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DOE OSTI2016

A Brief Technical History of the Large-Area Picosecond Photodetector (LAPPD) Collaboration

The Large Area Picosecond PhotoDetector (LAPPD) Collaboration was formed in 2009 to develop large-area photodetectors capable of time resolutions measured in pico-seconds, with accompanying sub-millimeter spatial resolution. During the next three and one-half years the Collaboration developed the LAPPD design of 20 x 20 cm modules with gains greater than $10^7$ and non-uniformity less than $15\%$, time resolution less than 50 psec for single photons and spatial resolution of 700~microns in both lateral dimensions. We describe the R\&D performed to develop large-area micro-channel plate glass substrates, resistive and secondary-emitting coatings, large-area bialkali photocathodes, and RF-capable hermetic packaging. In addition, the Collaboration developed the necessary electronics for large systems capable of precise timing, built up from a custom low-power 15-GigaSample/sec waveform sampling 6-channel integrated circuit and supported by a two-level modular data acquisition system based on Field-Programmable Gate Arrays for local control, data-sparcification, and triggering. We discuss the formation, organization, and technical successes and short-comings of the Collaboration. The Collaboration ended in December 2012 with a transition from R\&D to commercialization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2019

E-1039 "SpinQuest" FPGA Trigger

The SpinQuest experiment will measure an azimuthal asymmetry in the Drell-Yan production of $\mu+$ $\mu-$ pairs from 120 GeV/c proton interactions with polarized nucleons to extract the Sivers function for $\bar{u}$ and $\bar{d}$. A large combinatorial background from muons produced in the beam dump requires a trigger which is capable of identifying dimuon pairs originating from the target in a high rate environment. The trigger system consists of four stations of scintillator hodoscopes whose 96 channels are digitized and processed by field-programmable gate array (FPGA) based VMEbus modules. Hodoscope hit patterns are compared to predetermined sets, chosen from Monte Carlo simulations, in a tiered lookup table to generate trigger decisions. The design and current status of the FPGA trigger will be presented and planned upgrades to the trigger logic will be discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2017

A Lithography‐Free and Field‐Programmable Photonic Metacanvas

Abstract The unique correspondence between mathematical operators and photonic elements in wave optics enables quantitative analysis of light manipulation with individual optical devices. Phase‐transition materials are able to provide real‐time reconfigurability of these devices, which would create new optical functionalities via (re)compilation of photonic operators, as those achieved in other fields such as field‐programmable gate arrays (FPGA). Here, by exploiting the hysteretic phase transition of vanadium dioxide, an all‐solid, rewritable metacanvas on which nearly arbitrary photonic devices can be rapidly and repeatedly written and erased is presented. The writing is performed with a low‐power laser and the entire process stays below 90 °C. Using the metacanvas, dynamic manipulation of optical waves is demonstrated for light propagation, polarization, and reconstruction. The metacanvas supports physical (re)compilation of photonic operators akin to that of FPGA, opening up possibilities where photonic elements can be field programmed to deliver complex, system‐level functionalities.

Dong, Kaichen↗

DOE OSTI2023

Implementing machine learning methods on QICK hardware for qubit readout & control

Quantum readout and control is a fundamental aspect of quantum computing that requires accurate measurement of qubit states. Errors emerge in all stages, from initialization to readout, and identifying errors in post-processing necessitates resource-intensive statistical analysis. In our work, we use a lightweight fully-connected neural network (NN) to classify states of a transmon system with no prior processing. Our NN accelerator yields higher fidelities (92%) than the classical matched filter method (84%). By exploiting the natural parallelism of NNs and their placement near the source of data on field-programmable gate arrays (FPGAs), we can achieve ultra-low latency on the Quantum Instrumentation Control Kit (QICK). Integrating machine learning methods on QICK opens several pathways for efficient real-time processing of quantum circuits.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2015

Radiation testing campaign results for understanding the suitability of FPGAs in detector electronics

SRAM based Field Programmable Gate Arrays (FPGAs) have been rarely used in High Energy Physics (HEP) due to their sensitivity to radiation. The last generation of commercial FPGAs based on 28 nm feature size and on Silicon On Insulator (SOI) technologies are more tolerant to radiation to the level that their use in front-end electronics is now feasible. FPGAs provide re-programmability, high-speed computation and fast data transmission through the embedded serial transceivers. They could replace custom application specific integrated circuits in front end electronics in locations with moderate radiation field. Finally, the use of a FPGA in HEP experiments is only limited by our ability to mitigate single event effects induced by the high energy hadrons present in the radiation field.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2019

A Novel TDC Scheme: Combinatorial Gray Code Oscillator Based TDC for Low Power and Low Resource Usage Applications

In common digital electronics design practice, combinatorial loop is less preferable, especially in the multi-bit cases. An exception of multi-bit feedback system that is allowed to be implemented in combinatorial loop is the Gray code sequence generator. The Gray code sequence generator runs by itself without being driven by an external clock. It steps through Gray code sequence significantly faster than the Gray code counter under the same silicon technology. In high energy physics experiments, it is necessary to find a low resource usage and low power TDC (Time-to-Digital-Converter) scheme for high channel count detectors. A Gray code oscillator based TDC is a good candidate for such a scheme. In this paper, we describe our work of design and implementation of a TDC based on combinatorial Gray code oscillator in a Xilinx Kintex-7 FPGA (Field-Programmable Gate Array). The implementation and test results are presented. The test result shows that the TDC using only 8 logic elements is able to reach a RMS precision of 160 ps for time difference measurements of a single pulse. The single pulse measurement precision can be further improved to 51 ps with the weighted average scheme using data from the same TDC channels captured by 4 consecutive system clock edges.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Distilling particle knowledge for fast reconstruction at high-energy physics experiments

Knowledge distillation is a form of model compression that allows artificial neural networks of different sizes to learn from one another. Its main application is the compactification of large deep neural networks to free up computational resources, in particular on edge devices. In this article, we consider proton-proton collisions at the High-Luminosity Large Hadron Collider (HL-LHC) and demonstrate a successful knowledge transfer from an event-level graph neural network (GNN) to a particle-level small deep neural network (DNN). Our algorithm, DistillNet, is a DNN that is trained to learn about the provenance of particles, as provided by the soft labels that are the GNN outputs, to predict whether or not a particle originates from the primary interaction vertex. The results indicate that for this problem, which is one of the main challenges at the HL-LHC, there is minimal loss during the transfer of knowledge to the small student network, while improving significantly the computational resource needs compared to the teacher. This is demonstrated for the distilled student network on a CPU, as well as for a quantized and pruned student network deployed on a field programmable gate array. Our study proves that knowledge transfer between networks of different complexity can be used for fast artificial intelligence (AI) in high-energy physics that improves the expressiveness of observables over non-AI-based reconstruction algorithms. Such an approach can become essential at the HL-LHC experiments, e.g. to comply with the resource budget of their trigger stages.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Preliminary design overview and performance assessment of the ITER low-field side reflectometer

The design of the ITER low-field side reflectometer (LFSR) has matured to a complete end-to-end preliminary design. LFSR will supply three key plasma measurements: (1) electron density profile, (2) electron density fluctuations, and (3) poloidal rotation. Simultaneous measurements of the three quantities are enabled by an array of six monostatic antennas which inject from an equatorial port on the outboard side of the ITER vessel. Low-loss transmission lines, consisting of corrugated, overmoded waveguide and miter bends, transmit the 30–165 GHz, O- and X-mode signals to and from the ITER plasma. Integrated transmission-line components serve a range of purposes, such as protection from high-power stray radiofrequency radiation, accommodation of transmission-line displacement, and simultaneous measurement of reference and plasma phases during the discharge. Broadband transmission signals are realized by full-band microwave transceivers combined with quasi-optical multiplexing. A field-programmable gate array (FPGA) processor demodulates the profile reflectometer signals, enabling real-time density profile measurements for plasma control system feedback. A full-scale transmission line test facility provides an integrated environment to assess the performance of critical LFSR components. Theoretical modeling together with insertion loss measurements provide the basis for a comprehensive power budget, which accounts for transmitted output power, transmission-line losses, antenna coupling, and plasma effects. Results indicate that high signal-to-noise ratios are achievable with the current design. A synthetic reflectometer model, using real design parameters and baseline ITER profiles, has been developed to estimate the return signal. With evolving microwave and data acquisition technologies, full-band, ultrafast sweeps (<1 μs) will be realizable for ITER.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2016

An FPGA-based bolometer for the MAST-U Super-X divertor

A new resistive bolometer system has been developed for MAST-Upgrade. It will measure radiated power in the new Super-X divertor, with millisecond time resolution, along 16 vertical and 16 horizontal lines of sight. The system uses a Xilinx Zynq-7000 series Field-Programmable Gate Array (FPGA) in the D-TACQ ACQ2106 carrier to perform real time data acquisition and signal processing. The FPGA enables AC-synchronous detection using high performance digital filtering to achieve a high signal-to-noise ratio and will be able to output processed data in real time with millisecond latency. The system has been installed on 8 previously unused channels of the JET vertical bolometer system. Initial results suggest good agreement with data from existing vertical channels but with higher bandwidth and signal-to-noise ratio.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Evolution of the ATLAS event data model for the HL-LHC

The upcoming high-luminosity run of the CERN Large Hadron Collider (HL-LHC) will yield an unprecedented volume of data. In order to process this data, the ATLAS collaboration is evolving its offline software to be able to use heterogeneous resources such as graphical processing units (GPUs) and field-programmable gate arrays (FPGAs). To reduce conversion overheads, the event data model (EDM) should be compatible with the requirements of these resources. While the ATLAS EDM has long allowed representing data as a structure of arrays, further evolution of the EDM can enable more efficient sharing of data between CPU and GPU resources. Some of this work will be summarized here, including extensions to allow controlling how memory for event data is allocated and the implementation of jagged vectors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

An Experimental Feasibility Study on Applying Neutron Tomography to Encapsulated Spent Nuclear Fuel - 20050

Visual inspection makes easier to ensure the integrity and safety of spent nuclear fuel (SNF) than any classical techniques. Various classical techniques have been applied but there are no reliable methods to qualitatively and quantitatively verify spent fuel in dry storage. Thus, the present authors have developed the prototype safeguards apparatus for dry storage employing the array of He-4 gas scintillation detectors (S670E, Arktis Radiation Detectors Ltd., Switzerland), newly designed to simultaneously measure thermal and fast neutrons without any moderators. The S670E detector has a cylindrical shape with a diameter of 52 mm and active length of 600 mm (total length: 875 mm). The detector is filled by He-4 gas with an approximate pressure of 180 bar for fast neutron detection, and its inner wall is coated by Li-6 for thermal neutron detection. The scintillation lights generated via Li-6 nuclear reaction and elastic scattering are collected by 24 SiPMs linearly paired at the center of the detector. The detector delivers a TTL (Transistor-Transistor Logic) output for pulse readout and UART (Universal Asynchronous Receiver Transmitter) for device control. In order to assess feasibility of the apparatus, an experimental system has been designed, built, and optimized via computational studies. Cf-252 neutron sources and linearly arrayed detectors, working as a single detector, were occupied for this study due to the difficulties in working with SNF. The laboratory scale cask (diameter: 0.67 m, height: 1.5 m), minimized by a factor of 10 compared to the actual thickness of a commercial TN-32 cask, was also manufactured. The detector array was designed to rotate the lab-scale cask and obtain 36 image profiles at every 10 degrees. All profiles were aligned in single frame image called a sinogram, and the cross-sectional image was then fabricated by the inverse radon transform algorithm. These experiments have been repeated with different configurations and numbers of sources. Some gamma-ray sources were also measured with neutron sources in order to distinguish between neutron and gamma-ray pulses. Basically, a He-4 detector is designed to run on Linux OS so it is difficult to directly apply to Windows-based equipment widely used in S. Korea. Therefore, a new data acquisition board working on Windows OS was designed and built. The board mainly consists of FPGA (Field Programmable Gate Array) and SoC (System on Chip) for TTL pulse readout, sorting measured data, and transferring data to a user interface. In conclusion, the tomographic system at lab-scale has shown considerable potential to detect a partial or gross defect of encapsulated assemblies in dry storage. Next steps of this study will be to 1) repeatedly carry out experiments to demonstrate scientific reliability and validity, and 2) numerically integrate signals with weight factors to enhance the image quality since the suggested system based on passive interrogation method requires longer measurement time. Finally, the system will apply to a commercial dry storage phased out soon in S. Korea. (authors)

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2016

Development of an FPGA-based multipoint laser pyroshock measurement system for explosive bolts

Pyroshock can cause failure to the objective of an aerospace structure by damaging its sensitive electronic equipment, which is responsible for performing decisive operations. A pyroshock is the high intensity shock wave that is generated when a pyrotechnic device is explosively triggered to separate, release, or activate structural subsystems of an aerospace architecture. Pyroshock measurement plays an important role in experimental simulations to understand the characteristics of pyroshock on the host structure. This paper presents a technology to measure a pyroshock wave at multiple points using laser Doppler vibrometers (LDVs). These LDVs detect the pyroshock wave generated due to an explosive-based pyrotechnical event. Field programmable gate array (FPGA) based data acquisition is used in the study to acquire pyroshock signals simultaneously from multiple channels. This paper describes the complete system design for multipoint pyroshock measurement. The firmware architecture for the implementation of multichannel data acquisition on an FPGA-based development board is also discussed. An experiment using explosive bolts was configured to test the reliability of the system. Pyroshock was generated using explosive excitation on a 22-mm-thick steel plate. Three LDVs were deployed to capture the pyroshock wave at different points. The pyroshocks captured were displayed as acceleration plots. The results showed that our system effectively captured the pyroshock wave with a peak-to-peak magnitude of 303 741 g. The contribution of this paper is a specialized architecture of firmware design programmed in FPGA for data acquisition of large amount of multichannel pyroshock data. The advantages of the developed system are the near-field, multipoint, non-contact, and remote measurement of a pyroshock wave, which is dangerous and expensive to produce in aerospace pyrotechnic tests.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Nanosecond anomaly detection with decision trees and real-time application to exotic Higgs decays

Abstract We present an interpretable implementation of the autoencoding algorithm, used as an anomaly detector, built with a forest of deep decision trees on FPGA, field programmable gate arrays. Scenarios at the Large Hadron Collider at CERN are considered, for which the autoencoder is trained using known physical processes of the Standard Model. The design is then deployed in real-time trigger systems for anomaly detection of unknown physical processes, such as the detection of rare exotic decays of the Higgs boson. The inference is made with a latency value of 30 ns at percent-level resource usage using the Xilinx Virtex UltraScale+ VU9P FPGA. Our method offers anomaly detection at low latency values for edge AI users with resource constraints.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Searching for Clues for a Matter Dominated Universe in Liquid Argon Time Projection Chambers

Liquid Argon Time Projection Chambers (LArTPCs) represent one of the most widely utilized neutrino detection techniques in neutrino experiments, for instance, in the Short Baseline Neutrino (SBN) program and the future large-scale LArTPC: Deep Underground Neutrino Experiment (DUNE). The high-end technique, facilitating excellent spatial and calorimetric reconstruction resolution, also enables testing exotic Beyond Standard Model (BSM) theories, such as baryon number violation (BNV) processes (e.g., proton-decay, neutron-antineutron oscillation). At the same time, Machine Learning (ML) techniques have demonstrated their ubiquitous use in recent decades; ML techniques have also become some of the most powerful tools in high-energy physics (HEP) analyses. Furthermore, the development of algorithms to cater to the needs of problems in HEP (i.e., triggering, reconstruction, improving sensitivity, etc.) has also become an active area of research. By developing a combined approach using Convolutional Neural Network (CNN) and Boosted Decision Tree (BDT) techniques, the sensitivity of neutron-antineutron oscillation in DUNE is evaluated for a projected exposure of 400kton·years. Additionally, to meet the triggering requirement to select such rare events in DUNE, such a search is only supported with highly efficient self-triggering algorithms. An ML-based self-triggering scheme for large-scale LArTPCs, such as DUNE, is also developed with the intention of implementation on field-programmable gate arrays (FPGAs). The ML-based approach for searching for neutron-antineutron oscillation can be demonstrated and validated on the current LArTPC MicroBooNE. The analysis in MicroBooNE represents the first-ever search for neutron-antineutron oscillation in a LArTPC. DUNE's projected 90% C.L. sensitivity to the neutron antineutron oscillation lifetime is 6.45×10³² years, assuming 1.327×10³⁵ neutron·years, equivalent to 10 years of DUNE far detector exposure (400kton·years). For MicroBooNE, assuming 372 seconds of exposure (equivalent to 3.13×10³⁶ neutron·years), the 90% C.L. lifetime sensitivity is found at 3.07×10²⁵ yrs, after accounting for Monte-Carlo statistical uncertainty and systematic uncertainty from detector effects.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2017

Mitigated FPGA design of multi-gigabit transceivers for application in high radiation environments of High Energy Physics experiments

SRAM-ba8ed Field Programmable Gate Array (FPGA) logic devices arc very attractive in applications where high data throughput is needed, such as the latest generation of High Energy Physics (HEP) experiments. FPGAs have been rarely used in such experiments because of their sensitivity to radiation. The present paper proposes a mitigation approach applied to commercial FPGA devices to meet the reliability requirements for the front-end electronics of the Liquid Argon (LAr) electromagnetic calorimeter of the ATLAS experiment, located at CERN. Particular attention will be devoted to define a proper mitigation scheme of the multi-gigabit transceivers embedded in the FPGA, which is a critical part of the LAr data acquisition chain. A demonstrator board is being developed to validate the proposed methodology. :!\litigation techniques such as Triple Modular Redundancy (T:t\IR) and scrubbing will be used to increase the robustness of the design and to maximize the fault tolerance from Single-Event Upsets (SEUs).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Fast convolutional neural networks on FPGAs with hls4ml

We introduce an automated tool for deploying ultra low-latency, low-power deep neural networks with convolutional layers on field-programmable gate arrays (FPGAs). By extending the hls4ml library, we demonstrate an inference latency of 5 µs using convolutional architectures, targeting microsecond latency applications like those at the CERN Large Hadron Collider. Considering benchmark models trained on the Street View House Numbers Dataset, we demonstrate various methods for model compression in order to fit the computational constraints of a typical FPGA device used in trigger and data acquisition systems of particle detectors. In particular, we discuss pruning and quantization-aware training, and demonstrate how resource utilization can be significantly reduced with little to no loss in model accuracy. We show that the FPGA critical resource consumption can be reduced by 97% with zero loss in model accuracy, and by 99% when tolerating a 6% accuracy degradation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2018

Instrumentation and Control Selection for the 12 GeV Hall-B Magnets at Jefferson Lab

Here, as part of the Jefferson Lab 12 GeV accelerator upgrade, the Experimental Physics Hall B detector system requires two superconducting magnets – a Torus and a Solenoid. The specifications required maximum space for the detectors which led to the choice of conduction cooling for each magnet. The Torus consists of 6 trapezoidal 'race-track'-type coils connected in series with an operating current of 3770 A. The Solenoid is an actively shielded 5 Tesla magnet consisting of 5 coils connected in series operating at 2416 A. Within the hall the two magnets are located in close proximity to each other and are surrounded by particle detectors. We describe the philosophy behind the instrumentation selection and control design that accounts for this proximity and other challenging working conditions. We describe the choice of sensor technologies, as well as the control and data acquisition methods. The magnet power and cryogenic control sub-systems are implemented using Allen Bradley Control Logix 1756-L72 Programmable Logic Controllers. Sensor instrumentation read-backs are routed into the PLC via National Instruments cRIO hardware (Field Programmable Gate Arrays or FPGA/RT application) using Jefferson Lab designed FPGA-based multi-sensor-excitation-chassis. Configuration, monitoring, and alarm handlers for the magnet systems are provided via an Experimental Physics Instrumentation & Control System interface (EPICS). Failure Modes and Effects Analysis (FMEA) and the requirement to monitor critical parameters during operation guided the selection of instrumentation and associated hardware. The design of the quench protection and voltage tap sub-systems was driven by the anticipated level of voltages developed during a magnet quench. The primary hard-wired quench detection and protection sub-system together with the secondary PLC-based protection sub-system is also discussed. The successful commissioning and subsequent performance of these magnets demonstrates the robustness of the design and implementation approach that was adopted by the Jefferson Lab team and serves as an excellent 'How To' guide for future projects of this size and complexity.

12 GeV↗

DOE OSTI2024

wa-hls4ml: A GNN Surrogate Model for hls4ml

Recent advancements in use of machine learning techniques on field-programmable gate arrays (FPGAs) have allowed for implementation of embedded neural networks with extremely low latency. This is invaluable for particle detectors at the Large Hadron Collider, where latency and used area must be strictly bounded. The hls4ml framework is a procedure for converting from trained machine learning model software, to a synthesis result that can be used on an FPGA. However, running the pipeline is a time-consuming procedure, and there is a strong risk of failure. In particular, it is possible that the model is unable to be converted into a synthesis result, or that the resource consumption of the model will exceed the resources of the target FPGA. To aid with this development, we introduce wa-hls4ml, a surrogate model which uses a graph neural network to emulate the structure of the source models. The goal is to estimate the chance of success and resource consumption of an arbitrary model when passed through the hls4ml procedure, without the time consumption of actually running the pipeline.

43 PARTICLE ACCELERATORS↗