606 papers
This collection explores the fascinating world of instrumentation and detection within physics, focusing on the tools and sensors that allow scientists to measure the universe. From advanced particle trackers to sensitive gravitational wave detectors, these innovations form the backbone of modern discovery, turning abstract theories into observable data.
On Gist.Science, we process every new preprint in this field as it appears on arXiv, ensuring you stay ahead of the curve. Each paper is accompanied by a clear, plain-language explanation alongside a detailed technical summary, bridging the gap between complex research and accessible knowledge.
Below are the latest papers in physics instrumentation and detection, offering fresh insights into how we observe the fundamental nature of reality.
This paper presents and validates novel channel-level calibration methods for the Silicon Photomultipliers in the JUNO-TAO detector, enabling precise measurement of key parameters such as dark count rate, photon detection efficiency, gain, and optical crosstalk to achieve the experiment's goal of sub-2% energy resolution.
This paper resolves the wide dispersion in reported charge-carrier mobility data for diamond by attributing it to experimental and modeling variables, then benchmarks and recommends specific parameterizations for electrons and holes to improve the accuracy of detector simulations.
This paper presents the design and experimental characterization of the POKERINO prototype, a PbWO-based electromagnetic calorimeter utilizing SiPM sensors, to validate its performance and energy resolution capabilities for the NA64 experiment's search for light dark matter.
This paper demonstrates that a non-destructive external fiber monitor using Ce-doped silica scintillating fibers can effectively detect secondary radiation from an 18 MeV medical cyclotron beamline to provide linear intensity monitoring, beam-loss tracking, and decoupled spatial displacement measurements across various operational scenarios.
This paper presents two complementary machine learning strategies for the CYGNO dark matter experiment: an unsupervised convolutional autoencoder that efficiently reduces data volume by isolating signal regions from noise, and a weakly supervised Classification Without Labels (CWoLa) framework that successfully identifies nuclear-recoil-like topologies without requiring event-level labels.
This paper presents a machine learning-driven inverse-design framework that systematically optimizes the boundary shapes of three-dimensional microwave cavities to maximize electromagnetic helicity, identifying robust, high-performance geometries that surpass traditional heuristic design methods.
This design report outlines the revised Advanced Virgo Plus (AdV+) upgrade strategy for the O5 observing run, which integrates stable recycling cavities, a modified central interferometer layout, and comprehensive subsystem renewals to overcome previous stability limitations and significantly enhance detector sensitivity and astrophysical reach.
This paper presents the testing and characterization of two prototype wafer-scale stitched CMOS sensors, MOSS and MOST, developed for the ALICE ITS3 upgrade, demonstrating their high efficiency, radiation hardness, and the feasibility of using stitched sensors in high-energy physics experiments despite identified design-related failure modes.
This paper introduces and experimentally demonstrates a robust quantum magnetometry scheme using Floquet prethermalization to steer spin orbits, achieving broadband sensitivity to target magnetic fields while intrinsically suppressing environmental noise and control imperfections by over 1000-fold.
This paper presents the development and characterization of the PhotonPix, a plug-and-play single-photon detector featuring an 8 mm Exosens FT MCP-PMT that achieves 10 ps timing precision and operates effectively across a wide dynamic range up to 1 GHz in burst mode and 100 MHz continuously.