Quantum computing and algorithms

Application of Quantum Machine Learning to High Energy Physics Analysis at LHC using Quantum Computer Simulators and Quantum Computer Hardware

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Machine learning enjoys widespread success in High Energy Physics (HEP) analysis at LHC. However the ambitious HL-LHC program will require much more computing resources in the next two decades. Quantum computing may offer speed-up for HEP physics analysis at HL-LHC, and can be a new computational

Start date
04 November, 2020

Application of Quantum Machine Learning to High Energy Physics Analysis at LHC using Quantum Computer Simulators and Quantum Computer Hardware

Start date
04 November, 2020

Quantum Computing for High Energy Physics Applications

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With the commissioning of the upgraded LHC-HL machine, High Energy Physics will face a large shortage of computing resources that has been evaluated between a factor 10 and 100. It is therefore necessary to explore all avenues that can lead to an improvement of the performance of HEP software

Start date
09 July, 2019

Quantum Computing for High Energy Physics Applications

Start date
09 July, 2019

Quantum Computing for High Energy Physics

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The ambitious upgrade programme for CERN’s Large Hadron Collider (LHC) will result in significant challenges related to information and communications technologies (ICTs) over the next decade and beyond. It is therefore vital that we — members of the high-energy physics (HEP) research community and

Start date
05 November, 2018

Quantum Computing for High Energy Physics

Start date
05 November, 2018

Viewpoint: Quantum thinking required

Particle physicists need to start thinking about tomorrow’s computing technology today.

29 October, 2018