Opendata, web and dolomites

Quromorphic SIGNED

Neuromrophic Quantum Computing

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

Project "Quromorphic" data sheet

The following table provides information about the project.

Coordinator
FRIEDRICH-ALEXANDER-UNIVERSITAET ERLANGEN NUERNBERG 

Organization address
address: SCHLOSSPLATZ 4
city: ERLANGEN
postcode: 91054
website: www.uni-erlangen.de

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 Germany [DE]
 Total cost 2˙882˙752 €
 EC max contribution 2˙882˙752 € (100%)
 Programme 1. H2020-EU.1.2.1. (FET Open)
 Code Call H2020-FETOPEN-2018-2019-2020-01
 Funding Scheme RIA
 Starting year 2019
 Duration (year-month-day) from 2019-06-01   to  2022-05-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    FRIEDRICH-ALEXANDER-UNIVERSITAET ERLANGEN NUERNBERG DE (ERLANGEN) coordinator 612˙482.00
2    TECHNISCHE UNIVERSITEIT DELFT NL (DELFT) participant 557˙302.00
3    EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH CH (ZUERICH) participant 556˙875.00
4    IBM RESEARCH GMBH CH (RUESCHLIKON) participant 544˙937.00
5    VOLKSWAGEN AG DE (WOLFSBURG) participant 306˙405.00
6    UNIVERSIDAD DEL PAIS VASCO/ EUSKAL HERRIKO UNIBERTSITATEA ES (LEIOA) participant 304˙750.00
7    HERIOT-WATT UNIVERSITY UK (EDINBURGH) participant 0.00

Map

 Project objective

The Quromorphic project will introduce human brain inspired hardware with quantum functionalities: It will build superconducting quantum neural networks to develop dedicated, neuromorphic quantum machine learning hardware, which can, in its next generation, outperform classical von Neumann architectures. This breakthrough will combine two cutting edge developments in information processing, machine learning and quantum computing, into a radically new technology. In contrast to established machine learning approaches that emulate neural function in software on conventional von Neumann hardware, neuromorphic quantum hardware can offer a significant advantage as it can b e trained on multiple batches of real world data in parallel. This feature is expected to lead to a quantum advantage. Moreover, our approach of implementing neuromorphic quantum hardware is very promising since there exist indications that a quantum advantage in machine learning can already be achieved with moderate fault tolerance. In a longer term perspective neuromorphic hardware architectures will become extremely important in both, classical and quantum computing, particularly for distributed and embedded computing tasks, where the vast scaling of existing architectures does not provide a long-term solution. Quromorphic aims to provide proof of concept demonstrations of this new technology and a roadmap for the path towards its exploitation. To achieve this breakthrough, we will implement two classes of quantum neural networks that have immediate applications in quantum machine learning, feed forward networks and non-equilibrium quantum annealers. This effort will be completed by the development of strategies for scaling the devices to the threshold where they will surpass the capabilities of existing machine learning technology and achieve quantum advantage. In preparation for future exploitation of this new technology, we will run simulations to explore its application to real world problems.

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "QUROMORPHIC" 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 "QUROMORPHIC" are provided by the European Opendata Portal: CORDIS opendata.

More projects from the same programme (H2020-EU.1.2.1.)

FLIX (2020)

FLow chemistry for Isotopic eXchange

Read More  

EDRA (2019)

Hardware-Assisted Decoupled Access Execution on the Digital Market: The EDRA Framework

Read More  

ph-coding (2019)

Predictive Haptic COding Devices In Next Generation interfaces

Read More