Tootfinder

The optical photometric variability of Herbig Ae/Be stars from TESS
Ann Marie Cody, Lynne A. Hillenbrand, Shreya Chandragiri, Marvin Morgan
https://arxiv.org/abs/2510.08633 http…

The optical photometric variability of Herbig Ae/Be stars from TESS
We have carried out a photometric time domain study of 188 intermediate-mass young stars observed in Full Frame Image mode with the TESS satellite over the first 3.3 years of its mission. The majority of these targets are classified as Herbig Ae/Be stars (HAeBes). All were monitored at optical wavelengths for at least one 27-day TESS sector, with many having multiple sectors of data. From a custom aperture photometry pipeline, we produced light curves and analyzed the variability therein, as a …

State-Dependent X-ray Variability in Cygnus X-1: A 12-Year NuSTAR Timing Study of Accretion Flow Geometry
Kshitij Duraphe, Kartik Mandar, Chooda Khanal, Abha Pareek, Tejaswi Kondhiya, V Sree Suswara, Deeksha Dinesh, Vidyasagar Bhat, Gopal Bhatta
https://arxiv.org/abs/2510.10746

State-Dependent X-ray Variability in Cygnus X-1: A 12-Year NuSTAR Timing Study of Accretion Flow Geometry
We present a comprehensive timing analysis of the black hole X-ray binary Cygnus X-1 using 26 NuSTAR observations spanning 2012-2024, providing the most detailed characterization to date of its accretion flow variability across spectral states. Our analysis reveals fundamental insights into the physics governing state transitions in stellar-mass black holes. We discover distinct bimodal flux distributions in the 8-79 keV band with well-separated peaks, contrasting with overlapping distributions…

STaTS: Structure-Aware Temporal Sequence Summarization via Statistical Window Merging
Disharee Bhowmick, Ranjith Ramanathan, Sathyanarayanan N. Aakur
https://arxiv.org/abs/2510.09593

STaTS: Structure-Aware Temporal Sequence Summarization via Statistical Window Merging
Time series data often contain latent temporal structure, transitions between locally stationary regimes, repeated motifs, and bursts of variability, that are rarely leveraged in standard representation learning pipelines. Existing models typically operate on raw or fixed-window sequences, treating all time steps as equally informative, which leads to inefficiencies, poor robustness, and limited scalability in long or noisy sequences. We propose STaTS, a lightweight, unsupervised framework for …

Harvests and Hooky in the Hills: Crop Yield Variability and Gendered School Enrollment in Rwanda
Maxwell Fogler
https://arxiv.org/abs/2510.10780 https://ar…

Harvests and Hooky in the Hills: Crop Yield Variability and Gendered School Enrollment in Rwanda
This paper investigates the trade-off that households in agrarian economies face between immediate production needs and long-term human capital investment. We ask how exogenous agricultural productivity shocks affect primary and secondary school enrollment in Rwanda, a country characterized by a heavy reliance on rain-fed agriculture alongside ambitious development goals. Using a district-level panel dataset for the years 2010-2021, we employ a two-stage least squares (2SLS) instrumental variab…

A Probabilistic Framework for Predicting Spatiotemporal Intensity and Variability of Outdoor Thermal Comfort
Shisheng Chen, Ruohan Xu, Nyuk Hien Wong, Shanshan Tong, Jiashuo Wang, Matthaios Santamouris
https://arxiv.org/abs/2509.09468

A Probabilistic Framework for Predicting Spatiotemporal Intensity and Variability of Outdoor Thermal Comfort
Thermal conditions in the urban canopy exhibit stochastic variability driven by varied radiative fluxes and turbulent wind fields, requiring probabilistic rather than deterministic prediction methods. This study presents a probabilistic framework for predicting the spatial and temporal intensity and variability of outdoor thermal comfort in tropical urban environments. The framework integrates ground-measured meteorological data and remote sensing urban morphological data to calculate Physiolog…

Probing spectral variability in NGC 4490 ULX-8 over 24 years of XMM-Newton, Chandra and Swift-XRT observations
Tarang Vashisht, Aru Beri, Tanuman Ghosh, Aman Upadhyay, Vikram Rana
https://arxiv.org/abs/2510.11415

Probing spectral variability in NGC 4490 ULX-8 over 24 years of XMM-Newton, Chandra and Swift-XRT observations
We present comprehensive spectral and timing results of 14 Chandra, 6 XMM-Newton and 19 Swift-XRT observations of the ultraluminous X-ray source NGC 4490 ULX-8, spanning from 2000 to 2024. We model the source spectra using absorbed power-law and absorbed multicolour disc blackbody models. The best-fit photon indices span 0.92-2.68, with typical uncertainties ranging from $\pm$0.1 to $\pm$1 depending on data quality. The inner disk temperature range from 0.97 to 1.69 keV, consistent with blackbo…

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training
Yuhao Pan, Xiucheng Wang, Nan Cheng, Wenchao Xu
https://arxiv.org/abs/2510.09405

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training
Radio frequency fingerprint identification (RFFI) is a critical technique for wireless network security, leveraging intrinsic hardware-level imperfections introduced during device manufacturing to enable precise transmitter identification. While deep neural networks have shown remarkable capability in extracting discriminative features, their real-world deployment is hindered by receiver-induced variability. In practice, RF fingerprint signals comprise transmitter-specific features as well as c…

Large-scale variability in macroturbulence driven by pulsations in the rapidly rotating massive star Zeta Oph from high-cadence ESPRESSO spectroscopy and TESS photometry
A. J. Kalita, D. M. Bowman, M. Abdul-Masih, S. Sim\'on-D\'iaz
https://arxiv.org/abs/2509.09635

Large-scale variability in macroturbulence driven by pulsations in the rapidly rotating massive star Zeta Oph from high-cadence ESPRESSO spectroscopy and TESS photometry
Despite their importance, the dynamical properties of massive stars remain poorly understood. Rotation is a key driver of internal mixing and angular momentum transport, significantly influencing massive star evolution. However, constraining rotation from spectroscopy is challenging, as spectral lines often exhibit excess broadening beyond rotation. The origin of this additional broadening, typically attributed to large-scale velocity fields and commonly referred to as macroturbulence, remains …

Efficient Bayesian Inference from Noisy Pairwise Comparisons
Till Aczel, Lucas Theis, Wattenhofer Roger
https://arxiv.org/abs/2510.09333 https://arxiv.org/…

Efficient Bayesian Inference from Noisy Pairwise Comparisons
Evaluating generative models is challenging because standard metrics often fail to reflect human preferences. Human evaluations are more reliable but costly and noisy, as participants vary in expertise, attention, and diligence. Pairwise comparisons improve consistency, yet aggregating them into overall quality scores requires careful modeling. Bradley-Terry-based methods update item scores from comparisons, but existing approaches either ignore rater variability or lack convergence guarantees,…

Lyman-Alpha Emission from K and M Dwarfs: Intrinsic Profiles, Variability, and Flux in the Habitable Zone
Sarah Peacock, Travis S. Barman, R. O. Parke Loyd, Adam C. Schneider, Allison Youngblood, Kenneth G. Carpenter, Evgenya L. Shkolnik
https://arxiv.org/abs/2509.09029

Lyman-Alpha Emission from K and M Dwarfs: Intrinsic Profiles, Variability, and Flux in the Habitable Zone
Lyman-$α$ (Ly$α$) is the most prominent ultraviolet emission line in low-mass stars, playing a crucial role in exoplanet atmospheric photochemistry, heating, and escape. However, interstellar medium (ISM) absorption typically obscures most of the Ly$α$ profile, requiring reconstructions that introduce systematic uncertainties. We present intrinsic Ly$α$ profiles for 12 high radial velocity K and M dwarfs, where Doppler shifting minimizes ISM contamination, allowing direct measurements of $\…