1
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Olarte Hernandez R, Champagne B, Soldera A. Simulating Vibronic Spectra by Direct Application of Doktorov Formulas on a Superconducting Quantum Simulator. J Phys Chem A 2024; 128:4369-4377. [PMID: 38751235 DOI: 10.1021/acs.jpca.4c01234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/31/2024]
Abstract
In this work, a direct quantum implementation of the Doktorov formulas for calculating the vibronic spectrum of molecules under the harmonic approximation is presented. It is applied to the three-atom molecules H2O, SO2, ClO2, HS2, and ZnOH. The method solves the classically hard problem of estimating the Franck-Condon (FC) factors by using the Duschinsky matrices as the only input via the Doktorov quantum circuit. This has the advantage of avoiding basis changes, artificial squeezing parameters, and symmetry dependencies. In other words, it is a general method for three-atom molecules that can easily be generalized to bigger molecules. The results are compared with other quantum algorithms and classical anharmonic algorithms. Furthermore, the circuit requirements are studied in order to estimate its applicability on real superconducting quantum hardware.
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Affiliation(s)
- Renato Olarte Hernandez
- Theoretical Chemistry Lab, Unit of Theoretical and Structural Physical Chemistry, Namur Institute of Structured Matter, University of Namur, rue de Bruxelles 61, B-5000 Namur, Belgium
- Laboratory of Physical Chemistry of Matter, Department of Chemistry, Université de Sherbrooke, Sherbrooke, QC J1K 2R1, Canada
| | - Benoît Champagne
- Theoretical Chemistry Lab, Unit of Theoretical and Structural Physical Chemistry, Namur Institute of Structured Matter, University of Namur, rue de Bruxelles 61, B-5000 Namur, Belgium
| | - Armand Soldera
- Laboratory of Physical Chemistry of Matter, Department of Chemistry, Université de Sherbrooke, Sherbrooke, QC J1K 2R1, Canada
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2
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Bruschi M, Gallina F, Fresch B. A Quantum Algorithm from Response Theory: Digital Quantum Simulation of Two-Dimensional Electronic Spectroscopy. J Phys Chem Lett 2024; 15:1484-1492. [PMID: 38295347 DOI: 10.1021/acs.jpclett.3c03499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2024]
Abstract
Multidimensional optical spectroscopies are powerful techniques to investigate energy transfer pathways in natural and artificial systems. Because of the high information content of the spectra, numerical simulations of the optical response are of primary importance to assist the interpretation of spectral features. However, the increasing complexity of the investigated systems and their quantum dynamics call for the development of novel simulation strategies. In this work, we consider using digital quantum computers. By combining quantum dynamical simulation and nonlinear response theory, we present a quantum algorithm for computing the optical response of molecular systems. The quantum advantage stems from the efficient quantum simulation of the dynamics governed by the molecular Hamiltonian, and it is demonstrated by explicitly considering exciton-vibrational coupling. The protocol is tested on a near-term quantum device, providing the digital quantum simulation of the linear and nonlinear response of simple molecular models.
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Affiliation(s)
- Matteo Bruschi
- Dipartimento di Scienze Chimiche, Università degli Studi di Padova, via Marzolo 1, Padua 35131, Italy
| | - Federico Gallina
- Dipartimento di Scienze Chimiche, Università degli Studi di Padova, via Marzolo 1, Padua 35131, Italy
| | - Barbara Fresch
- Dipartimento di Scienze Chimiche, Università degli Studi di Padova, via Marzolo 1, Padua 35131, Italy
- Padua Quantum Technologies Research Center, Università degli Studi di Padova, via Gradenigo 6/A, Padua 35131, Italy
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3
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MacDonell RJ, Navickas T, Wohlers-Reichel TF, Valahu CH, Rao AD, Millican MJ, Currington MA, Biercuk MJ, Tan TR, Hempel C, Kassal I. Predicting molecular vibronic spectra using time-domain analog quantum simulation. Chem Sci 2023; 14:9439-9451. [PMID: 37712022 PMCID: PMC10498668 DOI: 10.1039/d3sc02453a] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Accepted: 08/09/2023] [Indexed: 09/16/2023] Open
Abstract
Spectroscopy is one of the most accurate probes of the molecular world. However, predicting molecular spectra accurately is computationally difficult because of the presence of entanglement between electronic and nuclear degrees of freedom. Although quantum computers promise to reduce this computational cost, existing quantum approaches rely on combining signals from individual eigenstates, an approach whose cost grows exponentially with molecule size. Here, we introduce a method for scalable analog quantum simulation of molecular spectroscopy: by performing simulations in the time domain, the number of required measurements depends on the desired spectral range and resolution, not molecular size. Our approach can treat more complicated molecular models than previous ones, requires fewer approximations, and can be extended to open quantum systems with minimal overhead. We present a direct mapping of the underlying problem of time-domain simulation of molecular spectra to the degrees of freedom and control fields available in a trapped-ion quantum simulator. We experimentally demonstrate our algorithm on a trapped-ion device, exploiting both intrinsic electronic and motional degrees of freedom, showing excellent quantitative agreement for a single-mode vibronic photoelectron spectrum of SO2.
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Affiliation(s)
- Ryan J MacDonell
- School of Chemistry, University of Sydney NSW 2006 Australia
- ARC Centre of Excellence for Engineered Quantum Systems, University of Sydney NSW 2006 Australia
- University of Sydney Nano Institute, University of Sydney NSW 2006 Australia
| | - Tomas Navickas
- School of Physics, University of Sydney NSW 2006 Australia
- ARC Centre of Excellence for Engineered Quantum Systems, University of Sydney NSW 2006 Australia
| | - Tim F Wohlers-Reichel
- School of Physics, University of Sydney NSW 2006 Australia
- ARC Centre of Excellence for Engineered Quantum Systems, University of Sydney NSW 2006 Australia
| | - Christophe H Valahu
- School of Physics, University of Sydney NSW 2006 Australia
- ARC Centre of Excellence for Engineered Quantum Systems, University of Sydney NSW 2006 Australia
| | - Arjun D Rao
- School of Physics, University of Sydney NSW 2006 Australia
- ARC Centre of Excellence for Engineered Quantum Systems, University of Sydney NSW 2006 Australia
| | - Maverick J Millican
- School of Physics, University of Sydney NSW 2006 Australia
- ARC Centre of Excellence for Engineered Quantum Systems, University of Sydney NSW 2006 Australia
| | | | - Michael J Biercuk
- School of Physics, University of Sydney NSW 2006 Australia
- ARC Centre of Excellence for Engineered Quantum Systems, University of Sydney NSW 2006 Australia
| | - Ting Rei Tan
- School of Physics, University of Sydney NSW 2006 Australia
- ARC Centre of Excellence for Engineered Quantum Systems, University of Sydney NSW 2006 Australia
| | - Cornelius Hempel
- School of Physics, University of Sydney NSW 2006 Australia
- ARC Centre of Excellence for Engineered Quantum Systems, University of Sydney NSW 2006 Australia
- ETH Zurich-PSI Quantum Computing Hub, Laboratory for Nano and Quantum Technologies (LNQ), Paul Scherrer Institut 5232 Villigen Switzerland
| | - Ivan Kassal
- School of Chemistry, University of Sydney NSW 2006 Australia
- ARC Centre of Excellence for Engineered Quantum Systems, University of Sydney NSW 2006 Australia
- University of Sydney Nano Institute, University of Sydney NSW 2006 Australia
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4
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Pyrkov A, Aliper A, Bezrukov D, Lin YC, Polykovskiy D, Kamya P, Ren F, Zhavoronkov A. Quantum computing for near-term applications in generative chemistry and drug discovery. Drug Discov Today 2023; 28:103675. [PMID: 37331692 DOI: 10.1016/j.drudis.2023.103675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 05/22/2023] [Accepted: 06/13/2023] [Indexed: 06/20/2023]
Abstract
In recent years, drug discovery and life sciences have been revolutionized with machine learning and artificial intelligence (AI) methods. Quantum computing is touted to be the next most significant leap in technology; one of the main early practical applications for quantum computing solutions is predicted to be in quantum chemistry simulations. Here, we review the near-term applications of quantum computing and their advantages for generative chemistry and highlight the challenges that can be addressed with noisy intermediate-scale quantum (NISQ) devices. We also discuss the possible integration of generative systems running on quantum computers into established generative AI platforms.
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Affiliation(s)
- Alexey Pyrkov
- Insilico Medicine Hong Kong Ltd, Pak Shek Kok, New Territories, Hong Kong.
| | - Alex Aliper
- Insilico Medicine AI Ltd, Masdar City, Abu Dhabi, United Arab Emirates
| | - Dmitry Bezrukov
- Insilico Medicine Hong Kong Ltd, Pak Shek Kok, New Territories, Hong Kong
| | - Yen-Chu Lin
- Insilico Medicine Taiwan Ltd, Taipei, Taiwan
| | | | | | - Feng Ren
- Insilico Medicine Shanghai Ltd, Shanghai, China
| | - Alex Zhavoronkov
- Insilico Medicine Hong Kong Ltd, Pak Shek Kok, New Territories, Hong Kong
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5
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Excited-state molecular dynamics simulation based on variational quantum algorithms. Chem Phys Lett 2023. [DOI: 10.1016/j.cplett.2023.140404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/27/2023]
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6
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Cordier BA, Sawaya NPD, Guerreschi GG, McWeeney SK. Biology and medicine in the landscape of quantum advantages. J R Soc Interface 2022; 19:20220541. [PMID: 36448288 PMCID: PMC9709576 DOI: 10.1098/rsif.2022.0541] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
Abstract
Quantum computing holds substantial potential for applications in biology and medicine, spanning from the simulation of biomolecules to machine learning methods for subtyping cancers on the basis of clinical features. This potential is encapsulated by the concept of a quantum advantage, which is contingent on a reduction in the consumption of a computational resource, such as time, space or data. Here, we distill the concept of a quantum advantage into a simple framework to aid researchers in biology and medicine pursuing the development of quantum applications. We then apply this framework to a wide variety of computational problems relevant to these domains in an effort to (i) assess the potential of practical advantages in specific application areas and (ii) identify gaps that may be addressed with novel quantum approaches. In doing so, we provide an extensive survey of the intersection of biology and medicine with the current landscape of quantum algorithms and their potential advantages. While we endeavour to identify specific computational problems that may admit practical advantages throughout this work, the rapid pace of change in the fields of quantum computing, classical algorithms and biological research implies that this intersection will remain highly dynamic for the foreseeable future.
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Affiliation(s)
- Benjamin A. Cordier
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, OR 97202, USA
| | | | | | - Shannon K. McWeeney
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, OR 97202, USA,Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97202, USA,Oregon Clinical and Translational Research Institute, Oregon Health and Science University, Portland, OR 97202, USA
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7
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Wang Y, Ren J, Li W, Shuai Z. Hybrid Quantum-Classical Boson Sampling Algorithm for Molecular Vibrationally Resolved Electronic Spectroscopy with Duschinsky Rotation and Anharmonicity. J Phys Chem Lett 2022; 13:6391-6399. [PMID: 35802770 DOI: 10.1021/acs.jpclett.2c01475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Using a photonic quantum computer for boson sampling has demonstrated a tremendous advantage over classical supercomputers. It is highly desirable to develop boson sampling algorithms for realistic scientific problems. In this work, we propose a hybrid quantum-classical sampling (HQCS) algorithm to calculate the optical spectrum for complex molecules considering Duschinsky rotation effects and anharmonicity. The classical sum-over-states method for this problem has a computational complexity that exponentially increases with system size. The HQCS algorithm creates an intermediate harmonic potential energy surface (PES) to bridge the initial and final PESs. The magnitude and sign of the overlap between the initial and the intermediate state are estimated by boson sampling and classical algorithms, respectively. The overlap between the intermediate and the final state is efficiently evaluated by classical algorithms. The feasibility of HQCS is demonstrated in calculations of the emission spectrum of a Morse model as well as the pyridine molecule.
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Affiliation(s)
- Yuanheng Wang
- MOE Key Laboratory of Organic OptoElectronics and Molecular Engineering, Department of Chemistry, Tsinghua University, Beijing 100084, People's Republic of China
| | - Jiajun Ren
- MOE Key Laboratory of Organic OptoElectronics and Molecular Engineering, Department of Chemistry, Tsinghua University, Beijing 100084, People's Republic of China
| | - Weitang Li
- MOE Key Laboratory of Organic OptoElectronics and Molecular Engineering, Department of Chemistry, Tsinghua University, Beijing 100084, People's Republic of China
| | - Zhigang Shuai
- MOE Key Laboratory of Organic OptoElectronics and Molecular Engineering, Department of Chemistry, Tsinghua University, Beijing 100084, People's Republic of China
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8
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Motta M, Rice JE. Emerging quantum computing algorithms for quantum chemistry. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2022. [DOI: 10.1002/wcms.1580] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Affiliation(s)
- Mario Motta
- IBM Quantum, IBM Research‐Almaden San Jose California USA
| | - Julia E. Rice
- IBM Quantum, IBM Research‐Almaden San Jose California USA
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9
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Lee CK, Zhong Lau JW, Shi L, Kwek LC. Simulating Energy Transfer in Molecular Systems with Digital Quantum Computers. J Chem Theory Comput 2022; 18:1347-1358. [PMID: 35192771 DOI: 10.1021/acs.jctc.1c01296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Quantum computers have the potential to simulate chemical systems beyond the capability of classical computers. Recent developments in hybrid quantum-classical approaches enable the determinations of the ground or low energy states of molecular systems. Here, we extend near-term quantum simulations of chemistry to time-dependent processes by simulating energy transfer in organic semiconducting molecules. We developed a multiscale modeling workflow that combines conventional molecular dynamics and quantum chemistry simulations with hybrid variational quantum algorithm to compute the exciton dynamics in both the single excitation subspace (i.e., Frenkel Hamiltonian) and the full-Hilbert space (i.e., multiexciton) regimes. Our numerical examples demonstrate the feasibility of our approach, and simulations on IBM Q devices capture the qualitative behaviors of exciton dynamics, but with considerable errors. We present an error mitigation technique that combines experimental results from the variational and Trotter algorithms, and obtain significantly improved quantum dynamics. Our approach opens up new opportunities for modeling quantum dynamics in chemical, biological, and material systems with quantum computers.
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Affiliation(s)
- Chee-Kong Lee
- Tencent America, Palo Alto, California 94306, United States
| | | | - Liang Shi
- Chemistry and Biochemistry, University of California, Merced, California 95343, United States
| | - Leong Chuan Kwek
- Centre for Quantum Technologies, National University of Singapore, 117543, Singapore.,National Institute of Education, Nanyang Technological University, 1 Nanyang Walk, Singapore 637616.,MajuLab, CNRS-UNS-NUS-NTU International Joint Research Unit, UMI 3654, Singapore
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10
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Aroeira GJR, Davis MM, Turney JM, Schaefer HF. Fermi.jl: A Modern Design for Quantum Chemistry. J Chem Theory Comput 2022; 18:677-686. [PMID: 34978451 DOI: 10.1021/acs.jctc.1c00719] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Approximating molecular wave functions involves heavy numerical effort; therefore, codes for such tasks are written completely or partially in efficient languages such as C, C++, and Fortran. While these tools are dominant throughout quantum chemistry packages, the efficient development of new methods is often hindered by the complexity associated with code development. In order to ameliorate this scenario, some software packages take a dual approach where a simpler, higher-level language, such as Python, substitutes the traditional ones wherever performance is not critical. Julia is a novel, dynamically typed, programming language that aims to solve this two-language problem. It gained attention because of its modern and intuitive design, while still being highly optimized to compete with "low-level" languages. Recently, some chemistry-related projects have emerged exploring the capabilities of Julia. Herein, we introduce the quantum chemistry package Fermi.jl, which contains the first implementations of post-Hartree-Fock methods written in Julia. Its design makes use of many Julia core features, including multiple dispatch, metaprogramming, and interactive usage. Fermi.jl is a modular package, where new methods and implementations can be easily added to the existing code. Furthermore, it is designed to maximize code reusability by relying on general functions with specialized methods for particular cases. The feasibility of the project is explored through evaluating the performance of popular ab initio methods. It is our hope that this project motivates the usage of Julia within the community and brings new contributions into Fermi.jl.
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Affiliation(s)
- Gustavo J R Aroeira
- Center for Computational Quantum Chemistry, University of Georgia, Athens, Georgia 30602, United States
| | - Matthew M Davis
- Center for Computational Quantum Chemistry, University of Georgia, Athens, Georgia 30602, United States
| | - Justin M Turney
- Center for Computational Quantum Chemistry, University of Georgia, Athens, Georgia 30602, United States
| | - Henry F Schaefer
- Center for Computational Quantum Chemistry, University of Georgia, Athens, Georgia 30602, United States
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11
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Lee CK, Hsieh CY, Zhang S, Shi L. Simulation of Condensed-Phase Spectroscopy with Near-Term Digital Quantum Computers. J Chem Theory Comput 2021; 17:7178-7186. [PMID: 34648713 DOI: 10.1021/acs.jctc.1c00849] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Spectroscopy is an indispensable tool for understanding the structures and dynamics of molecular systems. However, computational modeling of spectroscopy is challenging due to the exponential scaling of computational complexity with system sizes unless drastic approximations are made. Quantum computers could potentially overcome these classically intractable computational tasks, but the existing approaches using quantum computers to simulate spectroscopy can only handle isolated and static molecules. In this work, we develop a workflow that combines multi-scale modeling and a time-dependent variational quantum algorithm to compute the linear spectroscopy of systems interacting with their condensed-phase environment via the relevant time correlation function. We demonstrate the feasibility of our approach by numerically simulating the UV-vis absorption spectra of organic semiconductors. We show that our dynamical approach captures several spectral features that are otherwise overlooked by static methods. Our method can be directly used for other linear condensed-phase spectroscopy and could potentially be extended to nonlinear multi-dimensional spectroscopy.
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Affiliation(s)
- Chee-Kong Lee
- Tencent America, Palo Alto, California 94306, United States
| | | | | | - Liang Shi
- Chemistry and Biochemistry, University of California, Merced, Merced, California 95343, United States
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12
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MacDonell RJ, Dickerson CE, Birch CJT, Kumar A, Edmunds CL, Biercuk MJ, Hempel C, Kassal I. Analog quantum simulation of chemical dynamics. Chem Sci 2021; 12:9794-9805. [PMID: 34349953 PMCID: PMC8293981 DOI: 10.1039/d1sc02142g] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Accepted: 06/14/2021] [Indexed: 11/21/2022] Open
Abstract
Ultrafast chemical reactions are difficult to simulate because they involve entangled, many-body wavefunctions whose computational complexity grows rapidly with molecular size. In photochemistry, the breakdown of the Born-Oppenheimer approximation further complicates the problem by entangling nuclear and electronic degrees of freedom. Here, we show that analog quantum simulators can efficiently simulate molecular dynamics using commonly available bosonic modes to represent molecular vibrations. Our approach can be implemented in any device with a qudit controllably coupled to bosonic oscillators and with quantum hardware resources that scale linearly with molecular size, and offers significant resource savings compared to digital quantum simulation algorithms. Advantages of our approach include a time resolution orders of magnitude better than ultrafast spectroscopy, the ability to simulate large molecules with limited hardware using a Suzuki-Trotter expansion, and the ability to implement realistic system-bath interactions with only one additional interaction per mode. Our approach can be implemented with current technology; e.g., the conical intersection in pyrazine can be simulated using a single trapped ion. Therefore, we expect our method will enable classically intractable chemical dynamics simulations in the near term.
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Affiliation(s)
- Ryan J MacDonell
- School of Chemistry, University of Sydney NSW 2006 Australia
- University of Sydney Nano Institute, University of Sydney NSW 2006 Australia
| | - Claire E Dickerson
- School of Chemistry, University of Sydney NSW 2006 Australia
- School of Physics, University of Sydney NSW 2006 Australia
- ARC Centre of Excellence for Engineered Quantum Systems, University of Sydney NSW 2006 Australia
- University of Sydney Nano Institute, University of Sydney NSW 2006 Australia
| | - Clare J T Birch
- School of Chemistry, University of Sydney NSW 2006 Australia
- University of Sydney Nano Institute, University of Sydney NSW 2006 Australia
| | - Alok Kumar
- Department of Chemistry, Indian Institute of Technology Bombay Mumbai 400076 India
| | - Claire L Edmunds
- School of Physics, University of Sydney NSW 2006 Australia
- ARC Centre of Excellence for Engineered Quantum Systems, University of Sydney NSW 2006 Australia
| | - Michael J Biercuk
- School of Physics, University of Sydney NSW 2006 Australia
- ARC Centre of Excellence for Engineered Quantum Systems, University of Sydney NSW 2006 Australia
| | - Cornelius Hempel
- School of Physics, University of Sydney NSW 2006 Australia
- ARC Centre of Excellence for Engineered Quantum Systems, University of Sydney NSW 2006 Australia
- University of Sydney Nano Institute, University of Sydney NSW 2006 Australia
| | - Ivan Kassal
- School of Chemistry, University of Sydney NSW 2006 Australia
- University of Sydney Nano Institute, University of Sydney NSW 2006 Australia
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13
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Jahangiri S, Arrazola JM, Delgado A. Quantum Algorithm for Simulating Single-Molecule Electron Transport. J Phys Chem Lett 2021; 12:1256-1261. [PMID: 33497214 DOI: 10.1021/acs.jpclett.0c03724] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
An accurate description of electron transport at a molecular level requires a precise treatment of quantum effects. These effects play a crucial role in determining the electron transport properties of single molecules, which can be challenging to simulate classically. Here we introduce a quantum algorithm to efficiently calculate electronic current through single-molecule junctions in the weak-coupling regime. We show that a quantum computer programmed to simulate vibronic transitions between different charge states of a molecule can be used to compute electron-transfer rates and electronic current. In the harmonic approximation, the algorithm can be implemented using Gaussian boson sampling devices, which are a near-term platform for photonic quantum computing. We apply the algorithm to simulate the current and conductance of a magnesium porphine molecule. The algorithm provides a means for better understanding the mechanism of electron transport at a molecular level, which paves the way for building practical molecular electronic devices.
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14
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Bauer B, Bravyi S, Motta M, Chan GKL. Quantum Algorithms for Quantum Chemistry and Quantum Materials Science. Chem Rev 2020; 120:12685-12717. [DOI: 10.1021/acs.chemrev.9b00829] [Citation(s) in RCA: 134] [Impact Index Per Article: 33.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Affiliation(s)
- Bela Bauer
- Microsoft Quantum, Station Q, University of California
, Santa Barbara, California 93106, United States
| | - Sergey Bravyi
- IBM Quantum, IBM T. J. Watson Research Center
, Yorktown Heights, New York 10598, United States
| | - Mario Motta
- IBM Quantum, IBM Research Almaden
, San Jose, California 95120, United States
| | - Garnet Kin-Lic Chan
- Division of Chemistry and Chemical Engineering, California Institute of Technology
, Pasadena, California 91125, United States
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15
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Jahangiri S, Arrazola JM, Quesada N, Delgado A. Quantum algorithm for simulating molecular vibrational excitations. Phys Chem Chem Phys 2020; 22:25528-25537. [DOI: 10.1039/d0cp03593a] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
We introduce a quantum algorithm for simulating molecular vibrational excitations during vibronic transitions. The algorithm is used to simulate vibrational excitations of pyrrole and butane during photochemical and mechanochemical excitations.
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