Tootfinder

Optical tweezers as a tool for quantitative imaging
Ilya M Beskin, Jordan Zesch, Emma Hunt, Alexander Weinstein, Ernst-Ludwig Florin
https://arxiv.org/abs/2506.08186

Optical tweezers as a tool for quantitative imaging
Optical tweezers equipped with position detection allow for application of piconewton-scale forces and high-temporal-resolution measurements of nanometer-scale motion. While typically used for trapping microscopic objects, the optical tweezer detection pathway can also be used for a microscopy technique sensitive to nanometer-sized structures. Optical tweezers most commonly use back-focal-plane detection to determine the position of the trapped object. This technique involves analyzing the inte…

Hot Rocks Survey III: A deep eclipse for LHS 1140c and a new Gaussian process method to account for correlated noise in individual pixels
Mark Fortune, Neale P. Gibson, Hannah Diamond-Lowe, Jo\~ao M. Mendon\c{c}a, Am\'elie Gressier, Daniel Kitzmann, Natalie H. Allen, Prune C. August, Jegug Ih, Erik Meier Vald\'es, Merlin Zgraggen, Lars A. Buchhave, Brice-Olivier Demory, N\'estor Espinoza, Kevin Heng, Kathryn Jones, Alexander D. Rathcke

Hot Rocks Survey III: A deep eclipse for LHS 1140c and a new Gaussian process method to account for correlated noise in individual pixels
Time-series photometry at mid-infrared wavelengths is becoming a common technique to search for atmospheres around rocky exoplanets. This method constrains the brightness temperature of the planet to determine whether heat redistribution is taking place - indicative of an atmosphere - or whether the heat is reradiated from a low albedo bare rock. By observing at 15$μ$m we are also highly sensitive to CO$_2$ absorption. We observed three eclipses of the rocky super-Earth LHS 1140c using MIRI/Im…

Probabilistic measures afford fair comparisons of AIWP and NWP model output
Tilmann Gneiting, Tobias Biegert, Kristof Kraus, Eva-Maria Walz, Alexander I. Jordan, Sebastian Lerch
https://arxiv.org/abs/2506.03744

Probabilistic measures afford fair comparisons of AIWP and NWP model output
We introduce a new measure for fair and meaningful comparisons of single-valued output from artificial intelligence based weather prediction (AIWP) and numerical weather prediction (NWP) models, called potential continuous ranked probability score (PC). In a nutshell, we subject the deterministic backbone of physics-based and data-driven models post hoc to the same statistical postprocessing technique, namely, isotonic distributional regression (IDR). Then we find PC as the mean continuous rank…