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ConQuER SIGNED

Controlling Quantum Experiments with Reinforcement Learning

Total Cost €

0

EC-Contrib. €

0

Partnership

0

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Project "ConQuER" data sheet

The following table provides information about the project.

Coordinator
KOBENHAVNS UNIVERSITET 

Organization address
address: NORREGADE 10
city: KOBENHAVN
postcode: 1165
website: www.ku.dk

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Denmark [DK]
 Total cost 219˙312 €
 EC max contribution 219˙312 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2019
 Funding Scheme MSCA-IF-EF-RI
 Starting year 2020
 Duration (year-month-day) from 2020-09-01   to  2022-08-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    KOBENHAVNS UNIVERSITET DK (KOBENHAVN) coordinator 219˙312.00

Map

 Project 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.

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The information about "CONQUER" are provided by the European Opendata Portal: CORDIS opendata.

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