Approximating outcome probabilities of linear optical circuits
Abstract Quasiprobability representations are important tools for analyzing a quantum system, such as a quantum state or a quantum circuit. In this work, we propose classical algorithms specialized for approximating outcome probabilities of a linear optical circuit using quasiprobability distributio...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-12-01
|
| Series: | npj Quantum Information |
| Online Access: | https://doi.org/10.1038/s41534-023-00791-9 |
| _version_ | 1797388111766880256 |
|---|---|
| author | Youngrong Lim Changhun Oh |
| author_facet | Youngrong Lim Changhun Oh |
| author_sort | Youngrong Lim |
| collection | DOAJ |
| description | Abstract Quasiprobability representations are important tools for analyzing a quantum system, such as a quantum state or a quantum circuit. In this work, we propose classical algorithms specialized for approximating outcome probabilities of a linear optical circuit using quasiprobability distributions. Notably, we can reduce the negativity bound of a circuit from exponential to at most polynomial for specific cases by modulating the shapes of quasiprobability distributions thanks to the symmetry of the linear optical transformation in the phase space. Consequently, our scheme provides an efficient estimation of outcome probabilities within an additive-error whose precision depends on the classicality of the input state. When the classicality is high enough, we reach a polynomial-time estimation algorithm of a probability within a multiplicative-error by an efficient sampling from a log-concave function. By choosing appropriate input states and measurements, our results provide plenty of quantum-inspired classical algorithms for approximating various matrix functions beating best-known results. Moreover, we give sufficient conditions for the classical simulability of Gaussian Boson sampling using our approximating algorithm for any (marginal) outcome probability under the poly-sparse condition. |
| first_indexed | 2024-03-08T22:36:08Z |
| format | Article |
| id | doaj.art-1fa4379d2d484b5eafb95bf073d1bf6a |
| institution | Directory Open Access Journal |
| issn | 2056-6387 |
| language | English |
| last_indexed | 2024-03-08T22:36:08Z |
| publishDate | 2023-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Quantum Information |
| spelling | doaj.art-1fa4379d2d484b5eafb95bf073d1bf6a2023-12-17T12:26:06ZengNature Portfolionpj Quantum Information2056-63872023-12-01911710.1038/s41534-023-00791-9Approximating outcome probabilities of linear optical circuitsYoungrong Lim0Changhun Oh1School of Computational Sciences, Korea Institute for Advanced StudyPritzker School of Molecular Engineering, University of ChicagoAbstract Quasiprobability representations are important tools for analyzing a quantum system, such as a quantum state or a quantum circuit. In this work, we propose classical algorithms specialized for approximating outcome probabilities of a linear optical circuit using quasiprobability distributions. Notably, we can reduce the negativity bound of a circuit from exponential to at most polynomial for specific cases by modulating the shapes of quasiprobability distributions thanks to the symmetry of the linear optical transformation in the phase space. Consequently, our scheme provides an efficient estimation of outcome probabilities within an additive-error whose precision depends on the classicality of the input state. When the classicality is high enough, we reach a polynomial-time estimation algorithm of a probability within a multiplicative-error by an efficient sampling from a log-concave function. By choosing appropriate input states and measurements, our results provide plenty of quantum-inspired classical algorithms for approximating various matrix functions beating best-known results. Moreover, we give sufficient conditions for the classical simulability of Gaussian Boson sampling using our approximating algorithm for any (marginal) outcome probability under the poly-sparse condition.https://doi.org/10.1038/s41534-023-00791-9 |
| spellingShingle | Youngrong Lim Changhun Oh Approximating outcome probabilities of linear optical circuits npj Quantum Information |
| title | Approximating outcome probabilities of linear optical circuits |
| title_full | Approximating outcome probabilities of linear optical circuits |
| title_fullStr | Approximating outcome probabilities of linear optical circuits |
| title_full_unstemmed | Approximating outcome probabilities of linear optical circuits |
| title_short | Approximating outcome probabilities of linear optical circuits |
| title_sort | approximating outcome probabilities of linear optical circuits |
| url | https://doi.org/10.1038/s41534-023-00791-9 |
| work_keys_str_mv | AT youngronglim approximatingoutcomeprobabilitiesoflinearopticalcircuits AT changhunoh approximatingoutcomeprobabilitiesoflinearopticalcircuits |