Project description
New quantum algorithms that could tolerate noise
Noise, or imperfections in quantum devices, is a major bottleneck to advancing quantum computing. It disrupts calculations and makes it harder to develop reliable systems. The ERC-funded GIFNEQ project seeks to overcome this by creating scalable techniques to identify and characterise noise more effectively. It also aims to design quantum algorithms that can work despite substantial noise, reducing reliance on resource-intensive error correction. Using breakthroughs in learning theory and mathematical frameworks like quantum Gibbs states, GIFNEQ seeks to make quantum computing more practical and efficient. Project findings will have implications for quantum information, computer science and mathematical physics.
Objective
The GIFNEQ project one of the major bottlenecks in quantum computing: noise, an umbrella term for various imperfections affecting the device. The initiative establishes a unified theoretical framework, focusing on two primary goals: developing scalable noise characterization techniques and crafting verifiable quantum algorithms resilient to substantial noise levels. A particular focus is placed on revolutionizing dissipative preparation schemes—a subset of quantum algorithms analogous to Metropolis sampling—aiming to make them a preferred state preparation method by creating noise-aware, verifiable algorithms requiring considerably less quantum error correction, a resource-intensive element in quantum computing.
Simultaneously, GIFNEQ endeavors to radically simplify and augment the reliability of the traditionally complex noise characterization process. It leans on recent breakthroughs in robust learning theory to discern and detail structured noise sources efficiently. Introducing protocols resilient to anomalies ensures robust and reliable learning of quantum noise. These objectives are intertwined by the requisite mathematical framework, heavily contingent upon quantum Gibbs states, a quantum extension of Markov random fields, with the project also seeking to obtain various mathematical statements related to these states.
GIFNEQ promises to be a watershed in quantum computing, targeting practical resolutions with profound theoretical insights and bridging domains like quantum information, computer science, and mathematical physics to pave the way for breakthroughs that reshape the effective utilization of quantum devices. As a seasoned expert in the field, with a wealth of knowledge on noise impact, characterization, and quantum dissipation in quantum computation, substantiated by publications in renowned journals such as Nature Physics or Nature Communications, I present a uniquely qualified leadership to steer this transformative project.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
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Keywords
Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Topic(s)
Funding Scheme
HORIZON-ERC - HORIZON ERC GrantsHost institution
1165 Kobenhavn
Denmark