Project description
Bringing together AI and quantum physics
Physicists are hard at work trying to construct quantum computers, a difficult and challenging task. The question now is whether artificial intelligence (AI) can help solve some of the outstanding experimental challenges. The EU-funded ConQuER project will advance the integration of state-of-the-art machine learning and AI with quantum physics experiments. It will use the power and efficiency of machine learning methods to extract information from an abundance of physics data to go beyond traditional methods. The project will design and implement a reinforcement learning (RL) method to control, stabilise and tune a multiple-spin-qubit experiment at the Niels Bohr Institute in Copenhagen. The automatic device tuning will free up time resources that can be invested in experimental advances.
Objective
This proposal aims to advance the integration of state-of-the-art machine learning and artificial intelligence (AI) with quantum physics experiments. The abundance of physics data coming from experiments and simulations of quantum systems allows us to use the power and efficiency of machine learning methods to extract information from this data in a way that goes beyond traditional methods. Based on this insight, I will design and implement a reinforcement learning (RL) method that can directly control, stabilize (to create a quantum memory) and tune (for device characterization and setup) a multiple-spin-qubit experiment at the Niels Bohr Institute in Copenhagen. The resulting framework and open-source AI software are expected to be useful in any other quantum experiment for which tuning is a major component, and is expected to generate a large impact in the community. Automatic device tuning will free up precious time resources that can be invested in significant experimental advances.
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: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences software
- natural sciences physical sciences quantum physics
- natural sciences computer and information sciences artificial intelligence machine learning reinforcement learning
You need to log in or register to use this function
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
-
H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
See all projects funded under this programme -
H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
See all projects funded under this programme
Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)
See all projects funded under this funding scheme
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-MSCA-IF-2019
See all projects funded under this callCoordinator
Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
1165 KOBENHAVN
Denmark
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.