Energetics of Quantum Information Processing

Project funded by Fundação para a Ciência e a Tecnologia, I.P. (FCT), grant 2023.01162.BD. Runs 2023-11-01 to 2024-10-31. 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: This doctoral project aims to understand the energy requirements of quantum information processing and explore regimes where quantum technologies can be more energy-efficient than traditional technologies. First, we demonstrate classical logic processing using a trapped-ion quantum computer. A three-bit half-adder is implemented using electronic states of trapped ions, and the energetics are characterized by measuring consumed power and modeling theoretical energy expenditure. Second, we investigate energy-fidelity trade-offs when implementing unitaries in driven quantum systems. The fidelity of the operation is quantified by tracing out the degrees of freedom of the driving system, and rigorous mathematical bounds are sought for fidelity guarantees independent of the unitary operation. Finally, the implications of these mathematical bounds are explored in general quantum algorithms using the algorithmic framework of Quantum Singular Value Transforms (QSVT), including the impact of error correction on error-energy scaling.

Original source.

Source: OpenAIRE Graph: projects of national funders, OpenAIRE, from the project data of Fundação para a Ciência e a Tecnologia, I.P. (FCT). Retrieved 2026-10-28. 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).

AI-assisted summary: The project "Energetics of Quantum Information Processing" is funded by FCT and runs from November 1, 2023, to October 31, 2024. It aims to analyze energy requirements in quantum processing and includes experiments with trapped-ion quantum computers. Suggested technology pillar: computing. Generated by AI from the public source text; it may contain errors and the original source is authoritative.