587 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 the design of an affordable, motorized, 3D-printed turntable specifically engineered with RF considerations like cable phase stability to enable accurate active element pattern measurements for integrated sensing and communication technologies.
The KOTO experiment at J-PARC successfully suppressed neutron background by a factor of while maintaining 70% signal efficiency for the rare decay search by employing deep convolutional neural networks and Fourier frequency analysis to distinguish neutrons from photons based on their distinct cluster and pulse shapes in the undoped CsI electromagnetic calorimeter.
This paper presents a neural-network framework utilizing Geant4 simulations to reconstruct cosmic-ray nuclei properties in the RadMap Telescope, achieving high angular resolution, charge separation accuracy (up to 99.8% for hydrogen), and energy resolution (<20% below 1 GeV/n) to enable precise determination of astronaut radiation doses.
This paper demonstrates that a standard multi-pass tandem Fabry-Perot interferometer, when operated in a spectral filtering mode and combined with light-sheet illumination, enables rapid, full-field Brillouin microscopy with millisecond-scale acquisition times, overcoming the historical speed limitations of FPI-based systems for practical imaging applications.
This study proposes a novel machine learning framework combining a Monte Carlo-optimized gamma-ray spectrometer with a two-stage neural network (denoising autoencoder and U-Net) to achieve precise spectral reconstruction of GeV-scale gamma rays, addressing the challenges of ill-posed inverse problems and statistical noise in high-energy photon diagnostics.
This paper demonstrates the capabilities of a custom-built plug-flow fixed-bed cell for high-temperature (up to 1000°C) and high-pressure (up to 10 bar) operando laboratory X-ray absorption spectroscopy, successfully resolving oxidation state changes and catalytic activity in manganese and nickel systems during CO2 methanation within 5–15 minutes per spectrum.
This paper introduces the Lund Plane to Bloch (LP2B) encoding and a corresponding Quantum Tree-Topology Network (QTTN) that maps robust jet kinematics to qubit states, achieving competitive performance in object and polarization tagging with significantly fewer parameters and reduced systematic uncertainties compared to classical deep learning models, while also being validated on real quantum hardware.
This study proposes and demonstrates a practical method for reconstructing three-dimensional recoil-electron directions in electron-tracking Compton cameras by combining high-resolution 2D optical imaging, 1D waveform readout, and deep learning, achieving improved angular and starting-point resolution without the data volume constraints of full 3D readout systems.
This paper introduces snapshot-referencing (SSR), a software-based retrospective drift correction method that utilizes a fast-scan reference image and flexible basis functions to eliminate spatial distortions in long-duration S(T)EM spectral mapping, thereby restoring the integrity of hyperspectral data without requiring specialized hardware.
This paper presents the experimental characterization of a RNDR-DEPFET pixel detector, highlighting its deep sub-electron noise performance, high time resolution, and suitability for the DANAE experiment's search for light dark matter via electron recoil detection.