Built on

S. B. Bravyi and A. Y. Kitaev, Fermionic quantum computation, Ann. of Physics 298
2002
Earlier work this paper cites.
C. Derby and J. Klassen, A compact fermion to qubit mapping (2020), arXiv:2003.06939 [quant-ph]
Original
2003
Earlier work this paper cites.
J. S. Kottmann, M. Krenn, T. H. Kyaw, S. Alperin-Lea, and A. Aspuru-Guzik, Quantum computer-aided design of quantum optics hardware, arXiv:2006.03075 [quant-ph] (2020b)
Original
2006
Earlier work this paper cites.
I. Shavitt and R. J. Bartlett, Many-body methods in chemistry and physics: MBPT and coupled-cluster theory (Cambridge university press, 2009)
2009
Earlier work this paper cites.
R. W. Chien and J. D. Whitfield, Custom fermionic codes for quantum simulation (2020), arXiv:2009.11860 [quant-ph]
Original
2009
Earlier work this paper cites.
C. Loken, D. Gruner, L. Groer, R. Peltier, N. Bunn, M. Craig, T. Henriques, J. Dempsey, C.-H. Yu, J. Chen, et al. , SciNet: Lessons Learned from Building a Power-efficient Top-20 System and Data Centre, J. Phys. Conf. Ser. 256
Original
2010
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P. Jørgensen, Second quantization-based methods in quantum chemistry (Elsevier, 2012)
2012
Earlier work this paper cites.
P. R. Surján, Second quantized approach to quantum chemistry: an elementary introduction (Springer Science & Business Media, 2012)
2012
Earlier work this paper cites.
J. T. Seeley, M. J. Richard, and P. J. Love, The Bravyi-Kitaev transformation for quantum computation of electronic structure, J. Chem. Phys. 137
2012
Earlier work this paper cites.
A. Peruzzo, J. McClean, P. Shadbolt, M.-H. Yung, X.-Q. Zhou, P. J. Love, A. Aspuru-Guzik, and J. L. O’brien, A variational eigenvalue solver on a photonic quantum processor, Nat. Commun. 5
2014
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E. Farhi, J. Goldstone, and S. Gutmann, A quantum approximate optimization algorithm, arXiv:1411.4028 [quant-ph] (2014)
Original
2014
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P. Wittek, Quantum Machine Learning: What Quantum Computing Means to Data Mining (Elsevier, 2014)
2014
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T. Helgaker, P. Jorgensen, and J. Olsen, Molecular electronic-structure theory (John Wiley & Sons, 2014)
2014
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Q. Sun, Libcint: An efficient general integral library for gaussian basis functions, J. Comput. Chem. 36
2015
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R. S. Smith, M. J. Curtis, and W. J. Zeng, A practical quantum instruction set architecture, arXiv:1608.03355 [quant-ph] (2016)
Original
2016
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R. J. Harrison, G. Beylkin, F. A. Bischoff, J. A. Calvin, G. I. Fann, J. Fosso-Tande, D. Galindo, J. R. Hammond, R. Hartman-Baker, J. C. Hill, et al. , MADNESS: A multiresolution, adaptive numerical environment for scientific simulation, SIAM J. Sci. Comput. 38
2016
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T. G. authors, GPyOpt: A bayesian optimization framework in python (2016)
2016
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J. R. McClean, J. Romero, R. Babbush, and A. Aspuru-Guzik, The theory of variational hybrid quantum-classical algorithms, New J. Phys. 18
2016
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R. M. Parrish, L. A. Burns, D. G. Smith, A. C. Simmonett, A. E. DePrince III, E. G. Hohenstein, U. Bozkaya, A. Y. Sokolov, R. Di Remigio, R. M. Richard, et al. , Psi4 1.1: An open-source electronic structure program emphasizing automation, advanced libraries, and interoperability, J. Chem. Theory Comput. 13
2017
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J. R. McClean, K. J. Sung, I. D. Kivlichan, Y. Cao, C. Dai, E. S. Fried, C. Gidney, B. Gimby, P. Gokhale, T. Häner, T. Hardikar, V. Havlíček, O. Higgott, C. Huang, J. Izaac, Z. Jiang, X. Liu, S. McArdle, M. Neeley, T. O’Brien, B. O’Gorman, I. Ozfidan, M. D. Radin, J. Romero, N. Rubin, N. P. D. Sawaya, K. Setia, S. Sim, D. S. Steiger, M. Steudtner, Q. Sun, W. Sun, D. Wang, F. Zhang, and R. Babbush, Openfermion: The electronic structure package for quantum computers, arXiv:1710.07629 [quant-ph] (2017)
Original
2017
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M. Reiher, N. Wiebe, K. M. Svore, D. Wecker, and M. Troyer, Elucidating reaction mechanisms on quantum computers, PNAS 114
2017
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S. Bravyi, J. M. Gambetta, A. Mezzacapo, and K. Temme, Tapering off qubits to simulate fermionic hamiltonians, arXiv:1701.08213 [quant-ph] (2017)
Original
2017
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J. Preskill, Quantum computing in the NISQ era and beyond, Quantum 2
2018
Earlier work this paper cites.

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T. cirq developers, Cirq: A python framework for creating, editing, and invoking noisy intermediate scale quantum circuits (2018)
2018
Cited alongside, same era.
V. Bergholm, J. Izaac, M. Schuld, C. Gogolin, C. Blank, K. McKiernan, and N. Killoran, Pennylane: Automatic differentiation of hybrid quantum-classical computations, arXiv:1811.04968 [quant-ph] (2018)
Original
2018
Cited alongside, same era.
D. S. Steiger, T. Häner, and M. Troyer, ProjectQ: an open source software framework for quantum computing, Quantum 2
2018
Cited alongside, same era.
Q. Sun, T. C. Berkelbach, N. S. Blunt, G. H. Booth, S. Guo, Z. Li, J. Liu, J. D. McClain, E. R. Sayfutyarova, S. Sharma, S. Wouters, and G. K.-L. Chan, Pyscf: the python-based simulations of chemistry framework, Wiley Interdisciplinary Reviews: Computational Molecular Science 8
2018
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Then

X.-Z. Luo, J.-G. Liu, P. Zhang, and L. Wang, Yao. jl: Extensible, efficient framework for quantum algorithm design, Quantum 4
2020
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Y. Suzuki, Y. Kawase, Y. Masumura, Y. Hiraga, M. Nakadai, J. Chen, K. M. Nakanishi, K. Mitarai, R. Imai, S. Tamiya, T. Yamamoto, T. Yan, T. Kawakubo, Y. O. Nakagawa, Y. Ibe, Y. Zhang, H. Yamashita, H. Yoshimura, A. Hayashi, and K. Fujii, Qulacs: a fast and versatile quantum circuit simulator for research purpose, arXiv:2011.13524 [quant-ph] (2020)
Original
2020
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N. P. D. Sawaya, T. Menke, T. H. Kyaw, S. Johri, A. Aspuru-Guzik, and G. G. Guerreschi, Resource-efficient digital quantum simulation of d d -level systems for photonic, vibrational, and spin- s s Hamiltonians, npj Quantum Inf. 6
2020
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2020
Closest in time.

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2020

Tequila: A platform for rapid development of quantum algorithms

Kottmann, Jakob S., Alperin-Lea, Sumner, Tamayo-Mendoza, Teresa et al.

Understand

Variational quantum algorithms are currently the most promising class of algorithms for deployment on near-term quantum computers.

In contrast to classical algorithms, there are almost no standardized methods in quantum algorithmic development yet, and the field continues to evolve rapidly.
As in classical computing, heuristics play a crucial role in the development of new quantum algorithms, resulting in high demand for flexible and reliable ways to implement, test, and share new ideas.
Inspired by this demand, we introduce tequila, a development package for quantum algorithms in python, designed for fast and flexible implementation, prototyping, and deployment of novel quantum algorithms in electronic structure and other fields.

Built on

S. B. Bravyi and A. Y. Kitaev, Fermionic quantum computation, Ann. of Physics 298
2002
Earlier work this paper cites.
C. Derby and J. Klassen, A compact fermion to qubit mapping (2020), arXiv:2003.06939 [quant-ph]
Original
2003
Earlier work this paper cites.
J. S. Kottmann, M. Krenn, T. H. Kyaw, S. Alperin-Lea, and A. Aspuru-Guzik, Quantum computer-aided design of quantum optics hardware, arXiv:2006.03075 [quant-ph] (2020b)
Original
2006
Earlier work this paper cites.
I. Shavitt and R. J. Bartlett, Many-body methods in chemistry and physics: MBPT and coupled-cluster theory (Cambridge university press, 2009)
2009
Earlier work this paper cites.
R. W. Chien and J. D. Whitfield, Custom fermionic codes for quantum simulation (2020), arXiv:2009.11860 [quant-ph]
Original
2009
Earlier work this paper cites.
C. Loken, D. Gruner, L. Groer, R. Peltier, N. Bunn, M. Craig, T. Henriques, J. Dempsey, C.-H. Yu, J. Chen, et al. , SciNet: Lessons Learned from Building a Power-efficient Top-20 System and Data Centre, J. Phys. Conf. Ser. 256
Original
2010
Earlier work this paper cites.
P. Jørgensen, Second quantization-based methods in quantum chemistry (Elsevier, 2012)
2012
Earlier work this paper cites.
P. R. Surján, Second quantized approach to quantum chemistry: an elementary introduction (Springer Science & Business Media, 2012)
2012
Earlier work this paper cites.
J. T. Seeley, M. J. Richard, and P. J. Love, The Bravyi-Kitaev transformation for quantum computation of electronic structure, J. Chem. Phys. 137
2012
Earlier work this paper cites.
A. Peruzzo, J. McClean, P. Shadbolt, M.-H. Yung, X.-Q. Zhou, P. J. Love, A. Aspuru-Guzik, and J. L. O’brien, A variational eigenvalue solver on a photonic quantum processor, Nat. Commun. 5
2014
Earlier work this paper cites.
E. Farhi, J. Goldstone, and S. Gutmann, A quantum approximate optimization algorithm, arXiv:1411.4028 [quant-ph] (2014)
Original
2014
Earlier work this paper cites.
P. Wittek, Quantum Machine Learning: What Quantum Computing Means to Data Mining (Elsevier, 2014)
2014
Earlier work this paper cites.
T. Helgaker, P. Jorgensen, and J. Olsen, Molecular electronic-structure theory (John Wiley & Sons, 2014)
2014
Earlier work this paper cites.
Q. Sun, Libcint: An efficient general integral library for gaussian basis functions, J. Comput. Chem. 36
2015
Earlier work this paper cites.
R. S. Smith, M. J. Curtis, and W. J. Zeng, A practical quantum instruction set architecture, arXiv:1608.03355 [quant-ph] (2016)
Original
2016
Earlier work this paper cites.
R. J. Harrison, G. Beylkin, F. A. Bischoff, J. A. Calvin, G. I. Fann, J. Fosso-Tande, D. Galindo, J. R. Hammond, R. Hartman-Baker, J. C. Hill, et al. , MADNESS: A multiresolution, adaptive numerical environment for scientific simulation, SIAM J. Sci. Comput. 38
2016
Earlier work this paper cites.
T. G. authors, GPyOpt: A bayesian optimization framework in python (2016)
2016
Earlier work this paper cites.
J. R. McClean, J. Romero, R. Babbush, and A. Aspuru-Guzik, The theory of variational hybrid quantum-classical algorithms, New J. Phys. 18
2016
Earlier work this paper cites.
R. M. Parrish, L. A. Burns, D. G. Smith, A. C. Simmonett, A. E. DePrince III, E. G. Hohenstein, U. Bozkaya, A. Y. Sokolov, R. Di Remigio, R. M. Richard, et al. , Psi4 1.1: An open-source electronic structure program emphasizing automation, advanced libraries, and interoperability, J. Chem. Theory Comput. 13
2017
Earlier work this paper cites.
J. R. McClean, K. J. Sung, I. D. Kivlichan, Y. Cao, C. Dai, E. S. Fried, C. Gidney, B. Gimby, P. Gokhale, T. Häner, T. Hardikar, V. Havlíček, O. Higgott, C. Huang, J. Izaac, Z. Jiang, X. Liu, S. McArdle, M. Neeley, T. O’Brien, B. O’Gorman, I. Ozfidan, M. D. Radin, J. Romero, N. Rubin, N. P. D. Sawaya, K. Setia, S. Sim, D. S. Steiger, M. Steudtner, Q. Sun, W. Sun, D. Wang, F. Zhang, and R. Babbush, Openfermion: The electronic structure package for quantum computers, arXiv:1710.07629 [quant-ph] (2017)
Original
2017
Earlier work this paper cites.
M. Reiher, N. Wiebe, K. M. Svore, D. Wecker, and M. Troyer, Elucidating reaction mechanisms on quantum computers, PNAS 114
2017
Earlier work this paper cites.
S. Bravyi, J. M. Gambetta, A. Mezzacapo, and K. Temme, Tapering off qubits to simulate fermionic hamiltonians, arXiv:1701.08213 [quant-ph] (2017)
Original
2017
Earlier work this paper cites.
J. Preskill, Quantum computing in the NISQ era and beyond, Quantum 2
2018
Earlier work this paper cites.

Similar

T. cirq developers, Cirq: A python framework for creating, editing, and invoking noisy intermediate scale quantum circuits (2018)
2018
Cited alongside, same era.
V. Bergholm, J. Izaac, M. Schuld, C. Gogolin, C. Blank, K. McKiernan, and N. Killoran, Pennylane: Automatic differentiation of hybrid quantum-classical computations, arXiv:1811.04968 [quant-ph] (2018)
Original
2018
Cited alongside, same era.
D. S. Steiger, T. Häner, and M. Troyer, ProjectQ: an open source software framework for quantum computing, Quantum 2
2018
Cited alongside, same era.
Q. Sun, T. C. Berkelbach, N. S. Blunt, G. H. Booth, S. Guo, Z. Li, J. Liu, J. D. McClain, E. R. Sayfutyarova, S. Sharma, S. Wouters, and G. K.-L. Chan, Pyscf: the python-based simulations of chemistry framework, Wiley Interdisciplinary Reviews: Computational Molecular Science 8
2018
Cited alongside, same era.

Then

X.-Z. Luo, J.-G. Liu, P. Zhang, and L. Wang, Yao. jl: Extensible, efficient framework for quantum algorithm design, Quantum 4
2020
Closest in time.
Y. Suzuki, Y. Kawase, Y. Masumura, Y. Hiraga, M. Nakadai, J. Chen, K. M. Nakanishi, K. Mitarai, R. Imai, S. Tamiya, T. Yamamoto, T. Yan, T. Kawakubo, Y. O. Nakagawa, Y. Ibe, Y. Zhang, H. Yamashita, H. Yoshimura, A. Hayashi, and K. Fujii, Qulacs: a fast and versatile quantum circuit simulator for research purpose, arXiv:2011.13524 [quant-ph] (2020)
Original
2020
Closest in time.
N. P. D. Sawaya, T. Menke, T. H. Kyaw, S. Johri, A. Aspuru-Guzik, and G. G. Guerreschi, Resource-efficient digital quantum simulation of d d -level systems for photonic, vibrational, and spin- s s Hamiltonians, npj Quantum Inf. 6
2020
Closest in time.
T.-C. Yen, V. Verteletskyi, and A. F. Izmaylov, Measuring all compatible operators in one series of single-qubit measurements using unitary transformations, J. Chem. Theory Comput. 16
2020
Closest in time.

Beyond the bibliography

alphaXiv searches the wider corpus for related work and actual follow-ups.

Open on alphaXiv

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