Speaker
Description
Quantum computing technology is developing rapidly and has attracted increasing attention and interest from governments and institutions around the world. Although in the NISQ era, quantum computing has begun to play a notable role in more and more fields such as logistics scheduling, quantum finance, and quantum chemistry, thanks to its computing power far superior to classical computers. And a number of high energy physics subjects as well have been explored like particle classification, track reconstruction with various quantum algorithms.
Current quantum computers are very immature in terms of hardware manufacturing software development, especially in terms of simulation development platforms for high-energy physics data processing and simulation. Unlike classical program development, quantum programs currently have great difficulties in problem abstraction, data processing, algorithm design and implementation due to the difference in quantum bits and computation modes. A large amount of infrastructure needs to be researched and developed to help the development of quantum computing.
Combined with the needs of LHAASO, BESIII and other high-energy physics experiments, we have developed and deployed a quantum computing simulation platform for high-energy physics analysis combined with existing data computing clusters to provide a friendly, interactive and efficient development environment for the development of high-energy physics quantum algorithms called “QuIHEP”, simplify the quantum algorithm development process, and improve the efficiency of quantum program development.
Our quantum computing platform provides a composer interface for education and introduction, like IBM Quantum Composer to show how quantum circuits are constructed visually. Also, an interactive developing environment based on Jupyter and combined with IHEP SSO auth, is provided to help researchers study quantum algorithms efficiently. We developed a python package based on slurm restful APIs that allows users to submit their large-scale quantum simulation tasks within a container to our GPU cluster to enhance the complexity of quantum algorithms.
Together with various physical experimental and theoretical researchers, we will explore the applications of quantum computing in physical analysis and multi-body simulation, etc. We will abstract generic algorithms to form a library of generic quantum algorithm templates and provide corresponding algorithm application examples. Users can use these examples to conduct research quickly.
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