The article provides a comprehensive review of the parallel tempering simulation method, tracing its origins from data analysis to its current status as a standard tool in physicochemical simulations. The method, initially introduced by Swendsen and Wang in 1986, involves simulating multiple replicas of a system at different temperatures, allowing for the exchange of configuration information between adjacent replicas. This approach enhances sampling efficiency by enabling lower-temperature systems to access a broader range of phase space, while higher-temperature systems help avoid local minima. The authors discuss the theoretical foundations of parallel tempering, including the detailed balance condition and the acceptance probability for swaps between replicas. They also explore various extensions and applications, such as molecular dynamics parallel tempering, Hamiltonian parallel tempering, and multidimensional parallel tempering. These extensions have been applied to a wide range of fields, including polymer science, protein folding, solid-state physics, spin glasses, quantum systems, and optimization problems. Key applications highlighted include the determination of crystal structures in solid-state physics, the study of protein folding and NMR structure refinement, and the exploration of complex phase diagrams in polymer systems. The review also addresses challenges and future directions, such as optimizing the number and temperature of replicas, partial configuration swapping, and the use of alternative parameters and sampling methods. Overall, the article underscores the versatility and effectiveness of parallel tempering in improving sampling efficiency and addressing computational challenges in various scientific disciplines.The article provides a comprehensive review of the parallel tempering simulation method, tracing its origins from data analysis to its current status as a standard tool in physicochemical simulations. The method, initially introduced by Swendsen and Wang in 1986, involves simulating multiple replicas of a system at different temperatures, allowing for the exchange of configuration information between adjacent replicas. This approach enhances sampling efficiency by enabling lower-temperature systems to access a broader range of phase space, while higher-temperature systems help avoid local minima. The authors discuss the theoretical foundations of parallel tempering, including the detailed balance condition and the acceptance probability for swaps between replicas. They also explore various extensions and applications, such as molecular dynamics parallel tempering, Hamiltonian parallel tempering, and multidimensional parallel tempering. These extensions have been applied to a wide range of fields, including polymer science, protein folding, solid-state physics, spin glasses, quantum systems, and optimization problems. Key applications highlighted include the determination of crystal structures in solid-state physics, the study of protein folding and NMR structure refinement, and the exploration of complex phase diagrams in polymer systems. The review also addresses challenges and future directions, such as optimizing the number and temperature of replicas, partial configuration swapping, and the use of alternative parameters and sampling methods. Overall, the article underscores the versatility and effectiveness of parallel tempering in improving sampling efficiency and addressing computational challenges in various scientific disciplines.