Analog quantum simulation offers a hardware-specific approach to studying quantum dynamics, but mapping a model Hamiltonian onto the available device parameters requires matching the hardware dynamics. We introduce a paradigm for quantum Hamiltonian simulation that leverages digital decomposition techniques and optimal control to perform analog simulation. We validate this approach by constructing the optimal analog controls for a superconducting transmon device to emulate the dynamics of an extended Bose-Hubbard model. We demonstrate the role of control time, digital error, and pulse complexity, and we explore the accuracy and robustness of these controls. We conclude by discussing the opportunity for implementing this paradigm in near-term quantum devices.
Analog quantum simulation offers a hardware-specific approach to studying quantum dynamics, but mapping a model Hamiltonian onto the available device parameters requires matching the hardware dynamics. We introduce a paradigm for quantum Hamiltonian simulation that leverages digital decomposition techniques and optimal control to perform analog simulation. We validate this approach by constructing the optimal analog controls for a superconducting transmon device to emulate the dynamics of an extended Bose-Hubbard model. We demonstrate the role of control time, digital error, and pulse complexity, and we explore the accuracy and robustness of these controls. We conclude by discussing the opportunity for implementing this paradigm in near-term quantum devices.
Analog quantum simulators emulate complex many-body dynamics through native continuous-time evolution under hardware-defined interactions. Yet once a platform is specified, its interaction structure is largely fixed by the underlying hardware, restricting the Hamiltonians that can be realized and limiting programmability. Here we introduce universal analog quantum simulation (UAQS), a hybrid framework that systematically expands the range of accessible quantum evolutions within a given analog platform. UAQS employs optimized continuous-time control fields to engineer target dynamics directly, avoiding decomposition into discrete gate sequences. By preserving native analog evolution while extending the set of achievable Hamiltonians, UAQS transforms fixed-interaction analog devices into programmable simulators. Numerical studies on representative architectures, including superconducting circuits and Rydberg-atom arrays, show that UAQS accurately reproduces non-trivial many-body dynamics beyond the intrinsic interaction structure of the hardware. These results establish UAQS as a practical route toward programmable analog quantum simulation.
We show that optimal control of the electron dynamics is able to prepare molecular ground states, within chemical accuracy, with evolution times approaching the bounds imposed by quantum mechanics. We propose a specific parameterization of the molecular evolution only in terms of interaction already present in the molecular Hamiltonian. Thus, the proposed method solely utilizes quantum simulation routines, retaining their favorable scalings. Due to the intimate relationships between variational quantum algorithms and optimal control, we compare, when possible, our results with state-of-the-art methods in the literature. We found that the number of parameters needed to reach chemical accuracy and algorithmic scaling is in line with compact adaptive strategies to build variational Ansätze. The algorithm, which is also suitable for quantum simulators, is implemented by emulating a digital quantum processor (up to 16 qubits) and tested on different molecules and geometries spanning different degrees of electron correlation.
Digital-analog quantum computation aims to reduce the currently infeasible resource requirements needed for near-term quantum information processing by replacing sequences of one-and two-qubit gates with a unitary transformation generated by the systems' underlying Hamiltonian.Inspired by this paradigm, we consider superconducting architectures and extend the cross-resonance effect, up to first order in perturbation theory, from a two-qubit interaction to an analog Hamiltonian acting on onedimensional (1D) chains and two-dimensional (2D) square lattices, which, in an appropriate reference frame, results in a purely two-local Hamiltonian.By augmenting the analog Hamiltonian dynamics with single-qubit gates we show how one may generate a larger variety of distinct analog Hamiltonians.We then synthesize unitary sequences, in which we toggle between the various analog Hamiltonians as needed, simulating the dynamics of Ising, XY, and Heisenberg spin models.Our dynamics simulations are Trotter error-free for the Ising and XY models in 1D.We also show that the Trotter errors for 2D XY and 1D Heisenberg chains are reduced, with respect to a digital decomposition, by a constant factor.In order to realize these important near-term speedups, we discuss the practical considerations needed to accurately characterize and calibrate our analog Hamiltonians for use in quantum simulations.We conclude with a discussion of how the Hamiltonian toggling techniques could be extended to derive new analog Hamiltonians, which may be of use in more complex digital-analog quantum simulations for various models of interacting spins.
The required precision to perform quantum simulations beyond the capabilities of classical computers imposes major experimental and theoretical challenges. Here, we develop a characterization technique to benchmark the implementation precision of a specific quantum simulation task. We infer all parameters of the bosonic Hamiltonian that governs the dynamics of excitations in a two-dimensional grid of nearest-neighbour coupled superconducting qubits. We devise a robust algorithm for identification of Hamiltonian parameters from measured times series of the expectation values of single-mode canonical coordinates. Using super-resolution and denoising methods, we first extract eigenfrequencies of the governing Hamiltonian from the complex time domain measurement; next, we recover the eigenvectors of the Hamiltonian via constrained manifold optimization over the orthogonal group. For five and six coupled qubits, we identify Hamiltonian parameters with sub-MHz precision and construct a spatial implementation error map for a grid of 27 qubits. Our approach enables us to distinguish and quantify the effects of state preparation and measurement errors and show that they are the dominant sources of errors in the implementation. Our results quantify the implementation accuracy of analog dynamics and introduce a diagnostic toolkit for understanding, calibrating, and improving analog quantum processors.
Analog quantum simulators and digital quantum computers are two distinct paradigms driving near-term applications in modern quantum science, from probing many-body phenomena to identifying computational advantage over classical systems. A transformative opportunity on the horizon is merging the high-fidelity many-body evolution in analog simulators with the robust control and measurement of digital machines. Such a hybrid platform would unlock new capabilities in state preparation, characterization and dynamical control. Here, we embed digital quantum control in the analog evolution of a synthetic quantum material by entangling the lattice potential landscape of a Bose-Hubbard circuit with an ancilla qubit. This Hamiltonian-level control induces dynamics under a superposition of different lattice configurations and guides the many-body system to novel strongly-correlated states where different phases of matter coexist -- ordering photons into superpositions of solid and fluid eigenstates. Leveraging hybrid control modalities, we adiabatically introduce disorder to localize the photons into an entangled cat state and enhance its coherence using a many-body echo technique. This work illustrates the potential for entangling quantum computers with quantum matter -- synthetic and solid-state -- for advantage in sensing and materials characterization.
Quantum computers based on superconducting circuits are experiencing rapid development, with the aim to outperform classical computers in certain useful tasks in the near future.However, the currently available chip fabrication technologies limit the capability of gathering a large number of high-quality qubits in a single superconducting chip, a requirement for implementing quantum error correction.Furthermore, achieving high connectivity in a chip poses a formidable technological challenge.Here, we propose a hybrid digital-analog quantum algorithm that enhances the physical connectivity among qubits coupled by an arbitrary inhomogeneous nearest-neighbor Ising Hamiltonian and generates an arbitrary all-to-all Ising Hamiltonian only by employing single-qubit rotations.Additionally, we optimize the proposed algorithm in the number of analog blocks and in the time required for the simulation.These results take advantage of the natural evolution of the system by combining the flexibility of digital steps with the robustness of analog quantum computing, allowing us to improve the connectivity of the hardware and the efficiency of quantum algorithms.