Search NASA⌕ Search

SEARCH · Search NASA

Results for “Liquid TPC”

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.

166 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

SCGSR Final Report

Dual phase noble liquid time projection chambers (TPCs) have an unprecedented sensitivity towards dark matter searches and neutrinos, owing to their ability to detect single electrons. When a particle deposits energy into one of these detectors, electrons are released and drifted into a gaseous region of high electric field. In the gas, the electrons are accelerated to produce extra light into what is called an S2 pulse. This light is far easier to detect than the current induced from a single electron. The two widely used elements for noble liquid detectors are Xe and Ar. Xe has a larger chance of being hit by neutrinos or dark matter, but ends with a lower (i.e. harder to detect) energy when struck. However, Ar light is hard to reflect and detect due to its short wavelength which is absorbed by most materials. While one may use TPB to re-emit this light at a longer wavelength, spatial variations of TPB thickness can smear the amount of re-emitted light, and thus cause a poor S2 energy resolution and spatial resolution. Furthermore, a single electron pulse in Ar is spread over a much longer time than one in Xe, which makes it harder to identify single electrons in Ar. The goal of Xe doping is to combine the best aspects of Ar with the best aspects of Xe. More specifically, this means a detector with a larger yield of photons and electrons produced per energy deposition, an ability to collect more of the light given by those signals, and a narrower pulse from the electron signal. During this project, we developed and operated a detector that can overcome the thermodynamic challenges of Xe doping – namely, preventing Xe from freezing. In the first experimental run during this award period, we found that we can achieve at least 5% of Xe in LAr, and measure the Xe concentration in the gas. In the second run, we installed our detector and saw the first S2 pulses in a dual phase Xe doped LAr TPC. With the data we took, we quantified the effect of Xe doping on the detectability of wavelength-shifted light produced in a Xe doped Ar mixture, as well as the single electron pulse shape. While the Ar light has successfully been wavelength shifted, we learned that much to our surprise, Xe doping actually makes the S2 pulse wider before it makes it narrower.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

The ProtoDUNE-SP LArTPC electronics production, commissioning, and performance

The ProtoDUNE-SP detector is a large-scale prototype of the Single-Phase (SP) Liquid Argon Time Projection Chamber (LArTPC) design proposed for the Deep Underground Neutrino Experiment (DUNE). 15,360 LArTPC wires are instrumented with low electronic noise pre-amplifier and digitization ASICs integrated into Front End Motherboards (FEMBs) operating at cryogenic temperature within the cryostat. The large number of electronics channels and high performance specifications required a large-scale production electronics quality control effort, careful installation into Anode Plane Assemblies (APAs), and rigorous detector commissioning. This successful collaboration-wide effort achieved a working LArTPC electronics channel percentage of 99.7% (15,318 of 15,360 channels in total), whose operating performance exceeded expectations. We summarize the ProtoDUNE-SP cold electronics design and quality control, installation, and commissioning efforts that enabled this excellent electronics performance.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Particle hit clustering and identification using point set transformers in liquid argon time projection chambers

Liquid argon time projection chambers are often used in neutrino physics and dark-matter searches because of their high spatial resolution. The images generated by these detectors are extremely sparse, as the energy values detected by most of the detector are equal to 0, meaning that despite their high resolution, most of the detector is unused in a particular interaction. Instead of representing all of the empty detections, the interaction is usually stored as a sparse matrix, a list of detection locations paired with their energy values. Traditional machine learning methods that have been applied to particle reconstruction such as convolutional neural networks (CNNs), however, cannot operate over data stored in this way and therefore must have the matrix fully instantiated as a dense matrix. Operating on dense matrices requires a lot of memory and computation time, in contrast to directly operating on the sparse matrix. We propose a machine learning model using a point set neural network that operates over a sparse matrix, greatly improving both processing speed and accuracy over methods that instantiate the dense matrix, as well as over other methods that operate over sparse matrices. Compared to competing state-of-the-art methods, our method improves classification performance by 14%, segmentation performance by more than 22%, while taking 80% less time and using 66% less memory. Compared to state-of-the-art CNN methods, our method improves classification performance by more than 86%, segmentation performance by more than 71%, while reducing runtime by 91% and reducing memory usage by 61%.

calibration and fitting methods↗
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)↗