Search NASA⌕ Search

SEARCH · Search NASA

Results for “streaming readout”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

A machine learning based approach to online electron reconstruction at CLAS12

Online reconstruction is key for monitoring purposes and real time analysis in High Energy and Nuclear Physics experiments. A necessary component of reconstruction algorithms is particle identification that combines information left by a particle passing through several detector components to identify the particle’s type. Of particular interest to electro-production Nuclear Physics experiments such as CLAS12 is electron identification which is used to trigger data recording. A machine learning approach was developed for CLAS12 to reconstruct and identify electrons by combining raw signals at the data acquisition level from several detector components. Here, this approach achieves an electron identification purity above 75% whilst retaining an efficiency close to 100%. The machine learning tools are capable of running at high rates exceeding the data acquisition rates and will allow electron reconstruction in real-time. This work enhances online analyses and monitoring and can contribute to improved triggering at CLAS12. This machine learning driven approach will also be crucial for experiments aiming to transition to streaming readout operations where online reconstruction will be a key component of the data taking paradigm.

Artificial intelligence↗
DOE OSTI2024

Real-time charged track reconstruction for CLAS12

Abstract This paper presents the results of charged particle track reconstruction in CLAS12 using artificial intelligence. In our approach, we use machine learning algorithms to reconstruct tracks, including their momentum and direction, with high accuracy from raw hits of the CLAS12 drift chambers. The reconstruction is performed in real-time, with the rate of data acquisition, and allows for the identification of event topologies in real-time. This approach revolutionizes the Nuclear Physics experiments' data processing, allowing us to identify and categorize the experimental data on the fly, and will lead to a significant reduction in experiment data processing. It can also be used in streaming readout applications leading to more efficient data acquisition and post-processing.

Instruments & Instrumentation↗
DOE OSTI2024

Lead tungstate calorimeters at Jefferson Lab and perspectives for the Electron–Ion Collider

Electromagnetic calorimeters based on PbWO4 scintillating crystals have a widespread applica- tion in experiments at different accelerator facilities such as CERN, FNAL, GSI, and Jefferson Lab. The unique properties of PbWO4 crystals, including a small radiation length and Molire radius, make them ideal for building high-granularity, radiation-hard detectors. This enables excellent spa- tial separation and energy resolution of reconstructed electromagnetic showers, making PbWO4 crystals the material of choice for numerous experiments. Lead tungstate calorimeters have been successfully used in several experiments at Jefferson Lab. Two large-scale detectors have been re- cently fabricated for future experiments : the Neutral Particle Spectrometer and the lead tungstate calorimeter of the GlueX detector. The future application of PbWO4 crystals in the ElectronIon Collider further highlights their ongoing importance in advancing experimental capabilities. In planning new experiments, the development of calorimeter instrumentation technologies becomes paramount. The integration of modern photodetectors, such as Silicon photomultipliers that are capable of operating in strong magnetic fields, and the implementation of streaming readout data acquisition systems, sophisticated shower reconstruction algorithms, and real-time data analysis are some examples of the continuously growing requirements of experimental setups. I will give an overview of the lead tungstate scintillating calorimeters and discuss some recent advancement in the calorimeter instrumentation.

Somov, Alexander↗
DOE OSTI2026

Intelligent Experiments Through Real-time AI: Fast Data Processing and Autonomous Detector Control for sPHENIX and Future EIC Detectors (Final Report)

The overall vision of this project was to integrate real-time artificial intelligence (AI) directly into the data acquisition and detector-control systems of nuclear physics experiments, including both fast online event selection and an autonomous detector-control feedback loop. The work carried out under the award focused on the fast online event-selection half of that vision: the efficient recording of low-momentum heavy-flavor (HF) hadron decays in proton-proton collisions at the sPHENIX experiment at the Relativistic Heavy Ion Collider (RHIC)—an observable that requires fast tracking and topological trigger selection not previously demonstrated at RHIC, and that is essential for QCD studies at future facilities such as the Electron-Ion Collider (EIC). The autonomous detector-control (GPU-based feedback) component named in the project title remained a design concept and was not implemented under this award. The Massachusetts Institute of Technology (MIT) group led the offline simulation and data processing needed to train the machine-learning (ML) models, the translation of trained models to Field-Programmable Gate Array (FPGA) firmware using the hls4ml framework, and the physics validation of heavy-flavor reconstruction. Over the award period, the team developed and hardware-tested the principal components of an AI-based heavy-flavor trigger on simulated and recorded sPHENIX tracker data: a software Bipartite Graph Attention Network (BiGAT) trigger model reaching > 95% signal efficiency at 99% background rejection; an FPGA-native hit clusterizer matching the offline clustering; smaller networks synthesized to FPGA within the required sub-10 µs latency; and an assembled decoder–clusterizer–inference firmware chain exercised on the FELIX readout board. A complete, fully integrated hardware demonstrator was not finished within the award period. This report documents the project goals, the MIT group’s contributions, the technical accomplishments, and the outlook toward applications at the future EIC ePIC detector.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Accurate and confident prediction of electron beam longitudinal properties using spectral virtual diagnostics

Abstract Longitudinal phase space (LPS) provides a critical information about electron beam dynamics for various scientific applications. For example, it can give insight into the high-brightness X-ray radiation from a free electron laser. Existing diagnostics are invasive, and often times cannot operate at the required resolution. In this work we present a machine learning-based Virtual Diagnostic (VD) tool to accurately predict the LPS for every shot using spectral information collected non-destructively from the radiation of relativistic electron beam. We demonstrate the tool’s accuracy for three different case studies with experimental or simulated data. For each case, we introduce a method to increase the confidence in the VD tool. We anticipate that spectral VD would improve the setup and understanding of experimental configurations at DOE’s user facilities as well as data sorting and analysis. The spectral VD can provide confident knowledge of the longitudinal bunch properties at the next generation of high-repetition rate linear accelerators while reducing the load on data storage, readout and streaming requirements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

ESnet/JLab FPGA Accelerated Transport

To increase the science rate for high data rates/volumes, Thomas Jefferson National Accelerator Facility (JLab) has partnered with Energy Sciences Network (ESnet) to define an edge to data center traffic shaping / steering transport capability featuring data event aware network shaping and forwarding. The keystone of this ESnet+JLab FPGA Accelerated Transport (EJFAT) is the joint development of an AI/ML directed dynamic compute work Load Balancer (LB) of UDP streamed data. The LB is a suite consisting of a Field Programmable Gate Array (FPGA) executing the dynamically configurable, low fixed latency LB data plane featuring real-time packet redirection and high throughput, and a control plane running on the FPGA host computer that monitors network and compute farm telemetry in order to make dynamic AI/ML guided decisions for destination compute host redirection/load balancing and destination resource provisioning. The LB provides for three-tier horizontal scaling across LB suites, core compute hosts, and CPUs within a host. The LB effectively provides seamless integration of edge/core computing to support direct experimental data processing for immediate use by JLab science programs and others such as the EIC as well as data centers of the future requiring high throughput and low latency for both hot and cooled data for both running experiment data acquisition systems and data center use cases.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1983

Design and performance of the Stratospheric Aerosol and Gas Experiment II (SAGE II) instrument

Design and performance data are analyzed for the Stratospheric Aerosol and Gas Experiment II (SAGE II) instrument, which has been developed for the NASA Earth Radiation Budget Satellite (ERBS). SAGE II is designed to monitor globally, from 70 degrees S to 70 degrees N latitude, the vertical distribution of stratospheric aerosols, ozone, water vapor, and nitrogen dioxide by measuring the extinction of solar radiation through the earth's atmosphere during the ERBS observatory solar occultations. A flat scanning mirror reflects solar radiation into a Cassegrain type telescope, which forms a solar image on the entrance slit of a grating spectrometer. The instantaneous-field-of-view of the SAGE II is scanned along the vertical solar diameter by the elevation scan mirror. The optical system is contained within an azimuth gimbal which tracks the solar radiometric centroid during the data event, while the spectrometer isolates seven spectral wavelengths from 0.385-1.02 micrometers. The seven channels of the spectrometer use silicon photodiode dedectors operated in the photovoltaic mode. The detector outputs are multiplexed into a serial data stream for readout by the ERBS telemetry system, with each output being sampled 64 times per second and digitized to 12 bit resolution.

Zaun, N. H.↗
NASA NTRS2008

Multichannel Networked Phasemeter Readout and Analysis

Netmeter software reads a data stream from up to 250 networked phasemeters, synchronizes the data, saves the reduced data to disk (after applying a low-pass filter), and provides a Web server interface for remote control. Unlike older phasemeter software that requires a special, real-time operating system, this program can run on any general-purpose computer. It needs about five percent of the CPU (central processing unit) to process 20 channels because it adds built-in data logging and network-based GUIs (graphical user interfaces) that are implemented in Scalable Vector Graphics (SVG). Netmeter runs on Linux and Windows. It displays the instantaneous displacements measured by several phasemeters at a user-selectable rate, up to 1 kHz. The program monitors the measure and reference channel frequencies. For ease of use, levels of status in Netmeter are color coded: green for normal operation, yellow for network errors, and red for optical misalignment problems. Netmeter includes user-selectable filters up to 4 k samples, and user-selectable averaging windows (after filtering). Before filtering, the program saves raw data to disk using a burst-write technique.

Edmonds, Karina↗
DOE OSTI2022

Active readout-error mitigation

Mitigating errors is a significant challenge for near-term quantum computers. One of the most important sources of errors is related to the readout of the quantum state into a classical bit stream. A variety of techniques have been proposed to mitigate these errors with post-hoc corrections. Here, we propose a complementary scheme to actively reduce readout errors on a shot-by-shot basis by encoding single qubits, immediately prior to readout, into multiqubit states. The computational resources of our technique are independent of the circuit depth and are compatible with the error rates and connectivity of many current devices. We analyze the potential of our approach using two types of error-correcting codes, and, as a proof of principle, we demonstrate an 80% improvement in readout error on the IBMQ Mumbai quantum computer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Large-scale real-time signal processing in physics experiments: the ALICE TPC FPGA pipeline

For LHC Run 3, the ALICE Time Projection Chamber was upgraded to operate in continuous readout mode. Interaction rates of up to 50 kHz in Pb-Pb collisions require real-time processing of more than 3 TB s -1 of raw detector data. This requirement is met by a custom FPGA-based processing pipeline that performs the complete front-end data treatment fully in-stream, including common-mode correction, pedestal subtraction, ion-tail filtering, zero suppression, and dense data packing. A central element of the design is a highly parallel common-mode correction algorithm operating directly on the streaming data. It robustly identifies signal-free readout channels on a time-bin basis and applies pad-dependent scaling to compensate for local variations in capacitive coupling in the GEM readout. In combination with pedestal subtraction and ion-tail filtering, this enables accurate baseline restoration under extreme high-occupancy conditions, preventing signal loss while efficiently suppressing noise prior to zero suppression. The pipeline operates continuously at the full detector bandwidth and reduces the raw input rate of approximately 3 TB s -1 to about 900 GBps for Pb-Pb collisions at the target interaction rate. Overall, it represents a large-scale FPGA-based real-time signal-processing implementation for high-energy physics detector readout.

Digital signal processing (DSP)↗
DOE OSTI2022

Highly Segmented Silicon Strip Detectors for Radiation Detection (LDRD Final Report)

Large area highly segmented silicon strip detectors were investigated for use in applied radiation detection applications. Two ASIC-based readout electronics solutions were tested for compatibility. During the analysis, it was determined that significant computational resources and highly specialized firmware are required to reconstruct the data into a meaningful data stream for generalized spectroscopic performance. Future investment in the technology and careful choice of readout ASIC is expected to demonstrate relevance in measuring high activity samples.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

DUNE DAQ R&D integration in ProtoDUNE Single-Phase at CERN

The DAQ system of ProtoDUNE-SP successfully proved its design principles and met the requirements of the beam run of 2018. The technical design of the DAQ system for the DUNE experiment has major differences compared to the prototype due to different requirements placed on the detector, as well as a radically different location of operation. The single-phase prototype at CERN is a major integration facility for R&D aspects of the DUNE DAQ system. The facility allows for the exploration of additional data processing capabilities and optimization of the FELIX system, which is the chosen TPC readout solution for the DUNE single-phase detectors. One of the fundamental differences from the prototype is that the DUNE DAQ relies on self-triggering. Therefore, real-time processing of the data stream for hit and trigger primitive finding is essential for the requirement of continuous readout. The supernova burst trigger requires a large and fast buffering technique, where 3D XPoint persistent memory solutions are evaluated and integrated. In order to maximize resource utilization of the FELIX hosting servers, the elimination of the 100 Gb network communication stack is desired. This implies the design and development of a single-host application layer, which is a fundamental element of the self-triggering chain. This paper discusses the evaluation and integration of these developments for the DUNE DAQ, in the ProtoDUNE environment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Functional Verification for Endcap Concentrator ASICs in the High-Granularity Calorimeter Upgrade of CMS

The High-Granularity Calorimeter (HGCAL) of CMS will undergo a major upgrade during Long-Shutdown 3. The Endcap Concentrator (ECON) ASICs represent key elements in the readout chain, processing trigger (ECON-T) and data (ECON-D) streams from the HGCROC to the lpGBT. The ECONs will operate in a radiation environment with a High-Energy Hadron (HEH) flux of $3\cdot10^{6} cm^{-2}s^{-1}$. This contribution describes the Universal Verification Methodology (UVM)-based functional verification of the ECON ASICs focusing on the re-use of existing components to manage the complexity of the verification environment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Rate-capability of the VMM3a front-end in the RD51 Scalable Readout System

The VMM3a is an Application Specific Integrated Circuit (ASIC), specifically developed for the readout of gaseous detectors. Originally developed within the ATLAS New Small Wheel (NSW) upgrade, it has been successfully integrated into the Scalable Readout System (SRS) of the RD51 collaboration. This allows, to use the VMM3a also in small laboratory set-ups and mid-scale experiments, which make use of Micro-Pattern Gaseous Detectors (MPGDs). As part of the integration of the VMM3a into the SRS, the readout and data transfer scheme was optimised to reach a high rate-capability of the entire readout system and profit from the VMM3a's high single-channel rate-capability of 3.6Mhits/s. The optimisation focused mainly on the handling of the data output stream of the VMM3a, but also on the development of a trigger-logic between the front-end cards and the DAQ computer. In this article, two firmware implementations of the non-ATLAS continuous readout mode are presented, as well as the implementation of the trigger-logic. Afterwards, a short overview on X-ray imaging results is presented, to illustrate the high rate-capability from an application point-of-view.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1975

A CCD image transducer and processor suitable for space flight

A satellite borne extreme ultraviolet solar telescope makes use of CCD area arrays for both image readout and onboard data processing. The instrument is designed to view the inner solar corona in the wavelength band 170 - 630 A, and the output video stream may be selected by ground command to present the coronal scene, or the time-rate-of-change of the scene. Details of the CCD application to onboard image processing are described, and a discussion of the processor's potential for telemetry bandwidth compression is included. Optical coupling methods, data storage requirements, spatial and temporal resolution, and nonsymmetry of resolution (pitch) in the CCD are discussed.

Michels, D. J.↗
DOE OSTI2022

Machine learning on FPGA for event selection

Real-time data processing is a frontier field in experimental particle physics. The application of FPGAs at the trigger level is used by many current and planned experiments (CMS, LHCb, Belle2, PANDA). Usually they use conventional processing algorithms. LHCb has implemented Machine Learning (ML) elements for real-time data processing with a triggered readout system that runs most of the ML algorithms on a computer farm. The work described in this article aims to test the ML-FPGA algorithms for streaming data acquisition. Herein, there are many experiments working in this area and they have a lot in common, but there are many specific solutions for detector and accelerator parameters that are worth exploring further. This report describes the purpose of the work and progress in evaluating the ML-FPGA application.

47 OTHER INSTRUMENTATION↗
NASA NTRS2008

A Temperature Sensor using a Silicon-on-Insulator (SOI) Timer for Very Wide Temperature Measurement

A temperature sensor based on a commercial-off-the-shelf (COTS) Silicon-on-Insulator (SOI) Timer was designed for extreme temperature applications. The sensor can operate under a wide temperature range from hot jet engine compartments to cryogenic space exploration missions. For example, in Jet Engine Distributed Control Architecture, the sensor must be able to operate at temperatures exceeding 150 C. For space missions, extremely low cryogenic temperatures need to be measured. The output of the sensor, which consisted of a stream of digitized pulses whose period was proportional to the sensed temperature, can be interfaced with a controller or a computer. The data acquisition system would then give a direct readout of the temperature through the use of a look-up table, a built-in algorithm, or a mathematical model. Because of the wide range of temperature measurement and because the sensor is made of carefully selected COTS parts, this work is directly applicable to the NASA Fundamental Aeronautics/Subsonic Fixed Wing Program--Jet Engine Distributed Engine Control Task and to the NASA Electronic Parts and Packaging (NEPP) Program. In the past, a temperature sensor was designed and built using an SOI operational amplifier, and a report was issued. This work used an SOI 555 timer as its core and is completely new work.

Patterson, Richard L.↗
DOE OSTI2025

A virtual Frisch-grid geometry-based CZT gamma detector for in-field radioisotope identification

Here, we present a Virtual Frisch-Grid geometry-based CZT gamma detector developed for identifying different radioisotopes over an energy range from a few keV up to 2 MeV, and useful for efficient characterization of CZT crystals. The detector is built with a 3 x 3 matrix of CZT crystals, each measuring approximately 6 mm x 6 mm x 15 mm. The charge generated within the sensor’s active volume is read out via an anode connected directly to the AVG3_Dev integrated circuit. A current signal induced by charge drift is collected on side pads of the crystals, enabling reconstruction of a 3D interaction position. This paper discusses the design, development, and performance of the standalone, mobile detector system, which integrates the AVG3_Dev readout IC developed at Brookhaven National Laboratory, a high-speed FPGA-based with per-channel digital signal processing, and embedded system capabilities. The device is compact, battery-powered, and supports wireless data streaming, making it suitable for field operations for radioisotope identification.

47 OTHER INSTRUMENTATION↗