Variational Quantum Eigensolver Boosted by Adiabatic Connection
Status PubMed-not-MEDLINE Jazyk angličtina Země Spojené státy americké Médium print-electronic
Typ dokumentu časopisecké články
PubMed
38214999
PubMed Central
PMC10823474
DOI
10.1021/acs.jpca.3c07590
Knihovny.cz E-zdroje
- Publikační typ
- časopisecké články MeSH
In this work, we integrate the variational quantum eigensolver (VQE) with the adiabatic connection (AC) method for efficient simulations of chemical problems on near-term quantum computers. Orbital-optimized VQE methods are employed to capture the strong correlation within an active space, and classical AC corrections recover the dynamical correlation effects comprising electrons outside of the active space. On two challenging strongly correlated problems, namely, the dissociation of N2 and the electronic structure of the tetramethyleneethane biradical, we show that the combined VQE-AC approach enhances the performance of VQE dramatically. Moreover, since the AC corrections do not bring any additional requirements on quantum resources or measurements, they can actually boost the VQE algorithms. Our work paves the way toward quantum simulations of real-life problems on near-term quantum computers.
Algorithmiq Limited Kanavakatu 3C FI 00160 Helsinki Finland
Faculty of Mathematics and Physics Charles University 121 16 Prague Czech Republic
Institute of Physics Lodz University of Technology ul Wolczanska 217 221 93 005 Lodz Poland
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Nielsen M. A.; Chuang I. L.. Quantum Computation and Quantum Information; Cambridge University Press, 2000.
Cao Y.; Romero J.; Olson J. P.; Degroote M.; Johnson P. D.; Kieferová M.; Kivlichan I. D.; Menke T.; Peropadre B.; Sawaya N. P. D.; et al. Quantum Chemistry in the Age of Quantum Computing. Chem. Rev. 2019, 119, 10856–10915. 10.1021/acs.chemrev.8b00803. PubMed DOI
McArdle S.; Endo S.; Aspuru-Guzik A.; Benjamin S. C.; Yuan X. Quantum computational chemistry. Rev. Mod. Phys. 2020, 92, 015003.10.1103/revmodphys.92.015003. DOI
Head-Marsden K.; Flick J.; Ciccarino C. J.; Narang P. Quantum Information and Algorithms for Correlated Quantum Matter. Chem. Rev. 2021, 121, 3061–3120. 10.1021/acs.chemrev.0c00620. PubMed DOI
Bauer B.; Bravyi S.; Motta M.; Chan G. K.-L. Quantum Algorithms for Quantum Chemistry and Quantum Materials Science. Chem. Rev. 2020, 120, 12685–12717. 10.1021/acs.chemrev.9b00829. PubMed DOI
Motta M.; Rice J. E. Emerging quantum computing algorithms for quantum chemistry. Wiley Interdiscip. Rev.: Comput. Mol. Sci. 2022, 12, e158010.1002/wcms.1580. DOI
Aspuru-Guzik A.; Dutoi A. D.; Love P. J.; Head-Gordon M. Simulated Quantum Computation of Molecular Energies. Science 2005, 309, 1704–1707. 10.1126/science.1113479. PubMed DOI
Abrams D. S.; Lloyd S. Simulation of Many-Body Fermi Systems on a Universal Quantum Computer. Phys. Rev. Lett. 1997, 79, 2586–2589. 10.1103/PhysRevLett.79.2586. DOI
Abrams D. S.; Lloyd S. Quantum Algorithm Providing Exponential Speed Increase for Finding Eigenvalues and Eigenvectors. Phys. Rev. Lett. 1999, 83, 5162–5165. 10.1103/PhysRevLett.83.5162. DOI
Reiher M.; Wiebe N.; Svore K. M.; Wecker D.; Troyer M. Elucidating reaction mechanisms on quantum computers. Proc. Natl. Acad. Sci. U.S.A. 2017, 114, 7555–7560. 10.1073/pnas.1619152114. PubMed DOI PMC
Terhal B. M. Quantum error correction for quantum memories. Rev. Mod. Phys. 2015, 87, 307–346. 10.1103/RevModPhys.87.307. DOI
Preskill J. Quantum Computing in the NISQ era and beyond. Quantum 2018, 2, 79.10.22331/q-2018-08-06-79. DOI
Peruzzo A.; McClean J.; Shadbolt P.; Yung M.-H.; Zhou X.-Q.; Love P. J.; Aspuru-Guzik A.; O’Brien J. L. A variational eigenvalue solver on a photonic quantum processor. Nat. Commun. 2014, 5, 4213.10.1038/ncomms5213. PubMed DOI PMC
McClean J. R.; Romero J.; Babbush R.; Aspuru-Guzik A. The theory of variational hybrid quantum-classical algorithms. New J. Phys. 2016, 18, 023023.10.1088/1367-2630/18/2/023023. DOI
Tilly J.; Chen H.; Cao S.; Picozzi D.; Setia K.; Li Y.; Grant E.; Wossnig L.; Rungger I.; Booth G. H.; et al. The Variational Quantum Eigensolver: A review of methods and best practices. Phys. Rep. 2022, 986, 1–128. 10.1016/j.physrep.2022.08.003. DOI
Romero J.; Babbush R.; McClean J. R.; Hempel C.; Love P. J.; Aspuru-Guzik A. Strategies for quantum computing molecular energies using the unitary coupled cluster ansatz. Quantum Sci. Technol. 2019, 4, 014008.10.1088/2058-9565/aad3e4. DOI
Smart S. E.; Mazziotti D. A. Quantum Solver of Contracted Eigenvalue Equations for Scalable Molecular Simulations on Quantum Computing Devices. Phys. Rev. Lett. 2021, 126, 070504.10.1103/PhysRevLett.126.070504. PubMed DOI
Stair N. H.; Evangelista F. A. Simulating Many-Body Systems with a Projective Quantum Eigensolver. PRX Quantum 2021, 2, 030301.10.1103/PRXQuantum.2.030301. DOI
Motta M.; Gujarati T. P.; Rice J. E.; Kumar A.; Masteran C.; Latone J. A.; Lee E.; Valeev E. F.; Takeshita T. Y. Quantum simulation of electronic structure with a transcorrelated Hamiltonian: improved accuracy with a smaller footprint on the quantum computer. Phys. Chem. Chem. Phys. 2020, 22, 24270–24281. 10.1039/D0CP04106H. PubMed DOI
Sokolov I. O.; Dobrautz W.; Luo H.; Alavi A.; Tavernelli I. Orders of magnitude increased accuracy for quantum many-body problems on quantum computers via an exact transcorrelated method. Phys. Rev. Res. 2023, 5, 023174.10.1103/PhysRevResearch.5.023174. DOI
Bauman N. P.; Bylaska E. J.; Krishnamoorthy S.; Low G. H.; Wiebe N.; Granade C. E.; Roetteler M.; Troyer M.; Kowalski K. Downfolding of many-body Hamiltonians using active-space models: Extension of the sub-system embedding sub-algebras approach to unitary coupled cluster formalisms. J. Chem. Phys. 2019, 151, 014107.10.1063/1.5094643. PubMed DOI
Nicholas P B.; Chládek J.; Veis L.; Pittner J.; Karol K. Variational quantum eigensolver for approximate diagonalization of downfolded Hamiltonians using generalized unitary coupled cluster ansatz. Quantum Sci. Technol. 2021, 6, 034008.10.1088/2058-9565/abf602. DOI
Le N. T.; Tran L. N. Correlated Reference-Assisted Variational Quantum Eigensolver. J. Phys. Chem. A 2023, 127, 5222–5230. 10.1021/acs.jpca.3c00993. PubMed DOI
Kowalski K. Dimensionality reduction of the many-body problem using coupled-cluster subsystem flow equations: Classical and quantum computing perspective. Phys. Rev. A 2021, 104, 032804.10.1103/PhysRevA.104.032804. DOI
Kowalski K.; Bauman N. P. Quantum Flow Algorithms for Simulating Many-Body Systems on Quantum Computers. Phys. Rev. Lett. 2023, 131, 200601.10.1103/PhysRevLett.131.200601. PubMed DOI
McClean J. R.; Kimchi-Schwartz M. E.; Carter J.; de Jong W. A. Hybrid quantum-classical hierarchy for mitigation of decoherence and determination of excited states. Phys. Rev. A 2017, 95, 042308.10.1103/PhysRevA.95.042308. DOI
Takeshita T.; Rubin N. C.; Jiang Z.; Lee E.; Babbush R.; McClean J. R. Increasing the Representation Accuracy of Quantum Simulations of Chemistry without Extra Quantum Resources. Phys. Rev. X 2020, 10, 011004.10.1103/PhysRevX.10.011004. DOI
Krompiec M.; Ramo D. M. Strongly Contracted N-Electron Valence State Perturbation Theory Using Reduced Density Matrices from a Quantum Computer. arXiv 2022, arXiv:2210.05702.10.48550/arXiv.2210.05702. DOI
Tammaro A.; Galli D. E.; Rice J. E.; Motta M. N-Electron Valence Perturbation Theory with Reference Wave Functions from Quantum Computing: Application to the Relative Stability of Hydroxide Anion and Hydroxyl Radical. J. Phys. Chem. A 2023, 127, 817–827. 10.1021/acs.jpca.2c07653. PubMed DOI
Pernal K. Electron Correlation from the Adiabatic Connection for Multireference Wave Functions. Phys. Rev. Lett. 2018, 120, 013001.10.1103/PhysRevLett.120.013001. PubMed DOI
Pastorczak E.; Pernal K. Correlation Energy from the Adiabatic Connection Formalism for Complete Active Space Wave Functions. J. Chem. Theory Comput. 2018, 14, 3493–3503. 10.1021/acs.jctc.8b00213. PubMed DOI
Pastorczak E.; Hapka M.; Veis L.; Pernal K. Capturing the Dynamic Correlation for Arbitrary Spin-Symmetry CASSCF Reference with Adiabatic Connection Approaches: Insights into the Electronic Structure of the Tetramethyleneethane Diradical. J. Phys. Chem. Lett. 2019, 10, 4668–4674. 10.1021/acs.jpclett.9b01582. PubMed DOI
Drwal D.; Beran P.; Hapka M.; Modrzejewski M.; Sokół A.; Veis L.; Pernal K. Efficient Adiabatic Connection Approach for Strongly Correlated Systems: Application to Singlet–Triplet Gaps of Biradicals. J. Phys. Chem. Lett. 2022, 13, 4570–4578. 10.1021/acs.jpclett.2c00993. PubMed DOI PMC
Boyn J.-N.; Lykhin A. O.; Smart S. E.; Gagliardi L.; Mazziotti D. A. Quantum-classical hybrid algorithm for the simulation of all-electron correlation. J. Chem. Phys. 2021, 155, 244106.10.1063/5.0074842. PubMed DOI
Veis L.; Višňák J.; Nishizawa H.; Nakai H.; Pittner J. Quantum chemistry beyond Born-Oppenheimer approximation on a quantum computer: A simulated phase estimation study. Int. J. Quantum Chem. 2016, 116, 1328–1336. 10.1002/qua.25176. DOI
Pavošević F.; Culpitt T.; Hammes-Schiffer S. Multicomponent Quantum Chemistry: Integrating Electronic and Nuclear Quantum Effects via the Nuclear–Electronic Orbital Method. Chem. Rev. 2020, 120, 4222–4253. 10.1021/acs.chemrev.9b00798. PubMed DOI
Pavošević F.; Hammes-Schiffer S. Multicomponent Unitary Coupled Cluster and Equation-of-Motion for Quantum Computation. J. Chem. Theory Comput. 2021, 17, 3252–3258. 10.1021/acs.jctc.1c00220. PubMed DOI
Szabo A.; Ostlund N.. Modern Quantum Chemistry: Introduction to Advanced Electronic Structure Theory; Dover Publications, 1996.
Claudino D. The basics of quantum computing for chemists. Int. J. Quantum Chem. 2022, 122, e2699010.1002/qua.26990. DOI
Jordan P.; Wigner E. Uber das paulische Aquivalenzverbot. Z. Phys. A 1928, 47, 631–651. 10.1007/BF01331938. DOI
Whitfield J. D.; Biamonte J.; Aspuru-Guzik A. Simulation of electronic structure Hamiltonians using quantum computers. Mol. Phys. 2011, 109, 735–750. 10.1080/00268976.2011.552441. DOI
Bravyi S. B.; Kitaev A. Y. Fermionic Quantum Computation. Ann. Phys. 2002, 298, 210–226. 10.1006/aphy.2002.6254. DOI
Seeley J. T.; Richard M. J.; Love P. J. The Bravyi-Kitaev transformation for quantum computation of electronic structure. J. Chem. Phys. 2012, 137, 224109.10.1063/1.4768229. PubMed DOI
Kandala A.; Mezzacapo A.; Temme K.; Takita M.; Brink M.; Chow J. M.; Gambetta J. M. Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets. Nature 2017, 549, 242–246. 10.1038/nature23879. PubMed DOI
Anand A.; Schleich P.; Alperin-Lea S.; Jensen P. W. K.; Sim S.; Díaz-Tinoco M.; Kottmann J. S.; Degroote M.; Izmaylov A. F.; Aspuru-Guzik A. A quantum computing view on unitary coupled cluster theory. Chem. Soc. Rev. 2022, 51, 1659–1684. 10.1039/D1CS00932J. PubMed DOI
Lee J.; Huggins W. J.; Head-Gordon M.; Whaley K. B. Generalized Unitary Coupled Cluster Wave functions for Quantum Computation. J. Chem. Theory Comput. 2019, 15, 311–324. 10.1021/acs.jctc.8b01004. PubMed DOI
Matsuzawa Y.; Kurashige Y. Jastrow-type Decomposition in Quantum Chemistry for Low-Depth Quantum Circuits. J. Chem. Theory Comput. 2020, 16, 944–952. 10.1021/acs.jctc.9b00963. PubMed DOI
Culpitt T.; Tellgren E. I.; Pavošević F. Unitary coupled-cluster for quantum computation of molecular properties in a strong magnetic field. J. Chem. Phys. 2023, 159, 204101.10.1063/5.0177417. PubMed DOI
Sokolov I. O.; Barkoutsos P. K.; Ollitrault P. J.; Greenberg D.; Rice J.; Pistoia M.; Tavernelli I. Quantum orbital-optimized unitary coupled cluster methods in the strongly correlated regime: Can quantum algorithms outperform their classical equivalents?. J. Chem. Phys. 2020, 152, 124107.10.1063/1.5141835. PubMed DOI
Evangelista F. A.; Chan G. K.-L.; Scuseria G. E. Exact parameterization of fermionic wave functions via unitary coupled cluster theory. J. Chem. Phys. 2019, 151, 244112.10.1063/1.5133059. PubMed DOI
Grimsley H. R.; Economou S. E.; Barnes E.; Mayhall N. J. An adaptive variational algorithm for exact molecular simulations on a quantum computer. Nat. Commun. 2019, 10, 3007.10.1038/s41467-019-10988-2. PubMed DOI PMC
Ryabinkin I. G.; Yen T.-C.; Genin S. N.; Izmaylov A. F. Qubit Coupled Cluster Method: A Systematic Approach to Quantum Chemistry on a Quantum Computer. J. Chem. Theory Comput. 2018, 14, 6317–6326. 10.1021/acs.jctc.8b00932. PubMed DOI
Tang H. L.; Shkolnikov V.; Barron G. S.; Grimsley H. R.; Mayhall N. J.; Barnes E.; Economou S. E. Qubit-ADAPT-VQE: An Adaptive Algorithm for Constructing Hardware-Efficient Ansätze on a Quantum Processor. PRX Quantum 2021, 2, 020310.10.1103/PRXQuantum.2.020310. DOI
Matoušek M.; Hapka M.; Veis L.; Pernal K. Toward more accurate adiabatic connection approach for multireference wavefunctions. J. Chem. Phys. 2023, 158, 054105.10.1063/5.0131448. PubMed DOI
Chatterjee K.; Pernal K. Excitation energies from extended random phase approximation employed with approximate one- and two-electron reduced density matrices. J. Chem. Phys. 2012, 137, 204109.10.1063/1.4766934. PubMed DOI
Rowe D. J. Equations-of-Motion Method and the Extended Shell Model. Rev. Mod. Phys. 1968, 40, 153–166. 10.1103/RevModPhys.40.153. DOI
Ollitrault P. J.; Kandala A.; Chen C.-F.; Barkoutsos P. K.; Mezzacapo A.; Pistoia M.; Sheldon S.; Woerner S.; Gambetta J. M.; Tavernelli I. Quantum equation of motion for computing molecular excitation energies on a noisy quantum processor. Phys. Rev. Res. 2020, 2, 043140.10.1103/PhysRevResearch.2.043140. DOI
Asthana A.; Kumar A.; Abraham V.; Grimsley H.; Zhang Y.; Cincio L.; Tretiak S.; Dub P. A.; Economou S. E.; Barnes E.; Mayhall N. J. Quantum self-consistent equation-of-motion method for computing molecular excitation energies, ionization potentials, and electron affinities on a quantum computer. Chem. Sci. 2023, 14, 2405–2418. 10.1039/D2SC05371C. PubMed DOI PMC
Pavošević F.; Tavernelli I.; Rubio A. Spin-Flip Unitary Coupled Cluster Method: Toward Accurate Description of Strong Electron Correlation on Quantum Computers. J. Phys. Chem. Lett. 2023, 14, 7876–7882. 10.1021/acs.jpclett.3c01935. PubMed DOI
Beran P.; Matoušek M.; Hapka M.; Pernal K.; Veis L. Density Matrix Renormalization Group with Dynamical Correlation via Adiabatic Connection. J. Chem. Theory Comput. 2021, 17, 7575–7585. 10.1021/acs.jctc.1c00896. PubMed DOI
Mizukami W.; Mitarai K.; Nakagawa Y. O.; Yamamoto T.; Yan T.; Ohnishi Y. y. Orbital optimized unitary coupled cluster theory for quantum computer. Phys. Rev. Res. 2020, 2, 033421.10.1103/physrevresearch.2.033421. DOI
Yalouz S.; Senjean B.; Günther J.; Buda F.; O’Brien T. E.; Visscher L. A state-averaged orbital-optimized hybrid quantum–classical algorithm for a democratic description of ground and excited states. Quantum Sci. Technol. 2021, 6, 024004.10.1088/2058-9565/abd334. DOI
de Gracia Triviño J. A.; Delcey M. G.; Wendin G. Complete Active Space Methods for NISQ Devices: The Importance of Canonical Orbital Optimization for Accuracy and Noise Resilience. J. Chem. Theory Comput. 2023, 19, 2863–2872. 10.1021/acs.jctc.3c00123. PubMed DOI PMC
Fitzpatrick A.; Nykänen A.; Talarico N. W.; Lunghi A.; Maniscalco S.; García-Pérez G.; Knecht S.. A self-consistent field approach for the variational quantum eigensolver: orbital optimization goes adaptive. arXiv 2022, arXiv:2212.11405.10.48550/arXiv.2212.11405, quant-ph, submitted Dec 21, 2022. https://arxiv.org/abs/2212.11405 (accessed Dec 28, 2023). PubMed DOI
Helgaker T.; Jørgensen P.; Olsen J.. Molecular Electronic Structure Theory; John Wiley & Sons, LTD: Chichester, 2000.
Sun Q.; Yang J.; Chan G. K.-L. A general second order complete active space self-consistent-field solver for large-scale systems. Chem. Phys. Lett. 2017, 683, 291–299. 10.1016/j.cplett.2017.03.004. DOI
Levine D. S.; Hait D.; Tubman N. M.; Lehtola S.; Whaley K. B.; Head-Gordon M. CASSCF with Extremely Large Active Spaces Using the Adaptive Sampling Configuration Interaction Method. J. Chem. Theory Comput. 2020, 16, 2340–2354. 10.1021/acs.jctc.9b01255. PubMed DOI
Pozun Z. D.; Su X.; Jordan K. D. Establishing the Ground State of the Disjoint Diradical Tetramethyleneethane with Quantum Monte Carlo. J. Am. Chem. Soc. 2013, 135, 13862–13869. 10.1021/ja406002n. PubMed DOI
Dunning T. H. Gaussian Basis Sets for use in Correlated Molecular Calculations. I. The Atoms Boron Through Neon and Hydrogen. J. Chem. Phys. 1989, 90, 1007–1023. 10.1063/1.456153. DOI
Stein C. J.; Reiher M. Automated Selection of Active Orbital Spaces. J. Chem. Theory Comput. 2016, 12, 1760–1771. 10.1021/acs.jctc.6b00156. PubMed DOI
Veis L.; Pittner J. Quantum computing applied to calculations of molecular energies: CH2 benchmark. J. Chem. Phys. 2010, 133, 194106.10.1063/1.3503767. PubMed DOI
Veis L.; Višňák J.; Fleig T.; Knecht S.; Saue T.; Visscher L.; Pittner J. Relativistic quantum chemistry on quantum computers. Phys. Rev. A: At., Mol., Opt. Phys. 2012, 85, 030304.10.1103/PhysRevA.85.030304. DOI
Veis L.; Pittner J. Adiabatic state preparation study of methylene. J. Chem. Phys. 2014, 140, 214111.10.1063/1.4880755. PubMed DOI
Neese F. The ORCA program system. Wiley Interdiscip. Rev.: Comput. Mol. Sci. 2012, 2, 73–78. 10.1002/wcms.81. DOI
Pernal K.; Hapka M.; Przybytek M.; Modrzejewski M.; Sokół A.. GammCor code. https://github.com/pernalk/GAMMCOR (accessed Dec 28, 2023).
Brabec J.; Brandejs J.; Kowalski K.; Xantheas S.; Legeza Ö.; Veis L. Massively parallel quantum chemical density matrix renormalization group method. J. Comput. Chem. 2020, 42, 534–544. 10.1002/jcc.26476. PubMed DOI
Qiskit Contributors . Qiskit: An Open-source Framework for Quantum Computing, 2023.
Bravyi S.; Gambetta J. M.; Mezzacapo A.; Temme K.. Tapering off qubits to simulate fermionic Hamiltonians. arXiv 2017, arXiv:1701.08213.10.48550/arXiv.1701.08213, quant-ph, submitted Jan 27, 2017. https://arxiv.org/abs/1701.08213 (accessed Dec 28, 2023). DOI
Setia K.; Chen R.; Rice J. E.; Mezzacapo A.; Pistoia M.; Whitfield J. D. Reducing Qubit Requirements for Quantum Simulations Using Molecular Point Group Symmetries. J. Chem. Theory Comput. 2020, 16, 6091–6097. 10.1021/acs.jctc.0c00113. PubMed DOI
Veis L.; Antalík A.; Legeza Ö.; Alavi A.; Pittner J. The Intricate Case of Tetramethyleneethane: A Full Configuration Interaction Quantum Monte Carlo Benchmark and Multireference Coupled Cluster Studies. J. Chem. Theory Comput. 2018, 14, 2439–2445. 10.1021/acs.jctc.8b00022. PubMed DOI
Clifford E. P.; Wenthold P. G.; Lineberger W. C.; Ellison G. B.; Wang C. X.; Grabowski J. J.; Vila F.; Jordan K. D. Properties of tetramethyleneethane (TME) as revealed by ion chemistry and ion photoelectron spectroscopy. J. Chem. Soc., Perkin Trans. 2 1998, 1015–1022. 10.1039/a707322d. DOI
Beran P.; Pernal K.; Pavošević F.; Veis L. Projection-Based Density Matrix Renormalization Group in Density Functional Theory Embedding. J. Phys. Chem. Lett. 2023, 14, 716–722. 10.1021/acs.jpclett.2c03298. PubMed DOI PMC
Rossmannek M.; Pavošević F.; Rubio A.; Tavernelli I. Quantum Embedding Method for the Simulation of Strongly Correlated Systems on Quantum Computers. J. Phys. Chem. Lett. 2023, 14, 3491–3497. 10.1021/acs.jpclett.3c00330. PubMed DOI