PhysicsarXiv
Ranked by formulaVerdict: NotableHardware-Friendly Estimation of LCU-Based Expectation Values via Quantum-to-Classical Workload Shifting
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.
Caveats
- Preprint; not yet peer reviewed.
VerdictWorth a reader's time today.
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 devices. We propose HERMES (Hardware-Efficient Reusable Measurements for Estimating LCU-based expectation valueS), which moves the processing of A entirely to the classical domain. Expanding A and O in the Pauli basis and sampling pairs of Pauli terms classically, HERMES rewrites μ= Tr(OAρA^dagger)/Tr(AρA^dagger) as a ratio of weighted sums of Pauli expectation values on the unmodified state $ρ$, with no ancillas, controlled unitaries, or quantum implementation of A. 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 H₂ and LiH 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 LiH simulation infeasible for the baseline, at the cost of classical overhead growing with the number of Pauli terms in A.
The editor's rubric
- Leverage3 / 5
- A method or resource many groups across the field will adopt within a year.
- Magnitude3 / 5
- Large gain: roughly 2x, or a clear new state of the art on a hard, unsaturated problem.
- Evidence3 / 5
- Solid: multiple benchmarks or cohorts, ablations, fair baselines, released code or data.
- Novelty2 / 5
- A new combination of known ideas.
- Trajectory2 / 5
- Some room to improve with obvious engineering.
- Stakes2 / 5
- Benefits a professional community (practitioners, clinicians, engineers).
Editor’s rationale
Heuristic triage from title and abstract text only, not a reading of the paper. Cues found: method (we propose); gains (outperforms); design (randomized); scale (efficient); stakes (energy).
How the score was computed
Desks place stronger verdicts first, then use this score to order work within the same verdict.
- Merit
- 5.2 / 10
- Adjusted merit
- 4.5 / 10
- Attention
- 0%
- Freshness
- 77%