Hardware-Friendly Estimation of LCU-Based Expectation Values via Quantum-to-Classical Workload Shifting
Abstract
Estimating the expectation value of an observable $O$ for a quantum state evolved under a general, possibly non-unitary, operator $A$ is a fundamental task in quantum simulation, chemistry, and variational algorithms. Existing linear-combination-of-unitaries (LCU) approaches implement $A$ on hardware, requiring ancilla qubits, controlled unitaries and, in randomized variants, fresh circuit executions for every Monte Carlo sample. These costs are prohibitive on NISQ and early fault-tolerant devic...
Description / Details
Estimating the expectation value of an observable for a quantum state evolved under a general, possibly non-unitary, operator is a fundamental task in quantum simulation, chemistry, and variational algorithms. Existing linear-combination-of-unitaries (LCU) approaches implement on hardware, requiring ancilla qubits, controlled unitaries and, in randomized variants, fresh circuit executions for every Monte Carlo sample. These costs are prohibitive on NISQ and early fault-tolerant devices. We propose HERMES (Hardware-Efficient Reusable Measurements for Estimating LCU-based expectation valueS), which moves the processing of entirely to the classical domain. Expanding and in the Pauli basis and sampling pairs of Pauli terms classically, HERMES rewrites as a ratio of weighted sums of Pauli expectation values on the unmodified state , with no ancillas, controlled unitaries, or quantum implementation of . A two-level measurement reduction scheme (Pauli deduplication and commuting-group partitioning) bounds the number of distinct measurement settings independently of the sample count, unlike randomized LCU methods whose circuit executions grow linearly with it. On ground-state energy estimation of and via imaginary-time evolution, HERMES matches or beats Pauli single-ancilla LCU baseline using shallow circuits with no two-qubit gates beyond state preparation under qubit-wise commuting grouping. It is also more robust to noise and completes a noisy simulation infeasible for the baseline, at the cost of classical overhead growing with the number of Pauli terms in .
Source: arXiv:2610.32841v1 - http://arxiv.org/abs/2610.32841v1 PDF: https://arxiv.org/pdf/2610.32841v1 Original Link: http://arxiv.org/abs/2610.32841v1
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Oct 26, 2026
Quantum Computing
Quantum Physics
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