One Person’s Journey into Quantum Reservoir Computing: An Interview with Loughborough University Postdoc Researcher Wendy Otieno Working on the QRC-4-ESP Project

Dr. Wendy Otieno, Loughborough University Postdoc Researcher

1. What first sparked your interest in quantum research, and how did it lead you to join the QRC-4-ESP project?

Numerically solving Schrödinger’s equation for quantum systems like particles in finite and infinite potential wells first sparked my interest in quantum research. Through this process, I developed a deep appreciation for the elegant yet challenging mathematical structures that underpin quantum systems. As I delved deeper into classical computational methods, I came to recognize their struggles in simulating complex quantum phenomena. This realization led me to quantum computing which harnesses quantum principles to perform computations that are intractable in classical algorithms. The concept of using qubits and quantum gates to simulate quantum phenomena felt like a natural extension of my earlier work. Building on this foundation, I became intrigued in quantum reservoir computing which leverages quantum dynamics for temporal data processing. This led me to join the QRC-4-ESP Project where I am involved in developing QRC frameworks based on superconducting qubits and defect-based silicon carbide (SiC) qubits and benchmarking their performance across a range of computational tasks.

2. How does collaboration with international partners shape your experience on this project?

Working with international collaborators has profoundly shaped my experience in the QRC-4-ESP project. These partnerships have exposed me to a wide range of methodologies, pushing me to embrace diverse problem-solving approaches and explore novel directions beyond conventional QRC frameworks. Results are compared across different labs during theoretical and experimental meetings, giving me deeper insights into the accelerating pace of innovation. Hands-on experimentation with superconducting qubits and defect-based SiC qubits is accessible as various labs in distinct countries provide access to rare quantum hardware. Also, participating in yearly Quantum based Summer Schools and attending international meetings has sharpened my presentation and networking skills.

3. Can you share an example of a breakthrough or memorable moment you’ve had while working on QRC-4-ESP?

My most memorable moment in the QRC-4-ESP project was presenting a live QRC demonstration of chaotic time series prediction. I was able to give a step-by-step guide on how to implement the main features of our QRC framework in python code to predict future values of the Mackey Glass time series. It was rewarding seeing the audience respond to real time results with curiosity and answering the great questions that were sparked during the delay embedding portion of the demonstration.

4. Beyond physics, which other fields do you think could benefit most from advances in quantum reservoir computing?

QRC shows significant promise in fields such as Healthcare, Finance and Cognitive Computing. It can be used to generate synthetic datasets that are essential in developing recognition systems aimed at medical diagnosis when real world data is scarce or sensitive. It can capture subtle patterns in noisy stock price data making it ideal for financial applications such as fraud detection, algorithmic trading and risk assessments. It can mimic aspects of brain like computation that can be applied to audio and speech recognition and even reproduce behaviour observed in cognitive tasks such as sequential decision making, working memory and recall.

5. What skills or perspectives have you developed through this project that you didn’t expect at the start?

The skills/perspectives I have developed that I didn't expect at the start include (1) learning how to utilize delay embeddings in our framework to enhance the overall performance of the QRC (2) looking at various encoding techniques outside our Hamiltonian parameter encoding approach, such as amplitude encoding and measurement driven encoding, for performance comparison (3) learning how to apply our QRC framework in games and music and (4) understanding the dynamics of point defect SiC qubits to incorporate into a QRC framework.

6. If you had to describe the value of QRC-4-ESP to a non-scientist friend, what would you say?

The QRC-4-ESP project is working on developing new technology that uses the unique behaviour of quantum particles to process complex and changing information - like satellite signals or medical devices. This new technology will be made of advanced materials (superconducting qubits and defect based SiC qubits) to make them much faster and energy-efficient in environments where traditional computers struggle. This could lead to breakthroughs in secure communication, advanced smart sensors and ultra-fast decision-making technologies all powered by quantum physics.

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