Tootfinder

Now out in #TMLR:
🍇 GRAPES: Learning to Sample Graphs for Scalable Graph Neural Networks 🍇
There's lots of work on sampling subgraphs for GNNs, but relatively little on making this sampling process _adaptive_. That is, learning to select the data from the graph that is relevant for your task.
We introduce an RL-based and a GFLowNet-based sampler and show that the approach perf…

Improving Reinforcement Learning Sample-Efficiency using Local Approximation
Mohit Prashant, Arvind Easwaran
https://arxiv.org/abs/2507.12383 https://

Improving Reinforcement Learning Sample-Efficiency using Local Approximation
In this study, we derive Probably Approximately Correct (PAC) bounds on the asymptotic sample-complexity for RL within the infinite-horizon Markov Decision Process (MDP) setting that are sharper than those in existing literature. The premise of our study is twofold: firstly, the further two states are from each other, transition-wise, the less relevant the value of the first state is when learning the $ε$-optimal value of the second; secondly, the amount of 'effort', sample-complexity-wise, ex…

Sample-optimal single-copy quantum state tomography via shallow depth measurements
Gyungmin Cho, Dohun Kim
https://arxiv.org/abs/2509.12703 https://arxiv.o…

Sample-optimal single-copy quantum state tomography via shallow depth measurements
Quantum state tomography (QST) is one of the fundamental problems in quantum information. Among various metrics, sample complexity is widely used to evaluate QST algorithms. While multi-copy measurements are known to achieve optimal sample complexity, they are challenging to implement on near-term quantum devices. In practice, single-copy measurements with shallow-depth circuits are more feasible. Although a near-optimal QST algorithm under single-qubit measurements has recently been proposed, …

Two-Sample Testing with Missing Data via Energy Distance: Weighting and Imputation Approaches
Danijel G. Aleksi\'c, Bojana Milo\v{s}evi\'c
https://arxiv.org/abs/2508.11421

Two-Sample Testing with Missing Data via Energy Distance: Weighting and Imputation Approaches
In this paper, we address the problem of two-sample testing in the presence of missing data under a variety of missingness mechanisms. Our focus is on the well-known energy distance-based two-sample test. In addition to the standard complete-case approach, we propose a modification of the test statistic that incorporates all available data, utilizing appropriate weights. The asymptotic null distribution of the test statistic is derived and two resampling procedures for approximating the corresp…

Sample Variance Denoising in Cylindrical 21-cm Power Spectra
Daniela Breitman, Andrei Mesinger, Steven G. Murray, Anshuman Acharya
https://arxiv.org/abs/2507.12545

Sample Variance Denoising in Cylindrical 21-cm Power Spectra
State-of-the-art simulations of reionisation-era 21-cm signal have limited volumes, generally orders of magnitude smaller than observations. Consequently, the Fourier modes in common between simulation and observation have limited overlap, especially in cylindrical (2D) k-space that is natural for 21-cm interferometry. This makes sample variance (i.e. the deviation of the simulated sample from the population mean due to finite box size) a potential issue when interpreting upcoming 21-cm observa…

Refining music sample identification with a self-supervised graph neural network
Aditya Bhattacharjee, Ivan Meresman Higgs, Mark Sandler, Emmanouil Benetos
https://arxiv.org/abs/2506.14684

Refining music sample identification with a self-supervised graph neural network
Automatic sample identification (ASID), the detection and identification of portions of audio recordings that have been reused in new musical works, is an essential but challenging task in the field of audio query-based retrieval. While a related task, audio fingerprinting, has made significant progress in accurately retrieving musical content under "real world" (noisy, reverberant) conditions, ASID systems struggle to identify samples that have undergone musical modifications. Thus, a system r…

SAMPLE -- Stratospheric Altitude Microbiology Probe for Life Existence -- A Method of Collection of Stratospheric Samples Using Balloon-Borne Payload System
Margarita Safonova, Bharat Chandra P, Binukumar G. Nair, Akshay Datey, Dipshikha Chakravortty, Ajin Prakash, Mahesh Babu, Shubham Ghatul, Shubhangi Jain, Rekhesh Mohan, Jayant Murthy
https://

SAMPLE -- Stratospheric Altitude Microbiology Probe for Life Existence -- A Method of Collection of Stratospheric Samples Using Balloon-Borne Payload System
The Earth possesses many environmental extremes that mimic conditions on extraterrestrial worlds. The stratosphere at 30-40 km altitude closely resembles the surface of Mars in terms of pressure, temperature, and radiation levels (UV, proton, and Galactic cosmic rays). While microbial life in the troposphere is well documented, the true upper limit of Earth's biosphere remains unclear. The stratosphere offers a promising environment to explore microbial survival in such extreme conditions. Desp…

New Software Synth, Solstice, Turns Any Sample Into A Playable Landscape
#MusicTech
https://www.synthtopia.com/content/2025/09

New Software Synth, Solstice, Turns Any Sample Into A Playable Landscape
Solstice is a new software synth for Mac & Windows, designed to “Turn any sample into an explorable landscape.”

CLASSY XIV: Nitrogen Enrichment Shaped by Gas Density and Feedback
Karla Z. Arellano-C\'ordova, Danielle A. Berg, Matilde Mingozzi, Bethan L. James, Fiorenzo Vincenzo, Noah S. J. Rogers, Evan D. Skillman, Ricardo O. Amor\'in, Fergus Cullen, Sophia R. Flury, Valentina Abril-Melgarejo, John Chisholm, Timothy Heckman, Matthew J. Hayes, Svea Hernandez, Nimisha Kumari, Chiaki Kobayashi, Claus Leitherer, Crystal L. Martin, Zorayda Martinez, Themiya Nanayakkara, Kaelee S. Parker, Pete…

CLASSY XIV: Nitrogen Enrichment Shaped by Gas Density and Feedback
We investigate the chemical evolution of N/O using a sample of 45 local star-forming galaxies (SFGs) from the CLASSY survey. This sample spans a wide range of galaxy properties, with robust determinations of nitrogen and oxygen abundances via the direct-$T_{\rm e}$ method. We explore how N/O relates to density structure, stellar mass, star formation rate (SFR), stellar age, compactness, and gas kinematics. In addition, we compare our results with those of galaxies at $z =2-10$ where N/O ratios …

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…

A Spatial-Physics Informed Model for 3D Spiral Sample Scanned by SQUID Microscopy
J. Senthilnath, Jayasanker Jayabalan, Zhuoyi Lin, Aye Phyu Phyu Aung, Chen Hao, Kaixin Xu, Yeow Kheng Lim, F. C. Wellstood
https://arxiv.org/abs/2507.11853

A Spatial-Physics Informed Model for 3D Spiral Sample Scanned by SQUID Microscopy
The development of advanced packaging is essential in the semiconductor manufacturing industry. However, non-destructive testing (NDT) of advanced packaging becomes increasingly challenging due to the depth and complexity of the layers involved. In such a scenario, Magnetic field imaging (MFI) enables the imaging of magnetic fields generated by currents. For MFI to be effective in NDT, the magnetic fields must be converted into current density. This conversion has typically relied solely on a F…

MM-Food-100K: A 100,000-Sample Multimodal Food Intelligence Dataset with Verifiable Provenance
Yi Dong, Yusuke Muraoka, Scott Shi, Yi Zhang
https://arxiv.org/abs/2508.10429 http…

MM-Food-100K: A 100,000-Sample Multimodal Food Intelligence Dataset with Verifiable Provenance
We present MM-Food-100K, a public 100,000-sample multimodal food intelligence dataset with verifiable provenance. It is a curated approximately 10% open subset of an original 1.2 million, quality-accepted corpus of food images annotated for a wide range of information (such as dish name, region of creation). The corpus was collected over six weeks from over 87,000 contributors using the Codatta contribution model, which combines community sourcing with configurable AI-assisted quality checks; e…

Contrastive CUR: Interpretable Joint Feature and Sample Selection for Case-Control Studies
Eric Zhang, Michael Love, Didong Li
https://arxiv.org/abs/2508.11557 https://

Contrastive CUR: Interpretable Joint Feature and Sample Selection for Case-Control Studies
Dimension reduction is an essential tool for analyzing high dimensional data. Most existing methods, including principal component analysis (PCA), as well as their extensions, provide principal components that are often linear combinations of features, which are often challenging to interpret. CUR decomposition, another matrix decomposition technique, is a more interpretable and efficient alternative, offers simultaneous feature and sample selection. Despite this, many biomedical studies involv…

VITA: Vision-to-Action Flow Matching Policy
Dechen Gao, Boqi Zhao, Andrew Lee, Ian Chuang, Hanchu Zhou, Hang Wang, Zhe Zhao, Junshan Zhang, Iman Soltani
https://arxiv.org/abs/2507.13231

VITA: Vision-to-Action Flow Matching Policy
We present VITA, a Vision-To-Action flow matching policy that evolves latent visual representations into latent actions for visuomotor control. Traditional flow matching and diffusion policies sample from standard source distributions (e.g., Gaussian noise) and require additional conditioning mechanisms like cross-attention to condition action generation on visual information, creating time and space overheads. VITA proposes a novel paradigm that treats latent images as the flow source, learnin…

Rationalizing Transformer Predictions via End-To-End Differentiable Self-Training
Marc Brinner, Sina Zarrie{\ss}
https://arxiv.org/abs/2508.11393 https://a…

Rationalizing Transformer Predictions via End-To-End Differentiable Self-Training
We propose an end-to-end differentiable training paradigm for stable training of a rationalized transformer classifier. Our approach results in a single model that simultaneously classifies a sample and scores input tokens based on their relevance to the classification. To this end, we build on the widely-used three-player-game for training rationalized models, which typically relies on training a rationale selector, a classifier and a complement classifier. We simplify this approach by making …

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…

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…

Empowering Multi-Robot Cooperation via Sequential World Models
Zijie Zhao, Honglei Guo, Shengqian Chen, Kaixuan Xu, Bo Jiang, Yuanheng Zhu, Dongbin Zhao
https://arxiv.org/abs/2509.13095

Empowering Multi-Robot Cooperation via Sequential World Models
Model-based reinforcement learning (MBRL) has shown significant potential in robotics due to its high sample efficiency and planning capability. However, extending MBRL to multi-robot cooperation remains challenging due to the complexity of joint dynamics. To address this, we propose the Sequential World Model (SeqWM), a novel framework that integrates the sequential paradigm into model-based multi-agent reinforcement learning. SeqWM employs independent, sequentially structured agent-wise world…

Back to poking at the solder cross section test sample.
Initial findings:
1) I should have sanded them more by hand prior to embedding. There's a LOT of material to burn through. I've probably worn out 5-10 P180 sanding disks so far and am not even at the PTHs on the main region of interest yet.
2) The samples are quite a bit off level. I need to figure out a better way to fixture them in the embedding mold so they don't tip forward.
I'll keep on polis…

Rademacher learning rates for iterated random functions
Nikola Sandri\'c
https://arxiv.org/abs/2506.13946 https://arxiv.org/pdf/2…

Rademacher learning rates for iterated random functions
Most existing literature on supervised machine learning assumes that the training dataset is drawn from an i.i.d. sample. However, many real-world problems exhibit temporal dependence and strong correlations between the marginal distributions of the data-generating process, suggesting that the i.i.d. assumption is often unrealistic. In such cases, models naturally include time-series processes with mixing properties, as well as irreducible and aperiodic ergodic Markov chains. Moreover, the lear…

Sample-Constrained Black Box Optimization for Audio Personalization
Rajalaxmi Rajagopalan, Yu-Lin Wei, Romit Roy Choudhury
https://arxiv.org/abs/2507.12773

Sample-Constrained Black Box Optimization for Audio Personalization
We consider the problem of personalizing audio to maximize user experience. Briefly, we aim to find a filter $h^*$, which applied to any music or speech, will maximize the user's satisfaction. This is a black-box optimization problem since the user's satisfaction function is unknown. Substantive work has been done on this topic where the key idea is to play audio samples to the user, each shaped by a different filter $h_i$, and query the user for their satisfaction scores $f(h_i)$. A family of …

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 …

Instruction and Solution Probabilities as Heuristics for Inductive Programming
Edward McDaid, Sarah McDaid
https://arxiv.org/abs/2506.13804 https://…

Instruction and Solution Probabilities as Heuristics for Inductive Programming
Instruction subsets (ISs) are heuristics that can shrink the size of the inductive programming (IP) search space by tens of orders of magnitude. Here, we extend the IS approach by introducing instruction and solution probabilities as additional heuristics. Instruction probability reflects the expectation of an instruction occurring in a solution, based on the frequency of instruction occurrence in a large code sample. The solution probability for a partial or complete program is simply the prod…

The Impact of Generative AI on Social Media: An Experimental Study
Anders Giovanni M{\o}ller, Daniel M. Romero, David Jurgens, Luca Maria Aiello
https://arxiv.org/abs/2506.14295

The Impact of Generative AI on Social Media: An Experimental Study
Generative Artificial Intelligence (AI) tools are increasingly deployed across social media platforms, yet their implications for user behavior and experience remain understudied, particularly regarding two critical dimensions: (1) how AI tools affect the behaviors of content producers in a social media context, and (2) how content generated with AI assistance is perceived by users. To fill this gap, we conduct a controlled experiment with a representative sample of 680 U.S. participants in a r…

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…

The threat of analytic flexibility in using large language models to simulate human data: A call to attention
Jamie Cummins
https://arxiv.org/abs/2509.13397 https://

The threat of analytic flexibility in using large language models to simulate human data: A call to attention
Social scientists are now using large language models to create "silicon samples" - synthetic datasets intended to stand in for human respondents, aimed at revolutionising human subjects research. However, there are many analytic choices which must be made to produce these samples. Though many of these choices are defensible, their impact on sample quality is poorly understood. I map out these analytic choices and demonstrate how a very small number of decisions can dramatically change the corr…

Classification Filtering
Ilker Bayram
https://arxiv.org/abs/2509.13975 https://arxiv.org/pdf/2509.13975

Classification Filtering
We consider a streaming signal in which each sample is linked to a latent class. We assume that multiple classifiers are available, each providing class probabilities with varying degrees of accuracy. These classifiers are employed following a straightforward and fixed policy. In this setting, we consider the problem of fusing the output of the classifiers while incorporating the temporal aspect to improve classification accuracy. We propose a state-space model and develop a filter tailored for…

Existence of Bulk Vortices in Superconductors with Strong Magnetic Fields
M. Correggi, A. Kachmar
https://arxiv.org/abs/2508.11299 https://arxiv.org/pdf/25…

Existence of Bulk Vortices in Superconductors with Strong Magnetic Fields
We study the vortex formation in extreme type-II superconductors immersed in strong magnetic fields in the framework of the the Ginzburg-Landau theory. We focus on the regime where superconductivity survives in the bulk of the material but the magnetic field penetrates the sample, i.e., for applied field much larger than the first critical one, but below the transition to surface superconductivity. Through a two-scale vortex construction, we obtain precise estimates for the vortex distribution …

The NFL teams already panicking, plus an MLB standings check https://www.nytimes.com/athletic/6629887/2025/09/15/nfl-week-2-the-pulse/

Splittable Spanning Trees and Balanced Forests in Dense Random Graphs
David Gillman, Jacob Platnick, Dana Randall
https://arxiv.org/abs/2507.12707 https://…

Splittable Spanning Trees and Balanced Forests in Dense Random Graphs
Weighted equitable partitioning of a graph has been of interest lately due to several applications, including redistricting, network algorithms, and image decomposition. Weighting a partition according to the spanning-tree metric has been of mathematical and practical interest because it typically favors partitions with more compact pieces. An appealing algorithm suggested by Charikar et al. is to sample a random spanning tree and remove k-1 edges, producing a random forest. If the components o…

Precision measurement of the ${\it{\Xi}}_b^0$ baryon lifetime
LHCb collaboration, et al.
https://arxiv.org/abs/2507.12402 https://arx…

Precision measurement of the ${\itΞ}_b^0$ baryon lifetime
A sample of $pp$ collision data, corresponding to an integrated luminosity of 5.4 fb$^{-1}$ and collected by the LHCb experiment during LHC Run 2, is used to measure the ratio of the lifetime of the ${\itΞ}_b^0$ baryon to that of the ${\itΛ}_b^0$ baryon, $r_τ\equivτ_{{\itΞ}_b^0}/τ_{{\itΛ}_b^0}$. The value ${r_τ^{\rm Run\,2}=1.004\pm0.009\pm0.006}$ is obtained, where the first uncertainty is statistical and the second systematic. This value is averaged with the corresponding value from R…

Do Outer Giants Inflate Neptune-sized Planets? An Architecture-Dependent Mass-Radius Relation
Dolev Bashi
https://arxiv.org/abs/2509.12328 https://arxiv.or…

Do Outer Giants Inflate Neptune-sized Planets? An Architecture-Dependent Mass-Radius Relation
Exoplanet demographics increasingly reveal that planetary properties depend not only on local irradiation and composition but also on the wider system architecture. We analyse a sample of Neptune-sized short-period planets with well-measured masses and radii, identifying those whose host stars harbour at least one confirmed outer-giant (OG) companion. On the mass-radius (M-R) plane, the two populations diverge modestly: inner planets in OG systems cluster at systematically larger radii than the…

Supernova Rates and Luminosity Functions from ASAS-SN II: 2014-2017 core-collapse supernovae and their subtypes
T. Pessi, D. D. Desai, J. L. Prieto, C. S. Kochanek, B. J. Shappee, J. P. Anderson, J. F. Beacom, Subo Dong, K. Z. Stanek, T. A. Thompson
https://arxiv.org/abs/2508.10985

Supernova Rates and Luminosity Functions from ASAS-SN II: 2014-2017 core-collapse supernovae and their subtypes
The volumetric rates and luminosity functions (LFs) of core-collapse supernovae (ccSN) and their subtypes are important for understanding the cosmic history of star formation and the buildup of ccSN products. To estimate these rates, we use data of nearby ccSNe discovered by the All-Sky Automated Survey for Supernovae (ASAS-SN) from 2014--2017, when all observations were made in the $V$-band. The sample is composed of 174 discovered or recovered events, with high spectroscopic completeness from…

Shape optimization for trailing-edge noise reduction using large-eddy simulation and ensemble-based method
Qingyong Luo, Xin-Lei Zhang, Guowei He
https://arxiv.org/abs/2509.13752

Shape optimization for trailing-edge noise reduction using large-eddy simulation and ensemble-based method
In this work, the trailing-edge shape of an airfoil is optimized to reduce the acoustic noise based on large-eddy simulation (LES). It is achieved by the ensemble Kalman method, which can enhance the optimization efficiency by using the gradient of cost function approximated with sample covariances. Moreover, the update scheme is reformulated to impose smoothness regularization and enable simultaneous reduction in the trailing edge noise and the drag-to-lift ratio. The trailing edge is optimize…

A break from the norm? Parametric representations of preference heterogeneity for discrete choice models in health
John Buckell, Alice Wreford, Matthew Quaife, Thomas O. Hancock
https://arxiv.org/abs/2506.14099

A break from the norm? Parametric representations of preference heterogeneity for discrete choice models in health
Background: Any sample of individuals has its own, unique distribution of preferences for choices that they make. Discrete choice models try to capture these distributions. Mixed logits are by far the most commonly used choice model in health. A raft of parametric model specifications for these models are available. We test a range of alternatives assumptions, and model averaging, to test if or how model outputs are impacted. Design: Scoping review of current modelling practices. Seven alternat…

Structural Inhomogeneities and Suppressed Magneto-Structural Coupling in Mn-Substituted GeCo2O4
Shivani Sharma, Pooja Jain, Benny Schundelmier, Chin-Wei Wang, Poonam Yadav, Adrienn Maria Szucs, Kaya Wei, N. P. Lalla, Theo Siegrist
https://arxiv.org/abs/2506.14017

Structural Inhomogeneities and Suppressed Magneto-Structural Coupling in Mn-Substituted GeCo2O4
A comprehensive study of Ge1-xMnxCo2O4 (GMCO) system was conducted using neutron powder diffraction (NPD), x-ray diffraction (XRD), Scanning electron microscopy, magnetometry, and heat capacity measurements. Comparative analysis with GeCo2O4 (GCO) highlights the influence of Mn substitution on the crystal and magnetic structure at low temperature. Surprisingly, phase separation is observed in GMCO with a targeted nominal composition of Ge0.5Mn0.5Co2O4. SEM/EDX analysis reveals that the sample p…

Online Robust Planning under Model Uncertainty: A Sample-Based Approach
Tamir Shazman, Idan Lev-Yehudi, Ron Benchetit, Vadim Indelman
https://arxiv.org/abs/2509.10162 https://…

Online Robust Planning under Model Uncertainty: A Sample-Based Approach
Online planning in Markov Decision Processes (MDPs) enables agents to make sequential decisions by simulating future trajectories from the current state, making it well-suited for large-scale or dynamic environments. Sample-based methods such as Sparse Sampling and Monte Carlo Tree Search (MCTS) are widely adopted for their ability to approximate optimal actions using a generative model. However, in practical settings, the generative model is often learned from limited data, introducing approxi…

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…

A curvature flow approach to dorsal closure modelling
Shuhui He, Ben Whale, Glen Wheeler, Valentina-Mira Wheeler
https://arxiv.org/abs/2507.12088 https://

A curvature flow approach to dorsal closure modelling
In this paper we propose and study a curvature-based mathematical model for dorsal closure in embryonic drosophila. Using an analysis that mixes maximum-principle and integral-estimates, we establish global existence and convergence for data that mimics the initial geometry of a dorsal closure event. Further, we present a numerical approximation scheme for the flow, establishing stability, consistence, and convergence. We also give sample simulations of the flow with initial configurations that…

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…

Mixture of Raytraced Experts
Andrea Perin, Giacomo Lagomarsini, Claudio Gallicchio, Giuseppe Nuti
https://arxiv.org/abs/2507.12419 https://

Mixture of Raytraced Experts
We introduce a Mixture of Raytraced Experts, a stacked Mixture of Experts (MoE) architecture which can dynamically select sequences of experts, producing computational graphs of variable width and depth. Existing MoE architectures generally require a fixed amount of computation for a given sample. Our approach, in contrast, yields predictions with increasing accuracy as the computation cycles through the experts' sequence. We train our model by iteratively sampling from a set of candidate exper…

Sample efficient likelihood-free inference for virus dynamics with different types of experiments
Yingying Xu, Ulpu Remes, Enrico Rinaldi, Henri Pesonen
https://arxiv.org/abs/2508.11042

Sample efficient likelihood-free inference for virus dynamics with different types of experiments
This study applied Bayesian optimization likelihood-free inference(BOLFI) to virus dynamics experimental data and efficiently inferred the model parameters with uncertainty measure. The computational benefit is remarkable compared to existing methodology on the same problem. No likelihood knowledge is needed in the inference. Improvement of the BOLFI algorithm with Gaussian process based classifier for treatment of extreme values are provided. Discrepancy design for combining different forms of…

Uma sondagem de mais de 35 mil pessoas, iniciada hš quase 3 anos, terminou agora. Pergunto a mim mesmo que percentagem destas contas continua ativa.
https://fosstodon.org/@MattTheQuick/109321444143425443
Mas mesmo deprimente? África: 1%.

Case-Based Decision-Theoretic Decoding with Quality Memories
Hiroyuki Deguchi, Masaaki Nagata
https://arxiv.org/abs/2509.12677 https://arxiv.org/pdf/2509.1…

Case-Based Decision-Theoretic Decoding with Quality Memories
Minimum Bayes risk (MBR) decoding is a decision rule of text generation, which selects the hypothesis that maximizes the expected utility and robustly generates higher-quality texts than maximum a posteriori (MAP) decoding. However, it depends on sample texts drawn from the text generation model; thus, it is difficult to find a hypothesis that correctly captures the knowledge or information of out-of-domain. To tackle this issue, we propose case-based decision-theoretic (CBDT) decoding, another…

AIM: Amending Inherent Interpretability via Self-Supervised Masking
Eyad Alshami, Shashank Agnihotri, Bernt Schiele, Margret Keuper
https://arxiv.org/abs/2508.11502 https://

AIM: Amending Inherent Interpretability via Self-Supervised Masking
It has been observed that deep neural networks (DNNs) often use both genuine as well as spurious features. In this work, we propose "Amending Inherent Interpretability via Self-Supervised Masking" (AIM), a simple yet interestingly effective method that promotes the network's utilization of genuine features over spurious alternatives without requiring additional annotations. In particular, AIM uses features at multiple encoding stages to guide a self-supervised, sample-specific feature-masking p…

Proof this book is old. "Telephone book"? Are we in the 80s?

🇺🇦 Auf radioeins läuft...
Foxwarren:
🎵 Listen2me
#NowPlaying #Foxwarren
https://foxwarren.bandcamp.com/track/listen2me-stem20-sample-listen2me
https://open.spotify.com/track/29WWHCuzU0OCWTfiBKbOm1

**"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

Dynamical measurement of saturation vapor pressures below and above room temperature
Mohsen Salimi, Andreas B. Pedersen, John E. V. Andersen, Henrik B. Pedersen, Aur\'elien Dantan
https://arxiv.org/abs/2508.10932

Dynamical measurement of saturation vapor pressures below and above room temperature
We report on the implementation of a dynamical method for the determination -- in an extended temperature range around room temperature -- of the saturation vapor pressure and enthalpy of vaporization of low-volatility liquid substances. The method relies on isolating a \textit{precooled} substance in a heated chamber under static vacuum conditions and monitoring the chamber pressure as the sample slowly thermalizes to the chamber temperature. We apply the method to four reference substances --…

Robust and efficient estimation of global quantum properties under realistic noise
Qingyue Zhang, Dayue Qin, Zhou You, Feng Xu, Jens Eisert, You Zhou
https://arxiv.org/abs/2507.13237

Robust and efficient estimation of global quantum properties under realistic noise
Measuring global quantum properties -- such as the fidelity to complex multipartite states -- is both an essential and experimentally challenging task. Classical shadow estimation offers favorable sample complexity, but typically relies on many-qubit circuits that are difficult to realize on current platforms. We propose the robust phase shadow scheme, a measurement framework based on random circuits with controlled-Z as the unique entangling gate type, tailored to architectures such as trapped…

Diffusion-based Inverse Observation Model for Artificial Skin
Ante Maric, Julius Jankowski, Giammarco Caroleo, Alessandro Albini, Perla Maiolino, Sylvain Calinon
https://arxiv.org/abs/2506.13986

Diffusion-based Inverse Observation Model for Artificial Skin
Contact-based estimation of object pose is challenging due to discontinuities and ambiguous observations that can correspond to multiple possible system states. This multimodality makes it difficult to efficiently sample valid hypotheses while respecting contact constraints. Diffusion models can learn to generate samples from such multimodal probability distributions through denoising algorithms. We leverage these probabilistic modeling capabilities to learn an inverse observation model conditi…

Uniform Mean Estimation for Heavy-Tailed Distributions via Median-of-Means
Mikael M{\o}ller H{\o}gsgaard, Andrea Paudice
https://arxiv.org/abs/2506.14673 h…

Uniform Mean Estimation for Heavy-Tailed Distributions via Median-of-Means
The Median of Means (MoM) is a mean estimator that has gained popularity in the context of heavy-tailed data. In this work, we analyze its performance in the task of simultaneously estimating the mean of each function in a class $\mathcal{F}$ when the data distribution possesses only the first $p$ moments for $p \in (1,2]$. We prove a new sample complexity bound using a novel symmetrization technique that may be of independent interest. Additionally, we present applications of our result to $k$…

Concentration inequalities for semidefinite least squares based on data
Filippo Fabiani, Andrea Simonetto
https://arxiv.org/abs/2509.13166 https://arxiv.or…

Concentration inequalities for semidefinite least squares based on data
We study data-driven least squares (LS) problems with semidefinite (SD) constraints and derive finite-sample guarantees on the spectrum of their optimal solutions when these constraints are relaxed. In particular, we provide a high confidence bound allowing one to solve a simpler program in place of the full SDLS problem, while ensuring that the eigenvalues of the resulting solution are $\varepsilon$-close of those enforced by the SD constraints. The developed certificate, which consistently sh…

LATIS: A Sample of IGM-selected Protoclusters and Protogroups at $z \sim 2.5$
Andrew B. Newman, Mahdi Qezlou, Gwen C. Rudie, Nima Chartab, Guillermo A. Blanc, Daniel D. Kelson, Simeon Bird, Caitlin Casey, Enrico Congiu, Olga Cucciati, Denise Hung, Brian C. Lemaux, Victoria P\'erez, Jorge Zavala
https://arxiv.org/abs/2507.109…

LATIS: A Sample of IGM-selected Protoclusters and Protogroups at $z \sim 2.5$
The Ly$α$ Tomography IMACS Survey (LATIS) has produced large 3D maps of the intergalactic medium (IGM), providing a new window on the cosmic web at $z\sim2.5$. A key advantage of Ly$α$ tomography is that it enables the discovery of overdense regions without the need to detect their galaxy members in spectroscopic surveys, circumventing possible selection biases. We use these maps to identify 37 IGM-selected overdensities as regions of strong and spatially coherent Ly$α$ absorption. Simulatio…

On the accretion luminosity of Class I protostars
L. Testi, A. Natta, S. Gozzi, C. F. Manara, J. P. Williams, R. Claes, U. Lebreuilly, P. Hennebelle, R. Klessen, S. Molinari
https://arxiv.org/abs/2506.14601

On the accretion luminosity of Class I protostars
The value of the accretion luminosity during the early phases of star formation is a crucial information which helps us understand how stars form, yet it is still very difficult to obtain. We develop a new methodology to measure accretion luminosity using mid-infrared hydrogen recombination lines, and apply it to a limited sample of Class~I protostars in the Taurus and Ophiuchus star forming regions. We adopt the commonly used assumption that the properties of disk-protostar accretion in Class …

Graph-Regularized Learning of Gaussian Mixture Models
Shamsiiat Abdurakhmanova, Alex Jung
https://arxiv.org/abs/2509.13855 https://arxiv.org/pdf/2509.13855…

Graph-Regularized Learning of Gaussian Mixture Models
We present a graph-regularized learning of Gaussian Mixture Models (GMMs) in distributed settings with heterogeneous and limited local data. The method exploits a provided similarity graph to guide parameter sharing among nodes, avoiding the transfer of raw data. The resulting model allows for flexible aggregation of neighbors' parameters and outperforms both centralized and locally trained GMMs in heterogeneous, low-sample regimes.

Euclid preparation. Simulating thousands of Euclid spectroscopic skies
Collaboration, Monaco, Parimbelli, Elkhashab, Salvalaggio, Castro, Lepinzan, Sarpa, Sefusatti, Stanco, Tornatore, Addison, Bruton, Carbone, Castander, Carretero, de la Torre, Fosalba, Lavaux, Lee, Markovic, McCarthy, Passalacqua, Percival, Risso, Scarlata, Tallada-Cresp\'i, Viel, Wang, Altieri, Andreon, Auricchio, Baccigalupi, Baldi, Bardelli, Battaglia, Bernardeau, Biviano, Branchini, Brescia, Brinchmann, Camer…

Euclid preparation. Simulating thousands of Euclid spectroscopic skies
We present two extensive sets of 3500+1000 simulations of dark matter haloes on the past light cone, and two corresponding sets of simulated (`mock') galaxy catalogues that represent the Euclid spectroscopic sample. The simulations were produced with the latest version of the PINOCCHIO code, and provide the largest, public set of simulated skies. Mock galaxy catalogues were obtained by populating haloes with galaxies using an halo occupation distribution (HOD) model extracted from the Flagship …

BOWIE-ALIGN: Weak spectral features in KELT-7b's JWST NIRSpec/G395H transmission spectrum imply a high cloud deck or a low-metallicity atmosphere
Eva-Maria Ahrer, Charlotte Fairman, James Kirk, Hannah R. Wakeford, Joanna K. Barstow, Anna B. T. Penzlin, Lili Alderson, Richard A. Booth, Duncan A. Christie, Alastair B. Claringbold, Emma Esparza-Borges, Carlos Gasc\'on, Mercedes L\'opez-Morales, N. J. Mayne, Mason McCormack, Annabella Meech, Paul Molli\`ere, James E. Owen, Vats…

BOWIE-ALIGN: Weak spectral features in KELT-7b's JWST NIRSpec/G395H transmission spectrum imply a high cloud deck or a low-metallicity atmosphere
Hot Jupiters and their atmospheres are prime targets for transmission spectroscopy due to their extended atmospheres and the corresponding large signal-to-noise, providing the best possible constraints for the atmospheric carbon-to-oxygen (C/O) ratio and metallicity of exoplanets. Within BOWIE-ALIGN, we aim to compare JWST spectra of a sample of orbitally aligned and misaligned hot Jupiters orbiting F-type stars to probe the link between hot Jupiter atmospheres and planet formation history. Her…

SENIOR: Efficient Query Selection and Preference-Guided Exploration in Preference-based Reinforcement Learning
Hexian Ni, Tao Lu, Haoyuan Hu, Yinghao Cai, Shuo Wang
https://arxiv.org/abs/2506.14648

SENIOR: Efficient Query Selection and Preference-Guided Exploration in Preference-based Reinforcement Learning
Preference-based Reinforcement Learning (PbRL) methods provide a solution to avoid reward engineering by learning reward models based on human preferences. However, poor feedback- and sample- efficiency still remain the problems that hinder the application of PbRL. In this paper, we present a novel efficient query selection and preference-guided exploration method, called SENIOR, which could select the meaningful and easy-to-comparison behavior segment pairs to improve human feedback-efficiency…

Measurements of ttW differential cross sections and the leptonic charge asymmetry at $\sqrt{s}$ = 13 TeV
CMS Collaboration
https://arxiv.org/abs/2509.13512 https://

Measurements of ttW differential cross sections and the leptonic charge asymmetry at $\sqrt{s}$ = 13 TeV
Measurements of properties of top quark-antiquark pair production in association with a W boson in proton-proton collisions at a center-of-mass energy of 13 TeV are presented, using a data sample corresponding to an integrated luminosity of 138 fb$^{-1}$, recorded by the CMS experiment at the CERN LHC. Events are selected based on the presence of either two leptons with the same electric charge or three leptons, and multiple jets and b-tagged jets. We present measurements of differential produc…

Coherent Driving of a Quantum System with Modulated Free-Space Electrons
Matthias Kolb, Thomas Spielauer, Thomas Weigner, Giovanni Boero, Dennis R\"atzel, Philipp Haslinger
https://arxiv.org/abs/2509.13904

Coherent Driving of a Quantum System with Modulated Free-Space Electrons
Control of quantum systems typically relies on the interaction with electromagnetic radiation. In this study, we experimentally show that the electromagnetic near-field of a spatially modulated freespace electron beam can be used to drive spin systems, demonstrating free-electron-bound-electron resonant interaction. By periodically deflecting the electron beam of a scanning electron microscope in close proximity to a spin-active solid-state sample, and sweeping the deflection frequency across t…

For all the marketing advice LinkedIn MBAs come up with, a surprising number of people forget one of the most basic steps: The Middle Schooler Test.
The process is simple:
1) Place a sample of your brochure, website, etc. in front of a recently calibrated 12-year-old boy.
2) If they start giggling uncontrollably, identify and correct the source of their amusement. Return to step 1.
3) If they aren't particularly amused, move on with the campaign.

On the Rate of Gaussian Approximation for Linear Regression Problems
Marat Khusainov, Marina Sheshukova, Alain Durmus, Sergey Samsonov
https://arxiv.org/abs/2509.14039 https://

On the Rate of Gaussian Approximation for Linear Regression Problems
In this paper, we consider the problem of Gaussian approximation for the online linear regression task. We derive the corresponding rates for the setting of a constant learning rate and study the explicit dependence of the convergence rate upon the problem dimension $d$ and quantities related to the design matrix. When the number of iterations $n$ is known in advance, our results yield the rate of normal approximation of order $\sqrt{\log{n}/n}$, provided that the sample size $n$ is large enoug…

Binary choice logit models with general fixed effects for panel and network data
Kevin Dano, Bo E. Honor\'e, Martin Weidner
https://arxiv.org/abs/2508.11556 https://

Binary choice logit models with general fixed effects for panel and network data
This paper systematically analyzes and reviews identification strategies for binary choice logit models with fixed effects in panel and network data settings. We examine both static and dynamic models with general fixed-effect structures, including individual effects, time trends, and two-way or dyadic effects. A key challenge is the incidental parameter problem, which arises from the increasing number of fixed effects as the sample size grows. We explore two main strategies for eliminating nui…

Liquid Helium Cryogenic TEM below 1 {\AA}
Suk Hyun Sung, Maya Gates, Nishkarsh Agarwal, Yang Zhang, William Millsaps, Miti Shah, Emily Rennich, Cong Li, Pu Yu, Miaofang Chi, Benjamin H. Savitzky, Ismail El Baggari, Robert Hovden
https://arxiv.org/abs/2509.12475

Liquid Helium Cryogenic TEM below 1 Å
Next-generation cryogenic transmission electron microscopes (TEM) aim to achieve high-resolution imaging at ultracold sample temperatures (< 90 K) and over extended hold times. Lower temperatures enable atomic-scale characterization with improved beam and dose resilience for organic specimens and access to emergent electronic phases in quantum materials. Side-entry liquid helium cooling stages presently lack the mechanical and thermal stability required to support sub-Angstrom information trans…

The GROND GRB sample: II. Fireball parameters for four GRB afterglows
Karla Varela, Jochen Greiner, Patricia Schady, Hendrik van Eerten
https://arxiv.org/abs/2507.09002

The GROND GRB sample: II. Fireball parameters for four GRB afterglows
Afterglows of GRBs are, in general, well described by the fireball model. Yet, deducing the full set of model parameters from observations without prior assumptions has been possible for only a handful of GRBs. With GROND, a 7-channel simultaneous optical and near-infrared imager at the 2.2m telescope of the Max-Planck Society at ESO/La Silla, a dedicated gamma-ray burst (GRB) afterglow observing program was performed between 2007 and 2016. Here, we combine GROND observations of four particul…

Scalable Variational Inference for Multinomial Probit Models under Large Choice Sets and Sample Sizes
Gyeongjun Kim, Yeseul Kang, Lucas Kock, Prateek Bansal, Keemin Sohn
https://arxiv.org/abs/2507.10945

Scalable Variational Inference for Multinomial Probit Models under Large Choice Sets and Sample Sizes
The multinomial probit (MNP) model is widely used to analyze categorical outcomes due to its ability to capture flexible substitution patterns among alternatives. Conventional likelihood based and Markov chain Monte Carlo (MCMC) estimators become computationally prohibitive in high dimensional choice settings. This study introduces a fast and accurate conditional variational inference (CVI) approach to calibrate MNP model parameters, which is scalable to large samples and large choice sets. A f…

🇺🇦 Auf radioeins läuft...
Foxwarren:
🎵 Listen2me
#NowPlaying #Foxwarren
https://foxwarren.bandcamp.com/track/listen2me-stem20-sample-listen2me
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WIYN Open Cluster Study. XCIII. An Extended Radial-Velocity Survey and Spectroscopic Binary Orbits in the Open Cluster NGC 188
Ritvik Sai Narayan, Evan Linck, Robert D. Mathieu, Aaron M. Geller
https://arxiv.org/abs/2509.12315

WIYN Open Cluster Study. XCIII. An Extended Radial-Velocity Survey and Spectroscopic Binary Orbits in the Open Cluster NGC 188
We present 32 new spectroscopic-binary orbits from our extended radial-velocity (RV) survey of the old ($6.4 \pm 0.2$ Gyr) open cluster NGC 188. Using data from the WIYN Open Cluster Study (WOCS) and APOGEE-2, this work nearly doubles the temporal baseline of the previous RV study of NGC 188. We obtain orbital solutions within a stellar sample that spans a magnitude range of $10.8 \leq \mathrm{G} \leq 16.5 \; (0.9\mbox{-}1.2 \; {M_\odot})$. With revised membership determinations using Gaia DR3 …

Replaced article(s) found for eess.SY. https://arxiv.org/list/eess.SY/new
[1/1]:
Sample Complexity of the Linear Quadratic Regulator: A Reinforcement Learning Lens

Acoustic scattering AI for non-invasive object classifications: A case study on hair assessment
Long-Vu Hoang, Tuan Nguyen, Tran Huy Dat
https://arxiv.org/abs/2506.14148

Acoustic scattering AI for non-invasive object classifications: A case study on hair assessment
This paper presents a novel non-invasive object classification approach using acoustic scattering, demonstrated through a case study on hair assessment. When an incident wave interacts with an object, it generates a scattered acoustic field encoding structural and material properties. By emitting acoustic stimuli and capturing the scattered signals from head-with-hair-sample objects, we classify hair type and moisture using AI-driven, deep-learning-based sound classification. We benchmark compr…

SHaRe-RL: Structured, Interactive Reinforcement Learning for Contact-Rich Industrial Assembly Tasks
Jannick Strangh\"oner, Philipp Hartmann, Marco Braun, Sebastian Wrede, Klaus Neumann
https://arxiv.org/abs/2509.13949

SHaRe-RL: Structured, Interactive Reinforcement Learning for Contact-Rich Industrial Assembly Tasks
High-mix low-volume (HMLV) industrial assembly, common in small and medium-sized enterprises (SMEs), requires the same precision, safety, and reliability as high-volume automation while remaining flexible to product variation and environmental uncertainty. Current robotic systems struggle to meet these demands. Manual programming is brittle and costly to adapt, while learning-based methods suffer from poor sample efficiency and unsafe exploration in contact-rich tasks. To address this, we prese…

The Last Stand Before Rubin: a consolidated sample of strong lensing systems in wide-field surveys
Renan Alves de Oliveira, Jo\~ao Paulo C. Fran\c{c}a, Mart\'in Makler
https://arxiv.org/abs/2509.09798

The Last Stand Before Rubin: a consolidated sample of strong lensing systems in wide-field surveys
As the Vera Rubin Observatory begins its ten-year survey in 2025, it will probe key observables such as strong lensing (SL) by galaxies and clusters. In preparation for this new era, we assemble an extensive compilation of SL candidate systems from the literature, comprising over 30,000 unique objects that can be used as a watch list of known systems. By cross-matching this sample with photometric and spectroscopic catalogs, we construct two value-added tables containing key parameters for SL a…

MeerKAT HI observations of Low Surface Brightness/Ultradiffuse Galaxy Candidates Projected around Two Southern Loose Groups
Chandreyee Sengupta, Tom C. Scott, Hao Chen, Hyein Yoon, Yogesh Chandola, Mengtian Li, Gyula I. G. J\'ozsa, O. Ivy Wong, Yin-Zhe Ma, Patricio Lagos, Ruta Kale, Denis Tramonte
https://arxiv.org/abs/2506.…

MeerKAT HI observations of Low Surface Brightness/Ultradiffuse Galaxy Candidates Projected around Two Southern Loose Groups
A large catalogue of low surface brightness galaxies (LSBGs) from the Dark Energy Survey showed significant clustering around nearby galaxy groups and clusters. Using the HIPASS survey, we tried to determine the redshift of a sub-sample of these LSBGs and determine whether they were members of the groups they were projected near, but this was hampered by HIPASS's high spectral rms. This letter reports on MeerKAT H I observations to determine the redshifts of 52 LSBG candidates projected in the …

Sample More to Think Less: Group Filtered Policy Optimization for Concise Reasoning
Vaishnavi Shrivastava, Ahmed Awadallah, Vidhisha Balachandran, Shivam Garg, Harkirat Behl, Dimitris Papailiopoulos
https://arxiv.org/abs/2508.09726

Sample More to Think Less: Group Filtered Policy Optimization for Concise Reasoning
Large language models trained with reinforcement learning with verifiable rewards tend to trade accuracy for length--inflating response lengths to achieve gains in accuracy. While longer answers may be warranted for harder problems, many tokens are merely "filler": repetitive, verbose text that makes no real progress. We introduce GFPO (Group Filtered Policy Optimization), which curbs this length explosion by sampling larger groups per problem during training and filtering responses to train on…

A Decision Theoretic Perspective on Artificial Superintelligence: Coping with Missing Data Problems in Prediction and Treatment Choice
Jeff Dominitz, Charles F. Manski
https://arxiv.org/abs/2509.12388 …

A Decision Theoretic Perspective on Artificial Superintelligence: Coping with Missing Data Problems in Prediction and Treatment Choice
Enormous attention and resources are being devoted to the quest for artificial general intelligence and, even more ambitiously, artificial superintelligence. We wonder about the implications for our methodological research, which aims to help decision makers cope with what econometricians call identification problems, inferential problems in empirical research that do not diminish as sample size grows. Of particular concern are missing data problems in prediction and treatment choice. Essential…

An Efficient Approach to Design Bayesian Platform Trials
Luke Hagar, Lara Maleyeff, Shirin Golchi, Dick Menzies
https://arxiv.org/abs/2507.12647 https://…

An Efficient Approach to Design Bayesian Platform Trials
Platform trials evaluate multiple experimental treatments against a common control group (and/or against each other), which often reduces the trial duration and sample size. Bayesian platform designs offer several practical advantages, including the flexible addition or removal of experimental arms using posterior probabilities and the incorporation of prior/external information. Regulatory agencies require that the operating characteristics of Bayesian designs are assessed by estimating the sa…

A New cw-NMR Q-meter for Dynamically Polarized Targets for Particle Physics
J. D. Maxwell, J. Brock, C. Cuevas, H. Dong, C. D. Keith, J. J. Pierce
https://arxiv.org/abs/2506.14637

A New cw-NMR Q-meter for Dynamically Polarized Targets for Particle Physics
Polarized solid targets produced via Dynamic Nuclear Polarization rely on Continuous-Wave Nuclear Magnetism Resonance measurements to accurately determine the degree of polarization of bulk samples polarized to nearly 100%. Since the late 1970's phase sensitive detection methods have been utilized to observe the magnetization of a sample as a small change in inductance under RF excitation near the Larmor frequency of the nuclear species of interest, using a device known as a Q-meter. Liverpool …

Distributionally Robust Equilibria over the Wasserstein Distance for Generalized Nash Game
Yixun Wen, Yulong Gao, Boli Chen
https://arxiv.org/abs/2509.13985 https://

Distributionally Robust Equilibria over the Wasserstein Distance for Generalized Nash Game
Generalized Nash equilibrium problem (GNEP) is fundamental for practical applications where multiple self-interested agents work together to make optimal decisions. In this work, we study GNEP with shared distributionally robust chance constraints (DRCCs) for incorporating inevitable uncertainties. The DRCCs are defined over the Wasserstein ball, which can be explicitly characterized even with limited sample data. To determine the equilibrium of the GNEP, we propose an exact approach to transfo…

First detection of ices in intermediate-mass young stellar objects beyond the Milky Way
Guido De Marchi, Nolan Habel, Margaret Meixner, Katia Biazzo, Giovanna Giardino, Elena Sabbi, Ciaran Rogers, Jeroen Jaspers, Massimo Robberto, Peter Zeidler, Olivia C. Jones, Katja Fahrion, Alec S. Hirschauer, Charles D. Keyes, David R. Soderblom, Laura Lenkic, Omnarayani Nayak, Bernhard Brandl

First detection of ices in intermediate-mass young stellar objects beyond the Milky Way
Using NIRSpec on JWST, we studied a sample of 15 intermediate-mass (1.8-4.1 Msun) young stellar objects (YSOs) previously identified with MIRI photometry in the low-metallicity NGC 346 star-forming cluster in the Small Magellanic Cloud (SMC). All objects, observed in the 1.7-5.3 micron range, show strong hydrogen recombination lines in the Paschen, Brackett, Pfund, and Humphreys series, confirming their very young ages. The spectra of 11 YSOs show prominent absorption bands from the three most …

Luminaries in the Sky: The TESS Legacy Sample of Bright Stars. I. Asteroseismic detections in naked-eye main-sequence and sub-giant solar-like oscillators
Mikkel N. Lund, Ashley Chontos, Frank Grundahl, Savita Mathur, Rafael A. Garc\'ia, Daniel Huber, Derek Buzasi, Timothy R. Bedding, Marc Hon, Yaguang Li
https://arxiv.org/abs/2508.086…

Luminaries in the Sky: The TESS Legacy Sample of Bright Stars. I. Asteroseismic detections in naked-eye main-sequence and sub-giant solar-like oscillators
We aim to detect and characterise solar-like oscillations in bright naked-eye (V<6) main-sequence (MS) and subgiant stars observed by TESS. We seek to expand the current benchmark sample of oscillators, provide accurate global asteroseismic parameters for these bright targets, and assess their potential for future detailed investigations -- including missions such as the HWO and PLATO. Our sample of bright stars was selected from the Hipparcos/Tycho catalogues. We analysed TESS 120-s and 20-s c…

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…

Inductance Estimation for High-Power Multilayer Rectangle Planar Windings
Theofilos Papadopoulos, Antonios Antonopoulos
https://arxiv.org/abs/2507.12082 ht…

Inductance Estimation for High-Power Multilayer Rectangle Planar Windings
This paper proposes a simple and accurate monomial-like equation for estimating the inductance of Multilayer Rectangle-shaped Planar Windings (MLRPWs) for high-frequency, high-power applications. The equation consists of the power product of the geometrical dimensions, raised at individual power coefficients. The coefficients are generated via Multiple Linear Regression (MLR), based on a large set of approximately 6,000 simulated windings, with an 80/20 training/evaluation sample ratio. The res…

The ALMA-CRISTAL survey: Resolved kinematic studies of main sequence star-forming galaxies at 4<z<6
Lilian L. Lee, Natascha M. F\"orster Schreiber, Rodrigo Herrera-Camus, Daizhong Liu, Sedona H. Price, Reinhard Genzel, Linda J. Tacconi, Dieter Lutz, Ric Davies, Thorsten Naab, Hannah \"Ubler, Manuel Aravena, Roberto J. Assef, Loreto Barcos-Mu\~noz, Rebecca A. A. Bowler, Andreas Burkert, Jianhang Chen, Rebecca L. Davies, Ilse De Looze, Tanio Diaz-Santos, Jorge Gonz\'a…

The ALMA-CRISTAL survey: Resolved kinematic studies of main sequence star-forming galaxies at 4
We present a detailed kinematic study of a sample of 32 massive ($9.5\leqslant\log(M_*/{\rm M_{\odot}})\leqslant10.9$) main-sequence star-forming galaxies (MS SFGs) at $4