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TFermion: A non-Clifford gate cost assessment library of quantum phase estimation algorithms for quantum chemistry

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Pablo A. M. Casares1, Roberto Campos1,2, and M. A. Martin-Delgado1,3

1Departamento de Física Teórica, Universidad Complutense de Madrid.
2Quasar Science Resources, SL.
3CCS-Center for Computational Simulation, Universidad Politécnica de Madrid.

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Abstract

Quantum Phase Estimation is one of the most useful quantum computing algorithms for quantum chemistry and as such, significant effort has been devoted to designing efficient implementations. In this article, we introduce TFermion, a library designed to estimate the T-gate cost of such algorithms, for an arbitrary molecule. As examples of usage, we estimate the T-gate cost of a few simple molecules and compare the same Taylorization algorithms using Gaussian and plane-wave basis.

Presentation of TFermion in the APS March meeting 2022:

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Chemistry and material science are often thought of as the killer application of quantum computing. Specifically, quantum phase estimation is a cornerstone quantum algorithm that can be used to study the energy of quantum systems, and thus estimate many of their chemical properties. On the other hand, implementing this algorithm depends on a few crucial choices, including how the system is represented and how it is made to evolve. These decisions will ultimately be reflected in the total time required to execute the algorithm, a key consideration if we want it to be useful. TFermion is a software library that estimates the number of the most costly logical gates in quantum phase estimation, thus allowing for comparing the cost of different options, and evaluating their practicality.

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Cited by

[1] Xiantao Li, “Some error analysis for the quantum phase estimation algorithms”, Journal of Physics A Mathematical General 55 32, 325303 (2022).

[2] Alain Delgado, Pablo A. M. Casares, Roberto dos Reis, Modjtaba Shokrian Zini, Roberto Campos, Norge Cruz-Hernández, Arne-Christian Voigt, Angus Lowe, Soran Jahangiri, M. A. Martin-Delgado, Jonathan E. Mueller, and Juan Miguel Arrazola, “How to simulate key properties of lithium-ion batteries with a fault-tolerant quantum computer”, arXiv:2204.11890.

The above citations are from SAO/NASA ADS (last updated successfully 2022-08-08 17:31:49). The list may be incomplete as not all publishers provide suitable and complete citation data.

On Crossref’s cited-by service no data on citing works was found (last attempt 2022-08-08 17:31:47).

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