Article
Physics, Multidisciplinary
Gian-Luca R. Anselmetti, David Wierichs, Christian Gogolin, Robert M. Parrish
Summary: The proposed VQE circuit fabrics have advantageous properties for simulating strongly correlated ground and excited states of molecules and materials. These entangler circuits are expressive even at low depth and parameter count, and may become universal when parameters are sufficiently large and properly initialized, without having to cross regions of vanishing gradient. Optimal four-term parameter shift rules are derived and numerical demonstrations are performed on highly correlated molecules up to 20 qubits.
NEW JOURNAL OF PHYSICS
(2021)
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.
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
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
Ar A. Melnikov, A. A. Termanova, S. Dolgov, F. Neukart, M. R. Perelshtein
Summary: In this study, a method for encoding vectors obtained by sampling analytical functions into quantum circuits is proposed. The method achieves >99.9% accuracy with polynomial runtime relative to the number of qubits, surpassing the fidelity of state-of-the-art two-qubit gates. The method utilizes hardware-efficient variational quantum circuits simulated using tensor networks and matrix product state representation of vectors. Riemannian optimization and auto-gradient calculation are employed to tune variational gates, while a "cut once, measure twice" method is proposed to mitigate barren plateaus during gate updates, with benchmarking conducted on up to 100-qubit circuits. Importantly, the presented approach supports the encoding of any vectors with low-rank structures, not limited to analytical functions. The method is easily implementable on modern quantum hardware and facilitates the use of hybrid-quantum computing architectures.
QUANTUM SCIENCE AND TECHNOLOGY
(2023)
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
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
Physics, Multidisciplinary
Zhimin He, Maijie Deng, Shenggen Zheng, Lvzhou Li, Haozhen Situ
Summary: GSQAS is a graph self-supervised quantum architecture search method that trains a predictor through self-supervised learning. It pre-trains a graph encoder on a large number of unlabeled quantum circuits and then trains a downstream predictor on a small set of labeled circuits. This approach achieves superior performance with fewer labeled circuits.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(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
Multidisciplinary Sciences
C-Y Pan, M. Hao, N. Barraza, E. Solano, F. Albarran-Arriagada
Summary: This work presents a semi-autonomous algorithm using IBM quantum computer to obtain an approximation of eigenvectors of arbitrary Hermitian operator, achieving high fidelities with relatively low resource demands. The algorithm reduces the number of measurements in the system using single-shot measurements and pseudo-random changes handled by a feedback loop. The results show that for both single-qubit and two-qubit observables, high-fidelity eigenvectors can be obtained with a comparatively low number of measurements, which is suitable for current quantum devices.
SCIENTIFIC REPORTS
(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
Multidisciplinary Sciences
Ming Gong, He-Liang Huang, Shiyu Wang, Chu Guo, Shaowei Li, Yulin Wu, Qingling Zhu, Youwei Zhao, Shaojun Guo, Haoran Qian, Yangsen Ye, Chen Zha, Fusheng Chen, Chong Ying, Jiale Yu, Daojin Fan, Dachao Wu, Hong Su, Hui Deng, Hao Rong, Kaili Zhang, Sirui Cao, Jin Lin, Yu Xu, Lihua Sun, Cheng Guo, Na Li, Futian Liang, Akitada Sakurai, Kae Nemoto, William J. Munro, Yong-Heng Huo, Chao-Yang Lu, Cheng-Zhi Peng, Xiaobo Zhu, Jian-Wei Pan
Summary: This study proposes a new method called "quantum neuronal sensing" which utilizes a quantum processor to efficiently classify two different types of many-body phenomena: the ergodic and localized phases of matter. By measuring only one qubit, this method extracts the necessary information and offers better phase resolution than conventional methods. The research demonstrates the feasibility and scalability of quantum neuronal sensing for near-term quantum processors and opens new avenues for exploring quantum many-body phenomena in larger-scale systems.
Article
Quantum Science & Technology
David Amaro, Carlo Modica, Matthias Rosenkranz, Mattia Fiorentini, Marcello Benedetti, Michael Lubasch
Summary: This article introduces a method that utilizes filtering operators to enhance combinatorial optimization efficiency, and explores the application of causal cones to reduce the number of qubits required. Through numerical analysis and experimental validation, the method outperforms traditional algorithms in the context of maximum weighted graph cut problems.
QUANTUM SCIENCE AND TECHNOLOGY
(2022)
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
Vibin Abraham, Nicholas J. Mayhall
Summary: The study introduces a method called cluster MBE for calculating correlation energy in strongly correlated systems by partitioning active space into orbital clusters and utilizing many-body expansion for improved convergence. The method shows more effectiveness in capturing correlation energy compared to traditional approaches.
JOURNAL OF CHEMICAL PHYSICS
(2021)
Article
Physics, Applied
George S. Barron, Bryan T. Gard, Orien J. Altman, Nicholas J. Mayhall, Edwin Barnes, Sophia E. Economou
Summary: Encoding symmetries of the simulated Hamiltonian in the VQE ansatz can reduce classical and quantum resources, and these improvements persist in the presence of noise, as demonstrated through simulations of H2 molecule and a Heisenberg model. Error-mitigation techniques further improve the quality of results.
PHYSICAL REVIEW APPLIED
(2021)
Article
Chemistry, Physical
Vibin Abraham, Nicholas J. Mayhall
Summary: Size extensivity is an important property for many-body methods, but traditional configuration interaction (CI) methods lack this property. Coupled electron pair approximation (CEPA) methods can ensure size extensivity, but they face singularity issues. In this study, we extend the CEPA methods to a new formulation based on tensor product states (TPS) and demonstrate their application in various systems. The results show that the TPS-CEPA method can eliminate singularities and provide improved numerical results.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2022)
Article
Chemistry, Physical
Luke W. Bertels, Harper R. Grimsley, Sophia E. Economou, Edwin Barnes, Nicholas J. Mayhall
Summary: In this study, the impact of symmetry breaking on the performance of ADAPT-VQE is explored using two strongly correlated systems. It is found that improving the energy of the reference states by breaking symmetry has a deleterious effect on ADAPT-VQE.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2022)
Article
Chemistry, Physical
Vikrant Tripathy, Nicholas J. Mayhall, Krishnan Raghavachari
Summary: The article introduces a new method called ONIOM-CT, which addresses the issue of boundary treatment and unbalanced charge distribution in hybrid methods like ONIOM. The method applies a potential in the form of point charges to achieve the desired charge redistribution and has been shown to improve computed reaction energies. Analytic gradients for ONIOM-CT are derived and implemented, and the method is generalized for model systems with multiple link atoms. The improvement of ONIOM-CT over ONIOM is demonstrated for proton transfer reactions using both Mulliken and Lo''wdin population analyses.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2022)
Article
Chemistry, Physical
Harper R. Grimsley, Nicholas J. Mayhall
Summary: The recent quantum information boom has revitalized interest in the unitary coupled cluster (UCC) theory. This paper explores the classical approach of truncating the Taylor series expansion of UCCSD energy at the second order, instead of using perturbative expansion. The approach utilizes derivatives of order three or greater to partially recover the variational lower bound of true UCCSD, simplifying the model by restricting these derivatives. Testing on several potential energy surfaces and reaction energies reveals that this diagonal approximation effectively reduces sensitivity near singularities in strongly correlated regimes without significantly diminishing the accuracy of weakly correlated systems.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2022)
Article
Quantum Science & Technology
Harper R. R. Grimsley, Nicholas J. J. Mayhall, George S. S. Barron, Edwin Barnes, Sophia E. E. Economou
Summary: Variational quantum eigensolvers (VQEs) are powerful hybrid quantum-classical algorithms for calculating molecular energies. However, these methods face numerical issues such as barren plateaus and numerous local minima. In this study, the impact of local minima on the Adaptive, Problem-Tailored Variational Quantum Eiegensolver (ADAPT-VQE) ansatze is investigated. The research finds that the gradient-informed, one-operator-at-a-time circuit construction of ADAPT-VQE provides an effective initialization strategy and allows the algorithm to burrow toward the exact solution even if it converges to a local trap.
NPJ QUANTUM INFORMATION
(2023)
Correction
Quantum Science & Technology
Harper R. R. Grimsley, George S. S. Barron, Edwin Barnes, Sophia E. E. Economou, Nicholas J. J. Mayhall
NPJ QUANTUM INFORMATION
(2023)
Article
Chemistry, Physical
Nicole M. Braunscheidel, Vibin Abraham, Nicholas J. Mayhall
Summary: In a recent paper, a new approach called Tensor Product Selected CI (TPSCI) was introduced for accurately approximating full CI ground states in large electronic active-spaces. TPSCI utilizes locally correlated many-body eigenstates as the basis for the full Hilbert space, resulting in increasingly sparse and compact selected CI expansion. The study demonstrates the accuracy of TPSCI for excited states, presents a more efficient implementation in the Julia programming language, and provides highly accurate estimates of eigenstates for a tetracene tetramer system.
JOURNAL OF PHYSICAL CHEMISTRY A
(2023)
Article
Physics, Multidisciplinary
Linghua Zhu, Ho Lun Tang, George S. Barron, F. A. Calderon-Vargas, Nicholas J. Mayhall, Edwin Barnes, Sophia E. Economou
Summary: This paper develops an iterative version of the quantum approximate optimization algorithm (QAOA) that is problem tailored and can be adapted to specific hardware constraints. The algorithm is simulated on a class of Max-Cut graph problems and shows faster convergence compared to the standard QAOA, while reducing the required number of gates and optimization parameters.
PHYSICAL REVIEW RESEARCH
(2022)
Article
Quantum Science & Technology
John S. Van Dyke, George S. Barron, Nicholas J. Mayhall, Edwin Barnes, Sophia E. Economou
Summary: Several one-dimensional quantum many-body models have exact solutions obtainable through the Bethe ansatz method, and a quantum algorithm has been proposed for preparing Bethe ansatz eigenstates directly on a quantum computer to extract physical properties via measurement. The algorithm, although probabilistic, shows promise in boosting success rate with amplitude amplification while requiring lower resource compared to other quantum simulation algorithms for small error-corrected devices.
Article
Quantum Science & Technology
Ho Lun Tang, V. O. Shkolnikov, George S. Barron, Harper R. Grimsley, Nicholas J. Mayhall, Edwin Barnes, Sophia E. Economou
Summary: The study introduces a new algorithm ADAPT-VQE for quantum simulation, which reduces circuit depths by constructing system-adapted ansatze with fewer parameters. Through numerical simulations, the effectiveness of the new algorithm is validated, significantly reducing circuit depths while maintaining accuracy.
Article
Chemistry, Physical
Luke W. Bertels, Harper R. Grimsley, Sophia E. Economou, Edwin Barnes, Nicholas J. Mayhall
Summary: This study investigates the impact of symmetry breaking on the performance of ADAPT-VQE in two strongly correlated systems. The increase in system correlation leads to spontaneous symmetry breaking of mean-field solutions. Breaking symmetry to improve the energy of reference states has a detrimental effect on ADAPT-VQE due to the increased length of the ansatz required for energy convergence.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2022)