Feynman's algorithm
Feynman's algorithm is an algorithm that is used to simulate the operations of a quantum computer on a classical computer. It is based on the Path integral formulation of quantum mechanics, which was formulated by Richard Feynman.[1]
Overview
An qubit quantum computer takes in a quantum circuit that contains gates and an input state . It then outputs a string of bits with probability .
In Schrödinger's algorithm, is calculated straightforwardly via matrix multiplication. That is, . The quantum state of the system can be tracked throughout its evolution.[2]
In Feynman's path algorithm, is calculated by summing up the contributions of histories. That is, . [3]
Schrödinger's takes less time to run compared to Feynman's while Feynman's takes more time and less space. More precisely, Schrödinger's takes time and space while Feynman's takes time and space.[4]
Example
Consider the problem of creating a Bell state. What is the probability that the resulting measurement will be ?
Since the quantum circuit that generates a Bell state is the H (Hadamard gate) gate followed by the CNOT gate, the unitary for this circuit is . In that case, using Schrödinger's algorithm. So probability resulting measurement will be is .
Using Feynman's algorithm, the Bell state circuit contains histories: . So = | + + + .
See also
References
- ^ Ethan Bernstein and Umesh Vazirani (1997). "Quantum Complexity Theory". SIAM Journal on Computing. 26 (5): 1411–1473. doi:10.1137/S0097539796300921.
- ^ Raedt, K. De; Michielsen, K.; Raedt, H. De; Trieu, B.; Lippert, Th.; Watanabe, H.; Ito, N. (2006). "Massively parallel quantum computer simulator". Comput. Phys. Commun. 176: 121–136. arXiv:1805.04708. doi:10.1016/j.cpc.2006.08.007.
- ^ Rudiak-Gould, Ben (2006). "The sum-over-histories formulation of quantum computing". arXiv:quant-ph/0607151.
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Aaronson, Scott; Chen, Lijie (2016). "Complexity-Theoretic Foundations of Quantum Supremacy Experiments". Proceedings of the 32nd Computational Complexity Conference: 1–67. arXiv:1612.05903. doi:10.4230/LIPIcs.CCC.2017.22.
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