Quantum Computation
and High-Energy Physics
Seminar
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Goals

The QuantHEP Seminar aims:

  • to present and discuss ideas and results on how Quantum Computing – and Quantum Technologies (QT) in general – can help address scientific challenges in High-Energy Physics (HEP), and how in turn HEP can bring new insights into Quantum Information Science;
  • to bring the QT and HEP communities closer together and foster their scientific collaboration.

The QuantHEP Seminar is an initiative of the research project QuantHEP – Quantum Computing Solutions for High-Energy Physics.

The acronym QuantHEP comes from the merging of the names of the sections of the arXiv used by the QT and HEP communities, respectively: Quantum Physics (quant-ph), and High-Energy Physics (hep-ex, hep-lat, hep-ph, hep-th).
 

Schedule & Venue

The QuantHEP Seminar takes places online in the first Wednesday of every month, at 17h00 Central European Time (in the corresponding Summer or Winter time, depending on the season).

The QuantHEP Seminar is streamed live on the QuantHEP Seminar YouTube channel. The video recording of the seminar and the corresponding slides will be made available on the QuantHEP Seminar website.

Duration

Each session of the QuantHEP Seminar is composed of a 45 minutes presentation, followed by a slot of 10 minutes for questions.
 

Mailing list & Calendar

To receive the announcements of the QuantHEP Seminar, subscribe to:

And follow QuantHEP on Twitter!

Support

Project QuantHEP – Quantum Computing Solutions for High-Energy Physics, promoting the QuantHEP seminar, is supported by the QuantERA ERA-NET Cofund in Quantum Technologies.

 

Scheduled Speakers

Sau Lan Wu

4 November 2020

Ignacio Cirac

2 December 2020

Scheduled Seminars

The QuantHEP Seminar takes places online in the first Wednesday of every month, at 17h00 Central European Time (in the corresponding Summer or Winter time, depending on the season).

Day 1
04 Nov 2020

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

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...
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Sau Lan Wu
Day 2
02 Dec 2020

Solving quantum lattice gauge theories with quantum computers

Quantum many-body systems are very hard to simulate, as computational resources (time and memory) typically grow exponentially with system size. Quantum computers or analog quantum simulators can circumvent this problem...
Read More
Ignacio Cirac