85 papers
This paper proposes a broadband impedance matching network utilizing the negative inductance of a biased Josephson junction to overcome the gain-bandwidth limitations of passive circuits, thereby enhancing the scan rate for axion dark matter searches.
This paper reports the successful off-line commissioning of the radio frequency quadrupole ion guide for the St. Benedict experiment, demonstrating transport efficiencies exceeding 95% from the upstream RF carpet chamber and 60% from the dedicated $90^\circ$ off-line source to facilitate future tests of the Standard Model's electroweak sector.
This paper demonstrates that the optical extinction manifold of dielectric materials exhibits intrinsic sparsity best captured by the Discrete Cosine Transform rather than the FFT, enabling a compressed sensing architecture that achieves high-fidelity material reconstruction with a 51–94% reduction in hardware sensors by overcoming traditional Nyquist limits.
This paper presents a novel physical model-based conversion formula that overcomes the inherent response delays of chemiresistive gas sensors by dynamically translating resistance changes into real-time gas concentrations, a strategy validated for NO2 and NH3 detection.
To support the ALICE Time Projection Chamber's continuous readout mode during LHC Run 3, the authors present a custom, large-scale FPGA-based pipeline that performs real-time signal processing—including common-mode correction, pedestal subtraction, and ion-tail filtering—to reduce raw data rates from over 3 TB/s to approximately 900 GB/s under extreme high-occupancy conditions.
This paper presents the first results of the CASSIA sensor, a novel monolithic active pixel sensor fabricated in 180 nm CMOS technology that utilizes fully integrated internal gain layers to achieve signal amplification, enabling operation in both low-gain proportional and high-gain single-photon avalanche modes for improved timing resolution and pile-up mitigation in high-luminosity particle physics experiments.
This paper demonstrates that applying Deep Neural Networks to a 2x2 array of linearly-graded Silicon Photomultipliers significantly improves position resolution and linearity while increasing the number of resolvable pixels by a factor of 5.7 to 12.1 compared to traditional reconstruction methods.
Researchers have developed new 1 mm-thick Silicon Drift Detectors that significantly enhance quantum efficiency at 30 keV while maintaining excellent energy resolution, enabling the upcoming EXKALIBUR and VIP-3 experiments to study heavier kaonic atoms and test the Pauli Exclusion Principle with greater precision.
This study characterizes the light yield and transmission properties of Saint-Gobain's BCF-91A and Eljen Technology's new EJ-160 wavelength-shifting fibers under ionizing radiation, revealing that the EJ-160 variants offer significantly higher light yields (5–7 times greater) despite varying attenuation lengths.
This paper presents a comprehensive experimental characterization of a YAG:Ce scintillator, detailing its light yield, temperature-dependent decay time, alpha quenching factors, and strong pulse-shape discrimination capabilities across a wide energy range to validate its suitability for reliable radiation detection and particle identification.
This paper reports recent advancements in GasPM technology aimed at mitigating photon-feedback-induced time-resolution degradation through improved beam tests with a high-speed digitizer and exploring the robustness of LaB photocathodes for future detector upgrades.
This paper reports on the early operation and single-phase commissioning of Proto-0, a small-scale dual-phase argon TPC at INFN Naples designed to validate key technologies for the upcoming DarkSide-20k experiment, with a specific focus on measuring scintillation light yield using calibration sources.
This paper presents a validated experimental and simulation framework that demonstrates the high linearity and precision of a combined LVDT position sensor and voice-coil actuator, confirming its suitability for low-frequency suspension control in gravitational wave detectors.
This study evaluates activation foils and capsule materials for fusion neutron yield measurements, demonstrating that aluminum and copper foils are suitable for multi-foil configurations, 3D-printed thermoplastic capsules introduce negligible measurement bias despite slight count reductions, and lanthanum-based detectors offer a viable alternative to high-purity germanium spectrometers.
This paper introduces TRec, a physics-informed muon scattering tomography framework that significantly enhances the detection of missing fuel in sealed microreactor cores by reconstructing curved muon trajectories and incorporating momentum measurements, thereby outperforming conventional methods like PoCA in both sensitivity and speed under realistic cosmic-ray conditions.
This paper demonstrates a high-efficiency superconducting on-chip filterbank for sub-millimeter integral field units using directional filters, achieving an average peak coupling efficiency of 75% across the 125–220 GHz range.
This paper presents environmental measurements at the Sedrun Access Shaft in Switzerland, demonstrating that its low ground motion and electromagnetic background levels make it a viable site for an 800-meter atom interferometer designed to detect ultralight dark matter and gravitational waves.
This paper investigates how the angular momentum quantization of Rydberg atoms creates distinct, universal spectroscopic fingerprints in electromagnetically-induced transparency signals when exposed to rotating linearly polarized radio-frequency fields, revealing two disparate atomic ladder behaviors that challenge prevailing interpretations of SI-traceable Rydberg atom electrometers.
This paper details the design, mass production, and acceptance testing of the high-voltage dividers, waterproof cables, and connectors for the over 25,600 3-inch photomultiplier tubes used in the JUNO central detector.
This paper presents a real-time, all-fiber microendoscopic polarization sensor that achieves single-photon-level accuracy and complete state reconstruction in constrained, low-light environments by utilizing a few-mode fiber coupled with a deep-learning-based calibration neural network.