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At least 883 records · Page 49

Leveraging staggered tessellation for enhanced spatial resolution in high-granularity calorimeters

Here we advance the concept of high-granularity calorimeters with staggered tessellations, underscoring the effectiveness of a design incorporating multifold staggering cycles based on hexagonal cells to enhance position resolution. Moreover, we introduce HEXPLIT, a sub-cell re-weighting algorithm tailored to harness staggered designs, resulting in additional performance improvements. By combining our proposed staggered design with HEXPLIT, we achieve an approximately twofold enhancement in position resolution for neutrons across a wide energy range, as compared to unstaggered designs. These findings hold the potential to elevate particle-flow performance across various forthcoming facilities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Novel imaging technique for α-particles using a fast optical camera

A new imaging technique forα-particles using a fast optical camera focused on a thin scintillator is presented. Asα-particles interact in a thin layer of LYSO fast scintillator, they produce a localized flash of light. Furthermore, the light is collected with a lens to an intensified optical camera, Tpx3Cam, with single photon sensitivity and excellent spatial & temporal resolutions. The interactions of photons with the camera is reconstructed by means of a custom algorithm, capable of discriminating single photons using time and spatial information

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

MAGIS-100 environmental characterization and noise analysis

We investigate and analyze site specific systematics for the MAGIS-100 atomic interferometry experiment at Fermi National Accelerator Laboratory. As atom interferometers move out of the laboratory environment passive and active mitigation for noise sources must be implemented. To inform the research and development of the experiment design, we measure ambient temperature, humidity, and vibrations of the installation site. We find that temperature fluctuations will necessitate enclosures for critical subsystems and a temperature controlled laser room for the laser system. We also measure and analyze the vibration spectrum above and below ground for the installation site. The seismic vibration effect of gravity gradient noise is also modeled using input from a low-noise seismometer at multiple locations and a mitigation scheme is studied using a stochastic simulation and characterized by a suppression factor.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Neutron irradiation and electrical characterisation of the first 8” silicon pad sensor prototypes for the CMS calorimeter endcap upgrade

As part of its HL-LHC upgrade program, the CMS collaboration is replacing its existing endcap calorimeters with a high-granularity calorimeter (CE). The new calorimeter is a sampling calorimeter with unprecedented transverse and longitudinal readout for both electromagnetic and hadronic compartments. Due to its compactness, intrinsic time resolution, and radiation hardness, silicon has been chosen as active material for the regions exposed to higher radiation levels. The silicon sensors are fabricated as 20 cm (8”) wide hexagonal wafers and are segmented into several hundred pads which are read out individually. As part of the sensor qualification strategy, 8” sensor irradiation with neutrons has been conducted at the Rhode Island Nuclear Science Center (RINSC) and followed by their electrical characterisation in 2020-21. The completion of this important milestone in the CE's R&D program is documented in this paper and it provides detailed account of the associated infrastructure and procedures.The results on the electrical properties of the irradiated CE silicon sensors are presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Data-driven precision determination of the material budget in ALICE

The knowledge of the material budget with a high precision is fundamental for measurements of direct photon production using the photon conversion method due to its direct impact on the total systematic uncertainty. Moreover, it influences many aspects of the charged-particle reconstruction performance. In this article, two procedures to determine data-driven corrections to the material-budget description in ALICE simulation software are developed. One is based on the precise knowledge of the gas composition in the Time Projection Chamber. The other is based on the robustness of the ratio between the produced number of photons and charged particles, to a large extent due to the approximate isospin symmetry in the number of produced neutral and charged pions. Both methods are applied to ALICE data allowing for a reduction of the overall material budget systematic uncertainty from 4.5% down to 2.5%. Using these methods, a locally correct material budget is also achieved. The two proposed methods are generic and can be applied to any experiment in a similar fashion.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

First operation of a multi-channel Q-Pix prototype: measuring transverse electron diffusion in a gas time projection chamber

We report measurements of the transverse diffusion of electrons in P-10 gas (90% Ar, 10% CH 4 ) in a laboratory-scale time projection chamber (TPC) utilizing a novel pixelated signal capture and digitization technique known as Q-Pix. The Q-Pix method incorporates a precision switched integrating transimpedance amplifier whose output is compared to a threshold voltage. Upon reaching the threshold, a comparator sends a 'reset' signal, initiating a discharge of the integrating capacitor. The time difference between successive resets is inversely proportional to the average current at the pixel in that time interval, and the number of resets is directly proportional to the total collected charge. We developed a 16-channel Q-Pix prototype fabricated from commercial off-the-shelf components and coupled them to 16 concentric annular anode electrodes to measure the spatial extent of the electron swarm that reaches the anode after drifting through the uniform field of the TPC. The swarm is produced at a gold photocathode using pulsed UV light. The measured transverse diffusion agrees with simulations in PyBoltz across a range of operating pressures (200–1500 Torr). These results demonstrate that a Q-Pix readout can successfully reconstruct the ionization topology in a TPC.

47 OTHER INSTRUMENTATION↗

Technical Note: SABRS-3 ZEP D3 Periodicities

This technical note documents an investigation of periodic structure in SABRS ZEP D3 detector data spanning February 2022 through April 2026. The analysis was motivated by reports from the co-located NRL SIRI-2 instrument of a 5-minute periodicity beginning in 2026. This report presents null results for the 5-minute search and documents an ambiguous 18.6-hour spectral feature for future reference.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Shortwave Spectrometer (SWS) zenith radiance swsrad.b1 v3 and higher

Hyperspectral zenith radiances from the SWS instrument reported at 1 Hz. This data stream contains calibrated, dark-subtracted, radiances from two grating array spectrometers: a Si-detector based spectrometer denoted by SW and an InGaAs based detector denoted by LW. Spectra from both spectrometers are calibrated based on the spectral responsivity determined by reference against NIST-traceable light sources are reported independently as separate arrays having the same time record but wavelength dimension specified for each detector. Because the LW spectrometer is more susceptible to temperature-induced changes, a scale factor adjustment is applied the the LW spectra to yield agreement with the SW spectra over the wavelength range where they overlap. The final radiances incorporate QC to flag saturated values, periods where house-keeping fields fall outside acceptable bounds, and to flag pixels for which the spectral responsivity is not acceptable.

54 ENVIRONMENTAL SCIENCES↗

Measurement of H(e,e’) and D(e,e’) Cross-Sections for Bloom-Gilman Quark-Hadron Duality Study

The E12-10-002 experiment which ran in 2018 in Hall C at the Thomas Jefferson National Accelerator Facility measured the inclusive electron scattering cross-sections for hydrogen and deuterium. This was the first experiment conducted with the new Super High-Momentum Spectrometer and accompanying instrumentation. These measurements extend the previous Hall C measurements up to Q2 = 16 GeV2. This dissertation presents the analyses of the new detectors and shows the preliminary results for F2 structure function and the study of quark-hadron duality in the four nucleon-resonance regions.

Sun, Abel↗

Study of Nuclear Structure Functions at Jefferson Lab

This thesis presents a study of nuclear modification of quark distributions (the EMC effect) using inclusive electron-scattering data from Jefferson Lab Hall C, with emphasis on experiment E12-10-008 (XEM2). The analysis spans nuclei from light to heavy targets and combines measurements at multiple spectrometer settings to constrain EMC ratios over a broad range in Bjorken-x and Q2. A complete analysis framework was developed to extract charge-normalized and efficiency-corrected yields, including detector calibrations, beam-current calibration, density-loss corrections for cryogenic targets, background subtraction, radiative and Coulomb corrections, and systematic studies. Instrumental cross-checks, including HMS–SHMS comparisons and reconstruction studies, show that residual spectrometer differences are predominantly multiplicative in the kinematic region relevant to the EMC analysis. The extracted EMC ratios are broadly consistent with previous measurements while extending coverage across many nuclei. The EMC slope increases from light to heavy nuclei and shows signs of saturation at large A. After accounting for the dominant A dependence, the results are consistent with no isospin dependence, but also consistent with the predicted modification from the isovector model.

Sharda, Abhyuday [Univ. of Tennessee, Knoxville, T↗

Real-Time Detection of Charge Jumps in Superconducting Qubits with a Convolutional Neural Network

Ionizing radiation from cosmic rays and gammas can induce discontinuous jumps in the environmental charge of superconducting qubits (charge jumps), causing correlated errors that challenge fault-tolerant quantum computing while simultaneously providing a detection signature for quantum sensing applications. Current detection methods operate offline, introducing latency incompatible with in-the-loop qubit control. In this paper, an online detector of charge jumps for superconducting qubits, based on a dilated causal convolutional neural network (DCCNN) designed for in-the-loop deployment on the Quantum Instrumentation Control Kit (QICK) platform, is presented. The network is trained on synthetic Ramsey tomography scans generated from qubit templates measured at the Northwestern Experimental Underground Site (NEXUS) at Fermilab, and translated to FPGA firmware via hls4ml with ap_fixed$\langle 16,6 \rangle$ quantization, reaching a per-inference latency of $6.19 μ$s on the Zynq UltraScale+ RFSoC ZCU216. At this operating point the DCCNN matches the detection efficiency of the established offline $χ^2$ algorithm ($0.843 \pm 0.022$ vs. $0.866 \pm 0.020$ on $|Δq| \in [0.1, 0.5] e$ at matched false-positive rate), while requiring no per-qubit hyperparameter tuning. This shifts charge-jump detection from a post-hoc diagnostic to a control-loop primitive, enabling adaptive protocols that respond to radiation-induced events in situ, with applications to quantum-computing error mitigation and to the use of superconducting qubits as particle detectors.

Gaytan-Villarreal, Daniel [Carnegie Mellon U.]↗

Passive and active neutron signatures of 233 U for nondestructive assay

The thorium fuel cycle is emerging as an attractive alternative to conventional nuclear fuel cycles, as it does not require the enrichment of uranium for long-term sustainability. The operating principle of this fuel cycle is the irradiation of 232 Th to produce 233 U, which is fissile and sustains the fission chain reaction. 233 U poses unique challenges for nuclear safeguards, as it is associated with a uniquely extreme γ-ray environment from 232 U contamination, which limits the feasibility of the γ-ray-based assay, as well as more conservative accountability requirements than for 235 U set by the International Atomic Energy Agency. Consequently, instrumentation used for safeguarding 235 U in traditional fuel cycles may be inapplicable. It is essential that the nondestructive signatures of 233 U be characterized so that nuclear safeguards can be applied to thorium fuel-cycle facilities as they come online. In this work, a set of 233 U 3 O 8 plates, containing 984 g 233 U, was measured at the National Criticality Experiments Research Center. A high-pressure 4 He gaseous scintillation detector, which is insensitive to γ-rays, was used to perform a passive fast neutron spectral signature measurement of 233 U 3 O 8 , and was used in conjunction with a pulsed deuterium-tritium neutron generator to demonstrate the differential die-away signature of this material. Furthermore, an array of 3 He detectors was used in conjunction with the same neutron generator to measure the delayed neutron time profile of 233 U, which is unique to this nuclide. These measurements provide a benchmark for future nondestructive assay instrumentation development, and demonstrate a set of key neutron signatures to be leveraged for nuclear safeguards in the thorium fuel cycle.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

On-chip probabilistic inference for charged-particle tracking at the sensor edge

Modern scientific instruments operate under increasingly extreme constraints on bandwidth, latency, and power. Inference at the sensor edge determines experimental data collection efficiency by deciding which information to save for further analysis. Particle tracking detectors at the Large Hadron Collider exemplify this challenge: pixelated silicon sensors generate rich spatiotemporal ionization patterns, yet most of this information is discarded due to data-rate limitations. Concurrently, advancements in co-design tools provide rapid turn-around for incorporating machine learning into application-specific integrated circuits, motivating designs for particle detectors with new integrated technologies. We demonstrate that neural networks embedded in the front-end electronics can infer charged-particle kinematic parameters from a single silicon layer. We regress hit positions and incident angles with calibrated uncertainties, while satisfying stringent constraints on numerical precision, latency, and silicon area. Our results establish a path toward probabilistic inference directly at the edge, opening new opportunities for intelligent sensing in high-rate scientific instruments.

Das, Arghya Ranjan [Purdue U.] (ORCID:000000018451↗

Neural network methods for radiation detectors and imaging

Recent advances in image data proccesing through deep learning allow for new optimization and performance-enhancement schemes for radiation detectors and imaging hardware. This enables radiation experiments, which includes photon sciences in synchrotron and X-ray free electron lasers as a subclass, through data-endowed artificial intelligence. We give an overview of data generation at photon sources, deep learning-based methods for image processing tasks, and hardware solutions for deep learning acceleration. Most existing deep learning approaches are trained offline, typically using large amounts of computational resources. However, once trained, DNNs can achieve fast inference speeds and can be deployed to edge devices. A new trend is edge computing with less energy consumption (hundreds of watts or less) and real-time analysis potential. While popularly used for edge computing, electronic-based hardware accelerators ranging from general purpose processors such as central processing units (CPUs) to application-specific integrated circuits (ASICs) are constantly reaching performance limits in latency, energy consumption, and other physical constraints. These limits give rise to next-generation analog neuromorhpic hardware platforms, such as optical neural networks (ONNs), for high parallel, low latency, and low energy computing to boost deep learning acceleration (LA-UR-23-32395).

edge computing↗

GRAPH — an readout ASIC for large MCP based detectors

We present a programmable 16 channel, mixed signal, low power readout ASIC, having the project historically named Gigasample Recorder of Analog waveforms from a PHotodetector (GRAPH). It is designed to read large aperture single photon imaging detectors using micro channel plates for charge multiplication, and measuring the detector's response on crossed strips anodes to extrapolate the incoming photon position. Each channel consists of a fast, low power and low noise charge sensitive amplifier, which provides a myriad of coarse and fine programmable options for gain and shaping settings. Further, the amplified signal is recorded using, to our knowledge novel, the Hybrid Universal sampLing Architecture (HULA) ADC. A kind of mixed signal double buffer memory, that enables concurrent waveform recording, and selected event digitized data extraction. The sampling frequency is freely adjustable between few kHz up to 125 MHz, while the chip's internal digital memory holds a history 2048 samples for each channel, with a digital headroom of 12 bits. An optimized region of interest sample-read algorithm allows to extract the information just around the event pulse peak, while selecting the next event, thus substantially reducing the operational dead time. The chip is designed in 130 nm TSMC CMOS technology, and its power consumption is around 47 mW per channel.

47 OTHER INSTRUMENTATION↗

The SparkPix-S ASIC for the sparsified readout of 1 MHz frame-rate X-ray cameras at LCLS-II: pixel design and simulation results

Exploiting the “sparse” nature of the information in XPCS (X-ray Photon Correlation Spectroscopy) and XSVS (Speckle Visibility Spectroscopy) experiments, we present the SparkPix-S, a 3-sides buttable Application Specific Integrated Circuit (ASIC) based on a sparsified readout strategy for large-format hybrid detectors. The SparkPix-S architecture, based on the successful ePix family, will be composed as follows: a front-end 2-D matrix of 384×352 square pixels with 50 µm pitch is arranged to match the dimensions of a PIN Si-sensor matrix; charge readout, signal shaping and amplitude discrimination is performed at pixel-level, by means of a low-power (<18 µW) analog processor, which, in case of an event, negotiates access to an analog bus placed every other column; on the chip periphery (balcony), the information on each bus is digitized by an array of successive approximation analog-to-digital converters (SAR-ADCs) running at 10 Msps; on the digital back-end the global logic will generate the output data stream using low-voltage differential signalling (LVDS). A first prototype of the SparkPix-S, with a reduced matrix size of 96×96 pixels, is currently under production on a 130 nm CMOS technology. Simulated performance results show an equivalent noise charge <60 el. r.m.s. at 1 MHz repetition rate, with a maximum input energy of 60 keV and capability to discriminate charge signals with equivalent energy as low as 900 eV.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗