A research project led by Jacobs’ ANSWERS Software Service, in collaboration with the UK’s National Quantum Computing Centre, Oxford Quantum Circuits, National Nuclear Laboratory, Sellafield Ltd, and the University of Cambridge, has explored the potential of quantum computing in improving radiation facilities in the nuclear, medical and space industries. The project focused on accelerating Monte Carlo methods used for simulating radiation transport. Quantum computing could offer significant advantages over traditional digital computing, including generating truly random numbers and increased processing power. However, challenges such as quantum noise and the need for further research were also highlighted.
Quantum Computing’s Potential in the Nuclear Industry
A recent research project has underscored the potential of quantum computing to bring about significant improvements in the design and operation of radiation facilities across various industries, including nuclear, medical, and space. These industries rely heavily on modelling radiation transport, a fundamental aspect of nuclear physics. This process is integral to various operations, from reactor design and operation to fuel fabrication, storage, transport, decommissioning, and geological disposal. It also plays a crucial role in nuclear medicine, the space industry, food irradiation, and oil well logging.
“Quantum random number generation has the clear advantage of generating truly random numbers, based on truly random quantum processes, whereas traditional computational methods are only capable of generating pseudo random numbers or quasi random numbers which can be subject to subtle correlations that can introduce bias into calculation results.”
Professor Paul Smith, Jacobs ANSWERS Technical Director
Monte Carlo Codes and Quantum Computing
Monte Carlo codes are the standard method for creating simulations and solving equations to understand radiation transport, which involves the transfer of physical energy through the absorption, emission, and scattering of electromagnetic radiation. These codes are designed to model and understand the movement and interactions of radiation particles as they travel through different materials and interact with various structures.
There are two main approaches to solving the equations for radiation transport. The deterministic approach uses traditional numerical methods to solve mathematical equations involving several approximations. The alternative Monte Carlo approach simulates the paths of individual particles, which involves less approximation but can be slow for some applications.
“This allows quantum computers to process many states in a single operation, increasing their processing power exponentially and achieving complex problem-solving which is impossible on digital computers.”
Professor Paul Smith, Jacobs ANSWERS Technical Director
Quantum Computing in Accelerating Monte Carlo Methods
The ANSWERS Software Service, a part of Jacobs, spearheaded a project to explore the potential benefits of quantum computing in accelerating Monte Carlo methods. This project, supported by the UK’s National Quantum Computing Centre’s SparQ programme, aimed to investigate the advantages of leveraging quantum computing over conventional digital computing to improve the runtime of Monte Carlo methods, making them more competitive.
“Modelling radiation transport is fundamental to nuclear physics and plays a part in everything from reactor design and operation, fuel fabrication, storage, transport, decommissioning and geological disposal. Beyond nuclear power and decommissioning, it plays a vital role in nuclear medicine, the space industry, food irradiation and oil well logging.” –
Professor Paul Smith, Jacobs ANSWERS Technical Director
Quantum Algorithms and Quantum Noise
Quantum algorithms are available or under development for several processes that contribute significantly to the computational cost of performing Monte Carlo radiation transport calculations. These include random number generation, nuclear database searches, ray tracing, and the Monte Carlo process. Quantum random number generation has the clear advantage of generating truly random numbers based on truly random quantum processes. In contrast, traditional computational methods can only generate pseudo or quasi-random numbers, which can introduce bias into calculation results.
However, one of the biggest challenges faced by quantum computing at present is the presence of quantum noise. Being microscopic, quantum systems are very delicate. Any interaction with the surrounding environment can change the system’s state, for example, changing a qubit from state 0 to state 1 or vice versa.
“The ANSWERS Software Service, part of Jacobs, led a project to explore the potential benefits of quantum computing in accelerating Monte Carlo methods.”
Professor Paul Smith, Jacobs ANSWERS Technical Director
Future Research and Applications
The project partners, which include Jacobs, National Quantum Computing Centre, Oxford Quantum Circuits, National Nuclear Laboratory, Sellafield Ltd, and the University of Cambridge, note that there are promising signs that quantum algorithms could transform the computational aspects of ray tracing and Monte Carlo radiation transport simulation. However, further research is needed to evaluate their applicability.
“One of the biggest challenges faced by quantum computing at present is the presence of quantum noise. Being microscopic, quantum systems are very delicate.”
Professor Paul Smith, Jacobs ANSWERS Technical Director
Quick Quantum Summary
“Quantum computing has the potential to significantly enhance the design and operation of radiation facilities across nuclear, medical and space industries by accelerating Monte Carlo methods used in radiation transport simulations. Despite current challenges such as quantum noise, research indicates promising signs that quantum algorithms could revolutionise computational aspects of these simulations, although further investigation is required to confirm their applicability.”
“The project partners – Jacobs, National Quantum Computing Centre (part of UK Research & Innovation), Oxford Quantum Circuits, National Nuclear Laboratory, Sellafield Ltd, and the University of Cambridge – note that there are promising signs that quantum algorithms could transform the computational aspects of ray tracing and Monte Carlo radiation transport simulation, but further research is needed to evaluate their applicability.”
Professor Paul Smith, Jacobs ANSWERS Technical Director
- A research project led by the ANSWERS Software Service, part of Jacobs, has explored the potential benefits of quantum computing in the nuclear industry.
- The project was supported by the UK’s National Quantum Computing Centre’s SparQ programme. It involved partners such as Oxford Quantum Circuits, National Nuclear Laboratory, Sellafield Ltd, and the University of Cambridge.
- Quantum computing could significantly improve the design and operation of radiation facilities in the nuclear, medical and space industries by accelerating Monte Carlo methods, which are used to simulate and understand the movement and interactions of radiation particles.
- Quantum computers use qubits, which can process many states in a single operation, increasing their processing power exponentially. This could make complex problem-solving, which is impossible on digital computers, achievable.
- Quantum random number generation, which generates truly random numbers, could reduce bias in calculation results, a problem with traditional computational methods.
- The project successfully demonstrated new techniques for reducing quantum noise, a major challenge in quantum computing, using the Oxford Quantum Circuits computer, Lucy.
- Further research is needed to evaluate the applicability of quantum algorithms in transforming the computational aspects of ray tracing and Monte Carlo radiation transport simulation.
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