories, forcing users to repeatedly sample to discover diverse modes, which is a costly and inefficient process. We present a training-free, inference-time control mechanism that makes the flow itself diversity-aware. Our method simultaneously encourages lateral spread among trajectories via a feature-space objective and reintroduces uncertainty through a time-scheduled stochastic perturbation. Crucially, this perturbation is projected …

SAGE: Sample-Aware Guarding Engine for Robust Intrusion Detection Against Adversarial Attacks
Jing Chen, Onat Gungor, Zhengli Shang, Tajana Rosing
https://arxiv.org/abs/2509.08091

SAGE: Sample-Aware Guarding Engine for Robust Intrusion Detection Against Adversarial Attacks
The rapid proliferation of the Internet of Things (IoT) continues to expose critical security vulnerabilities, necessitating the development of efficient and robust intrusion detection systems (IDS). Machine learning-based intrusion detection systems (ML-IDS) have significantly improved threat detection capabilities; however, they remain highly susceptible to adversarial attacks. While numerous defense mechanisms have been proposed to enhance ML-IDS resilience, a systematic approach for selecti…

Universality in the velocity jump in the crack propagation observed for food-wrapping films for daily use
Aoi Nohara, Ko Okumura
https://arxiv.org/abs/2509.09347 https://…

Universality in the velocity jump in the crack propagation observed for food-wrapping films for daily use
The velocity jump found in the crack propagation for rubbers has been a powerful tool for developing tough rubber materials. Although it is suggested by a theory that the jump could be observed widely for viscoelastic materials, the report on a clear jump is very limited and, even in such a case, reproducibility is low, except for elastomers. Here, we use a mundane food-wrapping film as a sample and observe the crack propagation velocity with pulling the sample at a constant speed in the direct…

Generalized Taylor's Law for Dependent and Heterogeneous Heavy-Tailed Data
Pok Him Cheng, Joel E. Cohen, Hok Kan Ling, Sheung Chi Phillip Yam
https://arxiv.org/abs/2510.09562

Generalized Taylor's Law for Dependent and Heterogeneous Heavy-Tailed Data
Taylor's law, also known as fluctuation scaling in physics and the power-law variance function in statistics, is an empirical pattern widely observed across fields including ecology, physics, finance, and epidemiology. It states that the variance of a sample scales as a power function of the mean of the sample. We study generalizations of Taylor's law in the context of heavy-tailed distributions with infinite mean and variance. We establish the probabilistic limit and analyze the associated con…

> Cambridge’s preservationists don’t just mount disks and hope for the best; they sample the raw magnetic signal itself. Specialized hardware, such as the KryoFlux and open-hardware Greaseweazle interfaces, captures the flux transitions — the tiny changes in polarity that encode data — and reconstructs the file structure later in software.

Cambridge University launches project to rescue data trapped on old floppy disks
Cambridge’s 'Future Nostalgia' project is racing to save decades of digital history from vanishing floppy disks.

**"NASA will hold a press conference to discuss an enigmatic Martian rock that contains possible biosignatures.**"
NASA to Make Major Announcement About Martian Rock Sample on Wednesday. Here's How to Watch
https://gizmodo.com/nasa-to-make-major-announcement-about-martian-rock-sample-on-wednesday-heres-how-to-watch-2000655885

LADB: Latent Aligned Diffusion Bridges for Semi-Supervised Domain Translation
Xuqin Wang, Tao Wu, Yanfeng Zhang, Lu Liu, Dong Wang, Mingwei Sun, Yongliang Wang, Niclas Zeller, Daniel Cremers
https://arxiv.org/abs/2509.08628

LADB: Latent Aligned Diffusion Bridges for Semi-Supervised Domain Translation
Diffusion models excel at generating high-quality outputs but face challenges in data-scarce domains, where exhaustive retraining or costly paired data are often required. To address these limitations, we propose Latent Aligned Diffusion Bridges (LADB), a semi-supervised framework for sample-to-sample translation that effectively bridges domain gaps using partially paired data. By aligning source and target distributions within a shared latent space, LADB seamlessly integrates pretrained source…

Back to the HMCAD1520 FA.
This is sample 6A1 after initial partial decap. It's still covered in the north and easy because I guessed how big the die would be and apparently underestimated its size.
The good news is that it's gold ball bonded, so more time in the acid shouldn't risk damaging the bond wires at all.
Time to re-mount it with a bigger mask and try again.

Interpretable Generative and Discriminative Learning for Multimodal and Incomplete Clinical Data
Albert Belenguer-Llorens, Carlos Sevilla-Salcedo, Janaina Mourao-Miranda, Vanessa G\'omez-Verdejo
https://arxiv.org/abs/2510.09513

Interpretable Generative and Discriminative Learning for Multimodal and Incomplete Clinical Data
Real-world clinical problems are often characterized by multimodal data, usually associated with incomplete views and limited sample sizes in their cohorts, posing significant limitations for machine learning algorithms. In this work, we propose a Bayesian approach designed to efficiently handle these challenges while providing interpretable solutions. Our approach integrates (1) a generative formulation to capture cross-view relationships with a semi-supervised strategy, and (2) a discriminati…

Dark Energy Survey Year 6 Results: Redshift Calibration of the MagLim Lens Sample
G. Giannini, A. Alarcon, W. d'Assignies, G. M. Bernstein, M. A. Troxel, C. Chang, B. Yin, A. Amon, J. Myles, N. Weaverdyck, A. Porredon, D. Anbajagane, S. Avila, K. Bechtol, M. R. Becker, J. Blazek, M. Crocce, D. Gruen, M. Rodriguez-Monroy, C. S\'anchez, D. Sanchez Cid, I. Sevilla-Noarbe, M. Aguena, S. Allam, O. Alves, F. Andrade-Oliveira, D. Bacon, S. Bocquet, D. Brooks, R. Camilleri, A. Carner…

Dark Energy Survey Year 6 Results: Redshift Calibration of the MagLim++ Lens Sample
In this work, we derive and calibrate the redshift distribution of the MagLim++ lens galaxy sample used in the Dark Energy Survey Year 6 (DES Y6) 3x2pt cosmology analysis. The 3x2pt analysis combines galaxy clustering from the lens galaxy sample and weak gravitational lensing. The redshift distributions are inferred using the SOMPZ method - a Self-Organizing Map framework that combines deep-field multi-band photometry, wide-field data, and a synthetic source injection (Balrog) catalog. Key impr…

The #Perseverance press conference panel consists of 5 NASA managers and 1 Mars researcher - so the topic is likely some follow-up to "the
discovery of a potential #biosignature" in an outcrop reported earlier this year in #spectroscopy method to hunt for microbial markers was discussed in March in https://www.u-tokyo.ac.jp/focus/en/press/z0508_00392.html

Quantum Adams operations in quasimap K-theory
Shaoyun Bai, Jae Hee Lee
https://arxiv.org/abs/2510.09335 https://arxiv.org/pdf/2510.09335

Quantum Adams operations in quasimap K-theory
We define quantum deformations of Adams operations in $K$-theory, in the framework of quasimap quantum $K$-theory. They provide $K$-theoretic analogs of the quantum Steenrod operations from equivariant symplectic Gromov--Witten theory. We verify the compatibility of these operations with the Kahler and equivariant $q$-difference module structures, provide sample computations via $\mathbb{Z}/k$-equivariant localization, and identify them with $p$-curvature operators of the Kahler $q$-difference …

Boosting Data Utilization for Multilingual Dense Retrieval
Chao Huang, Fengran Mo, Yufeng Chen, Changhao Guan, Zhenrui Yue, Xinyu Wang, Jinan Xu, Kaiyu Huang
https://arxiv.org/abs/2509.09459

Boosting Data Utilization for Multilingual Dense Retrieval
Multilingual dense retrieval aims to retrieve relevant documents across different languages based on a unified retriever model. The challenge lies in aligning representations of different languages in a shared vector space. The common practice is to fine-tune the dense retriever via contrastive learning, whose effectiveness highly relies on the quality of the negative sample and the efficacy of mini-batch data. Different from the existing studies that focus on developing sophisticated model arc…

HWO Target Stars and Systems: A Survey of Archival UV and X-ray Data
Sarah Peacock, David J. Wilson, Tyler Richey-Yowell, Noah W. Tuchow, Kevin France, Jos\'e A. Caballero, Riccardo Spinelli, L\'ia Corrales, Aiden S. Zelakiewicz, Seth Redfield, Keighley Rockcliffe, Allison Youngblood, Cynthia S. Froning, Girish M. Duvvuri, Breanna A. Binder, Natalie R. Hinkel, Eric E. Mamajek
…

HWO Target Stars and Systems: A Survey of Archival UV and X-ray Data
We assess archival high-energy data for key stars on the Habitable Worlds Observatory (HWO) Target Stars and Systems 2025 list, as stellar radiation is critical to shaping and interpreting planetary atmospheres. Using a sample of 98 nearby stars (HWO Tier 1 targets), we compile and evaluate X-ray and ultraviolet (UV) data from archival eROSITA, Chandra, XMM-Newton, ROSAT, EUVE, Swift, FUSE, IUE, GALEX, and HST. We examine spectral and temporal coverage, assess data quality, and identify major g…

DiFlow-TTS: Discrete Flow Matching with Factorized Speech Tokens for Low-Latency Zero-Shot Text-To-Speech
Ngoc-Son Nguyen, Hieu-Nghia Huynh-Nguyen, Thanh V. T. Tran, Truong-Son Hy, Van Nguyen
https://arxiv.org/abs/2509.09631

DiFlow-TTS: Discrete Flow Matching with Factorized Speech Tokens for Low-Latency Zero-Shot Text-To-Speech
Zero-shot Text-to-Speech (TTS) aims to synthesize high-quality speech that mimics the voice of an unseen speaker using only a short reference sample, requiring not only speaker adaptation but also accurate modeling of prosodic attributes. Recent approaches based on language models, diffusion, and flow matching have shown promising results in zero-shot TTS, but still suffer from slow inference and repetition artifacts. Discrete codec representations have been widely adopted for speech synthesis,…

Crosslisted article(s) found for stat.ME. https://arxiv.org/list/stat.ME/new
[1/1]:
- SHAP-Based Supervised Clustering for Sample Classification and the Generalized Waterfall Plot
Justin Lin, Julia Fukuyama

I do think the results of the above (even with a small sample) suggest that there is a big expectations mismatch in how security issues are communicated in the JavaScript ecosystem

LATIS: Galaxy-Environment Relations at Cosmic Noon and the Role of Sample Selection
Nima Chartab, Andrew B. Newman, Gwen C. Rudie, Guillermo Blanc, Daniel D. Kelson, Mahdi Qezlou, Simeon Bird, Brian C. Lemaux, Olga Cucciati
https://arxiv.org/abs/2510.07445

LATIS: Galaxy-Environment Relations at Cosmic Noon and the Role of Sample Selection
We investigate the environmental dependence of galaxy properties at $z\sim2.5$ using the Ly$α$ Tomography IMACS Survey (LATIS), which provides high-resolution three-dimensional maps of intergalactic medium (IGM) overdensity via Ly$α$ forest tomography. Our analysis focuses on a UV-selected spectroscopic sample of 2185 galaxies from LATIS and a complementary set of 1157 galaxies from heterogeneous spectroscopic surveys in the COSMOS field. We compare these datasets to forward-modeled mock cata…

Unsupervised full-field Bayesian inference of orthotropic hyperelasticity from a single biaxial test: a myocardial case study
Rogier P. Krijnen, Akshay Joshi, Siddhant Kumar, Mathias Peirlinck
https://arxiv.org/abs/2510.09498

Unsupervised full-field Bayesian inference of orthotropic hyperelasticity from a single biaxial test: a myocardial case study
Fully capturing this behavior in traditional homogenized tissue testing requires the excitation of multiple deformation modes, i.e. combined triaxial shear tests and biaxial stretch tests. Inherently, such multimodal experimental protocols necessitate multiple tissue samples and extensive sample manipulations. Intrinsic inter-sample variability and manipulation-induced tissue damage might have an adverse effect on the inversely identified tissue behavior. In this work, we aim to overcome this g…

Observation of $\psi(3686)\to \gamma \eta(1405)$ via $\eta(1405)\to f_0(980)\pi^0$
M. Ablikim, et al.
https://arxiv.org/abs/2509.09156 https://arxiv.org/pd…

Observation of $ψ(3686)\to γη(1405)$ via $η(1405)\to f_0(980)π^0$
The decay $ψ(3686)\toγπ^+π^-π^0$ is studied using a sample of $(2712.4\pm14.3)\times10^6$ $ψ(3686)$ events collected with the BESIII detector. The decay $η(1405)\toπ^+π^-π^0$ is observed for the first time in $ψ(3686)$ decays via the intermediate state $f_0(980)$ and the product branching fraction $\mathcal{B}(ψ(3686)\toγη(1405))\times\mathcal{B}(η(1405)\to f_0(980)π^0)\times \mathcal{B}(f_0(980)\toπ^+π^-)$ is determined to be $(3.77\pm0.43\pm0.29)\times10^{-7}$, where the fir…

The joys of doing semiconductor lab work while getting over the tail end of some kind of respiratory bug: trying not to cough and yeet the sample you've been working on for two weeks across the lab

Dynamic Redeployment of Nurses Across Hospitals: A Sample Robust Optimization Approach
Wei Liu, Tianchun Li, Mengshi Lu, Pengyi Shi
https://arxiv.org/abs/2509.07387 https://

Dynamic Redeployment of Nurses Across Hospitals: A Sample Robust Optimization Approach
Problem definition: We study a workforce redeployment problem in hospital networks, where clinical staff, such as nurses, are temporarily reassigned from overstaffed to understaffed sites to address short-term imbalances. This practice of ``internal travel,'' which gained traction during the COVID-19 pandemic to tackle nurse shortages, presents new operational challenges that require tailored analytical support. Key requirements such as advance notice and short-term secondments must be incorpor…

NASA Says Mars Rover Discovered Potential Biosignature Last Year
https://www.nasa.gov/news-release/nasa-says-mars-rover-discovered-potential-biosignature-last-year/

NASA Says Mars Rover Discovered Potential Biosignature Last Year - NASA
A sample collected by NASA’s Perseverance Mars rover from an ancient dry riverbed in Jezero Crater could preserve evidence of ancient microbial life. Taken

Unsupervised Multi-Attention Meta Transformer for Rotating Machinery Fault Diagnosis
Hanyang Wang, Yuxuan Yang, Hongjun Wang, Lihui Wang
https://arxiv.org/abs/2509.09251 https:/…

Unsupervised Multi-Attention Meta Transformer for Rotating Machinery Fault Diagnosis
The intelligent fault diagnosis of rotating mechanical equipment usually requires a large amount of labeled sample data. However, in practical industrial applications, acquiring enough data is both challenging and expensive in terms of time and cost. Moreover, different types of rotating mechanical equipment with different unique mechanical properties, require separate training of diagnostic models for each case. To address the challenges of limited fault samples and the lack of generalizabilit…

Oh wow this is amazing 🤩 Perseverance Rover found biosignatures on Mars https://www.nasa.gov/news-release/nasa-says-mars-rover-discovered-potential-biosignature-last-year/

NASA Says Mars Rover Discovered Potential Biosignature Last Year - NASA
A sample collected by NASA’s Perseverance Mars rover from an ancient dry riverbed in Jezero Crater could preserve evidence of ancient microbial life. Taken

MCMC: Bridging Rendering, Optimization and Generative AI
Gurprit Singh, Wenzel Jakob
https://arxiv.org/abs/2510.09078 https://arxiv.org/pdf/2510.09078

MCMC: Bridging Rendering, Optimization and Generative AI
Generative artificial intelligence (AI) has made unprecedented advances in vision language models over the past two years. During the generative process, new samples (images) are generated from an unknown high-dimensional distribution. Markov Chain Monte Carlo (MCMC) methods are particularly effective in drawing samples from such complex, high-dimensional distributions. This makes MCMC methods an integral component for models like EBMs, ensuring accurate sample generation. Gradient-based opti…

Correcting sample selection bias with categorical outcomes
Onil Boussim
https://arxiv.org/abs/2510.05551 https://arxiv.org/pdf/2510.05551

Correcting sample selection bias with categorical outcomes
In this paper, we propose a method for correcting sample selection bias when the outcome of interest is categorical, such as occupational choice, health status, or field of study. Classical approaches to sample selection rely on strong parametric distributional assumptions, which may be restrictive in practice. While the recent framework of Chernozhukov et al. (2023) offers a nonparametric identification using a local Gaussian representation (LGR) that holds for any bivariate joint distribution…

Divide, Interact, Sample: The Two-System Paradigm
James Chok, Myung Won Lee, Daniel Paulin, Geoffrey M. Vasil
https://arxiv.org/abs/2509.09162 https://arxi…

Divide, Interact, Sample: The Two-System Paradigm
Mean-field, ensemble-chain, and adaptive samplers have historically been viewed as distinct approaches to Monte Carlo sampling. In this paper, we present a unifying {two-system} framework that brings all three under one roof. In our approach, an ensemble of particles is split into two interacting subsystems that propose updates for each other in a symmetric, alternating fashion. This cross-system interaction ensures that the overall ensemble has $ρ(x)$ as its invariant distribution in both the…

From a 1903 book republished in 1910

I swear the finale of one of #kpopdemonhunters songs is a Dead Can Dance/Lisa Gerrard sample.

twitter: Twitter followers (2010)
A directed network of following relationships from Twitter, from a snowball sample crawl across "quality" users in 2009. A directed edge (i, j) indicates that user i follows user j.
This network has 465017 nodes and 834797 edges.
Tags: Social, Online, Unweighted
https://network…

Magneto-optical Kerr-effect measurements under pulsed magnetic fields over 40 T using a compact sample fixture
Atsutoshi Ikeda, Sota Nakamura, Soichiro Yamane, Kosuke Noda, Akihiko Ikeda, Shingo Yonezawa
https://arxiv.org/abs/2509.07383

Magneto-optical Kerr-effect measurements under pulsed magnetic fields over 40 T using a compact sample fixture
Magnetic field is one of the most fundamental control parameters in materials science. Pulsed magnetic-field apparatus can generate high magnetic fields that are inaccessible by conventional DC-field magnets. One important issue is that measurement techniques compatible with pulsed fields are rather limited due to short pulse duration and large electromagnetic or mechanical noises originating from field pulses. Magneto-optical Kerr effect (MOKE), change in states of light polarization upon refl…

Are BabyLMs Deaf to Gricean Maxims? A Pragmatic Evaluation of Sample-efficient Language Models
Raha Askari, Sina Zarrie{\ss}, \"Ozge Alacam, Judith Sieker
https://arxiv.org/abs/2510.04764

Are BabyLMs Deaf to Gricean Maxims? A Pragmatic Evaluation of Sample-efficient Language Models
Implicit meanings are integral to human communication, making it essential for language models to be capable of identifying and interpreting them. Grice (1975) proposed a set of conversational maxims that guide cooperative dialogue, noting that speakers may deliberately violate these principles to express meanings beyond literal words, and that listeners, in turn, recognize such violations to draw pragmatic inferences. Building on Surian et al. (1996)'s study of children's sensitivity to viol…

Validation of a CT-brain analysis tool for measuring global cortical atrophy in older patient cohorts
Sukhdeep Bal, Emma Colbourne, Jasmine Gan, Ludovica Griffanti, Taylor Hanayik, Nele Demeyere, Jim Davies, Sarah T Pendlebury, Mark Jenkinson
https://arxiv.org/abs/2509.08012

Validation of a CT-brain analysis tool for measuring global cortical atrophy in older patient cohorts
Quantification of brain atrophy currently requires visual rating scales which are time consuming and automated brain image analysis is warranted. We validated our automated deep learning (DL) tool measuring the Global Cerebral Atrophy (GCA) score against trained human raters, and associations with age and cognitive impairment, in representative older (>65 years) patients. CT-brain scans were obtained from patients in acute medicine (ORCHARD-EPR), acute stroke (OCS studies) and a legacy sample. …

Locally Optimal Private Sampling: Beyond the Global Minimax
Hrad Ghoukasian, Bonwoo Lee, Shahab Asoodeh
https://arxiv.org/abs/2510.09485 https://arxiv.org/…

Locally Optimal Private Sampling: Beyond the Global Minimax
We study the problem of sampling from a distribution under local differential privacy (LDP). Given a private distribution $P \in \mathcal{P}$, the goal is to generate a single sample from a distribution that remains close to $P$ in $f$-divergence while satisfying the constraints of LDP. This task captures the fundamental challenge of producing realistic-looking data under strong privacy guarantees. While prior work by Park et al. (NeurIPS'24) focuses on global minimax-optimality across a class …

Learning Barycenters from Signature Matrices
Carlos Am\'endola, Leonard Schmitz
https://arxiv.org/abs/2509.07815 https://arxiv.org/pdf/2509.07815

Learning Barycenters from Signature Matrices
The expected signature of a family of paths need not be a signature of a path itself. Motivated by this, we consider the notion of a Lie group barycenter introduced by Buser and Karcher to propose a barycenter on path signatures. We show that every element of the free nilpotent Lie group is a barycenter of a group sample, where all but one sample element can be fixed arbitrarily. In the case of piecewise linear paths, we study the problem of recovering an underlying path corresponding to the ba…

The fate of Gaia's wide binaries: Interplay of white-dwarf recoil and tidal capture
Christopher E. O'Connor
https://arxiv.org/abs/2509.08880 https://

The fate of Gaia's wide binaries: Interplay of white-dwarf recoil and tidal capture
White dwarfs (WDs) receive natal velocity boosts of $\sim 1 \, \mathrm{km \, s^{-1}}$ due to recoil from asymmetric mass loss during the late asymptotic giant branch (AGB) stage. In a wide binary, the acceleration of a proto-WD exerts a torque, modifying the orbital eccentricity. Potential signatures of this effect have been detected in Gaia's astrometric binary sample. At the same time, an AGB star's puffy envelope facilitates strong tidal interactions in binaries with periapsis separations of…

Multidimensional Poverty Mapping for Small Areas
Soumojit Das, Dilshanie Deepawansa, Partha Lahiri
https://arxiv.org/abs/2510.08898 https://arxiv.org/pdf/2…

Multidimensional Poverty Mapping for Small Areas
Many countries measure poverty based only on income or consumption. However, there is a growing awareness of measuring poverty through multiple dimensions that captures a more reasonable status of poverty. Estimating poverty measure(s) for small geographical areas, commonly referred to as poverty mapping, is challenging due to small or no sample for the small areas. While there is a huge literature available on unidimensional poverty mapping, only a limited effort has been made to address speci…

Thermodynamics of data
Borko Stosic
https://arxiv.org/abs/2510.06818 https://arxiv.org/pdf/2510.06818

Thermodynamics of data
The recently introduced concept of generalized thermodynamics is explored here in the context of 1d, 2d and 3d data analysis, performed on samples drawn from a 3d X-ray soil sample image. Different threshold levels are used to binarize the 3d sample, wherefrom relative frequencies of binary patterns are found and then used to address finite size scaling behavior of the response functions as a function of the disorder parameter (equivalent of temperature in thermodynamics). It is found that for …

Sample-Efficient and Smooth Cross-Entropy Method Model Predictive Control Using Deterministic Samples
Markus Walker, Daniel Frisch, Uwe D. Hanebeck
https://arxiv.org/abs/2510.05706

Sample-Efficient and Smooth Cross-Entropy Method Model Predictive Control Using Deterministic Samples
Cross-entropy method model predictive control (CEM--MPC) is a powerful gradient-free technique for nonlinear optimal control, but its performance is often limited by the reliance on random sampling. This conventional approach can lead to inefficient exploration of the solution space and non-smooth control inputs, requiring a large number of samples to achieve satisfactory results. To address these limitations, we propose deterministic sampling CEM (dsCEM), a novel framework that replaces the ra…

Searching for GEMS: The Occurrence of Giant Planets orbiting M-dwarfs within 100 pc
Rowen I. Glusman, Caleb I. Ca\~nas, Shubham Kanodia, Te Han, Rachel B. Fernandes, Gu{\dh}mundur Stef\'ansson, Marissa Maney, Andrew Monson, Andrew Hotnisky, Suvrath Mahadevan, Michael Rodruck, Kristo Ment, Andrew McWilliam, William D. Cochran, Knicole D. Col\'on, Mark R. Giovinazzi, Jaime A. Alvarado-Montes, Chad F. Bender, Cullun H. Blake, Alexandra Boone, Scott A. Diddams, Arvind F. Gupta, Sam…

Searching for GEMS: The Occurrence of Giant Planets orbiting M-dwarfs within 100 pc
We present results from a systematic search for transiting short-period Giant Exoplanets around M-dwarf Stars (GEMS; $P < 10$ days, $R_p \gtrsim 8~R_\oplus$) within a distance-limited 100\,pc sample of 149,316 M-dwarfs using TESS-Gaia Light Curve (TGLC) data. This search led to the discovery of one new candidate GEM, following spectroscopic vetting of 12 additional candidates to eliminate astrophysical false positives and refine our occurrence rate estimates. We describe the development and app…

Probing the Infrared/Radio correlation of the full IRAS Revised Bright Galaxy Sample with MeerKAT and the VLA
M. E. Moloko, L. Marchetti, T. H. Jarrett, J. J. Condon, W. D. Cotton, A. M. Matthews, T. Mauch, M. Vaccari
https://arxiv.org/abs/2509.07105

Probing the Infrared/Radio correlation of the full IRAS Revised Bright Galaxy Sample with MeerKAT and the VLA
We study the infrared/radio correlation of galaxies in the IRAS Revised Bright Galaxy Sample using new MeerKAT observations at $\rmν= 1.28\, GHz$, complemented with VLA data. We classify the objects by primary energy source (Active Galactic Nuclei vs. Star-Forming) and take into account their merger status. With this, we aim to explore the effect of galaxy-galaxy interaction on the total-infrared (TIR)/radio correlation ($q_\mathrm{TIR}$) of star-forming galaxies by comparing the $q_\mathrm{TI…

Spectral Thresholds for Identifiability and Stability:Finite-Sample Phase Transitions in High-Dimensional Learning
William Hao-Cheng Huang
https://arxiv.org/abs/2510.03809 https…

Spectral Thresholds for Identifiability and Stability:Finite-Sample Phase Transitions in High-Dimensional Learning
In high-dimensional learning, models remain stable until they collapse abruptly once the sample size falls below a critical level. This instability is not algorithm-specific but a geometric mechanism: when the weakest Fisher eigendirection falls beneath sample-level fluctuations, identifiability fails. Our Fisher Threshold Theorem formalizes this by proving that stability requires the minimal Fisher eigenvalue to exceed an explicit $O(\sqrt{d/n})$ bound. Unlike prior asymptotic or model-specifi…

A Cycle Walk for Sampling Measures on Spanning Forests for Redistricting
Daryl R. DeFord, Gregory Herschlag, Jonathan C. Mattingly
https://arxiv.org/abs/2509.08629 https://

A Cycle Walk for Sampling Measures on Spanning Forests for Redistricting
We introduce a new Markov Chain called the Cycle Walk for sampling measures of graph partitions where the partition elements have roughly equal size. Such Markov Chains are of current interest in the generation and evaluation of political districts. We present numerical evidence that this chain can efficiently sample target distributions that have been difficult for existing sampling Markov chains.

On the Reliability of Quasars as Cosmological Distance Indicators
Ariadna Montiel, Sofia Samario-Nava, Juan Carlos Hidalgo, Jose Ignacio Cabrera
https://arxiv.org/abs/2509.08983

On the Reliability of Quasars as Cosmological Distance Indicators
The goal of the present paper is to assess the usefulness of quasars as cosmological distance indicators. We calibrate, in a model-independent way, the non-linear relation between X-ray and UV emission to derive quasar luminosity distances. Using this calibration, we construct the Hubble diagram up to redshift $z \sim 7.5$, and test the ability of quasars to constrain the $Λ$CDM and $ω$CDM models at low and high redshifts, in combination with the Type Ia supernova Pantheon Plus sample, as wel…

Sequentially Auditing Differential Privacy
Tom\'as Gonz\'alez, Mateo Dulce-Rubio, Aaditya Ramdas, M\'onica Ribero
https://arxiv.org/abs/2509.07055 https://

Sequentially Auditing Differential Privacy
We propose a practical sequential test for auditing differential privacy guarantees of black-box mechanisms. The test processes streams of mechanisms' outputs providing anytime-valid inference while controlling Type I error, overcoming the fixed sample size limitation of previous batch auditing methods. Experiments show this test detects violations with sample sizes that are orders of magnitude smaller than existing methods, reducing this number from 50K to a few hundred examples, across divers…

Rate optimal learning of equilibria from data
Till Freihaut, Luca Viano, Emanuele Nevali, Volkan Cevher, Matthieu Geist, Giorgia Ramponi
https://arxiv.org/abs/2510.09325 https:/…

Rate optimal learning of equilibria from data
We close open theoretical gaps in Multi-Agent Imitation Learning (MAIL) by characterizing the limits of non-interactive MAIL and presenting the first interactive algorithm with near-optimal sample complexity. In the non-interactive setting, we prove a statistical lower bound that identifies the all-policy deviation concentrability coefficient as the fundamental complexity measure, and we show that Behavior Cloning (BC) is rate-optimal. For the interactive setting, we introduce a framework that …

Replaced article(s) found for math.ST. https://arxiv.org/list/math.ST/new
[1/1]:
- A semiparametric probability distribution estimator of sample maximums
Taku Moriyama

Another few minutes in HF on the PIC12F683 sample and it looks like parts of M2 are starting to delaminate, while other parts still had oxide over them??
Gonna clean and see how this goes. This is the sort of thing that makes wet-etch deprocessing challenging though.

Doubly robust average treatment effect estimation for survival data
Byeonghee Lee, Joonsung Kang
https://arxiv.org/abs/2509.08788 https://arxiv.org/pdf/250…

Doubly robust average treatment effect estimation for survival data
Considering censored outcomes in survival analysis can lead to quite complex results in the model setting of causal inference. Causal inference has attracted a lot of attention over the past few years, but little research has been done on survival analysis. Even for the only research conducted, the machine learning method was considered assuming a large sample, which is not suitable in that the actual data are high dimensional low sample size (HDLSS) method. Therefore, penalty is considered for…

Redox-driven mineral and organic associations in Jezero Crater, #Mars: https://www.nature.com/articles/s41586-025-09413-0 -> "Here we report a detailed geological, petrographic and geochemical survey of these rocks and show that organic-carbon-bearing mudstones in the Bright Angel formation contain submillimetre-scale nodules and millimetre-scale reaction fronts enriched in ferrous iron phosphate and sulfide minerals, likely vivianite and greigite, respectively. This organic carbon appears to have participated in post-depositional redox reactions that produced the observed iron-phosphate and iron-sulfide minerals. Geological context and petrography indicate that these reactions occurred at low temperatures. Within this context, we review the various pathways by which redox reactions that involve organic matter can produce the observed suite of iron-, sulfur- and phosphorus-bearing minerals in laboratory and natural environments on Earth. Ultimately, we conclude that analysis of the core sample collected from this unit using high-sensitivity instrumentation on Earth will enable the measurements required to determine the origin of the minerals, organics and textures it contains."

Data-driven generative simulation of SDEs using diffusion models
Xuefeng Gao, Jiale Zha, Xun Yu Zhou
https://arxiv.org/abs/2509.08731 https://arxiv.org/pdf…

Data-driven generative simulation of SDEs using diffusion models
This paper introduces a new approach to generating sample paths of unknown stochastic differential equations (SDEs) using diffusion models, a class of generative AI models commonly employed in image and video applications. Unlike the traditional Monte Carlo methods for simulating SDEs, which require explicit specifications of the drift and diffusion coefficients, our method takes a model-free, data-driven approach. Given a finite set of sample paths from an SDE, we utilize conditional diffusion…

Galaxy Metallicity Gradients in the Reionization Epoch from the FIRE-2 Simulations
Xunda Sun, Xin Wang, Fangzhou Jiang, Houjun Mo, Luis C. Ho, Qianqiao Zhou, Xiangcheng Ma, Hu Zhan, Andrew Wetzel, Russell L. Graf, Philip F. Hopkins, Dusan Keres, Jonathan Stern
https://arxiv.org/abs/2510.08997

Galaxy Metallicity Gradients in the Reionization Epoch from the FIRE-2 Simulations
We employ the high-redshift suite of FIRE-2 cosmological hydrodynamic zoom-in simulations to investigate the evolution of gas-phase metallicity radial gradients in galaxies in the epoch of reionization (EoR). Our sample consists of 22 galaxies spanning the redshift range $z \sim 10-5$. We find that galaxies at $z\sim10$ exhibit a median metallicity gradient of $-0.15\,\mathrm{dex\cdot kpc^{-1}}$ with substantial scatter, which gradually flatten to $-0.1\,\mathrm{dex\cdot kpc^{-1}}$ at $z\sim6$,…

MSG: Multi-Stream Generative Policies for Sample-Efficient Robotic Manipulation
Jan Ole von Hartz, Lukas Schweizer, Joschka Boedecker, Abhinav Valada
https://arxiv.org/abs/2509.24956

MSG: Multi-Stream Generative Policies for Sample-Efficient Robotic Manipulation
Generative robot policies such as Flow Matching offer flexible, multi-modal policy learning but are sample-inefficient. Although object-centric policies improve sample efficiency, it does not resolve this limitation. In this work, we propose Multi-Stream Generative Policy (MSG), an inference-time composition framework that trains multiple object-centric policies and combines them at inference to improve generalization and sample efficiency. MSG is model-agnostic and inference-only, hence widely…

Weak phonon coupling to nematic quantum critical mode in $BaFe2(As1-xPx)2$
S. Wu, D. Ishikawa, A. Q. R. Baron, A. Alatas, A. H. Said, Jiayu Guo, Y. He, X. Chen, Y. Song, J. G. Analytis, Dung-Hai Lee, R. J. Birgeneau
https://arxiv.org/abs/2509.07114

Weak phonon coupling to nematic quantum critical mode in $BaFe2(As1-xPx)2$
In this work, we investigate the softening of the in-plane transverse acoustic phonon driven by electronic nematicity in BaFe$_2$(As$_{1-x}$P$_x$)$_2$ using inelastic X-ray scattering, with a focus on the optimally doped sample ($x = 0.31$) sample, a system exhibiting signatures of a putative nematic quantum critical point and minimal disorder among iron pnictides. We observe only a modest softening of the phonon frequency and no evidence of critical damping, suggesting that the nematic quantum…

CHUCKLE -- When Humans Teach AI To Learn Emotions The Easy Way
Ankush Pratap Singh, Houwei Cao, Yong Liu
https://arxiv.org/abs/2510.09382 https://arxiv.org…

CHUCKLE -- When Humans Teach AI To Learn Emotions The Easy Way
Curriculum learning (CL) structures training from simple to complex samples, facilitating progressive learning. However, existing CL approaches for emotion recognition often rely on heuristic, data-driven, or model-based definitions of sample difficulty, neglecting the difficulty for human perception, a critical factor in subjective tasks like emotion recognition. We propose CHUCKLE (Crowdsourced Human Understanding Curriculum for Knowledge Led Emotion Recognition), a perception-driven CL frame…

Theoretical guarantees for change localization using conformal p-values
Swapnaneel Bhattacharyya, Aaditya Ramdas
https://arxiv.org/abs/2510.08749 https://a…

Theoretical guarantees for change localization using conformal p-values
Changepoint localization aims to provide confidence sets for a changepoint (if one exists). Existing methods either relying on strong parametric assumptions or providing only asymptotic guarantees or focusing on a particular kind of change(e.g., change in the mean) rather than the entire distributional change. A method (possibly the first) to achieve distribution-free changepoint localization with finite-sample validity was recently introduced by \cite{dandapanthula2025conformal}. However, whil…

Gaze on the Prize: Shaping Visual Attention with Return-Guided Contrastive Learning
Andrew Lee, Ian Chuang, Dechen Gao, Kai Fukazawa, Iman Soltani
https://arxiv.org/abs/2510.08442

Gaze on the Prize: Shaping Visual Attention with Return-Guided Contrastive Learning
Visual Reinforcement Learning (RL) agents must learn to act based on high-dimensional image data where only a small fraction of the pixels is task-relevant. This forces agents to waste exploration and computational resources on irrelevant features, leading to sample-inefficient and unstable learning. To address this, inspired by human visual foveation, we introduce Gaze on the Prize. This framework augments visual RL with a learnable foveal attention mechanism (Gaze), guided by a self-supervise…

Estimating the heterogeneity of pressure profiles within a complete sample of 55 galaxy clusters: a Bayesian Hierarchical Model
Fabio Castagna, Stefano Andreon, Marco Landoni, Alberto Trombetta
https://arxiv.org/abs/2509.07095

Estimating the heterogeneity of pressure profiles within a complete sample of 55 galaxy clusters: a Bayesian Hierarchical Model
Galaxy clusters exhibit heterogeneity in their pressure profiles, even after rescaling, highlighting the need for adequately sized samples to accurately capture variations across the cluster population. We present a Bayesian hierarchical model that simultaneously fits individual cluster parameters and the underlying population distribution, providing estimates of the population-averaged pressure profile and the intrinsic scatter, as well as accurate pressure estimates for individual objects. We…

Single layer tiny Co$^4$ outpaces GPT-2 and GPT-BERT
Noor Ul Zain, Mohsin Raza, Ahsan Adeel
https://arxiv.org/abs/2510.08404 https://arxiv.org/pdf/2510.084…

Single layer tiny Co$^4$ outpaces GPT-2 and GPT-BERT
We show that a tiny Co$^4$ machine(Adeel,2025) with a single layer, two heads, and 8M parameters, operating at an approximate cost of $O(N)$ (where $N$ is the number of input tokens), outpaces the BabyLM Challenge baselines GPT-2 (124M, 12 layers, $O(N^2))$ and GPT-BERT (30M, 12 layers, $O(N^2))$ in just two epochs, while both are trained for ten. Co$^4$ achieves orders-of-magnitude greater training efficiency on 10M tokens, demonstrating highly sample efficient pretraining. Using the BabyLM ch…

Samples are here and Andrew's Back Room IC FA Lab has a new project: a large lot of HMCAD1520s from the ThunderScope project.
My lab assistant helped me catalog them and we got 30 in inventory before having to pause for dinner and bath time, which should be more than enough to get started. She had lots of fun picking up the parts, putting them in labeled tubes, and putting the tubes into the correct location on the sample tray.
For somebody who loves stickers as much as most …

Constraining Brown Dwarf Desert Formation Mechanisms Through Statistical Comparison of Observed and Simulated Orbital Distributions
Behrooz Karamiqucham
https://arxiv.org/abs/2509.08737

Constraining Brown Dwarf Desert Formation Mechanisms Through Statistical Comparison of Observed and Simulated Orbital Distributions
We present a comprehensive statistical analysis of brown dwarf companions to investigate the physical mechanisms responsible for the observed "brown dwarf desert", the notable paucity of brown dwarf companions, at orbital separations between 0.1 and 5 AU. Using a sample of 108 confirmed brown dwarf companions from the NASA Exoplanet Archive with masses between 13-80 Jupiter masses and orbital semi-major axes between 0.1-5.0 AU, we employ Kolmogorov-Smirnov statistical (KS) tests to compare obse…

Gaseous disks in white dwarfs: properties of the current sample
L. Saker, M. Gomez, L. Garcia
https://arxiv.org/abs/2509.05180 https://arxiv.org/pdf/2509.0…

Gaseous disks in white dwarfs: properties of the current sample
In recent years, the number of white dwarfs (WDs) showing infrared (IR) excesses, attributed to circumstellar dust disks, has grown significantly. Gaseous disks have also been detected in some WDs with dust. We obtained optical spectra with Gemini/GMOS for thirteen WDs exhibiting IR excesses to search for gaseous components. No Ca II emission was detected, suggesting the gas phase may be short-lived compared to the dusty stage. Combining our data with literature, we compiled the largest sample …

Approximate Algorithms for Verifying Differential Privacy with Gaussian Distributions
Bishnu Bhusal, Rohit Chadha, A. Prasad Sistla, Mahesh Viswanathan
https://arxiv.org/abs/2509.08804

Approximate Algorithms for Verifying Differential Privacy with Gaussian Distributions
The verification of differential privacy algorithms that employ Gaussian distributions is little understood. This paper tackles the challenge of verifying such programs by introducing a novel approach to approximating probability distributions of loop-free programs that sample from both discrete and continuous distributions with computable probability density functions, including Gaussian and Laplace. We establish that verifying $(ε,δ)$-differential privacy for these programs is \emph{almost …

kNNSampler: Stochastic Imputations for Recovering Missing Value Distributions
Parastoo Pashmchi, Jerome Benoit, Motonobu Kanagawa
https://arxiv.org/abs/2509.08366 https://

kNNSampler: Stochastic Imputations for Recovering Missing Value Distributions
We study a missing-value imputation method, termed kNNSampler, that imputes a given unit's missing response by randomly sampling from the observed responses of the $k$ most similar units to the given unit in terms of the observed covariates. This method can sample unknown missing values from their distributions, quantify the uncertainties of missing values, and be readily used for multiple imputation. Unlike popular kNNImputer, which estimates the conditional mean of a missing response given an…

Near-Optimal Second-Order Guarantees for Model-Based Adversarial Imitation Learning
Shangzhe Li, Dongruo Zhou, Weitong Zhang
https://arxiv.org/abs/2510.09487 https://

Near-Optimal Second-Order Guarantees for Model-Based Adversarial Imitation Learning
We study online adversarial imitation learning (AIL), where an agent learns from offline expert demonstrations and interacts with the environment online without access to rewards. Despite strong empirical results, the benefits of online interaction and the impact of stochasticity remain poorly understood. We address these gaps by introducing a model-based AIL algorithm (MB-AIL) and establish its horizon-free, second-order sample-complexity guarantees under general function approximations for bo…

The WISSH quasar project. XII. X-ray view of the most luminous quasi-stellar objects at Cosmic Noon
C. Degli Agosti, C. Vignali, E. Piconcelli, L. Zappacosta, E. Bertola, R. Middei, I. Saccheo, G. Vietri, F. Vito, A. Bongiorno, M. Bischetti, G. Bruni, S. Carniani, G. Cresci, C. Feruglio, F. Salvestrini, A. Travascio, M. Gaspari, E. Glikman, E. Kammoun, G. Lanzuisi, M. Laurenti, G. Miniutti, C. Pinto, V. Testa, F. Tombesi, A. Tortosa, F. Fiore

The WISSH quasar project. XII. X-ray view of the most luminous quasi-stellar objects at Cosmic Noon
To improve our knowledge of nuclear emission in luminous QSOs at Cosmic Noon, we studied the X-ray emission of the WISE/SDSS-selected hyper-luminous (WISSH) QSO sample: 85 broad-line AGN with $L_{bol}>few\times 10^{47}\,erg\,s^{-1}$ at $z\sim 2-4$. Our aim is to characterise their X-ray spectra and explore relations between X-ray luminosity and other bands, comparing powerful QSOs with the general AGN population. We performed spectral analysis for about half of the sample; 16 sources were analy…

twitter: Twitter followers (2010)
A directed network of following relationships from Twitter, from a snowball sample crawl across "quality" users in 2009. A directed edge (i, j) indicates that user i follows user j.
This network has 465017 nodes and 834797 edges.
Tags: Social, Online, Unweighted
https://network…

Scalable Sample-to-Population Estimation of Hyperbolic Space Models for Hypergraphs
Cornelius Fritz, Yubai Yuan, Michael Schweinberger
https://arxiv.org/abs/2509.07031 https://

Scalable Sample-to-Population Estimation of Hyperbolic Space Models for Hypergraphs
Hypergraphs are useful mathematical representations of overlapping and nested subsets of interacting units, including groups of genes or brain regions, economic cartels, political or military coalitions, and groups of products that are purchased together. Despite the vast range of applications, the statistical analysis of hypergraphs is challenging: There are many hyperedges of small and large sizes, and hyperedges can overlap or be nested. We develop a novel statistical approach to hypergraphs…

DeGuV: Depth-Guided Visual Reinforcement Learning for Generalization and Interpretability in Manipulation
Tien Pham, Xinyun Chi, Khang Nguyen, Manfred Huber, Angelo Cangelosi
https://arxiv.org/abs/2509.04970

DeGuV: Depth-Guided Visual Reinforcement Learning for Generalization and Interpretability in Manipulation
Reinforcement learning (RL) agents can learn to solve complex tasks from visual inputs, but generalizing these learned skills to new environments remains a major challenge in RL application, especially robotics. While data augmentation can improve generalization, it often compromises sample efficiency and training stability. This paper introduces DeGuV, an RL framework that enhances both generalization and sample efficiency. In specific, we leverage a learnable masker network that produces a ma…

Accretion-Regulated Type Transitions in Changing-Look AGNs: Evidence from Two-Epoch Spectral Analysis
Yu-Heng Shen, Kai-Xing Lu, Wei-Jian Guo, Sha-Sha Li, Hai-Cheng Feng, Zhang Yue, Wen-Zhe Xi, Jian-Guo Wang, Jin-Ming Bai
https://arxiv.org/abs/2510.08868

Accretion-Regulated Type Transitions in Changing-Look AGNs: Evidence from Two-Epoch Spectral Analysis
The changing-look active galactic nucleus (CL-AGN), an extraordinary subpopulation of supermassive black holes, has attracted growing attention for understanding its nature. We present an analysis of the spectral properties of 203 low-redshift CL-AGNs ($z<0.35$) using two-epoch spectra from SDSS DR16 and DESI DR1 with time baseline ranging from $\sim$1000 to 8000 days, based on spectral fitting and decomposition. The sample consists of 11.3\% Type 1.0, 26.6\% Type 1.2, 43.1\% Type 1.5, and 19\%…

Classification for 969 double-mode RR Lyrae stars from Zwicky Transient Facility
Jianxing Zhang, Xiaodian Chen, Shu Wang, Jiyu Wang, Licai Deng
https://arxiv.org/abs/2510.07705 …

Classification for 969 double-mode RR Lyrae stars from Zwicky Transient Facility
RR Lyrae (RRL) variable stars are cornerstone distance indicators. In particular, double-mode RR Lyrae (RRd) stars enable period--luminosity relations (PLRs) that are less sensitive to metallicity, reducing systematic biases in distance measurements. However, their utility has been limited by a global sample of only $\sim$3,000 objects. We develop an automated RRd-screening pipeline and apply it to a cross-matched sample between the Gaia DR3 RRL catalog and ZTF DR22 time-series photometry. The …

Sample complexity for entropic optimal transport with radial cost
Ruiyu Han. Johannes Wiesel
https://arxiv.org/abs/2510.05685 https://arxiv.org/pdf/2510.05…

Sample complexity for entropic optimal transport with radial cost
We prove a new sample complexity result for entropy regularized optimal transport. Our bound holds for probability measures on $\mathbb R^d$ with exponential tail decay and for radial cost functions that satisfy a local Lipschitz condition. It is sharp up to logarithmic factors, and captures the intrinsic dimension of the marginal distributions through a generalized covering number of their supports. Examples that fit into our framework include subexponential and subgaussian distributions and r…

A new composite Mann-Whitney test for two-sample survival comparisons with right-censored data
Abid Hussain, Touqeer Ahmad
https://arxiv.org/abs/2510.05353 https://

A new composite Mann-Whitney test for two-sample survival comparisons with right-censored data
A fundamental challenge in comparing two survival distributions with right censored data is the selection of an appropriate nonparametric test, as the power of standard tests like the Log rank and Wilcoxon is highly dependent on the often unknown nature of the alternative hypothesis. This paper introduces a new, distribution free two sample test designed to overcome this limitation. The proposed method is based on a strategic decomposition of the data into uncensored and censored subsets, from …

A Sample of HeII {\lambda}4686 "Changing-Look" Quasars
Wentao Lu, Jun-Xian Wang
https://arxiv.org/abs/2510.06753 https://arxiv.org/pdf/2510.06753…

A Sample of HeII λ4686 "Changing-Look" Quasars
We present the first systematic search for "changing-look" ("CL") behavior in the broad He ii λ4686 emission line in quasars, utilizing repeated spectroscopy from the Sloan Digital Sky Survey (SDSS). The He ii line, originating from high-ionization gas and powered by extreme ultraviolet photons, serves as a sensitive tracer of changes in the ionizing continuum. After applying strict spectral selection criteria and visual inspection to a parent sample of over 9,000 quasars with multi-epoch spec…

Decoding RobKiNet: Insights into Efficient Training of Robotic Kinematics Informed Neural Network
Yanlong Peng, Zhigang Wang, Ziwen He, Pengxu Chang, Chuangchuang Zhou, Yu Yan, Ming Chen
https://arxiv.org/abs/2509.07646

Decoding RobKiNet: Insights into Efficient Training of Robotic Kinematics Informed Neural Network
In robots task and motion planning (TAMP), it is crucial to sample within the robot's configuration space to meet task-level global constraints and enhance the efficiency of subsequent motion planning. Due to the complexity of joint configuration sampling under multi-level constraints, traditional methods often lack efficiency. This paper introduces the principle of RobKiNet, a kinematics-informed neural network, for end-to-end sampling within the Continuous Feasible Set (CFS) under multiple co…

Optimal Stopping in Latent Diffusion Models
Yu-Han Wu, Quentin Berthet, G\'erard Biau, Claire Boyer, Romuald Elie, Pierre Marion
https://arxiv.org/abs/2510.08409 https://

Optimal Stopping in Latent Diffusion Models
We identify and analyze a surprising phenomenon of Latent Diffusion Models (LDMs) where the final steps of the diffusion can degrade sample quality. In contrast to conventional arguments that justify early stopping for numerical stability, this phenomenon is intrinsic to the dimensionality reduction in LDMs. We provide a principled explanation by analyzing the interaction between latent dimension and stopping time. Under a Gaussian framework with linear autoencoders, we characterize the conditi…

Carbon-Enhanced Dwarf Stars Are Predominantly a Halo Population
Jay Farihi, Jason L. Sanders, Sophia Lilleengen, Lewis J. Whitehouse, Denis Erkal
https://arxiv.org/abs/2509.06829

Carbon-Enhanced Dwarf Stars Are Predominantly a Halo Population
This paper reports a Galactic kinematical and dynamical analysis of 1003 main-sequence carbon stars. The sample is drawn from the Sloan Digital Sky Survey, and cross-matched with Gaia DR3 to obtain 6-dimensional positions and velocities using a Bayesian framework. The study provides the first reliable distances for a large sample of dwarf carbon stars, which are then analyzed using both space motions and actions. The results are combined with dynamical equilibrium models for the three primary G…

Sample Smart, Not Hard: Correctness-First Decoding for Better Reasoning in LLMs
Xueyan Li, Guinan Su, Mrinmaya Sachan, Jonas Geiping
https://arxiv.org/abs/2510.05987 https://

Sample Smart, Not Hard: Correctness-First Decoding for Better Reasoning in LLMs
Large Language Models (LLMs) are increasingly applied to complex tasks that require extended reasoning. In such settings, models often benefit from diverse chains-of-thought to arrive at multiple candidate solutions. This requires two competing objectives: to inject enough stochasticity to explore multiple reasoning chains, and to ensure sufficient accuracy and quality in each path. Existing works pursue the first objective by increasing exploration at highly uncertain steps with higher tempera…

EB-MBD: Emerging-Barrier Model-Based Diffusion for Safe Trajectory Optimization in Highly Constrained Environments
Raghav Mishra, Ian R. Manchester
https://arxiv.org/abs/2510.07700

EB-MBD: Emerging-Barrier Model-Based Diffusion for Safe Trajectory Optimization in Highly Constrained Environments
We propose enforcing constraints on Model-Based Diffusion by introducing emerging barrier functions inspired by interior point methods. We show that constraints on Model-Based Diffusion can lead to catastrophic performance degradation, even on simple 2D systems due to sample inefficiency in the Monte Carlo approximation of the score function. We introduce Emerging-Barrier Model-Based Diffusion (EB-MBD) which uses progressively introduced barrier constraints to avoid these problems, significantl…

When Robustness Meets Conservativeness: Conformalized Uncertainty Calibration for Balanced Decision Making
Wenbin Zhou, Shixiang Zhu
https://arxiv.org/abs/2510.07750 https://

When Robustness Meets Conservativeness: Conformalized Uncertainty Calibration for Balanced Decision Making
Robust optimization safeguards decisions against uncertainty by optimizing against worst-case scenarios, yet their effectiveness hinges on a prespecified robustness level that is often chosen ad hoc, leading to either insufficient protection or overly conservative and costly solutions. Recent approaches using conformal prediction construct data-driven uncertainty sets with finite-sample coverage guarantees, but they still fix coverage targets a priori and offer little guidance for selecting rob…

WISE: A Weighted Similarity Aggregation Test for Serial Independence
Qihua Zhu, Mingshuo Liu, Yuefeng Han, Doudou Zhou
https://arxiv.org/abs/2509.05678 https://

WISE: A Weighted Similarity Aggregation Test for Serial Independence
We propose a nonparametric test for serial independence that aggregates pairwise similarities of observations with lag-dependent weights. The resulting statistic is powerful to general forms of temporal dependence, including nonlinear and uncorrelated alternatives, and applies to ultra-high-dimensional and non-Euclidean data. We derive asymptotic normality under both permutation and population nulls, and establish consistency in classical large-sample and high-dimension-low-sample-size (HDLSS) …

The $M_{\rm BH}-M_{*}$ Relationship at $3<z<7$: Big Black Holes in Little Red Dots
Brenda L. Jones, Dale D. Kocevski, Fabio Pacucci, Anthony J. Taylor, Steven L. Finkelstein, Johannes Buchner, Jonathan R. Trump, Rachel S. Somerville, Michaela Hirschmann, L. Y. Aaron Yung, Guillermo Barro, Eric F. Bell, Laura Bisigello, Antonello Calabro, Nikko J. Cleri, Avishai Dekel, Mark Dickinson, Giovanni Gandolfi, Mauro Giavalisco, Norman A. Grogin, Kohei Inayoshi, Jeyhan S. Kartaltepe, Anto…

The $M_{\rm BH}-M_{*}$ Relationship at $3
JWST has identified a large population of faint, broad-line active galactic nuclei (AGN) in the early universe that are powered by black holes (BHs) that often appear overmassive relative to their host galaxies. In this study, we examine the relationship between BH mass and galaxy stellar mass at $3