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Quantum Algorithms
Polynomial computational complexity of matrix elements of finite-rank-generated single-particle operators in products of finite bosonic states
arXiv
Authors: Dmitri A. Ivanov
Year
2022
Paper ID
58181
Status
Preprint
Abstract Read
~2 min
Abstract Words
117
Citations
N/A
Abstract
It is known that computing the permanent of the matrix 1+A, where A is a finite-rank matrix, requires a number of operations polynomial in the matrix size. Motivated by the boson-sampling proposal of restricted quantum computation, I extend this result to a generalization of the matrix permanent: an expectation value in a product of a large number of identical bosonic states with a bounded number of bosons. This result complements earlier studies on the computational complexity in boson sampling and related setups. The proposed technique based on the Gaussian averaging is equally applicable to bosonic and fermionic systems. This also allows us to improve an earlier polynomial complexity estimate for the fermionic version of the same problem.
Why This Paper Matters
- It adds a 2022 reference point for readers tracking recent quantum research.
- It is known that computing the permanent of the matrix 1+A, where A is a finite-rank matrix, requires a number of operations polynomial in the matrix size.
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