Hamiltonian simulation with optimal sample complexity
Quantum Software from Quantum States One of the hallmarks of quantum computation is the storage and extraction of information within quantum systems. Recently, Lloyd, Mohseni and Rebentrost created a protocol to treat multiple identical copies of a quantum state as “quantum software”, specifying a q...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2017-03-01
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| Series: | npj Quantum Information |
| Online Access: | https://doi.org/10.1038/s41534-017-0013-7 |
| _version_ | 1818681347088056320 |
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| author | Shelby Kimmel Cedric Yen-Yu Lin Guang Hao Low Maris Ozols Theodore J. Yoder |
| author_facet | Shelby Kimmel Cedric Yen-Yu Lin Guang Hao Low Maris Ozols Theodore J. Yoder |
| author_sort | Shelby Kimmel |
| collection | DOAJ |
| description | Quantum Software from Quantum States One of the hallmarks of quantum computation is the storage and extraction of information within quantum systems. Recently, Lloyd, Mohseni and Rebentrost created a protocol to treat multiple identical copies of a quantum state as “quantum software”, specifying a quantum program to be run on any other state. They use this approach to do principal component analysis of the software state. Here, we expand on their results, providing protocols for running more-complex quantum programs specified by several different states. Our protocols can be used to analyze the relationship between different states (for example, deciding whether states are orthogonal) and to create new states (such as coherent linear combinations of two states). We also outline the optimality of Lloyd et al.’s original protocol, as well as our new protocols. |
| first_indexed | 2024-12-17T10:01:30Z |
| format | Article |
| id | doaj.art-991483e91eb14e1bb598a6138ba66485 |
| institution | Directory Open Access Journal |
| issn | 2056-6387 |
| language | English |
| last_indexed | 2024-12-17T10:01:30Z |
| publishDate | 2017-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Quantum Information |
| spelling | doaj.art-991483e91eb14e1bb598a6138ba664852022-12-21T21:53:17ZengNature Portfolionpj Quantum Information2056-63872017-03-01311710.1038/s41534-017-0013-7Hamiltonian simulation with optimal sample complexityShelby Kimmel0Cedric Yen-Yu Lin1Guang Hao Low2Maris Ozols3Theodore J. Yoder4Joint Center for Quantum Information and Computer Science (QuICS), University of MarylandJoint Center for Quantum Information and Computer Science (QuICS), University of MarylandDepartment of Physics, Massachusetts Institute of TechnologyDepartment of Applied Mathematics and Theoretical Physics, University of CambridgeDepartment of Physics, Massachusetts Institute of TechnologyQuantum Software from Quantum States One of the hallmarks of quantum computation is the storage and extraction of information within quantum systems. Recently, Lloyd, Mohseni and Rebentrost created a protocol to treat multiple identical copies of a quantum state as “quantum software”, specifying a quantum program to be run on any other state. They use this approach to do principal component analysis of the software state. Here, we expand on their results, providing protocols for running more-complex quantum programs specified by several different states. Our protocols can be used to analyze the relationship between different states (for example, deciding whether states are orthogonal) and to create new states (such as coherent linear combinations of two states). We also outline the optimality of Lloyd et al.’s original protocol, as well as our new protocols.https://doi.org/10.1038/s41534-017-0013-7 |
| spellingShingle | Shelby Kimmel Cedric Yen-Yu Lin Guang Hao Low Maris Ozols Theodore J. Yoder Hamiltonian simulation with optimal sample complexity npj Quantum Information |
| title | Hamiltonian simulation with optimal sample complexity |
| title_full | Hamiltonian simulation with optimal sample complexity |
| title_fullStr | Hamiltonian simulation with optimal sample complexity |
| title_full_unstemmed | Hamiltonian simulation with optimal sample complexity |
| title_short | Hamiltonian simulation with optimal sample complexity |
| title_sort | hamiltonian simulation with optimal sample complexity |
| url | https://doi.org/10.1038/s41534-017-0013-7 |
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