关键词: 相干伊辛机, 组合优化, 玻尔兹曼采样, 生命科学, 药物发现

Abstract:

In basic life science research and drug discovery, there are a large number of complex computational needs, often facing high-frequency large-scale combinatorial optimization problem solutions and complex distribution sampling. Methods based on classical computational frameworks are difficult to weigh the time and accuracy in these problems, and the computational results are often “a tiny bit out of whack”. Lower quality of the solution and sampling bias ultimately lead to conformational bias and high screening false positives, resulting in high time and cost of drug discovery. Therefore, there is an urgent need for a computational framework that combines screening efficiency and accuracy to get out of this predicament. With the development of physical hardware, a variety of new quantum computational frameworks have been widely validated on different complex computational problems, Among them, the coherent Ising machine (CIM) is one of the fastest developing technical routes. By using the optical parametric oscillatory pulses as the quantum bits, it can search out the spin configuration in the Ising model ground state during operation, and enhance the computational speed and correctness of the problem of solving combinatorial optimization. It has huge advantages over other existing technical routes in terms of bit fully connected characteristics, bit number scale, and long-time continuous solution stability. This paper mainly discusses the underlying principles, technical advantages, main applications in basic life science research and drug discovery of CIM, as well as the limitations of CIM’s current practical applications, and looks forward to the future development.

Key words: coherent Ising machine, combinatorial optimization, boltzmann sampling, life sciences, drug discovery