Review
Engineering, Chemical
Fedor V. Ryzhkov, Yuliya E. Ryzhkova, Michail N. Elinson
Summary: The popularity of Python in chemistry is steadily growing due to its versatility, simplicity, and wide range of libraries. It is widely used for kinetic and thermodynamic calculations, quantum chemistry, molecular mechanics, laboratory automation, software development, data analysis, and visualization. The future development of theoretical and computational chemistry is expected, especially in conjunction with fields like machine learning.
Article
Multidisciplinary Sciences
Joshua J. Goings, Alec White, Joonho Lee, Christofer S. Tautermann, Matthias Degroote, Craig Gidney, Toru Shiozaki, Ryan Babbush, Nicholas C. Rubin
Summary: An accurate assessment of the potential computational advantages of quantum computers in chemical simulation is crucial for their deployment. This study explores the resources required for assessing the electronic structure of cytochrome P450 enzymes using quantum and classical computations, defining a boundary for classical-quantum advantage. The results show that simulation of large-scale CYP models has the potential to be a quantum advantage problem, emphasizing the interplay between classical computations and quantum algorithms in chemical simulation.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Article
Quantum Science & Technology
Ilya G. Ryabinkin, Artur F. Izmaylov, Scott N. Genin
Summary: The iterative qubit coupled cluster (iQCC) method is a systematic variational approach for solving electronic structure problems on universal quantum computers. It reduces the number of iterations needed to achieve desired accuracy, and introduces corrections based on perturbation theory series for efficient evaluation on classical computers. Additionally, the method introduces the concept of qubit active-space to further reduce quantum resource requirements.
QUANTUM SCIENCE AND TECHNOLOGY
(2021)
Article
Quantum Science & Technology
Saad Yalouz, Bruno Senjean, Jakob Gunther, Francesco Buda, Thomas E. O'Brien, Lucas Visscher
Summary: In the NISQ era, solving the electronic structure problem in chemistry through a combination of different algorithms is crucial. Research on active spaces and conical intersections is essential for improving the accuracy of quantum computers.
QUANTUM SCIENCE AND TECHNOLOGY
(2021)
Article
Chemistry, Multidisciplinary
Karol Kowalski, Nicholas P. Bauman
Summary: This paper presents an extension of many-body downfolding methods to reduce the resources required in the quantum phase estimation (QPE) algorithm. By employing Fock-space variants of the SW transformation (or RRST), the qubit-mapped similarity-transformed Hamiltonians can have significantly increased locality, simplifying quantum circuit simulations of quantum dynamics.
APPLIED SCIENCES-BASEL
(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
Physics, Multidisciplinary
Dan-Bo Zhang, Bin-Lin Chen, Zhan-Hao Yuan, Tao Yin
Summary: This paper proposes a new variational quantum eigensolver (VQE) based on minimizing energy variance, called variance-VQE. Unlike traditional VQE methods, variance-VQE treats ground and excited states equally, and finds low-energy excited states by optimizing a combination of energy and variance, which is more efficient than minimizing energy or variance alone. The optimization can be boosted with stochastic gradient descent by Hamiltonian sampling, reducing the need for quantum resources.
Article
Physics, Multidisciplinary
Cica Gustiani, Richard Meister, Simon C. Benjamin
Summary: Variational methods are a promising approach for quantum computers to solve chemistry problems. In this study, we use adaptive evolving quantum circuits described in a related paper to solve problems. The results show that this approach can outperform human-designed circuits and we compare them for larger instances up to 14 qubits. Additionally, we propose a novel approach to improve the performance and compactness of circuits by constraining the circuit evolution in the physically relevant subspace. We consider both static and dynamic properties of molecular systems. The emulation environment used is QuESTlink and all resources are open source and linked in this paper.
NEW JOURNAL OF PHYSICS
(2023)
Article
Physics, Multidisciplinary
Oliver G. Maupin, Andrew D. Baczewski, Peter J. Love, Andrew J. Landahl
Summary: This article presents example quantum chemistry programs written with JaqalPaq, intended to be run on the QSCOUT platform, using the VQE algorithm to compute ground state energies of H2, HeH+, and LiH molecules. The second-quantized Hamiltonians are calculated with the PySCF package, and fermion-to-qubit mappings are obtained from the OpenFermion package. Emulation using JaqalPaq is used to compare simulated bond-dissociation curves with exact forms.
Article
Quantum Science & Technology
Kubra Yeter-Aydeniz, Bryan T. Gard, Jacek Jakowski, Swarnadeep Majumder, George S. Barron, George Siopsis, Travis S. Humble, Raphael C. Pooser
Summary: Quantum chemistry serves as a key benchmark for current and future quantum computer performance, with state-of-the-art methods outlined for achieving chemical accuracy on NISQ devices. These methods include extending variational eigensolvers with symmetry preserving Ansatze and using quantum imaginary time evolution and Lanczos as complementary methods. A new error mitigation method is also highlighted, demonstrating rapid advancements in electronic structure calculations.
ADVANCED QUANTUM TECHNOLOGIES
(2021)
Article
Physics, Multidisciplinary
Feng Bao, Hao Deng, Dawei Ding, Ran Gao, Xun Gao, Cupjin Huang, Xun Jiang, Hsiang-Sheng Ku, Zhisheng Li, Xizheng Ma, Xiaotong Ni, Jin Qin, Zhijun Song, Hantao Sun, Chengchun Tang, Tenghui Wang, Feng Wu, Tian Xia, Wenlong Yu, Fang Zhang, Gengyan Zhang, Xiaohang Zhang, Jingwei Zhou, Xing Zhu, Yaoyun Shi, Jianxin Chen, Hui-Hai Zhao, Chunqing Deng
Summary: Superconducting qubits provide a promising path toward building large-scale quantum computers. Among alternative superconducting qubits, fluxonium exhibits large anharmonicity and long coherence times, making it a particularly promising candidate. In this work, we engineer a fluxonium-based quantum processor that achieves high qubit coherence, fast frequency tunability, and individual-qubit addressability for reset, readout, and gates. With simple and fast gate schemes, we achieve high average fidelity for single-qubit and two-qubit gates, comparable to the highest reported values in literature.
PHYSICAL REVIEW LETTERS
(2022)
Article
Physics, Multidisciplinary
Brennan de Neeve, Thanh-Long Nguyen, Tanja Behrle, Jonathan P. Home
Summary: Stabilization of logical qubits encoded using quantum error correction is essential for reliable quantum computing. Implementing encoding with quantum oscillators such as GKP codes allows for correction of small displacement errors with a single physical entity. By introducing a dissipative map designed for finite GKP codes and demonstrating an extension in coherence time using both square and hexagonal GKP codes, the lifetime of qubits encoded in the motion of a trapped ion has been extended.
Article
Materials Science, Multidisciplinary
M. P. Liul, C. -H. Chien, C. -Y. Chen, P. Y. Wen, J. C. Chen, Y. -H. Lin, S. N. Shevchenko, Franco Nori, I. -C. Hoi
Summary: This study focuses on the dynamics and stationary regime of a capacitively shunted transmon-type qubit in front of a mirror. The qubit is influenced by probe and dressing signals, and by varying their parameters and analyzing the reflected probe signal, the system dynamics can be explored using the Bloch equation. The time-dependent occupation probabilities obtained are correlated with the experimentally measured reflection coefficient. This research opens up new perspectives in understanding the properties of qubit plus mirror circuits and related physical processes, such as Landau-Zener-Stuckelberg-Majorana transitions.
Article
Optics
Yuan Zhou, Chang-Sheng Hu, Dong-Yan Lu, Xin-Ke Li, Hai-Ming Huang, Yong-Chen Xiong, Xin-You Lu
Summary: This study explores a joint scheme to enhance the coherent coupling between NV centers and phonons, providing a potential platform for further applications in quantum information processing.
PHOTONICS RESEARCH
(2022)
Review
Chemistry, Physical
Daniel Claudino
Summary: The rapid progress in quantum chemistry over the past few decades has been largely due to the synergy between theoretical and computational advancements. However, the current computer architecture is reaching a state of stagnant development. Quantum computing has emerged as a promising avenue for the further advancement of quantum chemistry, but it presents several challenges. This review discusses the basic aspects of quantum information and their relation to quantum computing, specifically in the context of enabling simulations of quantum chemistry.
INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY
(2022)
Article
Quantum Science & Technology
Saad Yalouz, Bruno Senjean, Jakob Gunther, Francesco Buda, Thomas E. O'Brien, Lucas Visscher
Summary: In the NISQ era, solving the electronic structure problem in chemistry through a combination of different algorithms is crucial. Research on active spaces and conical intersections is essential for improving the accuracy of quantum computers.
QUANTUM SCIENCE AND TECHNOLOGY
(2021)
Article
Multidisciplinary Sciences
J. M. Arrazola, V Bergholm, K. Bradler, T. R. Bromley, M. J. Collins, I Dhand, A. Fumagalli, T. Gerrits, A. Goussev, L. G. Helt, J. Hundal, T. Isacsson, R. B. Israel, J. Izaac, S. Jahangiri, R. Janik, N. Killoran, S. P. Kumar, J. Lavoie, A. E. Lita, D. H. Mahler, M. Menotti, B. Morrison, S. W. Nam, L. Neuhaus, H. Y. Qi, N. Quesada, A. Repingon, K. K. Sabapathy, M. Schuld, D. Su, J. Swinarton, A. Szava, K. Tan, P. Tan, V. D. Vaidya, Z. Vernon, Z. Zabaneh, Y. Zhang
Summary: The newly introduced photon quantum computing system is capable of executing multiple quantum algorithms, surpassing the limitations of existing photon quantum computers, with significant breakthroughs in detecting the quantity and rate of multi-photon events. The platform validates the application prospects of photon technologies in quantum information processing, particularly in the breakthroughs brought by high squeezing and sampling rates.
Article
Quantum Science & Technology
Sukin Sim, Jonathan Romero, Jerome F. Gonthier, Alexander A. Kunitsa
Summary: Variational hybrid quantum-classical algorithms are powerful tools for maximizing the use of noisy intermediate-scale quantum devices. In this work, a heuristic optimization strategy called 'parameter-efficient circuit training (PECT)' is proposed for optimizing ansatze in variational quantum algorithms. By activating and optimizing a subset of parameters in each iteration, PECT can improve optimization efficiency for certain ansatze and reduce the depth of circuits encoding solution candidates.
QUANTUM SCIENCE AND TECHNOLOGY
(2021)
Article
Chemistry, Physical
Saad Yalouz, Emiel Koridon, Bruno Senjean, Benjamin Lasorne, Francesco Buda, Lucas Visscher
Summary: In this paper, we introduce several technical and analytical extensions to enhance the efficiency and accuracy of the state-averaged orbital-optimized variational quantum eigensolver (SA-OO-VQE) algorithm. These extensions include an efficient state-resolution procedure and the estimation of gradients and nonadiabatic couplings, which are crucial for practical applications such as conical intersection search and quantum dynamics simulation.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2022)
Review
Chemistry, Multidisciplinary
Filip Cernatic, Bruno Senjean, Vincent Robert, Emmanuel Fromager
Summary: This article reviews recent progress in the field of (time-independent) ensemble density-functional theory (DFT) for excited states, focusing on the GOK and N-centered ensemble formalisms. Key exact results are highlighted, and the article discusses in detail the variational evaluation of orbital-dependent ensemble Hartree-exchange (Hx) energies and the possibility of improving existing theories using the concept of density-driven correlation.
TOPICS IN CURRENT CHEMISTRY
(2022)
Article
Chemistry, Physical
Souloke Sen, Bruno Senjean, Lucas Visscher
Summary: This paper presents a simple one-step top-down embedding procedure to generate a set of localized orbitals with supermolecular connectivity, and a method for constructing local excitations and charge-transfer states within the linear response framework of TDDFT. This approach provides direct access to approximate diabatic excitation energies and electronic couplings, which are important in modeling energy transfer processes in complex biological systems.
JOURNAL OF CHEMICAL PHYSICS
(2023)
Article
Optics
Xavier Bonet-Monroig, Hao Wang, Diederick Vermetten, Bruno Senjean, Charles Moussa, Thomas Back, Vedran Dunjko, Thomas E. O'Brien
Summary: Variational quantum algorithms (VQAs) utilize classical optimization algorithms to optimize parametrized quantum circuits and approximate quantum solutions for various applications. This research explores the performance of commonly used gradient-free optimization methods in finding ground-state energies for chemistry and material science problems. The results demonstrate the importance of tailoring and hyperparameter tuning known optimization techniques for variational quantum algorithms in noisy environments. Future implementations of VQAs can benefit from this guidance.
Article
Materials Science, Multidisciplinary
Quentin Marecat, Bruno Senjean, Matthieu Saubanere
Summary: In this paper, we derive recursive relations for the Schrieffer-Wolff (SW) transformation applied to the half-filled Hubbard dimer. These recursive relations yield two types of modifications, variational or iterative, that approximate or enforce block-diagonalization at infinite order of perturbation. The modified SW unitary transformations are then used to design and test quantum algorithms adapted to the noisy and fault-tolerant era. This work paves the way for the design of alternative quantum algorithms for the general Hubbard Hamiltonian.
Article
Optics
Daochen Wang
Summary: In a breakthrough study, Bravyi, Gosset, and Konig demonstrated unconditionally that quantum circuits with constant depth are more powerful than classical circuits, requiring them to have a larger depth for simulation. They formalized the concept of possibilistic simulation and developed explicit classical circuits capable of simulating quantum circuits of depth d with Clifford and t T-gates in depth O(d + t).
Article
Optics
Bruno Senjean, Saad Yalouz, Naoki Nakatani, Emmanuel Fromager
Summary: There is currently a growing interest in the development of a new hierarchy of methods based on the concept of seniority in quantum chemistry. However, accurately describing both dynamical and static correlation effects within a single approach remains challenging. This work proposes an alternative formulation of reduced density-matrix functional theory (RDMFT) that maps the density matrix onto an ab initio seniority-zero wave function.
Article
Optics
Alain Delgado, Juan Miguel Arrazola, Soran Jahangiri, Zeyue Niu, Josh Izaac, Chase Roberts, Nathan Killoran
Summary: A variational quantum algorithm is introduced in this work for finding the most stable structure of molecules by considering the parametric dependence of the electronic Hamiltonian on nuclear coordinates. The algorithm is successfully applied to find the equilibrium geometries of various molecules, showing excellent agreement with classical quantum chemistry methods.
Article
Quantum Science & Technology
J. Eli Bourassa, Nicolas Quesada, Ilan Tzitrin, Antal Szava, Theodor Isacsson, Josh Izaac, Krishna Kumar Sabapathy, Guillaume Dauphinais, Ish Dhand
Summary: The study introduces a novel formalism for simulating states represented as linear combinations of Gaussian functions, enabling the analysis and simulation of a wide range of non-Gaussian states, transformations, and measurements. This approach has been used to simulate various types of bosonic qubits and critical circuits for the study of fault-tolerant quantum computing. The formalism offers levels of accuracy that are not achievable with existing methods and has been implemented in the open-source Strawberry Fields PYTHON library.
Article
Quantum Science & Technology
Abhinav Anand, Jonathan Romero, Matthias Degroote, Alan Aspuru-Guzik
Summary: The paper discusses the potential advantage of machine learning in quantum computers and its robustness in the presence of noise, as well as investigates the impact of training time on the algorithm's performance. The results provide a foundation for experimental exploration of different quantum machine learning algorithms on noisy intermediate-scale quantum devices.
ADVANCED QUANTUM TECHNOLOGIES
(2021)
Article
Mathematics
Kamil Bradler, Shmuel Friedland, Josh Izaac, Nathan Killoran, Daiqin Su
Summary: This study establishes a connection between a near-term quantum computing device and the graph isomorphism problem, encoding graphs into quantum states of light and probing their properties with photon-number-resolving detectors. The probabilities of different photon-detection events can be combined to give a complete set of graph invariants, with isomorphic graphs having equivalent detection probabilities. Additional methods for combining or coarse-graining measurement probabilities are presented to make experimental tests easier. Benchmarking with numerical simulations on the Titan supercomputer shows promising results for various types of graph families.
Article
Quantum Science & Technology
Jonathan Romero, Alan Aspuru-Guzik
Summary: A hybrid quantum-classical approach for modeling continuous classical probability distributions using a variational quantum circuit was proposed. The quantum generator architecture includes encoding classical random variables into quantum states and training a parameterized quantum circuit to mimic the target distribution. The model can interface smoothly with classical functions like neural networks, and is trained using an adversarial learning approach.
ADVANCED QUANTUM TECHNOLOGIES
(2021)
