QRC-4-ESP
Quantum reservoir computing for efficient signal processing
Runtime: 01.01.2024 - 31.12.2026
The project Quantum reservoir computing for efficient signal processing (QRC-4-ESP) is dedicated to pioneering advancements in quantum reservoir computing systems. The long-term objective is to develop the world’s foremost QRC systems utilizing superconducting qubits and silicon carbide (SiC) defect qubits. Through meticulous research and development significant enhancements in computational speed and efficiency are aimed to be achieved, surpassing classical machine learning systems by over 100x. By focusing on the utilization of superconducting qubits for microwave range quantum communication and SiC defect qubits for optical band applications, the project endeavors to facilitate groundbreaking progress in quantum communication and sensing technologies.
Moreover, the QRC-4-ESP project is not just about technological advancements but also about fostering international collaboration in research and development. By bringing together a diverse group of experts from different fields and countries, the project embodies a multidisciplinary approach that is essential for tackling complex modern challenges. This collaborative model serves as a blueprint for future scientific endeavors and strengthens Europe’s position as a leader in quantum research and innovation.
The Leibniz-IPHT is coordinating the project and responsible for realization of signal processing on the superconducting platform in frame of quantum reservoir computing. To do so, tailored superconducting circuits including qubit numbers growing during the project will be developed, fabricated, and experimentally characterized. In close exchange with the theoretical groups, we will prepare a demonstration experiments exploiting these superconducting circuits and additionally investigate synergies as well as possible interfaces to the SiC defect qubits.
The QRC-4-ESP project has received funding from the European Innovation Council’s Pathfinder Open programme under grant agreement number 101129663 as well as from the UK Research and Innovation’s Horizon Europe guarantee scheme.