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Materials Today Quantum

Variational methods for simulating the quantum dynamics of Ising spin chains

Mohamed Barhoumi, Milad Ghadimi, Muhammad Idham Habibie, Riccardo Bassoli, Frank H. P. Fitzek

Published Jun 1, 2026• 0 citations
Publisher

Abstract

Variational quantum time evolution is a fundamental issue in physics and engineering. It provides a strong framework for modeling the dynamics of quantum states, which is essential for efficiently running quantum networks. It presents an excellent toolkit that can improve the efficacy, reliability, resilience and performance of quantum networks, opening the door to more sophisticated distributed computer systems, quantum communication, and other quantum technologies. The imaginary time evolution of quantum systems is one useful tool that enables the generation of ground or thermal states. In this work, we address standard variational principles, such as the Dirac and Frenkel variational principles, the McLachlan variational principle and the time-dependent variational principle to model real-time dynamics, as well as the Rayleigh–Ritz approach to address static challenges. We also present the variational quantum time evolution VarQITE and VarQRTE formalism in the density matrix method, which is not influenced by the global phase of the quantum state. We calculate the ground-state energy of our quantum Ising spin chain, using VarQITE with different interaction energies J , where three cases are considered. In the non-interacting ( NI ) case ( J = 0 ), we show that the energy of the ground state accomplished with VarQITE converges to an energy of − 2 . 00 Hartree at t = 1 . 1 seconds. In the Ferromagnetic ( FM ) interaction case ( J > 0 ), four scenarios are used to obtain the energy of the Hamiltonian. We show that the convergence and the energy 〈 H 〉 are sensitive to the energy of interaction J . Furthermore, the influence of the negative values of J < 0 , which correspond to the antiferromagnetic ( AFM ) case, on the energy of the ground state is also studied. We find that VarQITE and the exact classical solution are matched. We also investigated the expectation values for magnetization 〈 m z 〉 , employing VarQRTE and the exact classical solution. The NI, FM, and AFM cases are accomplished here. We find that when the spins are not interacting, 〈 m z 〉 = 0 , while it oscillates over time t when J > 0 and J < 0 . We believe that our outcomes will improve our knowledge of the variational quantum time evolution and lead to a better understanding of real and imaginary time evolution of quantum systems (which form a quantum network) and therefore, to more information on the time in networks.

DOI
10.1016/j.mtquan.2026.100073

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Variational quantum time evolution is a fundamental issue in physics and engineering. It provides a strong framework for modeling the dynamics of quantum states, which is essential for efficiently running quantum networks. It presents an excellent toolkit that can improve the efficacy, reliability, resilience and performance of quantum networks, opening the door to more sophisticated distributed computer systems, quantum communication, and other quantum technologies. The imaginary time evolution of quantum systems is one useful tool that enables the generation of ground or thermal states. In this work, we address standard variational principles, such as the Dirac and Frenkel variational principles, the McLachlan variational principle and the time-dependent variational principle to model real-time dynamics, as well as the Rayleigh–Ritz approach to address static challenges. We also present the variational quantum time evolution VarQITE and VarQRTE formalism in the density matrix method, which is not influenced by the global phase of the quantum state. We calculate the ground-state energy of our quantum Ising spin chain, using VarQITE with different interaction energies J , where three cases are considered. In the non-interacting ( NI ) case ( J = 0 ), we show that the energy of the ground state accomplished with VarQITE converges to an energy of − 2 . 00 Hartree at t = 1 . 1 seconds. In the Ferromagnetic ( FM ) interaction case ( J > 0 ), four scenarios are used to obtain the energy of the Hamiltonian. We show that the convergence and the energy 〈 H 〉 are sensitive to the energy of interaction J . Furthermore, the influence of the negative values of J < 0 , which correspond to the antiferromagnetic ( AFM ) case, on the energy of the ground state is also studied. We find that VarQITE and the exact classical solution are matched. We also investigated the expectation values for magnetization 〈 m z 〉 , employing VarQRTE and the exact classical solution. The NI, FM, and AFM cases are accomplished here. We find that when the spins are not interacting, 〈 m z 〉 = 0 , while it oscillates over time t when J > 0 and J < 0 . We believe that our outcomes will improve our knowledge of the variational quantum time evolution and lead to a better understanding of real and imaginary time evolution of quantum systems (which form a quantum network) and therefore, to more information on the time in networks.
The variational method is a versatile tool for classical simulation of a variety of quantum systems. Great efforts have recently been devoted to its extension to quantum computing for efficiently solving static many-body problems and simulating real and imaginary time dynamics. In this work, we first review the conventional variational principles, including the Rayleigh-Ritz method for solving static problems, and the Dirac and Frenkel variational principle, the McLachlan's variational principle, and the time-dependent variational principle, for simulating real time dynamics. We focus on the simulation of dynamics and discuss the connections of the three variational principles. Previous works mainly focus on the unitary evolution of pure states. In this work, we introduce variational quantum simulation of mixed states under general stochastic evolution. We show how the results can be reduced to the pure state case with a correction term that takes accounts of global phase alignment. For variational simulation of imaginary time evolution, we also extend it to the mixed state scenario and discuss variational Gibbs state preparation. We further elaborate on the design of ansatz that is compatible with post-selection measurement and the implementation of the generalised variational algorithms with quantum circuits. Our work completes the theory of variational quantum simulation of general real and imaginary time evolution and it is applicable to near-term quantum hardware.
Abstract An adaptive variational quantum imaginary time evolution (AVQITE) approach is introduced that yields efficient representations of ground states for interacting Hamiltonians on near‐term quantum computers. It is based on McLachlan's variational principle applied to imaginary time evolution of variational wave functions. The variational parameters evolve deterministically according to equations of motions that minimize the difference to the exact imaginary time evolution, which is quantified by the McLachlan distance. Rather than working with a fixed variational ansatz, where the McLachlan distance is constrained by the quality of the ansatz, the AVQITE method iteratively expands the ansatz along the dynamical path to keep the McLachlan distance below a chosen threshold. This ensures the state is able to follow the quantum imaginary time evolution path in the system Hilbert space rather than in a restricted variational manifold set by a predefined fixed ansatz. AVQITE is used to prepare ground states of H 4 , H 2 O, and BeH 2 molecules, where it yields compact variational ansätze and ground state energies within chemical accuracy. Polynomial scaling of circuit depth with system size is shown through a set of AVQITE calculations of quantum spin models. Finally, quantum Lanczos calculations are demonstrated alongside AVQITE without additional quantum resource costs.
We introduce a variational method for simulating the dynamics of interacting open quantum spin systems. The method is based on the spin phase-space representation and variationally targets the Husimi-QQQ function with an ansatz based on a multi-dimensional mixture of spin-coherent states. Crucially, the mixture coefficients are allowed to take negative values, enabling the faithful capture of quantum correlations beyond semiclassical descriptions. The resulting equations of motion are derived from the Dirac-Frenkel variational principle and can be evaluated efficiently without resorting to Monte Carlo sampling by exploiting the analytical structure of the ansatz. As a first application, we demonstrate that this approach accurately captures both the full quantum dynamics and the non-equilibrium steady states of the transverse-field quantum Ising model, in excellent agreement with exact diagonalization. Furthermore, we show that the method scales efficiently to large two-dimensional lattices, a regime that remains challenging for other techniques.
We introduce a quantum-circuit algorithm for performing imaginary-time evolution on infinite one-dimensional lattice systems. The method uses a parameterized quantum circuit to represent a uniform matrix product state ansatz. We derive the ITE algorithm using the time-dependent variational principle and employ the quantum Lanczos algorithm to improve the ground-state energy estimate. As a benchmark, we simulate the transverse-field Ising model using both classical simulators and IBM Quantum devices. Our analysis includes a statistical study of the distributions of the cost function and energy density obtained from quantum measurements, illustrating the effects of finite-sampling noise on convergence.
In recent years, the application of machine learning to physics has been actively explored. In this paper, we study a method for estimating the ground-state energy of quantum Hamiltonians by applying data-driven Koopman analysis within the framework of variational wave functions. Koopman theory is a framework for analyzing the nonlinear dynamics of vectors, in which the dynamics are linearized by lifting the vectors to functions defined over the original vector space. We focus on the fact that the imaginary-time Schrödinger equation, when restricted to a variational wave function, is described by a nonlinear time evolution of the variational parameter vector. We collect sample points of this nonlinear dynamics at parameter configurations where the discrepancy between the true imaginary-time dynamics and the dynamics on the variational manifold is small, and perform data-driven continuous Koopman analysis. Within our formulation, the ground-state energy is reduced to the leading eigenvalue of a differential operator known as the Koopman generator. As a concrete example, we generate samples for the four-site transverse-field Ising model and estimate the ground-state energy using extended dynamic mode decomposition (EDMD). Furthermore, as an extension of this framework, we formulate the method for the case where the variational wave function is given by a uniform matrix product state on an infinite chain. By employing computational techniques developed within the framework of the time-dependent variational principle, all the quantities required for our analysis, including error estimation, can be computed efficiently in such systems. Since our approach provides predictions for the ground-state energy even when the true ground state lies outside the variational manifold, it is expected to complement conventional variational methods.
An adaptive variational quantum imaginary time evolution (AVQITE) approach is introduced that yields efficient representations of ground states for interacting Hamiltonians on near-term quantum computers. It is based on McLachlan's variational principle applied to imaginary time evolution of variational wave functions, and avoids difficult nonconvex high-dimensional optimization that plagues other variational approaches such as the variational quantum eigensolver. The variational parameters evolve according to equations of motions that minimize the difference to the exact imaginary time evolution, which is quantified by the McLachlan distance. Rather than working with a fixed variational ansatz, where the minimal McLachlan distance is constrained by the quality of the ansatz, the adaptive method iteratively expands the ansatz along the dynamical path to ensure the McLachlan distance remains below a chosen threshold. AVQITE is used to prepare ground states of H4_44​, H2_22​O and BeH2_22​ molecules and yields compact variational ansatze and ground state energies beyond chemical accuracy. Finally, quantum Lanczos calculations can also be naturally performed alongside AVQITE without additional quantum resource costs.