Quantum signal processing
Quantum Signal Processing is a Hamiltonian simulation algorithm with optimal lower bounds in query complexity. It linearizes the operator of a quantum walk using eigenvalue transformation. The quantum walk takes a constant number of queries. So quantum signal processing's cost depends on the constant number of calls to the quantum walk operator, number of single qubit quantum gates that aid in the eigenvalue transformation and an ancilla qubit.[1]
Eigenvalue transformation
Given a unitary , calculate . For example, if , . [1]
Algorithm
- Input: Given a Hamiltonian , define a quantum walk operator using 2 d-sparse oracles and . accepts inputs and ( is the row of the Hamiltonian and is the column) and outputs , so querying . accepts inputs and and computes the non-zero element in the row of . [2]
- Output:
- Create an input state
- Define a controlled-gate,
- Repeatedly apply single qubit gates to the ancilla followed applications of to the register that contains times.
References
- Low, Guang Hao; Chuang, Isaac (2017). "Optimal Hamiltonian Simulation by Quantum Signal Processing". Physical Review Letters. 118 (1): 010501. arXiv:1606.02685. Bibcode:2017PhRvL.118a0501L. doi:10.1103/PhysRevLett.118.010501. PMID 28106413. S2CID 1118993.
- Guan Hao Low (January 17, 2017). Optimal Hamiltonian simulation by quantum signal processing (YouTube). Retrieved September 9, 2019.
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