Quantum Systems for Enhanced High Energy Particle Physics Detectors

Doser, M.; Auffray, E.; Brunbauer, F.; Frank, Isabel; Hillemanns, H.; Orlandini, Giorgio; Kornakov, G.

doi:10.3389/fphy.2022.887738

Cited by 9 publications

(5 citation statements)

References 136 publications

(157 reference statements)

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“…High scintillation yields from QDs-based scintillators have been reported by other groups [61][62][63], suggesting that the optoelectronic properties of QDs offer advantages over organic compounds as scintillating materials. These results open up applications of liquid QD-based scintillators in particle physics [13][14][15].…”

Section: Discussionmentioning

confidence: 99%

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Water-based quantum dots liquid scintillator for particle physics

Zhao,

Taani,

Cole

et al. 2024

J. Inst.

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Liquid scintillators are typically composed from organic compounds dissolved in organic solvents. However, usage of such material is often restricted due to fire safety and environmental reasons. Because of this, R&D of water-based liquid scintillators is of extreme relevance; yet, no such scintillators have been made commercially available as yet. Here, we investigate an alternative, water-based quantum dots liquid scintillator. Pre-determined and controllable optical properties of the quantum dots, as well as the existence of large libraries of established protocols for their dispersion in aqueous solutions, make them an attractive option for nuclear and particle physics applications. We characterize the optical properties of water-based quantum dots liquid scintillator and find that most of its optical properties are preserved upon quantum dots' phase transfer into water, through the addition of an oleic acid hydrophilic layer. Using the developed scintillator, the time and charge responses from atmospheric muons are measured, highlighting the practical viability of water-based quantum dots liquid scintillators for nuclear and particle physics, special interest on neutrino physics.

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Section: Discussionmentioning

confidence: 99%

“…Here we are investigating the possibility of utlizing QDs for particle physics applications [13][14][15]. In particular, we are interested in the possibility of WbQDs liquid scintillator in nuclear fission reactor neutrino detection.…”

Section: Jinst 19 P07014mentioning

confidence: 99%

Water-based quantum dots liquid scintillator for particle physics

Zhao,

Taani,

Cole

et al. 2024

J. Inst.

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“…Another possible direction to explore is the possibility to feed the quantum algorithms directly with quantum input data, thus avoiding the quantum data encoding step. Since the research and development of quantum sensing in particle detectors is a rapidly developing sector [50][51][52], this could lead to identify a possible advantage from the use of quantum machine learning algorithms of the type proposed in this work, in a not too distant future.…”

Section: Discussionmentioning

confidence: 99%

Long-Lived Particles Anomaly Detection with Parametrized Quantum Circuits

et al. 2023

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We investigate the possibility to apply quantum machine learning techniques for data analysis, with particular regard to an interesting use-case in high-energy physics. We propose an anomaly detection algorithm based on a parametrized quantum circuit. This algorithm was trained on a classical computer and tested with simulations as well as on real quantum hardware. Tests on NISQ devices were performed with IBM quantum computers. For the execution on quantum hardware, specific hardware-driven adaptations were devised and implemented. The quantum anomaly detection algorithm was able to detect simple anomalies such as different characters in handwritten digits as well as more complex structures such as anomalous patterns in the particle detectors produced by the decay products of long-lived particles produced at a collider experiment. For the high-energy physics application, the performance was estimated in simulation only, as the quantum circuit was not simple enough to be executed on the available quantum hardware platform. This work demonstrates that it is possible to perform anomaly detection with quantum algorithms; however, as an amplitude encoding of classical data is required for the task, due to the noise level in the available quantum hardware platform, the current implementation cannot outperform classic anomaly detection algorithms based on deep neural networks.

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“…First, conventional sensors are prone to drift, which is the accumulation of errors caused by manufacturing faults and noise [8]. For example, metal sensor components, such as springs, contract and expand in response to temperature, thus affecting measurement readings and requiring recalibration owing to drift.…”

Section: Conceptual Backgroundmentioning

confidence: 99%

Exploring Quantum Sensing Potential for Systems Applications

et al. 2023

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The current rise of quantum technology is compelled by quantum sensing research. Thousands of research labs are developing and testing a broad range of sensor prototypes. However, there is a lack of knowledge about specific applications and real-world use cases where the benefits of these sensors will be most pronounced. This study presents a comprehensive review of quantum sensing state-of-practice. It also provides a detailed analysis of how quantum sensing overcomes the existing limitations of sensordriven systems' precision and performance. Based on the review of over 500 quantum sensor prototype reports, we determined four groups of quantum sensors and discussed their readiness for commercial usage. We concluded that quantum magnetometry and quantum optics are the most advanced sensing technologies with empirically proven results. In turn, quantum timing and kinetics are still in the early stages of practical validation. In addition, we defined four systems domains in which quantum sensors offer a solution for existing limitations of conventional sensing technologies. These domains are 1) GPS-free positioning and navigating services, 2) time-based operations, 3) topological visibility, and 4) environment detection, prediction, and modeling. Finally, we discussed the current constraints of quantum sensing technologies and offered directions for future research.

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Quantum Systems for Enhanced High Energy Particle Physics Detectors

Cited by 9 publications

References 136 publications

Water-based quantum dots liquid scintillator for particle physics

Water-based quantum dots liquid scintillator for particle physics

Long-Lived Particles Anomaly Detection with Parametrized Quantum Circuits

Exploring Quantum Sensing Potential for Systems Applications

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