Optimization of the design of Gas Cherenkov Detectors for ICF diagnosis

Liu, Bin; Hu, Huasi; Han, Hetong; Lv, Huanwen; Li, Lan

doi:10.1016/j.nima.2018.04.032

Cited by 6 publications

(4 citation statements)

References 14 publications

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“…The laser beams with pulse width of 25 fs were focused on the front edge of a supersonic nitrogen gas jet boundary at a height of 1 mm. The waist width of the focal spot was 8 microns approximately, and the average power density of focused laser beams was 1.6×10 19 W cm −2 . The energy spectra of the electron beams ejected from the gas jet were measured using a diagonal radioactive zone (DRZ) phosphor screen and a permanent magnet before the OprGCD installation.…”

Section: Experiments Results and Analysismentioning

confidence: 99%

“…The GRH used three 90°off-axis parabolic reflectors to collect the Cherenkov photons, which was better to improve the gamma sensitivity over GCD based on the nonimaging optical system [15,18]. Liu et al [19] proposed a global optimization method combining a genetic algorithm with Monte Carlo simulation to design GCD and GRH for ICF diagnosis. The efficiencies of GCD and GRH optimized by this method were improved by about 20% and 76%, respectively, higher than the results obtained by the traditional optical ray-tracing method.…”

Section: Introductionmentioning

confidence: 99%

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Design and performance study of a gas-Cherenkov detector with an off-axis parabolic reflector for inertial confinement fusion experiments

Zha¹,

Zhu²,

Xiao³

et al. 2020

Plasma Sci. Technol.

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In this work, the gas-Cherenkov detector with an off-axis parabolic reflector (OprGCD) is designed using the Geant4 Monte Carlo simulation toolkit, which is helpful to improve the collection efficiency of Cherenkov photons. The method to study the performance of OprGCD based on femtosecond laser-wakefield-accelerated electron beams is presented. Cherenkov signals with high signal-to-noise ratio were obtained, and the measured Cherenkov signals changing with the CO2 pressure were consistent well with the simulation results. The design and study of this OprGCD system lay the foundation for the application of fusion gamma diagnostics system in large laser facilities of China.

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Section: Experiments Results and Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Design and performance study of a gas-Cherenkov detector with an off-axis parabolic reflector for inertial confinement fusion experiments

Zha¹,

Zhu²,

Xiao³

et al. 2020

Plasma Sci. Technol.

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“…The use of GAs was initially motivated by the NASA ST-5 antenna, in which a simple, segmented wire antenna was designed by a GA for satellite communications [6]. GAs have also previously been used in the design of various detectors and experiments, although rarely used to optimize for a science outcome directly [7,8].…”

Section: The Genetis Projectmentioning

confidence: 99%

Using Genetic Algorithms to Evolve Antenna Gain Patterns with Greater Sensitivity to Ultra-High Energy Neutrinos

Reynolds¹,

Rolla²,

Ethan³

2023

Proceedings of 38th International Cosmic Ray Conference — PoS(ICRC2023)

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Evolutionary algorithms utilize principles of evolution to efficiently determine solutions to defined problems. These algorithms are especially proficient at finding solutions to complex optimization problems that would likely be inaccessible through traditional techniques. The GENETIS Collaboration is developing genetic algorithms (GAs) to design antennas that are more sensitive to ultra-high energy neutrino-induced radio pulses than current detectors. Improving antenna performance is critical because UHE neutrinos are rare, with experiments requiring either massive detector volumes with stations dispersed over hundreds of km, or extraordinarily long livetimes. Optimally performing antennas are imperative to ensuring that these rare UHE neutrino events have the highest possible chance to be detected when they occur. One technique for exploring antenna response with GAs is the Antenna Response Evolutionary Algorithm (AREA), developed by GENETIS. This algorithm evolves antenna gain patterns directly with the aim of determining the optimal antenna response for a specified science goal, independent of design constraints. This research could help quantify the maximum improvement to sensitivity, which can be compared to current design capabilities and inform future improvements. This proceeding will report on advancements to the algorithm, initial results, and planned future improvements and use cases.

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“…GAs have previously been used in the design of various detectors and experiments, although rarely to optimize for a science outcome directly [15,16]. A horn antenna was designed using a GA optimized for the detection of Cosmic Microwave Background radiation [17].…”

Section: Introductionmentioning

confidence: 99%

Using Evolutionary Algorithms to Design Antennas with Greater Sensitivity to Ultra High Energy Neutrinos

Rolla¹,

A.²,

Patton³

et al. 2021

Preprint

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Optimization of the design of Gas Cherenkov Detectors for ICF diagnosis

Cited by 6 publications

References 14 publications

Design and performance study of a gas-Cherenkov detector with an off-axis parabolic reflector for inertial confinement fusion experiments

Design and performance study of a gas-Cherenkov detector with an off-axis parabolic reflector for inertial confinement fusion experiments

Using Genetic Algorithms to Evolve Antenna Gain Patterns with Greater Sensitivity to Ultra-High Energy Neutrinos

Using Evolutionary Algorithms to Design Antennas with Greater Sensitivity to Ultra High Energy Neutrinos

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