#	Pagina
attuale pagina	/open-h2020/projects/227299/index.html

Opendata, web and dolomites

ConQuER SIGNED

Controlling Quantum Experiments with Reinforcement Learning

Total Cost €

EC-Contrib. €

Partnership

Views

ConQuER project word cloud

Explore the words cloud of the ConQuER project. It provides you a very rough idea of what is the project "ConQuER" about.

copenhagen rl integration ai tuning create memory abundance niels stabilize multiple efficiency intelligence device invested setup physics characterization machine precious data ing qubit source bohr artificial power quantum free software automatic experiments learning time experiment community spin framework goes extract simulations generate coming experimental tune

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 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.	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.

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "CONQUER" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

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