Quantum Computing Applications for High-Energy Physics
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Quantum Electronics".
Deadline for manuscript submissions: closed (20 July 2022) | Viewed by 2389
Special Issue Editors
Interests: quantum computing; quantum machine learning; high-energy physics
Special Issue Information
Dear Colleagues,
Over the years, the high-energy physics (HEP) community has witnessed the coevolution of computing and fundamental science. Researchers in the fields of particle physics and computing have built upon each other’s successes. Particularly, computing plays an essential role in HEP. As computing grew increasingly more sophisticated, its progress enabled new scientific discoveries and breakthroughs.
Quantum computing (QC) has the potential to speed up some of the most computationally expensive tasks in HEP. Therefore, in recent years, there has been a proliferation of quantum algorithms applied to HEP data analysis and simulations. The recent development of QC platforms and simulators available for public experimentation led to a general influx in research on quantum algorithms and applications. In particular, quantum algorithms were recently proposed to tackle the computational challenges of particle physics data processing and analysis. Some of these examples include assigning detector hits or signals into tracks to reconstruct the path of the originating particle, signal and background interactions, and clustering particles into so-called "particle jets".
Furthermore, it is expected that quantum computers will be more successful in the modeling of quantum effects, a difficult or impossible task for classical devices. Physicists use computer models to predict the behavior of fundamental particles. One such example is the modeling of parton showers. Additionally, quantum machine learning methods were extensively used in HEP.
This Special Issue will include any aspects related to quantum computing applications to HEP, such as simulations, data analysis, and quantum machine learning.
Dr. Andrea Delgado
Dr. Kathleen Hamilton
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- high-energy physics
- particle physics
- quantum computing
- quantum machine learning
