Diverse computing ecosystem for quantum machine learning via optical links

Project funded by Research Council of Finland, grant 350220. Participating organisations named by the source: VTT Technical Research Centre of Finland Ltd; VTT Technical Research Centre of Finland; Aalto University. Funded amount: EUR 552,533, as stated by the source. Runs 2022-01-01 to 2024-12-31. Keywords: Physical sciences. Source: OpenAIRE Graph, from the funder's project data (collected by OpenAIRE on 2026-07-23); national funding data, not CORDIS. Abstract given by the source: The QuantLearn project develops an optically linked computing ecosystem for quantum machine learning (QML). We develop optical communication between conventional computers and cryogenic classical single flux quantum quantum (SFQ) computers. Here, SFQ serves as an interface for quantum computing, but it is also a promising, high-speed and energy-efficient alternative for supporting conventional high-performance computing (HPC). We also develop QML software where classical HPC takes care of most of the computing, for example, runs the necessary computing loops, and the HPC sends specific computing tasks to a QC. We utilize and develop QML algorithms which can be exponentially faster than corresponding classical machine learning algorithms. Despite significant promise, QML in general is suffering from the problem of transmitting classical data between HPC and QC. We aim to solve this problem with our data bus.

Original source.

Source: OpenAIRE Graph: projects of national funders, OpenAIRE, from the project data of Research Council of Finland. Retrieved 2026-10-22. Licence: Creative Commons Attribution 4.0 (OpenAIRE Graph). Selected metadata, adapted presentation; the publisher's record is authoritative. No endorsement by the source is implied. Licence: Creative Commons Attribution 4.0 (CC BY 4.0).