Objective
Machine learning empowers computers to solve complex tasks such as pattern identification and strategy optimization with applications in, e.g. financial trading, fraud detection, medical diagnosis, and self-driving vehicles. The required computing power is, however, pushing existing computational resources to their limits, restraining their further advancement. In QFreC, I target the realization of photonic frequency-based quantum co-processors, specifically tailor-made to solve machine learning problems with capabilities commensurate with todays high-power, yet energy-efficient processing needs. In particular, I will use a high-dimensional photonic quantum frequency comb approach, where photons have hundreds to thousands of discrete and equidistantly spaced frequency modes, giving access to large, scalable information capacity. For implementing quantum-accelerated machine learning tasks such as the classification of classical or quantum data, I will follow i) the exploration of quantum photonic frequency-domain processing with the adaptation of qubit learning concepts (vector-based and neural network-based approaches) to high-dimensional quantum representations, i.e. quDits, ii) the realization of efficiency-enhanced and novel integrated quantum frequency comb systems with quantum resources that allow real-world applications using highly nonlinear on-chip platforms, and iii) the development of reconfigurable, fast, and broadband experimental control schemes using, e.g. quadrature amplitude modulation formats and nonlinear optical processes. To enable stable, compact, cost- and energy-efficient quantum processing devices, the QFreC project will build on the advances of the well-developed telecommunications infrastructure and the photonic chip fabrication industry. QFreC merges photonic quantum frequency-domain circuits with quantum machine learning, enabling large-scale controllable quantum resources for the exploration of quantum-enhanced machine learning
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.
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering computer hardware quantum computers
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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.
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H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)
MAIN PROGRAMME
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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.
ERC-STG - Starting Grant
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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) ERC-2020-STG
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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.
30167 Hannover
Germany
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.