Article
Physics, Multidisciplinary
Andrew Zhao, Nicholas C. Rubin, Akimasa Miyake
Summary: The proposed tomographic protocol estimates any k-body reduced density matrix of an n-mode fermionic state using a sampling method with randomized measurement settings generated by fermionic Gaussian unitaries. Numerical calculations demonstrate that the protocol offers a substantial improvement in constant overheads for k >= 2 compared to prior deterministic strategies. The method can also be adapted for particle-number symmetry with an option to reduce additional circuit depth at the cost of increased repetitions.
PHYSICAL REVIEW LETTERS
(2021)
Article
Optics
Stefano Polla, Gian-Luca R. Anselmetti, Thomas E. O'Brien
Summary: This article discusses a quantum computation that only extracts one bit of information per N-qubit quantum state preparation, which is relevant for error mitigation schemes. The estimation of the expectation value of an operator is optimized by decomposing it into bitwise-measurable terms. It is proven that optimal decompositions must involve reflections with eigenvalues of ±1. The optimal reflection decomposition of a fast-forwardable operator is found, demonstrating a numerical improvement over a simple Pauli decomposition by a factor of N^0.7.
Article
Quantum Science & Technology
Tatiana A. Bespalova, Oleksandr Kyriienko
Summary: The Hamiltonian operator approximation (HOA) is proposed as a method to approximate the Hamiltonian operator using a sum of propagators, benefiting analog quantum simulators. This approach is utilized in the hybrid quantum-classical workflow for energy measurements and shows promise in preparing ground states of complex material science models. The HOA method is found to outperform variational methods for systems with increasing size, especially for noisy large-scale quantum devices.
Review
Physics, Multidisciplinary
Jules Tilly, Hongxiang Chen, Shuxiang Cao, Dario Picozzi, Kanav Setia, Ying Li, Edward Grant, Leonard Wossnig, Ivan Rungger, George H. Booth, Jonathan Tennyson
Summary: The variational quantum eigensolver (VQE) is a method used to compute the ground state energy of a Hamiltonian, which is important in quantum chemistry and condensed matter physics. It has the advantage of being able to model complex wavefunctions in polynomial time, making it a promising application for quantum computing. However, there are still many open questions regarding optimization, quantum noise, and other challenges, which require further research and exploration.
PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS
(2022)
Article
Quantum Science & Technology
Lana Mineh, Ashley Montanaro
Summary: This paper details the research on running multiple small circuits simultaneously on the Rigetti Aspen-M-1 device. By utilizing error mitigation techniques, it demonstrates the real-time speedup achieved by parallelization on current quantum hardware, with an 18x speedup for exploring the VQE energy landscape and more than 8x speedup for running VQE optimization.
QUANTUM SCIENCE AND TECHNOLOGY
(2023)
Article
Chemistry, Physical
Ilya G. Ryabinkin, Andrew J. Jena, Scott N. Genin
Summary: We propose an efficient method for constructing a fully anticommutative set of Pauli generators from a commutative set of operators composed exclusively of purely X generators. The method involves using Gauss-Jordan elimination on a binary matrix encoding the X generators to reduce it to row-echelon form, followed by a modified Jordan-Wigner transformation to construct an anticommutative system in a standard basis. The resulting anticommutative sets are then used for the qubit coupled cluster Ansatz and applied to calculations of ground-state potential energy curves for molecular systems.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2023)
Article
Physics, Multidisciplinary
Qing Guo, Ping-Xing Chen
Summary: Accurately calculating molecular energy spectra is crucial in various applied fields, and the VQE-UCC algorithm shows promise in performing such calculations on noisy intermediate scale quantum computers. However, limitations in the number of qubits and coherent time in quantum computers require reducing the complexity of the VQE-UCC algorithm, which our new method addresses by leveraging system symmetry to calculate molecular ground states effectively. This approach has successfully obtained ground and excited states of four different molecules and holds significant implications for advancing quantum chemical simulations.
FRONTIERS IN PHYSICS
(2021)
Article
Optics
Donghwa Lee, Jinil Lee, Seongjin Hong, Hyang-Tag Lim, Young-Wook Cho, Sang-Wook Han, Hyundong Shin, Junaid Ur Rehman, Yong-Su Kim
Summary: Variational quantum algorithms, a representative class of modern quantum algorithms, offer practical uses of near-term quantum processors. This study presents an alternative approach to increase the Hilbert space by utilizing multiple degrees of freedom in individual quantum systems. They experimentally implement a variational quantum eigensolver (VQE) using four-dimensional photonic quantum states and employ a quantum error mitigation protocol to reduce noise effects. Their photonic VQE accurately estimates the bond dissociation curve of the He - H+ cation, even in the presence of large noise in the quantum processing unit. The study also discusses potential resource-efficient enhancements in photonic quantum processors.
Article
Physics, Applied
Ayush Asthana, Chenxu Liu, Oinam Romesh Meitei, Sophia E. Economou, Edwin Barnes, Nicholas J. Mayhall
Summary: Quantum simulation on noisy intermediate-scale quantum devices is limited by short qubit coherence times. Ctrl-VQE algorithm eliminates parameterized quantum circuits and reduces state preparation times. Leakage outside computational subspace speeds up state preparation due to an enlarged solution space and additional channels connecting initial and target states.
PHYSICAL REVIEW APPLIED
(2023)
Article
Materials Science, Multidisciplinary
Jan Lukas Bosse, Ashley Montanaro
Summary: In this study, the variational quantum eigensolver (VQE) is proposed to find the ground state of the antiferromagnetic Heisenberg model on the kagome lattice (KAFH) on a quantum computer. The expressiveness and scaling of the ansatz circuits are investigated through classical simulations. The results show that, except for a specific lattice configuration, the fidelity with the ground state approaches one exponentially with the circuit depth, indicating the potential achievability of representing the ground state of KAFH on inaccessible lattices using VQE circuits on near-term quantum hardware.
Article
Chemistry, Multidisciplinary
Ivana Mihalikova, Matej Pivoluska, Martin Plesch, Martin Friak, Daniel Nagaj, Mojmir Sob
Summary: New approaches in computational quantum chemistry are being developed using quantum computing, although current quantum resources are noisy and scarce. The study focuses on how errors affect the VQE algorithm and how to efficiently utilize available resources for precise computational results.
Article
Chemistry, Physical
Tim Weaving, Alexis Ralli, William M. Kirby, Andrew Tranter, Peter J. Love, Peter Coveney
Summary: Quantum chemistry is a promising application for quantum computers, but currently there is a lack of solutions to important scientific problems. Algorithmic advances are needed to fully utilize available low-precision quantum computers. We propose a method called Contextual Subspace VQE (CS-VQE) to estimate ground state energy, which involves partitioning the molecular Hamiltonian into noncontextual and contextual components. However, there are obstacles to deploying CS-VQE on low-precision devices, particularly in relation to the ansatz, a parametrized quantum state used in the optimization process. We propose a noncontextual projection approach that enables successful implementation of CS-VQE on low-precision devices.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2023)
Article
Quantum Science & Technology
Zi-Jian Zhang, Thi Ha Kyaw, Jakob S. Kottmann, Matthias Degroote, Alan Aspuru-Guzik
Summary: This work presents a method for constructing reduced-size entangler pools leveraging classical algorithms, which ranks and screens entanglers based on mutual information between qubits in classically approximated ground state. Numerical experiments demonstrate that a reduced entangler pool can achieve the same numerical accuracy as the original pool, paving a new way for adaptive construction of ansatz circuits in variational quantum algorithms.
QUANTUM SCIENCE AND TECHNOLOGY
(2021)
Article
Quantum Science & Technology
Yusen Wu, Zigeng Huang, Jinzhao Sun, Xiao Yuan, Jingbo B. Wang, Dingshun Lv
Summary: In this study, a novel framework called OE-VQE is proposed to address the limitations of the conventional VQE method in dealing with strongly correlated systems. By utilizing shallower quantum circuits and gradually expanding the active space, the OE-VQE framework significantly enhances the performance and convergence speed of VQE. Benchmark simulations on small representative molecules validate the effectiveness of the proposed convergence paths, providing a promising avenue for tackling complex molecular systems.
QUANTUM SCIENCE AND TECHNOLOGY
(2023)
Article
Quantum Science & Technology
Seonghoon Choi, Ignacio Loaiza, Artur F. Izmaylov
Summary: Measuring the expectation value of the molecular electronic Hamiltonian can be challenging, but a new method has been introduced to lower the variances of the fragments, reducing the number of measurements required.
Article
Chemistry, Physical
Edward G. Hohenstein, B. Scott Fales, Robert M. Parrish, Todd J. Martinez
Summary: The study presents a quartic-scaling implementation of CCSD based on low-rank tensor hypercontraction (THC) factorizations, which significantly reduces computational complexity and enables accurate correlation energy calculations.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Article
Chemistry, Multidisciplinary
Nanna H. List, Chey M. Jones, Todd J. Martinez
Summary: The study investigates the inherent excited-state behavior of the HBDI- chromophore, resolving competitive decay pathways and factors influencing efficiency and stereochemical outcomes. The research offers new insights into the internal conversion of HBDI- and provides principles for designing chromophore derivatives with improved photoswitching properties.
Article
Chemistry, Physical
Christoph Bannwarth, Todd J. Martinez
Summary: The article presents an approach to unify ab initio and semiempirical electronic structure code paths. By separating the wavefunction ansatz and the matrix representations of operators, the Hamiltonian can refer to either an ab initio or semiempirical treatment. The authors built a semiempirical integral library and interfaced it to the GPU-accelerated electronic structure code TeraChem. This approach enables the combination of semiempirical Hamiltonians with the full functionality of the ab initio electronic structure code.
JOURNAL OF CHEMICAL PHYSICS
(2023)
Article
Chemistry, Physical
Vinicius Wilian D. Cruzeiro, Yuanheng Wang, Elisa Pieri, Edward G. Hohenstein, Todd J. Martinez
Summary: This article introduces how to set up the GPU-accelerated electronic structure program TeraChem as an electronic structure server, which can be easily accessed by third-party client programs. The client interface, called TeraChem protocol buffers (TCPB), has been designed for ease of use and compatibility with multiple programming languages. By incorporating the TCPB client into Amber for QM/MM simulations, significant time savings and speedup have been achieved compared to prior implementations. The practical application of TCPB is demonstrated through the computation of the free energy profile of a model chromophore.
JOURNAL OF CHEMICAL PHYSICS
(2023)
Review
Chemistry, Physical
Umberto Raucci, Hayley Weir, Sukolsak Sakshuwong, Stefan Seritan, Colton B. Hicks, Fabio Vannucci, Francesco Rea, Todd J. Martinez
Summary: This article outlines methods to eliminate the barriers preventing the wider chemistry community from performing quantum chemistry calculations. These methods include GPU-accelerated quantum chemistry in the cloud, AI-driven natural molecule input methods, and extended reality visualization. The article also highlights the exciting applications of these methods in computing and visualizing spectra, 3D structures, molecular orbitals, and other chemical properties.
ANNUAL REVIEW OF PHYSICAL CHEMISTRY
(2023)
Editorial Material
Chemistry, Physical
Michele Ceriotti, Lasse Jensen, David E. Manolopoulos, Todd Martinez, David R. Reichman, Francesco Sciortino, C. David Sherrill, Qiang Shi, Carlos Vega, Lai-Sheng Wang, Emily A. Weiss, Xiaoyang Zhu, Jenny Stein, Tianquan Lian
JOURNAL OF CHEMICAL PHYSICS
(2023)
Article
Chemistry, Physical
David M. G. Williams, Eirik F. Kjonstad, Todd J. Martinez
Summary: It is found that the geometric phase effect is correctly reproduced around defective excited-state conical intersections in coupled cluster theory, indicating that these intersections are local artifacts.
JOURNAL OF CHEMICAL PHYSICS
(2023)
Article
Chemistry, Physical
Soren Holm, Pablo A. Unzueta, Keiran Thompson, Todd J. Martinez
Summary: In this study, a graph neural network model is developed and trained to correct the basis set incompleteness error between a small and large basis set at the RHF and B3LYP levels of theory. The results show that fitting an ML model to correct the BSIE is better at generalizing to systems not seen during training compared to fitting to the total potential. Acceptable performance is achieved when the training data sufficiently resemble the systems one wants to make predictions on.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2023)
Article
Chemistry, Multidisciplinary
Wei-Hai Fang, Todd J. Martinez, Lihong Liu
Summary: Light-driven molecular motors, such as the chiral N-alkyl imines reported by Greb and Lehn, show promising potential in material and biological systems. However, the mechanism of unidirectional rotation in these motors is not fully understood. Through computational study, we find that the location and energetics of conical intersections alone cannot explain the motor's mechanism, and dynamic effects and out-of-plane distortions play a crucial role. Our results provide insights on how to improve the efficiency of photoisomerization in this class of molecular motors.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
(2023)
Article
Optics
Tianyu Wang, Mandar M. Sohoni, Logan G. Wright, Martin M. Stein, Shi-Yuan Ma, Tatsuhiro Onodera, Maxwell G. Anderson, Peter L. McMahon
Summary: A nonlinear optical neural network image sensor based on an image intensifier enables efficient all-optical image encoding for various machine-vision tasks. The nonlinear ONN encoder outperforms linear optical encoders in machine-vision benchmarks, flow-cytometry image classification, and object identification in a 3D printed real scene. This concept allows for a significant reduction in camera resolution and electronic post-processing complexity, and enables image-sensing applications with fewer pixels, photons, higher throughput, and lower latency.
Article
Multidisciplinary Sciences
Y. Liu, D. M. Sanchez, M. R. Ware, E. G. Champenois, J. Yang, J. P. F. Nunes, A. Attar, M. Centurion, J. P. Cryan, R. Forbes, K. Hegazy, M. C. Hoffmann, F. Ji, M. F. Lin, D. Luo, S. K. Saha, X. Shen, X. J. Wang, T. J. Martinez, T. J. A. Wolf
Summary: Combining ultrafast electron diffraction and ab initio dynamics simulations, the authors visualize the structure of a pericyclic minimum, also known as a pericyclic minimum, in real time in a photochemical reaction. Electrocylic reactions involve the simultaneous formation and cleavage of sigma and pi bonds through a cyclic structure. This research provides experimental evidence for the importance of this structure in electrocyclic reactions.
NATURE COMMUNICATIONS
(2023)
Article
Chemistry, Physical
Keiran C. Thompson, Todd J. Martinez
Summary: Scalable numerical solutions to the time dependent Schrodinger equation remain an outstanding goal in theoretical chemistry. Here we present a method which adaptively adjusts a dictionary of basis functions to the dynamics of the system using recent breakthroughs in signal processing. Our results show that for two low-dimensional model problems, the size of the basis set does not grow quickly with time and is weakly dependent on dimensionality. The method primarily utilizes energies and gradients of the potential, suggesting its potential application in on-the-fly ab initio quantum wavepacket dynamics.
Article
Chemistry, Physical
Wenwen Xu, David M. M. Sanchez, Umberto Raucci, Hantao Zhou, Xinning Dong, Mingqiu Hu, Christopher J. J. Bardeen, Todd J. J. Martinez, Ryan C. C. Hayward
Summary: By incorporating diarylethene microcrystals into a polyethylene terephthalate matrix, highly ordered and compliant photomechanical composites with superior performance compared to single crystals are achieved. These composites exhibit rapid response times, sustain a high level of performance over numerous cycles, and generate high work densities.
Article
Chemistry, Multidisciplinary
Rui Xu, Jan Meisner, Alexander M. Chang, Keiran C. Thompson, Todd J. Martinez
Summary: Our recent success in utilizing GPUs to speed up quantum chemistry computations has led to the creation of the ab initio nanoreactor, a computational framework for automatic reaction discovery and kinetic model construction. In this work, we apply the ab initio nanoreactor to study methane pyrolysis, uncovering the elementary reactions through GPU-accelerated simulations and refining the reaction paths using transition state theory. With 53 species and 134 reactions, the kinetic model derived from the discovered reactions is validated against experimental data and literature models. We also demonstrate the effectiveness of local brute force and Monte Carlo sensitivity analysis for identifying important reactions and improving the accuracy of the kinetic model.
Article
Chemistry, Physical
Alexander M. Chang, Jan Meisner, Rui Xu, Todd J. Martinez
Summary: This study examines the effectiveness of using metadynamics, attractive potentials, and local thermostats for accelerating reaction discovery. By constructing different reaction networks, it is found that a combination of accelerating forces is best suited for reaction discovery.
JOURNAL OF PHYSICAL CHEMISTRY A
(2023)
