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arXiv:2506.15668

Analog Quantum Phase Estimation with Single-Mode Readout

Wei‐Chen Lin, Chiao-Hsuan Wang

Published Jun 18, 2025• 0 citations
arXivHTMLPDF

Abstract

Eigenvalue estimation is a central problem for demonstrating quantum advantage, yet its implementation on digital quantum computers remains limited by circuit depth and operational overhead. We present an analog quantum phase estimation (aQPE) protocol that extracts the eigenenergies of a target Hamiltonian via continuous time evolution and single-mode cavity measurement. By encoding eigenvalue information as conditional cavity phase-space rotations, the scheme avoids deep quantum circuits and entangling gates, while enabling readout through established cavity tomography techniques. We further illustrate the feasibility of this approach by engineering a Hamiltonian that implements aQPE of the XY model, whose ground-state energy problem is QMA-complete, within a physical architecture compatible with existing circuit quantum electrodynamics technology. Our results provide a resource-efficient and scalable framework for implementing quantum phase estimation in near-term quantum platforms.

DOI
10.48550/arxiv.2506.15668

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Eigenvalue estimation is a central problem for demonstrating quantum advantage, yet its implementation on digital quantum computers remains limited by circuit depth and operational overhead. We present an analog quantum phase estimation (aQPE) protocol that extracts the eigenenergies of a target Hamiltonian via continuous time evolution and single-mode cavity measurement. By encoding eigenvalue information as conditional cavity phase-space rotations, the scheme avoids deep quantum circuits and entangling gates, while enabling readout through established cavity tomography techniques. We further illustrate the feasibility of this approach by engineering a Hamiltonian that implements aQPE of the XY model, whose ground-state energy problem is QMA-complete, within a physical architecture compatible with existing circuit quantum electrodynamics technology. Our results provide a resource-efficient and scalable framework for implementing quantum phase estimation in near-term quantum platforms.
Quantum phase estimation (QPE) is a central algorithmic primitive that estimates eigenvalues of a Hamiltonian up to precision εεε in Heisenberg-limited time T=Θ(1/ε)T=Θ(1/ε)T=Θ(1/ε). Standard gate-based implementations of QPE require deep controlled time-evolution circuits and are not native to analog hardware. Here, we present a simple adiabatic protocol for QPE that achieves (up to logarithmic factors) the optimal Heisenberg-limited scaling T=O(1εlog⁡(δ−1))T = O\left( \frac{1}ε \log\left(δ^{-1}\right)\right)T=O(ε1​log(δ−1)) in both the precision εεε and failure probability δδδ. By encoding eigenvalues in populations of computational basis states rather than complex phases, our approach is naturally robust against certain dephasing errors. The adiabatic protocol only requires the ability to couple a single ancilla qubit to the system Hamiltonian as well as pairwise couplings within the ancilla register.
Quantum phase estimation is a cornerstone algorithm for determining eigenvalues of unitary operators with Heisenberg-limited precision. Conventional implementations rely on digital controlled-unitary operations together with phase-extraction circuits, which generally results in substantial circuit depth and hardware overhead. Here, we propose a hardware-native alternative that replaces digital controlled-unitary operations by analog bosonic interactions, naturally available in circuit quantum electrodynamics. The protocol extracts the phase through a sequence of binary threshold tests. A bosonic mode serves as an efficient quantum memory where the binary digits of the phase are encoded into the direction of phase-space rotations. These digits are then read out sequentially via high-fidelity homodyne measurements. We show that the protocol preserves Heisenberg scaling in estimation precision while simultaneously providing exponentially suppressed failure probability. By exploiting bosonic degrees of freedom and analog dispersive interactions, the scheme provides a hardware-efficient realization of quantum phase estimation and establishes a natural route toward implementing high-precision phase estimation on circuit quantum electrodynamics platforms.
Abstract Quantum phase estimation (QPE) is a fundamental tool in quantum computing, facilitating efficient simulations of complex problems in quantum chemistry and materials science. While most phase estimation algorithms are deterministic, recent advancements indicate that incorporating randomness can enhance performance. This study introduces a framework for randomized QPE that merges the benefits of randomized compilation with phase estimation algorithms based on quantum signal processing. Our proposed algorithms effectively reduce circuit depths by eliminating the need for precise Hamiltonian time evolution, making them advantageous for digital quantum computers estimating the eigenvalue and eigenvector properties of Hamiltonians. Notably, our findings show that the quantum stochastic drift protocol (qDRIFT)-based randomized algorithm surpasses the original phase estimation with qDRIFT, especially in scaling inverse failure probabilities. We also establish that a circuit depth of O ( log ⁡ ( M ) ) suffices for estimating M distinct observables. The protocol is executed through multiple iterations of the randomized algorithms combined with classical shadow techniques. Overall, our framework retains many advantages of the randomized compilation technique, making it a compelling solution for challenges in quantum chemistry.
Many optimally scaling quantum simulation algorithms employ controlled time evolution of the Hamiltonian, which is typically the major bottleneck for their efficient implementation. This work establishes a compression protocol for encoding the controlled time evolution operator of translationally invariant, local Hamiltonians into a quantum circuit. It achieves a near-optimal in time ttt scaling for circuit depth O(t polylog(tN/ε))\mathcal{O}(t \text{ polylog}(t N/ε))O(t polylog(tN/ε)), while reducing the control overhead from a multiplicative to an additive factor. We report that this compression protocol enables the implementation of Iterative Quantum Phase Estimation with as few as 414 CNOT gates for a frustrated quantum spin system on a 6$\times$6 triangular lattice and delivers ground state energy errors below 1% (with ±\pm± 1.5% variation, calculated with a hardware noise aware pipeline) on a 4$\times$4 triangular lattice using the noisy emulator of the Quantinuum H2 trapped ion device.
Quantum phase estimation (QPE) is the workhorse behind any quantum algorithm and a promising method for determining ground state energies of strongly correlated quantum systems. Low-cost QPE techniques make use of circuits which only use a single ancilla qubit, requiring classical post-processing to extract eigenvalue details of the system. We investigate choices for phase estimation for a unitary matrix with low-depth noise-free or noisy circuits, varying both the phase estimation circuits themselves as well as the classical post-processing to determine the eigenvalue phases. We work in the scenario when the input state is not an eigenstate of the unitary matrix. We develop a new post-processing technique to extract eigenvalues from phase estimation data based on a classical time-series (or frequency) analysis and contrast this to an analysis via Bayesian methods. We calculate the variance in estimating single eigenvalues via the time-series analysis analytically, finding that it scales to first order in the number of experiments performed, and to first or second order (depending on the experiment design) in the circuit depth. Numerical simulations confirm this scaling for both estimators. We attempt to compensate for the noise with both classical post-processing techniques, finding good results in the presence of depolarizing noise, but smaller improvements in 9-qubit circuit-level simulations of superconducting qubits aimed at resolving the electronic ground state of a H 4 -molecule.
Accurately determining ground-state properties of quantum many-body systems remains one of the major challenges of quantum simulation. In this work, we present a protocol for estimating the ground-state energy using only global time evolution under a target Hamiltonian. This avoids the need for controlled operations that are typically required in conventional quantum phase estimation and extends the algorithm applicability to analog simulators. Our method extracts energy differences from measurements of the Loschmidt echo over an initial ground-state approximation, combines them with direct energy measurements, and solves a set of equations to infer the individual eigenenergies. We benchmark this protocol on free-fermion systems, showing orders-of-magnitude precision gains over direct energy measurements on the initial state, with accuracy improving rapidly with initial-state fidelity and persisting for hundreds of modes. We further demonstrate applicability to the 2D Ising and Fermi-Hubbard models and show that the approach extends naturally to other observables such as order parameters. Finally, we analyze the effect of experimental imperfections and propose error-mitigation strategies. These results establish a practical route to compute physically relevant quantities with high precision using globally controlled quantum simulators.