Publications

Non-normal Hamiltonian dynamics in quantum systems and its realization on quantum computers

The eigenspectrum of a non-normal matrix, which does not commute with its Hermitian conjugate, is a central issue of non-Hermitian physics that has been extensively studied in the past few years. There is, however, another characteristic of a non-normal matrix that has often been overlooked: the pseudospectrum, or the set of spectra under small perturbations. In this paper, we study the dynamics driven by the non-normal matrix (Hamiltonian) realized as a continuous quantum trajectory of the Lindblad master equation in open quantum systems and point out that the dynamics can reveal the nature of unconventional pseudospectrum of the non-normal Hamiltonian. In particular, we focus on the transient dynamics of the norm of an unnormalized quantum state evolved with the non-normal Hamiltonian, which is related to the probability for observing the trajectory with no quantum jump. We formulate the transient suppression of the decay rate of the norm due to the pseudospectral behavior and derive a non-Hermitian/non-normal analog of the time-energy uncertainty relation. We also consider two methods to experimentally realize the non-normal dynamics and observe our theoretical findings on quantum computers: one uses a technique to realize non-unitary operations on quantum circuits and the other leverages a quantum-classical hybrid algorithm called variational quantum simulation. Our demonstrations using cloud-based quantum computers provided by IBM Quantum exhibit the frozen dynamics of the norm in transient time, which can be regarded as a non-normal analog of the quantum Zeno effect.

2021/07/18

Quantum chemistryCondensed matter physicsNISQ deviceJoint research
by Nobuyuki Okuma, Yuya O. Nakagawa

Molecular Structure Optimization based on Electrons-Nuclei Quantum Dynamics Computation

A new concept of the molecular structure optimization method based on quantum dynamics computations is presented. Nuclei are treated as quantum mechanical particles, as are electrons, and the many-body wave function of the system is optimized by the imaginary time evolution method. A demonstration with a 2-dimensional H2+ molecule shows that the optimized nuclear positions can be specified with a small number of observations. This method is considered to be suitable for quantum computers, the development of which will realize its application as a powerful method.

2021/07/14

Quantum chemistryNISQ deviceJoint research
by Hirotoshi Hirai, Takahiro Horiba, Soichi Shirai, Keita Kanno, Keita Arimitsu, Yuya O. Nakagawa, Sho Koh

Deep variational quantum eigensolver for excited states and its application to quantum chemistry calculation of periodic materials

A programmable quantum device that has a large number of qubits without fault-tolerance has emerged recently. Variational Quantum Eigensolver (VQE) is one of the most promising ways to utilize the computational power of such devices to solve problems in condensed matter physics and quantum chemistry. As the size of the current quantum devices is still not large for rivaling classical computers at solving practical problems, Fujii et al. proposed a method called "Deep VQE" which can provide the ground state of a given quantum system with the smaller number of qubits by combining the VQE and the technique of coarse-graining [K. Fujii, et al, arXiv:2007.10917]. In this paper, we extend the original proposal of Deep VQE to obtain the excited states and apply it to quantum chemistry calculation of a periodic material, which is one of the most impactful applications of the VQE. We first propose a modified scheme to construct quantum states for coarse-graining in Deep VQE to obtain the excited states. We also present a method to avoid a problem of meaningless eigenvalues in the original Deep VQE without restricting variational quantum states. Finally, we classically simulate our modified Deep VQE for quantum chemistry calculation of a periodic hydrogen chain as a typical periodic material. Our method reproduces the ground-state energy and the first-excited-state energy with the errors up to O(1)% despite the decrease in the number of qubits required for the calculation by two or four compared with the naive VQE. Our result will serve as a beacon for tackling quantum chemistry problems with classically-intractable sizes by smaller quantum devices in the near future.

2021/04/02

Quantum chemistryCondensed matter physicsNISQ deviceJoint research
by Kaoru Mizuta, Mikiya Fujii, Shigeki Fujii, Kazuhide Ichikawa, Yutaka Imamura, Yukihiro Okuno, Yuya O. Nakagawa

Qulacs: a fast and versatile quantum circuit simulator for research purpose

We introduce Qulacs, a fast simulator for quantum circuits intended for research purpose. To explore the possibilities of a near-term intermediate-scale quantum algorithm and long-term fault-tolerant quantum computing, a fast and versatile quantum circuit simulator is needed. Herein we show the main concepts of Qulacs, explain how to use its features via examples, and demonstrate its performance with numerical benchmarks.

2020/11/27

Quantum chemistryCondensed matter physicsMaterial scienceQuantum machine learning
by Yasunari Suzuki, Yoshiaki Kawase, Yuya Masumura, Yuria Hiraga, Masahiro Nakadai, Jiabao Chen, Ken M. Nakanishi, Kosuke Mitarai, Ryosuke Imai, Shiro Tamiya, Takahiro Yamamoto, Tennin Yan, Toru Kawakubo, Yuya O. Nakagawa, Yohei Ibe, Youyuan Zhang, Hirotsugu Yamashita, Hikaru Yoshimura, Akihiro Hayashi, Keisuke Fujii

Quadratic Clifford expansion for efficient benchmarking and initialization of variational quantum algorithms

Variational quantum algorithms are appealing applications of near-term quantum computers. However, there are two major issues to be solved, that is, we need an efficient initialization strategy for parametrized quantum circuit and to know the limitation of the algorithms by benchmarking it on large scale problems. Here, we propose a perturbative approach for efficient benchmarking and initialization of variational quantum algorithms. The proposed technique performs perturbative expansion of a circuit consisting of Clifford and Pauli rotation gates, which enables us to determine approximate optimal parameters and an optimal value of a cost function simultaneously. The classical simulatability of Clifford circuits is utilized to achieve this goal. Our method can be applied to a wide family of parameterized quantum circuits, which consist of Clifford gates and single-qubit rotation gates. Since the introduced technique provides us a perturbative energy of a quantum system when applied to the variational quantum eigensolver (VQE), our proposal can also be viewed as a quantum-inspired classical method for perturbative energy calculation. As the first application of the method, we perform a benchmark of so-called hardware-efficient-type ansatzes when they are applied to the VQE of one-dimensional hydrogen chains up to H24, which corresponds to 48-qubit system, using a standard workstation.

2020/11/19

Quantum chemistryNISQ deviceCondensed matter physics
by Kosuke Mitarai, Yasunari Suzuki, Wataru Mizukami, Yuya O Nakagawa, Keisuke Fujii

Penalty methods for variational quantum eigensolver

The variational quantum eigensolver (VQE) is a promising algorithm to compute eigenstates and eigenenergies of a given quantum system that can be performed on a near-term quantum computer. Obtaining eigenstates and eigenenergies in a specific symmetry sector of the system is often necessary for practical applications of the VQE in various fields ranging from high energy physics to quantum chemistry. It is common to add a penalty term in the cost function of the VQE to calculate such a symmetry-resolving energy spectrum, but systematic analysis on the effect of the penalty term has been lacking, and the use of the penalty term in the VQE has not been justified rigorously. In this work, we investigate two major types of penalty terms for the VQE that were proposed in the previous studies. We show a penalty term in one of the two types works properly in that eigenstates obtained by the VQE with the penalty term reside in the desired symmetry sector. We further give a convenient formula to determine the magnitude of the penalty term, which may lead to the faster convergence of the VQE. Meanwhile, we prove that the other type of penalty terms does not work for obtaining the target state with the desired symmetry in a rigorous sense and even gives completely wrong results in some cases. We finally provide numerical simulations to validate our analysis. Our results apply to general quantum systems and lay the theoretical foundation for the use of the VQE with the penalty terms to obtain the symmetry-resolving energy spectrum of the system, which fuels the application of a near-term quantum computer.

2020/10/26

Quantum chemistryNISQ deviceCondensed matter physics
by Kohdai Kuroiwa, Yuya O. Nakagawa

Variational Quantum Simulation for Periodic Materials

We present a quantum-classical hybrid algorithm that simulates electronic structures of periodic systems such as ground states and quasiparticle band structures. By extending the unitary coupled cluster (UCC) theory to describe crystals in arbitrary dimensions, we numerically demonstrate in hydrogen chain that the UCC ansatz implemented on a quantum circuit can be successfully optimized with a small deviation from the exact diagonalization over the entire range of the potential energy curves. Furthermore, with the aid of the quantum subspace expansion method, in which we truncate the Hilbert space within the linear response regime from the ground state, the quasiparticle band structure is computed as charged excited states. Our work establishes a powerful interface between the rapidly developing quantum technology and modern material science.

2020/08/21

Quantum chemistryCondensed matter physicsMaterial scienceNISQ deviceJoint research
by Nobuyuki Yoshioka, Yuya O. Nakagawa, Yu-ya Ohnishi, Wataru Mizukami

Deep Variational Quantum Eigensolver: a divide-and-conquer method for solving a larger problem with smaller size quantum computers

We propose a divide-and-conquer method for the quantum-classical hybrid algorithm to solve larger problems with small-scale quantum computers. Specifically, we concatenate variational quantum eigensolver (VQE) with reducing the dimensions of the system, where the interactions between divided subsystems are taken as an effective Hamiltonian expanded by the reduced basis. Then the effective Hamiltonian is further solved by VQE, which we call deep VQE. Deep VQE allows us to apply quantum-classical hybrid algorithms on small-scale quantum computers to large systems with strong intra-subsystem interactions and weak inter-subsystem interactions, or strongly correlated spin models on large regular lattices. As proof-of-principle numerical demonstrations, we use the proposed method for Heisenberg anti-ferromagnetic models, including one-dimensionally coupled 12-qubit Heisenberg anti-ferromagnetic models on Kagome lattices. The largest problem size of 48 qubits is solved by simulating 12-qubit quantum computers. The proposed scheme enables us to handle the problems of >1000 qubits by concatenating VQE with a few tens of qubits. Deep VQE will provide us a promising pathway to solve practically important problems on noisy intermediate-scale quantum computers.

2020/07/21

Condensed matter physicsQuantum chemistryNISQ device
by Keisuke Fujii, Kosuke Mitarai, Wataru Mizukami, Yuya O. Nakagawa

Calculating nonadiabatic couplings and Berry's phase by variational quantum eigensolvers

Investigating systems in quantum chemistry and quantum many-body physics with the variational quantum eigensolver (VQE) is one of the most promising applications of forthcoming near-term quantum computers. The VQE is a variational algorithm for finding eigenenergies and eigenstates of such quantum systems. In this paper, we propose VQE-based methods to calculate the nonadiabatic couplings of molecules in quantum chemical systems and Berry's phase in quantum many-body systems. Both quantities play an important role to understand various properties of a system (e.g., nonadiabatic dynamics and topological phase of matter) and are related to derivatives of eigenstates with respect to external parameters of the system. Here, we show that the evaluation of inner products between the eigenstate and the derivative of the same/different eigenstate reduces to the evaluation of expectation values of observables, and we propose quantum circuits and classical post-processings to calculate the nonadiabatic couplings and Berry's phase. In addition, we demonstrate our methods by numerical simulation of the nonadiabatic coupling of the hydrogen molecule and Berry's phase of a spin-1/2 model. Our proposal widens the applicability of the VQE and the possibility of near-term quantum computers to study molecules and quantum many-body systems.

2020/03/03

Quantum chemistryNISQ device
by Shiro Tamiya, Sho Koh, Yuya O. Nakagawa

Predicting excited states from ground state wavefunction by supervised quantum machine learning

Excited states of molecules lie in the heart of photochemistry and chemical reactions. The recent development in quantum computational chemistry leads to inventions of a variety of algorithms which calculate the excited states of molecules on near-term quantum computers, but they require more computational burdens than the algorithms for the ground states. In this study, we propose a scheme of supervised quantum machine learning which predicts excited state properties of molecules only from its ground state wavefunction and results in reducing the computational cost for calculating the excited states. Our model is comprised of a quantum reservoir and a classical machine learning unit which processes the results of measurements of single-qubit Pauli operators. The quantum reservoir effectively transforms the single-qubit operators into complicated multi-qubit ones which contain essential information of the system, so that the classical machine learning unit may decode them appropriately. The number of runs for quantum computers is saved by training only the classical machine learning unit and the whole model requires modest resources of quantum hardwares which may be implemented in current experiments. We illustrate the predictive ability of our model by numerical simulations for small molecules with and without including noise inevitable in near-term quantum computers. The results show that our scheme well reproduces the first and second excitation energies as well as the transition dipole moment between the ground states and excited states only from the ground state as an input. Our contribution will enhance applications of quantum computers in the study of quantum chemistry and quantum materials.

2020/02/28

Condensed matter physicsQuantum chemistryMaterial scienceNISQ deviceQuantum machine learning
by Hiroki Kawai, Yuya O. Nakagawa