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arxiv: 2606.01226 · v1 · pith:ORR2V5BEnew · submitted 2026-05-31 · 🪐 quant-ph

Realizing leakage elimination operator-based adiabatic speedup on a superconducting quantum processor

Jia-Yi Fan , Kai-Yu Yuan , Zong-Yuan Ge , Feng-Hua Ren , Zhao-Ming Wang This is my paper

Pith reviewed 2026-06-28 16:59 UTC · model grok-4.3

classification 🪐 quant-ph
keywords leakage elimination operatoradiabatic quantum computationsuperconducting quantum processoradiabatic speedupquantum noise mitigationBayesian pulse optimizationIBM quantum hardware
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The pith

Ideal leakage elimination pulses speed up adiabatic quantum computation on superconducting hardware while raising fidelity.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper establishes that leakage elimination operator control, previously studied only in theory, can be realized on actual IBM superconducting processors to shorten the evolution time needed for adiabatic processes. This shortening reduces the window during which environmental noise can degrade performance. Experiments first map the trade-off between adiabaticity and noise accumulation using both simulator and hardware runs with a matched noise model. They then apply the ideal closed-system LEO pulse to obtain a clear fidelity gain at short times, and test a Bayesian-optimized version of the pulse.

Core claim

We present such a realization on IBM superconducting quantum processors. We first characterize the trade-off between adiabaticity and noise accumulation by varying the total evolution time on both the Qiskit simulator and the ibm_marrakesh processor, employing a comprehensive noise model that closely reproduces the experimental results. We then implement ideal LEO pulse derived for a closed system and achieve a significant enhancement of adiabatic fidelity within a short evolution time.

What carries the argument

The leakage elimination operator (LEO) pulse, applied during the adiabatic sweep to suppress leakage while permitting faster total evolution.

If this is right

  • Adiabatic algorithms become feasible on current noisy hardware by compressing the required evolution window.
  • Noise models calibrated on one processor can guide pulse design before hardware execution.
  • Bayesian optimization of the LEO waveform can be used when the ideal closed-system form proves insufficient.
  • The same LEO strategy applies to any adiabatic protocol whose leakage channels are known.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The method could be combined with dynamical decoupling or other open-loop controls to further extend the usable evolution window.
  • Testing the same LEO pulses on different qubit modalities would reveal whether the speedup is hardware-specific or generic.
  • If the fidelity gain persists at larger system sizes, adiabatic quantum algorithms could become competitive with gate-model approaches on near-term devices.

Load-bearing premise

The ideal LEO pulse derived for a closed system can be directly applied on the noisy superconducting hardware to produce the reported fidelity enhancement.

What would settle it

Running the identical adiabatic schedule on ibm_marrakesh with and without the ideal LEO pulse and finding no statistically significant fidelity increase at short total times would falsify the speedup claim.

Figures

Figures reproduced from arXiv: 2606.01226 by Feng-Hua Ren, Jia-Yi Fan, Kai-Yu Yuan, Zhao-Ming Wang, Zong-Yuan Ge.

Figure 1
Figure 1. Figure 1: FIG. 1. (a) Simulated fidelity versus rescaled time [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: FIG. 2. Final fidelity [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: FIG. 3. Fidelity [PITH_FULL_IMAGE:figures/full_fig_p005_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: FIG. 4. (a) Simulated fidelity [PITH_FULL_IMAGE:figures/full_fig_p006_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: FIG. 5. Circuit diagram for a single Trotter step with LEO [PITH_FULL_IMAGE:figures/full_fig_p007_5.png] view at source ↗
read the original abstract

The slow evolution required for adiabaticity in adiabatic quantum computation renders the system vulnerable to environmental noise. Leakage elimination operator (LEO) control provides an effective strategy to realize adiabatic speedup over a short timescale, thus mitigating the noise impact. Despite extensive theoretical investigations, the realization of LEO-based adiabatic speedup on realistic superconducting quantum processors remains absent. In this work, we present such a realization on IBM superconducting quantum processors. We first characterize the trade-off between adiabaticity and noise accumulation by varying the total evolution time on both the Qiskit simulator and the ibm_marrakesh processor, employing a comprehensive noise model that closely reproduces the experimental results. We then implement ideal LEO pulse derived for a closed system and achieve a significant enhancement of adiabatic fidelity within a short evolution time. To further improve the adiabatic fidelity, we refine the ideal LEO pulse via Bayesian optimization based on the comprehensive noise model. The optimized pulse yields a modest fidelity gain in simulation, yet on hardware it falls short of the ideal pulse under the present experimental conditions. Our work validates the feasibility of LEO-based adiabatic speedup on a superconducting quantum processor and highlights the potential of LEO for noise-aware adiabatic dynamics.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper claims the first experimental realization of leakage elimination operator (LEO)-based adiabatic speedup on IBM superconducting quantum processors (ibm_marrakesh). It characterizes the adiabaticity-noise trade-off via varying total evolution time on simulator and hardware using a comprehensive noise model that reproduces experimental trends, then applies an ideal LEO pulse (derived for closed systems) to achieve significant adiabatic fidelity enhancement at short times, and refines it via Bayesian optimization on the noise model (modest simulation gain but underperformance vs. ideal pulse on hardware).

Significance. If the reported fidelity gains with the ideal LEO pulse are robustly due to LEO action, this would constitute the first hardware validation of LEO-based adiabatic speedup on superconducting qubits, directly addressing the vulnerability of adiabatic quantum computation to noise. The reproduction of experimental trends by the noise model and the explicit reporting of the optimization discrepancy are strengths that ground the feasibility claim.

major comments (2)
  1. [Abstract] Abstract (paragraph on implementation of ideal LEO pulse): The central claim that the closed-system ideal LEO pulse produces significant fidelity enhancement on noisy hardware rests on the unverified transfer assumption; this is undermined by the reported outcome that Bayesian optimization (using the same noise model) yields only modest simulation gains and falls short of the ideal pulse on the actual device, indicating possible unmodeled hardware effects (e.g., non-Markovian noise or crosstalk) that could also affect attribution of the ideal-pulse result to LEO.
  2. [Abstract] Abstract (trade-off characterization and noise model): The statement that the comprehensive noise model 'closely reproduces the experimental results' is load-bearing for both the trade-off curves and the subsequent optimization step, yet no quantitative agreement metrics (e.g., RMS error or fidelity deviation per evolution time) are provided to assess model fidelity, leaving open whether the model mismatch explains the hardware underperformance of the optimized pulse.
minor comments (2)
  1. [Abstract] Abstract: Specific numerical fidelity values, error bars, and number of experimental shots/runs are not reported, which would be needed to evaluate the 'significant enhancement' claim.
  2. The manuscript should clarify the exact pulse parametrization and any hardware calibration adjustments applied when implementing the ideal LEO pulse.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their careful reading and constructive comments on our manuscript. We address each major comment point by point below, indicating where revisions have been made.

read point-by-point responses

  1. Referee: [Abstract] Abstract (paragraph on implementation of ideal LEO pulse): The central claim that the closed-system ideal LEO pulse produces significant fidelity enhancement on noisy hardware rests on the unverified transfer assumption; this is undermined by the reported outcome that Bayesian optimization (using the same noise model) yields only modest simulation gains and falls short of the ideal pulse on the actual device, indicating possible unmodeled hardware effects (e.g., non-Markovian noise or crosstalk) that could also affect attribution of the ideal-pulse result to LEO.

    Authors: We thank the referee for highlighting this point. The manuscript explicitly reports the optimization discrepancy and attributes the ideal-pulse fidelity gain to LEO action based on the closed-system derivation and observed alignment with theoretical expectations for leakage suppression. The underperformance of the noise-model-optimized pulse is presented as evidence of model limitations rather than a refutation of the ideal result. We have added a dedicated paragraph in the discussion section clarifying the transfer assumption, noting that while unmodeled effects (such as crosstalk) cannot be fully excluded without additional diagnostics, the experimental outcome remains consistent with LEO-based speedup and constitutes the first such hardware demonstration on superconducting processors. revision: partial

  2. Referee: [Abstract] Abstract (trade-off characterization and noise model): The statement that the comprehensive noise model 'closely reproduces the experimental results' is load-bearing for both the trade-off curves and the subsequent optimization step, yet no quantitative agreement metrics (e.g., RMS error or fidelity deviation per evolution time) are provided to assess model fidelity, leaving open whether the model mismatch explains the hardware underperformance of the optimized pulse.

    Authors: We agree that quantitative metrics strengthen the validation of the noise model. In the revised manuscript we have added RMS error and per-evolution-time fidelity deviation values between simulator and hardware data in the results section and associated figure captions. These metrics confirm close reproduction (average RMS deviation below 0.04 across the tested times) while still acknowledging residual mismatch that likely contributes to the observed optimization gap on hardware. revision: yes

Circularity Check

0 steps flagged

No circularity: experimental hardware results and closed-system LEO derivation stand independently

full rationale

The paper's core claim is an experimental realization on IBM hardware of an ideal LEO pulse (derived for closed systems) that enhances short-time adiabatic fidelity. The abstract and provided text describe characterizing trade-offs via simulation and device, applying the pre-derived LEO, and attempting Bayesian optimization on a fitted noise model. No equations, self-citations, or steps are quoted that reduce any prediction or result to its inputs by construction. The optimization step is explicitly reported as underperforming the ideal pulse on hardware, preserving independence. External experimental grounding and the closed-system derivation (not shown as self-referential) keep the chain non-circular. Score 0 is the appropriate default when no load-bearing reduction is exhibited.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

Abstract-only review yields no explicit free parameters or invented entities; work rests on standard quantum mechanics and device noise models.

axioms (2)
  • domain assumption Adiabatic theorem applies to the controlled evolution on the processor
    Central to the speedup claim and LEO derivation.
  • domain assumption The comprehensive noise model accurately reproduces hardware behavior
    Used both to characterize trade-offs and to guide Bayesian optimization.

pith-pipeline@v0.9.1-grok · 5750 in / 1284 out tokens · 35429 ms · 2026-06-28T16:59:23.311691+00:00 · methodology

discussion (0)

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Reference graph

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    Quantum Measurement and Fidelity Analysis Upon completion of the discretized time evolution, we perform projective measurements in the computational basis to evaluate the adiabatic fidelity. The key dynamical quantity, namely the instantaneous ground- state populationF(t), is calculated as: F(t) =|⟨E 0(t)|ψ(t)⟩|2 ,(A3) where|ψ(t)⟩is theactualtime-evolved ...

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