The mathematical nature of rail transport planning and control is an optimisation problem under discrete constraints, which is NP-hard (non-deterministic polynomial) , having high computational complexity. As an important research direction for the future leapfrog development of computing power, quantum computing is expected to provide potential solutions to solve the complex problems in existing large-scale road networks. The basic concepts and algorithms of quantum computing are introduced, and its potential application scenarios in the field of rail transportation are analysed, including the optimization of train scheduling, automatic train operation control and dynamic coupling and decoupling of train groups. The advantages of quantum particle swarm algorithm in solving complex optimisation problems are verified through experiments, which show that quantum computing has significant computational efficiency improvement in dealing with large-scale discrete constrained optimisation problems. However, the application of quantum computing technology in rail transport still faces challenges such as quantum bit decoherence, hardware integration and result security. This paper summarizes the prospects of quantum computing applications in rail transit and the problems it may face, and highlights the potentials and challenges of quantum computing technology in promoting the intelligent development of rail transit.
| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |