Automated optimization of large quantum circuits with continuous parameters
Quantum computation: optimizing quantum circuits A new software tool significantly reduces the size of arbitrary quantum circuits, automatically optimizing the number of gates required for running algorithms. Yunseong Nam and colleagues from the University of Maryland developed a set of subroutines...
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| Autores principales: | , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2018
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/db98af5e361345b4b60bf97577dc99cb |
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| Sumario: | Quantum computation: optimizing quantum circuits A new software tool significantly reduces the size of arbitrary quantum circuits, automatically optimizing the number of gates required for running algorithms. Yunseong Nam and colleagues from the University of Maryland developed a set of subroutines which, given a certain quantum circuit, would remove redundant gates by changing the order of individual or multiple operations and combining them. After a pre-processing phase, the execution of these routines in careful order constitutes a powerful automatized approach for reducing the resources required to implement a given algorithm. The heuristic nature of this optimization makes its computational cost scale well with the size of the circuit, as shown by comparisons for the computation of discrete logarithms and Hamiltonian simulations. This makes it applicable to computations that can be run on existing hardware and might outperform classical computers. |
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