Rigetti Computing has been awarded an Innovate UK grant to develop quantum machine learning techniques for Quantum Finance using financial data streams. The project, which also involves Amazon Web Services (AWS), Imperial College London, and Standard Chartered, aims to improve the way financial institutions process and interpret complex data. The consortium will leverage Rigetti’s quantum computer and software, Standard Chartered’s datasets, Imperial College London’s expertise in machine learning models, and AWS’s high-performance computing resources. The project began on January 1, 2024, and will last 18 months.
Quantum Finance: Rigetti Computing Receives Innovate UK Grant for Quantum Machine Learning Development
Rigetti UK Limited, a subsidiary of Rigetti Computing, Inc., a company specializing in full-stack quantum-classical computing, has been awarded an Innovate UK grant. The grant is part of the Feasibility Studies in Quantum Computing Applications competition. Rigetti will collaborate with Amazon Web Services (AWS), Imperial College London, and Standard Chartered to develop quantum machine learning techniques. These techniques aim to enhance the ability of financial institutions to process, interpret, and make decisions with complex data streams.
Financial institutions often need to interpret complex data streams to provide accurate credit risk evaluations, manage market-making services, and predict emissions in the context of green finance. Classical machine learning techniques used to assist these services have limitations due to the complexity of these data streams. The consortium aims to combine quantum computing with classical machine learning methodology to offer more powerful resources for processing these data streams.
Consortium’s Research Objectives
The consortium will leverage Rigetti’s quantum computer and software, Standard Chartered’s datasets and classical benchmarks, Imperial College London’s expertise on classical machine learning models for data streams, and AWS classical high performance computing resources. The research objectives include further development of quantum signature kernels and quantum-enhanced feature maps, benchmarking the results against classical machine learning methods for streamed data, and building and studying quantum algorithms for computing signatures and signature kernels for long and high-dimensional data streams efficiently.
The signature, a key component of rough path theory, provides a top-down description of a stream that filters out local superfluous and noisy information while retaining essential information. Adding a quantum element has the potential to improve upon the classical signature kernel methods. These enhanced capabilities could provide a route to demonstrating a commercial application of quantum computing for finance and enable financial institutions to improve their efficiency through cost reduction and enhanced productivity.
Statements from Consortium Members
Rigetti CEO Dr. Subodh Kulkarni stated that developing quantum-enhanced machine learning solutions could enable financial institutions to use the full capability of NISQ-era computing. Richard Moulds, general manager, Amazon Braket at AWS, emphasized the importance of combining quantum with classical compute infrastructure as part of a unified, cloud-based environment. Dr. Cristopher Salvi, Lecturer in Mathematics and Machine Learning at Imperial College London highlighted the potential of combining quantum technologies with rough paths techniques to produce more scalable signal processing algorithms for complex financial data streams. Craig Corte, Global Head of Digital Channels and Client Data Analytics at Standard Chartered, stressed the importance of adopting new technology from an early stage to future-proof companies.
The project began on January 1, 2024, and will last 18 months. Rigetti is a pioneer in full-stack quantum computing and has operated quantum computers over the cloud since 2017. Imperial College London is a global top ten university with a world-class reputation. Standard Chartered is a leading international banking group, with a presence in 53 of the world’s most dynamic markets. AWS is a subsidiary of Amazon that provides on-demand cloud computing platforms and APIs to individuals, companies, and governments, on a metered pay-as-you-go basis.
“Developing quantum-enhanced machine learning solutions could enable financial institutions to use the full capability of NISQ-era computing, and has the potential to accelerate our work towards narrow quantum advantage, the point at which a quantum computer outperforms the best classical resources,”
Rigetti CEO Dr. Subodh Kulkarni.
“The future of quantum computing will be built on the combination of quantum with classical compute infrastructure as part of a unified, cloud-based environment. This project is a great example of leveraging classical HPC resources with the aim to accelerate innovation in quantum machine learning algorithms – an important step as we move toward quantum advantage,”
Richard Moulds, general manager, Amazon Braket at AWS.
“Combining quantum technologies with rough paths techniques has the potential to produce more scalable signal processing algorithms for complex financial data streams. Making the implementation open access is crucial to ensure further development of these tools both in academia and industry,”
Dr. Cristopher Salvi, Lecturer in Mathematics and Machine Learning at Imperial College London.
“Quantum computing, like previous and current major advancements in technology, is poised to deliver extensive advantages while simultaneously causing significant disruptions to established business processes. This is why it’s important for companies to future-proof themselves by adopting this new technology from an early stage. Our collaboration with Rigetti, Imperial College London, and AWS gives us access to high-performance computational resources and quantum algorithm expertise that could strengthen our position as an industry leader in a future quantum-ready economy,”
Craig Corte, Global Head of Digital Channels and Client Data Analytics at Standard Chartered.
Summary
A consortium, including Amazon Web Services, Imperial College London, and Standard Chartered, has been awarded a grant by Innovate UK to develop quantum machine learning techniques aimed at enhancing the processing and interpretation of complex financial data streams. The project, which began on January 1, 2024 and will last 18 months, seeks to combine quantum computing with classical machine learning methods, potentially offering more efficient resources for data processing and enabling financial institutions to improve their efficiency through cost reduction and enhanced productivity.
- Rigetti UK Limited, a subsidiary of Rigetti Computing, has been awarded an Innovate UK grant to develop quantum machine learning techniques for financial data streams.
- The project involves a consortium including Amazon Web Services (AWS), Imperial College London, and Standard Chartered.
- The aim is to improve current machine learning techniques used by financial institutions to analyse complex data streams.
- The consortium will leverage Rigetti’s quantum computer and software, Standard Chartered’s datasets, Imperial College London’s expertise on machine learning models, and AWS’s high-performance computing resources.
- The research objectives include developing quantum signature kernels and quantum-enhanced feature maps, benchmarking the results against classical machine learning methods, and building quantum algorithms for computing signatures efficiently.
- Rigetti CEO Dr. Subodh Kulkarni believes that developing quantum-enhanced machine learning solutions could enable financial institutions to use the full capability of NISQ-era computing.
- Richard Moulds, general manager, Amazon Braket at AWS, sees the future of quantum computing as a combination of quantum with classical compute infrastructure in a unified, cloud-based environment.
- The project began on January 1, 2024, and will last 18 months.
