Tootfinder

Sample-Efficient Omniprediction for Proper Losses
Isaac Gibbs, Ryan J. Tibshirani
https://arxiv.org/abs/2510.12769 https://arxiv.org/pdf/2510.12769

Sample-Efficient Omniprediction for Proper Losses
We consider the problem of constructing probabilistic predictions that lead to accurate decisions when employed by downstream users to inform actions. For a single decision maker, designing an optimal predictor is equivalent to minimizing a proper loss function corresponding to the negative utility of that individual. For multiple decision makers, our problem can be viewed as a variant of omniprediction in which the goal is to design a single predictor that simultaneously minimizes multiple los…

A Martingale Kernel Two-Sample Test
Anirban Chatterjee, Aaditya Ramdas
https://arxiv.org/abs/2510.11853 https://arxiv.org/pdf/2510.11853

A Martingale Kernel Two-Sample Test
The Maximum Mean Discrepancy (MMD) is a widely used multivariate distance metric for two-sample testing. The standard MMD test statistic has an intractable null distribution typically requiring costly resampling or permutation approaches for calibration. In this work we leverage a martingale interpretation of the estimated squared MMD to propose martingale MMD (mMMD), a quadratic-time statistic which has a limiting standard Gaussian distribution under the null. Moreover we show that the test is…

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…

Investigating Phosphorus Abundances in a Sample of APOGEE-2 Bulge Globular Clusters
Beatriz Barbuy, Jos\'e G. Fern\'andez-Trincado, Morgan S. Camargo, Doug Geisler, Maren Brauner, Sandro Villanova, Dante Minniti, Domingo Anibal Garc\'ia-Hern\'andez, Stefano O. Souza, Heitor Ernandes, Am\^ancio Fria\c{c}a, Marco Pignatari
https://

Investigating Phosphorus Abundances in a Sample of APOGEE-2 Bulge Globular Clusters
Phosphorus enhanced (P-rich; [P/Fe] > 0.8) giants have been found among mildly metal-poor fiels stars, but in only one star in a globular cluster (GC), M4 (NGC 6121). Also, in a sample of bulge spheroid stars, some of them showed a moderate P-enhancement in the range +0.5 < [P/Fe] < +1.0. In this paper we derive the P abundance of moderately metal-poor ([Fe/H] ~-1) GC stars, aiming to check if the phenomenon could be related to the unusual multiple stellar populations found in most GCs. Here we…

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…

High Effort, Low Gain: Fundamental Limits of Active Learning for Linear Dynamical Systems
Nicolas Chatzikiriakos, Kevin Jamieson, Andrea Iannelli
https://arxiv.org/abs/2509.11907

High Effort, Low Gain: Fundamental Limits of Active Learning for Linear Dynamical Systems
In this work, we consider the problem of identifying an unknown linear dynamical system given a finite hypothesis class. In particular, we analyze the effect of the excitation input on the sample complexity of identifying the true system with high probability. To this end, we present sample complexity lower bounds that capture the choice of the selected excitation input. The sample complexity lower bound gives rise to a system theoretic condition to determine the potential benefit of experiment…

Visual morphological classification of the full MaNGA DR17 sample: a general characterization
J. A. V\'azquez-Mata, H. M. Hern\'andez-Toledo, V. Avila-Reese, A. Rodr\'iguez-Puebla, L. A. Mart\'inez-V\'azquez, M. Herrera-Endoqui, I. Lacerna, L. C. Mascherpa, D. F. Morell
https://arxiv.org/abs/2510.12792

Visual morphological classification of the full MaNGA DR17 sample: a general characterization
We present the MaNGA Visual Morphology (MVM) catalogue, featuring a visual morphological classification of 10,059 galaxies in the final MaNGA sample. By combining SDSS and DESI Legacy Survey (DLS) images, we classified galaxies into 13 Hubble types, detected tidal features, categorized bars into different families, and estimated concentration, asymmetry, and clumpiness. The depth of the DLS images allowed us to identify structural details that were not evident in the SDSS images, resulting in a…

Preparation of the First Cu-based Nb$_3$Sn Sample via Bronze Route for Quadrupole Resonator Testing
Ming Lu, Sebastian Keckert, Felix Kramer, Alena Prudnikava, Jens Knobloch, Aleksandr Zubtsovskii, Oliver Kugeler
https://arxiv.org/abs/2509.11224

Preparation of the First Cu-based Nb$_3$Sn Sample via Bronze Route for Quadrupole Resonator Testing
We report the first successful production of a Cu-based Nb$_3$Sn sample specifically designed for Quadrupole Resonator (QPR) testing, representing a significant step toward scalable RF superconducting coatings of Nb$_3$Sn on copper substrates. The sample was fabricated using an optimized electrochemical thermal synthesis (ETS) via the bronze route, incorporating several key advancements: electropolishing of the Cu substrate, electroplating of the bronze precursor layer, a tailored heat treatmen…

Rate-Distortion Limits for Multimodal Retrieval: Theory, Optimal Codes, and Finite-Sample Guarantees
Thomas Y. Chen
https://arxiv.org/abs/2509.11054 https://

Rate-Distortion Limits for Multimodal Retrieval: Theory, Optimal Codes, and Finite-Sample Guarantees
We establish the first information-theoretic limits for multimodal retrieval. Casting ranking as lossy source coding, we derive a single-letter rate-distortion function $R(D)$ for reciprocal-rank distortion and prove a converse bound that splits into a modality-balanced term plus a skew penalty $κ\,ΔH$ capturing entropy imbalance and cross-modal redundancy. We then construct an explicit entropy-weighted stochastic quantizer with an adaptive, per-modality temperature decoder; a Blahut-Arimoto …

Out-of-sample gravity predictions and trade policy counterfactuals
Nicolas Apfel, Holger Breinlich, Nick Green, Dennis Novy, J. M. C. Santos Silva, Tom Zylkin
https://arxiv.org/abs/2509.11271

Out-of-sample gravity predictions and trade policy counterfactuals
Gravity equations are often used to evaluate counterfactual trade policy scenarios, such as the effect of regional trade agreements on trade flows. In this paper, we argue that the suitability of gravity equations for this purpose crucially depends on their out-of-sample predictive power. We propose a methodology that compares different versions of the gravity equation, both among themselves and with machine learning-based forecast methods such as random forests and neural networks. We find tha…

Automatic Music Sample Identification with Multi-Track Contrastive Learning
Alain Riou, Joan Serr\`a, Yuki Mitsufuji
https://arxiv.org/abs/2510.11507 https://

Automatic Music Sample Identification with Multi-Track Contrastive Learning
Sampling, the technique of reusing pieces of existing audio tracks to create new music content, is a very common practice in modern music production. In this paper, we tackle the challenging task of automatic sample identification, that is, detecting such sampled content and retrieving the material from which it originates. To do so, we adopt a self-supervised learning approach that leverages a multi-track dataset to create positive pairs of artificial mixes, and design a novel contrastive lear…

Infrared Spectroradiometry of Lithium Benzoate from 21 to 235 THz
Yoshitaka Okuyama, Youichi Ishikawa
https://arxiv.org/abs/2509.11643 https://arxiv.org/pd…

Infrared Spectroradiometry of Lithium Benzoate from 21 to 235 THz
This paper presents an extensive survey of the thermal radiation properties of lithium benzoate. We heated the sample from 313 to 553 K, just below the melting point, while performing an infrared spectroradiometry with an FT-IR spectrometer from 21 to 235 THz (700-7800 cm$^{-1}$). We have provided a detailed analysis of the infrared spectrum data and a comparison of the absorption spectrum of the same sample. It turned out that the recorded spectra are not only different from ordinary absorptio…

Towards Inference-time Scaling for Continuous Space Reasoning
Minghan Wang, Thuy-Trang Vu, Ehsan Shareghi, Gholamreza Haffari
https://arxiv.org/abs/2510.12167 https://

Towards Inference-time Scaling for Continuous Space Reasoning
Inference-time scaling through multiple sample generation in combination with Process- or Outcome-Reward Model (PRM or ORM) re-ranking has proven effective for text-based reasoning in large language models. This paper investigates whether such established techniques can be successfully adapted to reasoning in the continuous space, using COCONUT (Hao et al. 2024) continuous space reasoning LM as the backbone. We demonstrate the feasibility of generating diverse reasoning paths through dropout-ba…

Equity Premium Prediction: Taking into Account the Role of Long, even Asymmetric, Swings in Stock Market Behavior
Kuok Sin Un, Marcel Ausloos
https://arxiv.org/abs/2509.10483 ht…

Equity Premium Prediction: Taking into Account the Role of Long, even Asymmetric, Swings in Stock Market Behavior
Through a novel approach, this paper shows that substantial change in stock market behavior has a statistically and economically significant impact on equity risk premium predictability both on in-sample and out-of-sample cases. In line with Auer's ''Bullish ratio'', a ''Bullish index'' is introduced to measure the changes in stock market behavior, which we describe through a ''fluctuation detrending moving average analysis'' (FDMAA) for returns. We consider 28 indicators. We find that a ''posi…

CoIRL-AD: Collaborative-Competitive Imitation-Reinforcement Learning in Latent World Models for Autonomous Driving
Xiaoji Zheng, Ziyuan Yang, Yanhao Chen, Yuhang Peng, Yuanrong Tang, Gengyuan Liu, Bokui Chen, Jiangtao Gong
https://arxiv.org/abs/2510.12560

CoIRL-AD: Collaborative-Competitive Imitation-Reinforcement Learning in Latent World Models for Autonomous Driving
End-to-end autonomous driving models trained solely with imitation learning (IL) often suffer from poor generalization. In contrast, reinforcement learning (RL) promotes exploration through reward maximization but faces challenges such as sample inefficiency and unstable convergence. A natural solution is to combine IL and RL. Moving beyond the conventional two-stage paradigm (IL pretraining followed by RL fine-tuning), we propose CoIRL-AD, a competitive dual-policy framework that enables IL an…

Superradiance and Superabsorption Engine of $N$ Two-Level Systems: $N^{2}$-Power Scaling at Near-Unity Efficiency
L. F. Alves da Silva, H. Sanchez, M. A. Ponte, M. H. Y. Moussa, Norton G. de Almeida
https://arxiv.org/abs/2510.12017

Superradiance and Superabsorption Engine of $N$ Two-Level Systems: $N^{2}$-Power Scaling at Near-Unity Efficiency
We present a thermal engine that exploits the \emph{cooperative superradiance} and \emph{superabsorption} of a sample of \(N\) two-level atoms. This engine operates using a single cold reservoir via cycles of collective pumping followed by decay. Using an effective mean-field Hamiltonian to describe the many-body dynamics, we design optimized drive pulses that preserve adiabaticity and achieve an average power output scaling quadratically with the system size, \(P \propto N^2\). An experimental…

Formal Models and Convergence Analysis for Context-Aware Security Verification
Ayush Chaudhary
https://arxiv.org/abs/2510.12440 https://arxiv.org/pdf/2510.…

Formal Models and Convergence Analysis for Context-Aware Security Verification
We present a formal framework for context-aware security verification that establishes provable guarantees for ML-enhanced adaptive systems. We introduce context-completeness - a new security property - and prove: (1) sample complexity bounds showing when adaptive verification succeeds, (2) information-theoretic limits relating context richness to detection capability, (3) convergence guarantees for ML-based payload generators, and (4) compositional soundness bounds. We further provide a formal…

Replaced article(s) found for stat.ML. https://arxiv.org/list/stat.ML/new
[1/1]:
- Learning to sample fibers for goodness-of-fit testing
Ivan Gvozdanovi\'c, Sonja Petrovi\'c

Anyone know what the format of this "dotnet.config" file is?
It's mentioned in the #dotnet release notes, but it's the first time I see mention of it and my googling seems to be failing me.

Second-order Optimization under Heavy-Tailed Noise: Hessian Clipping and Sample Complexity Limits
Abdurakhmon Sadiev, Peter Richt\'arik, Ilyas Fatkhullin
https://arxiv.org/abs/2510.10690

Second-order Optimization under Heavy-Tailed Noise: Hessian Clipping and Sample Complexity Limits
Heavy-tailed noise is pervasive in modern machine learning applications, arising from data heterogeneity, outliers, and non-stationary stochastic environments. While second-order methods can significantly accelerate convergence in light-tailed or bounded-noise settings, such algorithms are often brittle and lack guarantees under heavy-tailed noise -- precisely the regimes where robustness is most critical. In this work, we take a first step toward a theoretical understanding of second-order opt…

An Interpretable Ensemble Framework for Multi-Omics Dementia Biomarker Discovery Under HDLSS Conditions
Byeonghee Lee, Joonsung Kang
https://arxiv.org/abs/2509.10527 https://

An Interpretable Ensemble Framework for Multi-Omics Dementia Biomarker Discovery Under HDLSS Conditions
Biomarker discovery in neurodegenerative diseases requires robust, interpretable frameworks capable of integrating high-dimensional multi-omics data under low-sample conditions. We propose a novel ensemble approach combining Graph Attention Networks (GAT), MultiOmics Variational AutoEncoder (MOVE), Elastic-net sparse regression, and Storey's False Discovery Rate (FDR). This framework is benchmarked against state-of-the-art methods including DIABLO, MOCAT, AMOGEL, and MOMLIN. We evaluate perform…

Generalized Jeffreys's approximate objective Bayes factor: Model-selection consistency, finite-sample accuracy, and statistical evidence in 71,126 clinical trial findings
Puneet Velidi, Zhengxiao Wei, Shreena Nisha Kalaria, Yimeng Liu, C\'eline M. Laumont, Brad H. Nelson, Farouk S. Nathoo
https://arxiv.org/abs/2510.10358

Generalized Jeffreys's approximate objective Bayes factor: Model-selection consistency, finite-sample accuracy, and statistical evidence in 71,126 clinical trial findings
Concerns about the misuse and misinterpretation of p-values and statistical significance have motivated alternatives for quantifying evidence. We define a generalized form of Jeffreys's approximate objective Bayes factor (eJAB), a one-line calculation that is a function of the p-value, sample size, and parameter dimension. We establish conditions under which eJAB is model-selection consistent and verify them for ten statistical tests. We assess finite-sample accuracy by comparing eJAB with Mark…

Eruptive mass loss less than a year before the explosion of superluminous supernovae. II. A systematic search for pre-explosion eruptions with VLT/X-shooter
A. Gkini, C. Fransson, R. Lunnan, S. Schulze, J. Sollerman K. Tsalapatas, N. Sarin, M. Nicholl, C. Angus, U. Burgaz, S. J. Brennan, T. -W. Chen, A. Gal-Yam, A. Gangopadhyay, Y. Hu, M. M. Kasliwal, R. R. Laher, P. J. Pessi, B. Rusholme, E. Russeil, A. Singh, C. Skoglund, R. Smith, B. van Baal, S. L. West, L. Yan

Eruptive mass loss less than a year before the explosion of superluminous supernovae. II. A systematic search for pre-explosion eruptions with VLT/X-shooter
We present X-shooter observations of a sample of 21 hydrogen-poor superluminous supernovae (SLSNe-I), spanning a redshift range of z=0.13-0.95, aimed at searching for shells of circumstellar material (CSM). Specifically, we focus on identifying broad Mg II absorption features that are blueshifted by several thousand kilometers per second and have previously been interpreted as arising from resonance line scattering of the SLSN continuum by rapidly expanding CSM ejected shortly before explosion.…

Focused Angular $N$-Body Event Generator (FANG)
Itay Horin, Arik Kreisel, Or Alon
https://arxiv.org/abs/2509.11105 https://arxiv.org/pdf/2509.11105

Focused Angular $N$-Body Event Generator (FANG)
We introduce FANG (Focused Angular $n$-body event Generator), a new Monte Carlo tool for efficient event generation in restricted Lorentz-invariant phase space (LIPS). Unlike conventional approaches that uniformly sample the full $4π$ solid angle, FANG directly generates events in which selected final-state particles are constrained to fixed directions or finite angular regions in the laboratory frame. Because of the way the generator is constructed, angular constraints can be imposed directly…

Moment-based Posterior Sampling for Multi-reference Alignment
Axel Janson, Joakim And\'en
https://arxiv.org/abs/2510.12651 https://arxiv.org/pdf/2510.1…

Moment-based Posterior Sampling for Multi-reference Alignment
We propose a Bayesian approach to the problem of multi-reference alignment -- the recovery of signals from noisy, randomly shifted observations. While existing frequentist methods accurately recover the signal at arbitrarily low signal-to-noise ratios, they require a large number of samples to do so. In contrast, our proposed method leverages diffusion models as data-driven plug-and-play priors, conditioning these on the sample power spectrum (a shift-invariant statistic) enabling both accurate…

Lossless Derandomization for Undirected Single-Source Shortest Paths and Approximate Distance Oracles
Shuyi Yan
https://arxiv.org/abs/2510.12598 https://ar…

Lossless Derandomization for Undirected Single-Source Shortest Paths and Approximate Distance Oracles
A common step in algorithms related to shortest paths in undirected graphs is that, we select a subset of vertices as centers, then grow a ball around each vertex until a center is reached. We want the balls to be as small as possible. A randomized algorithm can uniformly sample $r$ centers to achieve the optimal (expected) ball size of $Θ(n/r)$. A folklore derandomization is to use the $O(\log n)$ approximation for the set cover problem in the hitting set version where we want to hit all the …

The Blue Jay Survey: Deep JWST Spectroscopy for a Representative Sample of Galaxies at Cosmic Noon
Sirio Belli, Letizia Bugiani, Minjung Park, J. Trevor Mendel, Rebecca L. Davies, Amir H. Khoram, Benjamin D. Johnson, Joel Leja, Sandro Tacchella, Vanessa Brown, Charlie Conroy, Razieh Emami, Yijia Li, Caterina Liboni, Gabriel Maheson, Elijah P. Mathews, Rohan P. Naidu, Erica J. Nelson, Bryan A. Terrazas, Rainer Weinberger

The Blue Jay Survey: Deep JWST Spectroscopy for a Representative Sample of Galaxies at Cosmic Noon
We present the Blue Jay survey, a Cycle-1 JWST program aimed at studying the stellar and gas content of galaxies at Cosmic Noon. The survey consists of deep spectroscopy for 153 targets observed over two pointings in the COSMOS field using the NIRSpec micro-shutter assembly (MSA). We employ the three medium-resolution gratings G140M, G235M, and G395M, with exposure times of 13 hours, 3.2 hours, and 1.6 hours, respectively. We thus obtain full coverage of the 1-5 micron range, corresponding to t…

Tracing correlations between galaxy properties across the Cosmic Web: An IllustrisTNG-based study
Anindita Nandi, Biswajit Pandey, Prakash Sarkar
https://arxiv.org/abs/2509.11288

Tracing correlations between galaxy properties across the Cosmic Web: An IllustrisTNG-based study
We explore the impact of cosmic web environments on galaxy properties such as $(u-r)\,$colour, stellar mass, star formation rate, and stellar metallicity, using a stellar mass-matched sample of simulated galaxies from the IllustrisTNG simulation. We use Normalized Mutual Information (NMI) to quantify correlations among galaxy properties and apply Student's t-test to assess the statistical significance of their differences across cosmic web environments. In every case, the null hypothesis is rej…

Construction of Basis Functions for the Geometry Conforming Immersed Finite Element Method
Slimane Adjerid, Tao Lin, Haroun Meghaichi
https://arxiv.org/abs/2510.12018 https://…

Construction of Basis Functions for the Geometry Conforming Immersed Finite Element Method
The Frenet apparatus is a new framework for constructing high order geometry-conforming immersed finite element functions for interface problems. In this report, we present a procedure for constructing the local IFE bases in some detail as well as a new approach for constructing orthonormal bases using the singular value decomposition of the local generalized Vandermonde matrix. A sample implementation in MATLAB is provided to showcase the simplicity and extensionability of the framework.

Mitigating Random-Phase Sampling Noise in the Cepheid Period-Luminosity Relation: A Cross-Filter Consistency Approach
Mahdi Abdollahi, Atefeh Javadi, Barry F. Madore, Wendy L. Freedman, Hamidreza Mahani
https://arxiv.org/abs/2509.10901

Mitigating Random-Phase Sampling Noise in the Cepheid Period-Luminosity Relation: A Cross-Filter Consistency Approach
The Period-Luminosity (PL) relation is usually derived using time-averaged magnitudes, which require multiple-epoch observations to determine periods and adequately sample the light curves. Although single-epoch observations are more practical and require significantly less observational effort, they inherently introduce greater photometric scatter, leading to an increased dispersion in the derived Period-Luminosity relations. In this paper, we explore, in detail, a method that transforms singl…

Evidence for a gap in the envelope mass fraction of sub-Saturns
Luis Thomas, Louise D. Nielsen, Lorena Acu\~na-Aguirre, Alex Cridland
https://arxiv.org/abs/2509.12120 https://…

Evidence for a gap in the envelope mass fraction of sub-Saturns
Under the core-accretion model, gas giants form via runaway accretion. This process starts when the mass of the accreted envelope becomes equal to the mass of the core. Here, we model a population of warm sub-Saturns to search for imprints of their formation history in their internal structure. Using the GAS gianT modeL for Interiors (GASTLI), we calculate a grid of interior structure models on which we perform retrievals for our sample of 28 sub-Saturns to derive their envelope mass fractions …

Brownian motion on the Fubini extension space and applications
Hamed Amini, Nina H. Amini, Sofiane Chalal, Gaoyue Guo
https://arxiv.org/abs/2509.12096 https://

Brownian motion on the Fubini extension space and applications
The aim of this paper is to establish a certain equivalence between a Brownian motion on a Fubini extension space and a collection of essentially pairwise independent Brownian motions on the marginal sample spaces. This equivalence allows us to state a Girsanov theorem that preserves pairwise independence and to formulate graphon stochastic differential equations as a single McKean-Vlasov type equation driven by a standard Brownian motion.

Enhancing Diffusion-Based Sampling with Molecular Collective Variables
Juno Nam, B\'alint M\'at\'e, Artur P. Toshev, Manasa Kaniselvan, Rafael G\'omez-Bombarelli, Ricky T. Q. Chen, Brandon Wood, Guan-Horng Liu, Benjamin Kurt Miller
https://arxiv.org/abs/2510.11923

Enhancing Diffusion-Based Sampling with Molecular Collective Variables
Diffusion-based samplers learn to sample complex, high-dimensional distributions using energies or log densities alone, without training data. Yet, they remain impractical for molecular sampling because they are often slower than molecular dynamics and miss thermodynamically relevant modes. Inspired by enhanced sampling, we encourage exploration by introducing a sequential bias along bespoke, information-rich, low-dimensional projections of atomic coordinates known as collective variables (CVs)…

About the Multiplicative Inverse of a Non-Zero-Mean Gaussian Process
Marco Lanucara
https://arxiv.org/abs/2509.11650 https://arxiv.org/pdf/2509.11650

About the Multiplicative Inverse of a Non-Zero-Mean Gaussian Process
We study the spectral properties of a stochastic process obtained by multiplicative inversion of a non-zero-mean Gaussian process. We show that its autocorrelation and power spectrum exist for most regular processes, and we find a convergent series expansion of the autocorrelation function in powers of the ratio between mean and standard deviation of the underlying Gaussian process. We apply the results to two sample processes, and we validate the theoretical results with simulations based on s…

Evidence for the Meissner effect in the nickelate superconductor La3Ni2O7-delta single crystal using diamond quantum sensors
Lin Liu, Jianning Guo, Deyuan Hu, Guizhen Yan, Yuzhi Chen, Lunxuan Yu, Meng Wang, Xiao-Di Liu, Xiaoli Huang
https://arxiv.org/abs/2509.11557

Evidence for the Meissner effect in the nickelate superconductor La3Ni2O7-delta single crystal using diamond quantum sensors
Quantum sensing with nitrogen-vacancy (NV) centers in diamond enables the characterization of magnetic properties in the extreme situation of tiny sample with defects. Recent studies have reported superconductivity in La3Ni2O7-delta under pressure, with zero-resistance near 80 K, though the Meissner effect remains debated due to low superconducting volume fractions and limited high-pressure magnetic measurement techniques. In this work, we use diamond quantum sensors and four-probe detection to…

Towards a precise measurement of the $\Lambda_c^ /D^0$ ratio at RHIC
Joseph D. Osborn
https://arxiv.org/abs/2509.10772 https://arxiv.org/pdf/2509.10772

Towards a precise measurement of the $Λ_c^+/D^0$ ratio at RHIC
sPHENIX is a next-generation experiment at RHIC for jet and heavy-flavor physics which was fully commissioned during 2023 and 2024. Using its novel streaming-readout-capable, precision tracking system, sPHENIX collected 100 billion unbiased $p$$+$$p$ collisions, and a further sample of minimum-bias Au-Au collisions, in Run-24. A key measurement of the sPHENIX heavy flavor physics program is the comparison of $Λ_c^+$ to $D^0$ differential yields in both Au+Au and $p$$+$$p$ collisions, which pro…

Outlier-Resistant Heterogeneous Treatment Effect Estimation in HDLSS Settings via GAT--CVAE Framework
Byeonghee Lee, Joonsung Kang
https://arxiv.org/abs/2509.10787 https://

Outlier-Resistant Heterogeneous Treatment Effect Estimation in HDLSS Settings via GAT--CVAE Framework
We introduce a robust framework for heterogeneous treatment effect (HTE) estimation tailored to high-dimensional low sample size (HDLSS) settings. By combining Graph Attention Networks (GAT) to capture structural dependencies among confounders with a Conditional Variational Autoencoder (CVAE) for latent representation learning, our method expands the sample space and performs clustering that integrates even outlier sets into coherent subgroups. Clusterwise causal effects are then estimated usin…

Ego-Vision World Model for Humanoid Contact Planning
Hang Liu, Yuman Gao, Sangli Teng, Yufeng Chi, Yakun Sophia Shao, Zhongyu Li, Maani Ghaffari, Koushil Sreenath
https://arxiv.org/abs/2510.11682

Ego-Vision World Model for Humanoid Contact Planning
Enabling humanoid robots to exploit physical contact, rather than simply avoid collisions, is crucial for autonomy in unstructured environments. Traditional optimization-based planners struggle with contact complexity, while on-policy reinforcement learning (RL) is sample-inefficient and has limited multi-task ability. We propose a framework combining a learned world model with sampling-based Model Predictive Control (MPC), trained on a demonstration-free offline dataset to predict future outco…

Dimension-Free Minimax Rates for Learning Pairwise Interactions in Attention-Style Models
Shai Zucker, Xiong Wang, Fei Lu, Inbar Seroussi
https://arxiv.org/abs/2510.11789 https:…

Dimension-Free Minimax Rates for Learning Pairwise Interactions in Attention-Style Models
We study the convergence rate of learning pairwise interactions in single-layer attention-style models, where tokens interact through a weight matrix and a non-linear activation function. We prove that the minimax rate is $M^{-\frac{2β}{2β+1}}$ with $M$ being the sample size, depending only on the smoothness $β$ of the activation, and crucially independent of token count, ambient dimension, or rank of the weight matrix. These results highlight a fundamental dimension-free statistical efficie…

High-resolution electric field imaging based on intermittent-contact mode scanning NV center electrometry
Zhi Cheng, Zhiwei Yu, Mengqi Wang, Lingfeng Yang, Zihao Cui, Ya Wang, Pengfei Wang
https://arxiv.org/abs/2509.11586

High-resolution electric field imaging based on intermittent-contact mode scanning NV center electrometry
Scanning nitrogen-vacancy (NV) center electrometry has shown potential for quantitative quantum imaging of electric fields at the nanoscale. However, achieving nanoscale spatial resolution remains a challenge since employing gradiometry to overcome electrostatic screening causes resolution-limiting trade-offs including the averaging effect and the sensor-sample proximity. Here, we demonstrate a scanning NV center protocol that achieves an enhanced spatial resolution of approximately 10 nm. We d…

Precise boron abundance in a sample of metal-poor stars from far-ultraviolet lines
Monique Spite, Beatriz Barbuy, Kefeng Tan
https://arxiv.org/abs/2510.11594 https://

Precise boron abundance in a sample of metal-poor stars from far-ultraviolet lines
The light elements beryllium (Be; $Z=4$) and boron (B; $Z=5$) are mainly produced by spallation reactions between cosmic rays and carbon (C; $Z=6$), nitrogen (N; $Z=7$), and oxygen (O; $Z=8$) nuclei. Only traces of Be or B would have been produced in the Big Bang, but there could be a contribution from the $ν$-process in type II supernovae. Their abundances at very low metallicities have been debated in the literature, with the aim of understanding their origin. Our aim is to derive the bo…

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 …

Improved Rates for Stochastic Variance-Reduced Difference-of-Convex Algorithms
Anh Duc Nguyen, Alp Yurtsever, Suvrit Sra, Kim-Chuan Toh
https://arxiv.org/abs/2509.11657 https://…

Improved Rates for Stochastic Variance-Reduced Difference-of-Convex Algorithms
In this work, we propose and analyze DCA-PAGE, a novel algorithm that integrates the difference-of-convex algorithm (DCA) with the ProbAbilistic Gradient Estimator (PAGE) to solve structured nonsmooth difference-of-convex programs. In the finite-sum setting, our method achieves a gradient computation complexity of $O(N + N^{1/2}\varepsilon^{-2})$ with sample size $N$, surpassing the previous best-known complexity of $O(N + N^{2/3}\varepsilon^{-2})$ for stochastic variance-reduced (SVR) DCA meth…

Task-Agnostic Learnable Weighted-Knowledge Base Scheme for Robust Semantic Communications
Shiyao Jiang, Jian Jiao, Xingjian Zhang, Ye Wang, Dusit Niyato, Qinyu Zhang
https://arxiv.org/abs/2509.11636

Task-Agnostic Learnable Weighted-Knowledge Base Scheme for Robust Semantic Communications
With the emergence of diverse and massive data in the upcoming sixth-generation (6G) networks, the task-agnostic semantic communication system is regarded to provide robust intelligent services. In this paper, we propose a task-agnostic learnable weighted-knowledge base semantic communication (TALSC) framework for robust image transmission to address the real-world heterogeneous data bias in KB, including label flipping noise and class imbalance. The TALSC framework incorporates a sample confid…

Unified Distributed Estimation Framework for Sufficient Dimension Reduction Based on Conditional Moments
Hongying Li, Minyi Zhu, Yaqi Cao, Xinyi Xu
https://arxiv.org/abs/2509.11455

Unified Distributed Estimation Framework for Sufficient Dimension Reduction Based on Conditional Moments
Nowadays, massive datasets are typically dispersed across multiple locations, encountering dual challenges of high dimensionality and huge sample size. Therefore, it is necessary to explore sufficient dimension reduction (SDR) methods for distributed data. In this paper, we first propose an exact distributed estimation of sliced inverse regression, which substantially improves computational efficiency while obtaining identical estimation as that on the full sample. Then, we propose a unified di…

When you say "we don't need user research, I already know what users want" this is what you look like
#ux #UXDesign #userresearch

Hurst Index of Gamma-Ray Burst Light Curves and Its Statistical Study
Ruo-Yu Guan, Feifei Wang, Yuan-Chuan Zou
https://arxiv.org/abs/2509.11631 https://arx…

Hurst Index of Gamma-Ray Burst Light Curves and Its Statistical Study
Gamma-ray bursts (GRBs) rank among the most powerful astrophysical phenomena, characterized by complex and highly variable prompt emission light curves that reflect the dynamics of their central engines. In this work, we analyze a sample of 163 long-duration GRBs detected by the Burst and Transient Source Experiment (BATSE), applying detrended fluctuation analysis (DFA) to derive the Hurst index as a quantitative descriptor of temporal correlations in the light curves. We further explore statis…

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…

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.

High-Probability Bounds For Heterogeneous Local Differential Privacy
Maryam Aliakbarpour, Alireza Fallah, Swaha Roy, Ria Stevens
https://arxiv.org/abs/2510.11895 https://…

High-Probability Bounds For Heterogeneous Local Differential Privacy
We study statistical estimation under local differential privacy (LDP) when users may hold heterogeneous privacy levels and accuracy must be guaranteed with high probability. Departing from the common in-expectation analyses, and for one-dimensional and multi-dimensional mean estimation problems, we develop finite sample upper bounds in $\ell_2$-norm that hold with probability at least $1-β$. We complement these results with matching minimax lower bounds, establishing the optimality (up to 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.

Which one do you use the most, while not at work, but in your free personal time?
Please consider boosting for a larger sample size. Thank you.
#poll #computing #fediverse

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 …

This guy made a Synthetic Aperture Radar (i.e. a radar that gives you camera-like pictures) mounted on a drone. Scroll to the bottom for actual sample pictures and a movie. Lots of tech detail and open-source designs and software.
https://hforsten.com/synthetic-apertur

Central-star extinctions towards planetary nebulae
Alexander Csukai, Albert A. Zijlstra, Iain McDonald, Orsola De Marco
https://arxiv.org/abs/2509.10621 https://

Central-star extinctions towards planetary nebulae
Planetary nebulae trace the hottest and most luminous phase of evolution of solar-type stars. We use these hot, bright stars to investigate extinctions towards a complete sample of 262 confirmed PNe with large angular diameters, which have the most reliable photometry and hottest central stars. For 162 of these PNe, we identify central stars, produce spectral energy distributions from survey data using PySSED, then fit reddened model spectra to the observed photometry to obtain extinctions accu…

Thermal diffusivity characterization of impacted composites using evaporative cryocooling excitation and inverse physics-informed neural networks
Pengfei Zhu, Hai Zhang, Stefano Sfarra, Fabrizio Sarasini, Rub\'en Usamentiaga, Gunther Steenackers, Clemente Ibarra-Castanedo, Xavier Maldague
https://arxiv.org/abs/2509.10898

Thermal diffusivity characterization of impacted composites using evaporative cryocooling excitation and inverse physics-informed neural networks
The thermal diffusivity measurement of impacted composites using pulsed methods presents an ill-posed inverse problem influenced by multiple factors such as sample thickness, cooling duration, and excitation energy. In this study, a novel excitation method, evaporative cryocooling, was introduced for measuring the thermal diffusivity of tested samples. Compared to conventional excitation modalities, evaporative cryocooling excitation is compact, portable, and low cost. However, evaporative cryo…

An optimal two-step estimation approach for two-phase studies
Qingning Zhou, Kin Yau Wong
https://arxiv.org/abs/2510.11587 https://arxiv.org/pdf/2510.11587…

An optimal two-step estimation approach for two-phase studies
Two-phase sampling is commonly adopted for reducing cost and improving estimation efficiency. In many two-phase studies, the outcome and some cheap covariates are observed for a large sample in Phase I, and expensive covariates are obtained for a selected subset of the sample in Phase II. As a result, the analysis of the association between the outcome and covariates faces a missing data problem. Complete-case analysis, which relies solely on the Phase II sample, is generally inefficient. In th…

The dependence of the Type Ia Supernova colour-luminosity relation on their host galaxy properties
S. Ramaiya, M. Vincenzi, M. J. Jarvis, P. Wiseman, M. Sullivan
https://arxiv.org/abs/2509.12035

The dependence of the Type Ia Supernova colour-luminosity relation on their host galaxy properties
Using the Dark Energy Survey 5-year sample, we determine the properties of type Ia supernova (SN Ia) host galaxies across a wide multi-wavelength range - from the optical to far-infrared - including data from the $Herschel$ and $Spitzer$ space telescopes. We categorise the SNe Ia into three distinct groups according to the distribution of their host galaxies on the star-formation rate (SFR) - stellar mass ($M_\star$) plane. Each region comprises host galaxies at distinct stages in their evoluti…

E-ROBOT: a dimension-free method for robust statistics and machine learning via Schr\"odinger bridge
Davide La Vecchia, Hang Liu
https://arxiv.org/abs/2509.11532 https://…

E-ROBOT: a dimension-free method for robust statistics and machine learning via Schrödinger bridge
We propose the Entropic-regularized Robust Optimal Transport (E-ROBOT) framework, a novel method that combines the robustness of ROBOT with the computational and statistical benefits of entropic regularization. We show that, rooted in the Schrödinger bridge problem theory, E-ROBOT defines the robust Sinkhorn divergence $\overline{W}_{\varepsilon,λ}$, where the parameter $λ$ controls robustness and $\varepsilon$ governs the regularization strength. Letting $n\in \mathbb{N}$ denote the 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…

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

Magnetic Decay Index Profile and Coronal Mass Ejection Speed
Bernhard Kliem, Georgios Chintzoglou, Tibor T\"or\"ok, Jie Zhang
https://arxiv.org/abs/2510.11889 https://…

Magnetic Decay Index Profile and Coronal Mass Ejection Speed
We study the relationship between the speed of coronal mass ejections (CMEs) and the height profile of the ambient magnetic field, quantified by its decay index, n(h). Our sample is composed of 15 very fast CMEs (Vcme > 1500 km/s; all halo CMEs) and 22 halo CMEs below this speed limit from Solar Cycle 23. The very fast CMEs yield a high correlation of 0.81 between Vcme and the slope of n(h) in a height range above the onset height of the torus instability if one extremely fast outlier, which cl…

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 …

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…

TOI-3288 b and TOI-4666 b: two gas giants transiting low-mass stars characterised by NIRPS
Yolanda G. C. Frensch, Fran\c{c}ois Bouchy, Gaspare Lo Curto, Alexandrine L'Heureux, Roseane de Lima Gomes, Jo\~ao Faria, Xavier Dumusque, Lison Malo, Marion Cointepas, Avidaan Srivastava, Xavier Bonfils, Elisa Delgado-Mena, Nicola Nari, Khaled Al Moulla, Romain Allart, Jose M. Almenara, \'Etienne Artigau, Khalid Barkaoui, Fr\'ed\'erique Baron, Susana C. C. Barros, Bj\"orn Be…

TOI-3288 b and TOI-4666 b: two gas giants transiting low-mass stars characterised by NIRPS
Gas giant planets orbiting low-mass stars are uncommon outcomes of planet formation. Increasing the sample of well-characterised giants around early M dwarfs will enable population-level studies of their properties, offering valuable insights into their formation and evolutionary histories. We aim to characterise giant exoplanets transiting M dwarfs identified by TESS. High-resolution spectroscopic data are obtained in the optical and nIR, combining HARPS and NIRPS. We derive RVs via the cross-…

The impact of external gas accretion on the distribution of HI gas in galaxies
Qianhan Zhang, Min Bao, Yanmei Chen, Niankun Yu, Yong Shi, Luis C. Ho
https://arxiv.org/abs/2509.11891

The impact of external gas accretion on the distribution of HI gas in galaxies
Using the data from Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) and HI-MaNGA surveys, we build a sample of 37 gas-star misaligned galaxies with robust HI detections, which are believed to have undergone external gas accretion processes. Both star-forming (SF) and quiescent (QS) misaligned galaxies exhibit narrower HI linewidths compared to their gas-star aligned controls. The HI profiles of SF misaligned galaxies tend to be single-peaked, displaying a slightly higher fraction of…

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…

Group Diffusion: Enhancing Image Generation by Unlocking Cross-Sample Collaboration
Sicheng Mo, Thao Nguyen, Richard Zhang, Nick Kolkin, Siddharth Srinivasan Iyer, Eli Shechtman, Krishna Kumar Singh, Yong Jae Lee, Bolei Zhou, Yuheng Li
https://arxiv.org/abs/2512.10954

An FPCA-Enhanced Ensemble Learning Framework for Photometric Identification of Type Ia Supernovae
Moonzarin Reza, Lifan Wang, Lei Hu
https://arxiv.org/abs/2510.09990 https://

An FPCA-Enhanced Ensemble Learning Framework for Photometric Identification of Type Ia Supernovae
Type Ia supernovae (SNe Ia) are essential tools for addressing key cosmic questions, including the Hubble tension and the nature of dark energy. Modern surveys are predominantly photometry-based, making the construction of a clean photometric SNe Ia sample crucial. In this study, we investigate whether functional principal component analysis (FPCA) scores derived from photometric light curves, combined with ensemble learning, can reliably distinguish SNe Ia from other transients using the PLAsT…

Macroeconomic Forecasting and Machine Learning
Ta-Chung Chi (Kevin), Ting-Han Fan (Kevin), Raffaele M. Ghigliazza (Kevin), Domenico Giannone (Kevin), Zixuan (Kevin), Wang
https://arxiv.org/abs/2510.11008

Macroeconomic Forecasting and Machine Learning
We forecast the full conditional distribution of macroeconomic outcomes by systematically integrating three key principles: using high-dimensional data with appropriate regularization, adopting rigorous out-of-sample validation procedures, and incorporating nonlinearities. By exploiting the rich information embedded in a large set of macroeconomic and financial predictors, we produce accurate predictions of the entire profile of macroeconomic risk in real time. Our findings show that regulariza…

White Dwarfs with Infrared Excess in the HET Dark Energy Experiment
Rudy A. Morales, Barbara G. Castanheira, Jayden Blanchard, Detlev Koester, P\'eter N\'emeth, S. O. Kepler, Erin Mentuch Cooper, Karl Gebhardt
https://arxiv.org/abs/2509.12116

White Dwarfs with Infrared Excess in the HET Dark Energy Experiment
White dwarfs with infrared excess emission provide a window into the late stages of stellar evolution and the dynamics of circumstellar environments. Using data from the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX), we characterized 30 white dwarfs exhibiting infrared excess, including 29 DA and 1 DB stars. While an infrared excess can arise from dusty disks or cool (sub-)stellar companions, our sample is limited to stellar companions due to our selection based on SDSS photometry, whi…

Out of the following mobile operating systems, which one do you use the most, not at work, but in your free personal time?
Please consider boosting for a larger sample size. Thank you.
#poll #os #mobile

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…

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 …

A New Population of Point-like, Narrow-line Objects Revealed by the James Webb Space Telescope
Haojing Yan (University of Missouri-Columbia), Bangzheng Sun (University of Missouri-Columbia), Riley Shive (University of Missouri-Columbia)
https://arxiv.org/abs/2509.12177

A New Population of Point-like, Narrow-line Objects Revealed by the James Webb Space Telescope
We report a new population of objects discovered using the data from the James Webb Space Telescope, which are characterized by their point-like morphology and narrow permitted emission lines. Our sample includes nine objects found in three JWST wide survey fields, which have z=3.624 to 5.378 and M_B ~ -18.3 to -21.4 mag. Their light distributions follow gaussian profiles, with the full-width-at-half-maximum (FWHM) values only 3.7%--34.6% larger than those of the point spread functions. Their s…

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.

Quasi-Periodic Oscillations in Gamma-Ray Bursts' Prompt Light Curves
Mariusz Tarnopolski
https://arxiv.org/abs/2510.11136 https://arxiv.org/pdf/2510.11…

Quasi-Periodic Oscillations in Gamma-Ray Bursts' Prompt Light Curves
I report on the discovery of 34 new quasi-periodic oscillations (QPOs) in the prompt light curves of long gamma-ray bursts (GRBs) from the Swift/BAT catalog: with one or more constant leading periods, as well as several chirping signals. This is the largest homogenously identified sample or GRB QPOs to date. The presence of QPOs suggests the existence of characteristic time scales that at least in some GRBs might be related to the dynamical properties of plasma trajectories in the accretion dis…

MANGOS II: Five new giant planets orbiting low-mass stars
G. Dransfield, M. Timmermans, D. Sebastian, B. V. Rackham, A. Burgasser, K. Barkaoui, A. H. M. J. Triaud, M. Gillon, J. M. Almenara, S. L. Casewell, K. A. Collins, A. Fukui, C. Jano-Munoz, S. Kanodia, N. Narita, E. Palle, M. G. Scott, A. Soubkiou, A. Stokholm, J. Audenaert, G. \'A. Bakos, Y. Beletsky, Z. L. de Beurs, Z. Benkhaldoun, A. Burdanov, R. P. Butler, D. Caldwell, J. D. Crane, Y. T. Davis, B. O. Demory, E. Ducrot, Y.…

MANGOS II: Five new giant planets orbiting low-mass stars
Giant planets orbiting low-mass stars on short orbits present a conundrum, as in the most extreme cases their existence cannot be reconciled with current models of core accretion. Therefore, surveys dedicated to finding these rare planets have a key role to play by growing the sample to overcome small number statistics. In this work we present MANGOS, a programme dedicated to the search for giant objects (planets, brown dwarfs, and low-mass stars) orbiting M dwarfs. We report on the discovery o…

A census of quiescent galaxies across $0.5 < z < 8$ with JWST/MIRI: Mass-dependent number density evolution of quiescent galaxies in the early Universe
Tiancheng Yang, Tao Wang, Ke Xu, Hanwen Sun, Luwenjia Zhou, Lizhi Xie, Gabriella De Lucia, Claudia del P. Lagos, Kai Wang, Fabio Fontanot, Yuxuan Wu, Shiying Lu, Longyue Chen, Michaela Hirschmann
https://

A census of quiescent galaxies across $0.5 < z < 8$ with JWST/MIRI: Mass-dependent number density evolution of quiescent galaxies in the early Universe
JWST observations reveal numerous quiescent galaxies (QGs) at high redshift ($z \sim 4-8$), challenging models of early galaxy formation and quenching. Accurate number density estimates are crucial for comparison with theory but remain uncertain. We systematically study QGs at $0.5 < z < 8$ using a mass-complete sample from the JWST/PRIMER survey with deep NIRCam and MIRI imaging. The MIRI data, probing rest-frame near-infrared at $z \sim 3-8$, are vital for robust stellar mass measurement and …

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…

Crosslisted article(s) found for math.OC. https://arxiv.org/list/math.OC/new
[1/1]:
- Optimal control of Volterra integral diffusions and application to contract theory
Dylan Possama\"i, Mehdi Talbi
https://arxiv.org/abs/2511.09701 https://mastoxiv.page/@arXiv_mathPR_bot/115547093766733637
- Generalized infinite dimensional Alpha-Procrustes based geometries
Salvish Goomanee, Andi Han, Pratik Jawanpuria, Bamdev Mishra
https://arxiv.org/abs/2511.09801 https://mastoxiv.page/@arXiv_statML_bot/115547135711272091
- Sample Complexity of Quadratically Regularized Optimal Transport
Alberto Gonz\'alez-Sanz, Eustasio del Barrio, Marcel Nutz
https://arxiv.org/abs/2511.09807 https://mastoxiv.page/@arXiv_mathST_bot/115546975796760368
- On the Convergence of Overparameterized Problems: Inherent Properties of the Compositional Struct...
Arthur Castello Branco de Oliveira, Dhruv Jatkar, Eduardo Sontag
https://arxiv.org/abs/2511.09810 https://mastoxiv.page/@arXiv_csLG_bot/115547543989283588
- Implicit Multiple Tensor Decomposition
Kunjing Yang, Libin Zheng, Minru Bai
https://arxiv.org/abs/2511.09916 https://mastoxiv.page/@arXiv_mathNA_bot/115547169767663335
- Theoretical Analysis of Resource-Induced Phase Transitions in Estimation Strategies
Takehiro Tottori, Tetsuya J. Kobayashi
https://arxiv.org/abs/2511.10184 https://mastoxiv.page/@arXiv_physicsbioph_bot/115546979073652600
- Zeroes and Extrema of Functions via Random Measures
Athanasios Christou Micheas
https://arxiv.org/abs/2511.10293 https://mastoxiv.page/@arXiv_statME_bot/115547493525198835
- Operator Models for Continuous-Time Offline Reinforcement Learning
Nicolas Hoischen, Petar Bevanda, Max Beier, Stefan Sosnowski, Boris Houska, Sandra Hirche
https://arxiv.org/abs/2511.10383 https://mastoxiv.page/@arXiv_statML_bot/115547254989932993
- On topological properties of closed attractors
Wouter Jongeneel
https://arxiv.org/abs/2511.10429 https://mastoxiv.page/@arXiv_mathDS_bot/115547276594491411
- Learning parameter-dependent shear viscosity from data, with application to sea and land ice
Gonzalo G. de Diego, Georg Stadler
https://arxiv.org/abs/2511.10452 https://mastoxiv.page/@arXiv_mathNA_bot/115547323782478749
- Formal Verification of Control Lyapunov-Barrier Functions for Safe Stabilization with Bounded Con...
Jun Liu
https://arxiv.org/abs/2511.10510 https://mastoxiv.page/@arXiv_eessSY_bot/115547429321496393
- Direction-of-Arrival and Noise Covariance Matrix joint estimation for beamforming
Vitor Gelsleichter Probst Curtarelli
https://arxiv.org/abs/2511.10639 https://mastoxiv.page/@arXiv_eessAS_bot/115547188796143762
toXiv_bot_toot

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…

The AURORA Survey: Ionizing Photon Production Efficiency with Minimal Nebular Dust Attenuation Systematics
Anthony J. Pahl, Alice Shapley, Naveen A. Reddy, Ryan Sanders, Michael W. Topping, Danielle A. Berg, Callum T. Donnan, James S. Dunlop, Richard S. Ellis, N. M. F\"orster Schreiber, K. Glazebrook, Derek J. McLeod, Max Pettini, Daniel Schaerer
https://

The AURORA Survey: Ionizing Photon Production Efficiency with Minimal Nebular Dust Attenuation Systematics
We present ionizing photon production efficiencies ($ξ_{\rm ion}$) for 63 z=1.5-6.9 star-forming galaxies using precise nebular dust attenuation corrections from the JWST/AURORA survey. A subset of objects within AURORA have individually-determined nebular dust attenuation curves, which vary significantly in shape and normalization, resulting in reduced systematic uncertainty when constraining the total attenuation of H$α$ luminosity, and thus the intrinsic ionizing output within our sample. …

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 …

Efficiently Generating Correlated Sample Paths from Multi-step Time Series Foundation Models
Ethan Baron, Boris Oreshkin, Ruijun Ma, Hanyu Zhang, Kari Torkkola, Michael W. Mahoney, Andrew Gordon Wilson, Tatiana Konstantinova
https://arxiv.org/abs/2510.02224

Efficiently Generating Correlated Sample Paths from Multi-step Time Series Foundation Models
Many time series applications require access to multi-step forecast trajectories in the form of sample paths. Recently, time series foundation models have leveraged multi-step lookahead predictions to improve the quality and efficiency of multi-step forecasts. However, these models only predict independent marginal distributions for each time step, rather than a full joint predictive distribution. To generate forecast sample paths with realistic correlation structures, one typically resorts to …

The ZZ Ceti Instability Strip for The Most Massive White Dwarf Pulsators
Gracyn Jewett, Mukremin Kilic, Adam Moss, Alejandro H. C\'orsico, Matthew J. Green, Murat Uzundag, Pierre Bergeron, Warren R. Brown, Francisco C. De Ger\'onimo, Alberto Rebassa-Mansergas, Alex J. Brown, Vikram S. Dhillon, Stuart Littlefair
https://arxiv.org/ab…

The ZZ Ceti Instability Strip for The Most Massive White Dwarf Pulsators
We present time-series photometry of 31 massive DA white dwarfs with $M\gtrsim 0.9~M_\odot$ within the ZZ Ceti instability strip from the Montreal White Dwarf Database 100 pc sample. The majority of the targets had no previous time-series photometry available, though several were classified as non-variable or potential pulsators in the literature. Out of the 31 candidates, we confirm 16 as pulsating. Our observations at three observatories have led us to discover the most massive pulsating whit…

A Black-Box Debiasing Framework for Conditional Sampling
Han Cui, Jingbo Liu
https://arxiv.org/abs/2510.11071 https://arxiv.org/pdf/2510.11071

A Black-Box Debiasing Framework for Conditional Sampling
Conditional sampling is a fundamental task in Bayesian statistics and generative modeling. Consider the problem of sampling from the posterior distribution $P_{X|Y=y^*}$ for some observation $y^*$, where the likelihood $P_{Y|X}$ is known, and we are given $n$ i.i.d. samples $D=\{X_i\}_{i=1}^n$ drawn from an unknown prior distribution $π_X$. Suppose that $f(\hatπ_{X^n})$ is the distribution of a posterior sample generated by an algorithm (e.g. a conditional generative model or the Ba…

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…

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…

Insights into Planet Formation from the Ages, Masses, and Elemental Abundances of Host Stars
Xunzhou Chen, Tiancheng Sun, Lifei Ye
https://arxiv.org/abs/2510.10092 https://

Insights into Planet Formation from the Ages, Masses, and Elemental Abundances of Host Stars
How planetary systems form and evolve is a key question in astronomy. Revealing how host star properties, such as elemental abundances, age, and mass, differ from those of non-host stars, and how they correlate with planetary characteristics such as radius, provides new insights into the formation and evolutionary pathways of planetary systems. We determine precise ages for 18890 dwarfs and subgiants from the LAMOST-Kepler-Gaia sample with a mean age uncertainty of about 15 percent (median abou…

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…

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 …

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…

Double Descent as a Lens for Sample Efficiency in Autoregressive vs. Discrete Diffusion Models
Ahmad Fraij, Sam Dauncey
https://arxiv.org/abs/2509.24974 https://

Double Descent as a Lens for Sample Efficiency in Autoregressive vs. Discrete Diffusion Models
Data scarcity drives the need for more sample-efficient large language models. In this work, we use the double descent phenomenon to holistically compare the sample efficiency of discrete diffusion and autoregressive models. We show that discrete diffusion models require larger capacity and more training epochs to escape their underparameterized regime and reach the interpolation threshold. In the strongly overparameterized regime, both models exhibit similar behavior, with neither exhibiting a…

JWST Catches a Strongly Gravitationally Lensed AGN In Transition from Type II to Type I
Michael K Florian, Michael D Gladders, Gourav Khullar, Keren Sharon, Aidan P Cloonan, Eirk Solhaug, Brian Welch, Matthew Bayliss, Hakon Dahle, Taylor A Hutchison, Jane R Rigby
https://arxiv.org/abs/2510.10376

JWST Catches a Strongly Gravitationally Lensed AGN In Transition from Type II to Type I
JWST has enabled the discovery of a statistical sample of obscured (type II) active galactic nuclei (AGN) at cosmic noon. Studies comparing those type II AGN with type I AGN at that epoch have reinforced the long-standing idea of an evolutionary link between those classes of objects. Mergers, the idea goes, disturb the morphologies and angular momentum of galaxies. The disruption of angular momentum allows material to be funneled toward galactic cores, sparking AGN activity and potentially also…

Black Holes in the Shadow: The Missing High-Ionization Lines in the Earliest JWST AGNs
Greta Zucchi, Xihan Ji, Piero Madau, Roberto Maiolino, Ignas Joudzbalis, Francesco D'Eugenio, Sophia Geris, Yuki Isobe
https://arxiv.org/abs/2510.10772

Black Holes in the Shadow: The Missing High-Ionization Lines in the Earliest JWST AGNs
Observations with the James Webb Space Telescope (JWST) have uncovered a substantial population of high-redshift, broad-line active galactic nuclei (AGNs), whose properties challenge standard models of black hole growth and AGN emission. We analyze a spectroscopic sample of 34 Type 1 AGNs from the JWST Advanced Deep Survey (JADES) survey, spanning redshifts 1.7 < z < 9, to constrain the physical nature of the accretion flows powering these sources with broad-line diagnostics statistically for t…

Sample-Efficient Differentially Private Fine-Tuning via Gradient Matrix Denoising
Ali Dadsetan, Frank Rudzicz
https://arxiv.org/abs/2510.01137 https://arxi…

Sample-Efficient Differentially Private Fine-Tuning via Gradient Matrix Denoising
We address the challenge of sample efficiency in differentially private fine-tuning of large language models (LLMs) using DP-SGD. While DP-SGD provides strong privacy guarantees, the added noise significantly increases the entropy of gradient matrices, disrupting their low-rank structure and slowing optimization. We propose a post-processing algorithm that leverages random matrix theory to denoise gradients, restore low-rank structure, and improve alignment with the original signal. Applied to …

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…

Measuring the Evolution of Bulge, Disk and Colour Gradients in HST Observations of Galaxies with 3D Modelling
N. Welikala, L. Miller, A. N. Taylor, G. Congedo
https://arxiv.org/abs/2510.11156

Measuring the Evolution of Bulge, Disk and Colour Gradients in HST Observations of Galaxies with 3D Modelling
We measure galaxy structural properties and colour gradients using HST images to trace the evolution of galaxy components. We jointly fit 3D bulge and disk models to 2505 galaxies in GOODS-South across seven bands (bvizYJH) to IAB = 25.5, accounting for different component ellipticities and inclination-dependent dust extinction. Extinction strongly affects structural parameters and colour gradients in ~26% of the sample - primarily edge-on galaxies with central obscuration (B-band face-on optic…

Environmental Regulation of Dust and Star Formation Unveiled by Subaru Dual Narrow-band Imaging: Degree-scale Balmer Decrement Mapping across a z = 0.9 Supercluster
Zhaoran Liu, Tadayuki Kodama, Brian C. Lemaux, Mariko Kubo, Jose Manuel P\'erez-Mart\'inez, Yusei Koyama, Ichi Tanaka, Kazuki Daikuhara, Roy R. Gal, Denise Hung, Masahiro Konishi, Kosuke Kushibiki, Ronaldo Laishram, Lori M. Lubin, Kentaro Motohara, Hidenori Takahashi

Environmental Regulation of Dust and Star Formation Unveiled by Subaru Dual Narrow-band Imaging: Degree-scale Balmer Decrement Mapping across a z = 0.9 Supercluster
We present results from a dual narrow-band imaging survey targeting the CL1604 supercluster at z = 0.9 using the Subaru Telescope. By combining the NB921 filter on HSC and the NB1244 filter on SWIMS, we can detect redshifted H$α$ and H$β$ emission lines from the supercluster. This unique technique allows us to measure both star formation rates and dust extinction for a sample of 94 emission-line galaxies across the supercluster. We find that dust extinction, estimated from the Balmer decremen…