What does this research mean for the field?

Every computational substrate has a finite ordering capacity per unit of its own time, a fundamental law that, when respected by software, significantly improves the predictability and performance of quantum computers. Novelty: ClaimNovelty.NOVEL_FINDING. Consensus alignment: ConsensusAlignment.ESTABLISHES_NEW_DIRECTION.

What question did this study set out to answer?

To formulate and experimentally test a fundamental law of ordering capacity per unit time (λ ≤ σ) across physical computing substrates.

August 26, 2026Open Access

Time, Capacity, and the Self-Verifying Machine

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To formulate and experimentally test a fundamental law of ordering capacity per unit time (λ ≤ σ) across physical computing substrates.
Conducted preregistered benchmarks across cloud-accessible quantum hardware comparing capacity-constrained software against standard vendor toolchains.
Evaluated sealed cross-chip predictive forecasts and tracked quantum coherence duration under artifact control protocols with preregistered endpoints.
Achieved 96 preregistered head-to-head benchmark wins against native vendor software toolchains.
Demonstrated sealed cross-chip forecasts with a 1.6-point mean error.
Extended quantum coherence 3.4-fold under strict artifact control.

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Implication

Experimental evaluation demonstrates quantum coherence extension and performance gains under capacity constraints, suggesting substrate-independent limits for computation.

Cite This Study

Raffael Kasprzak (2026) studied this question.

synapsesocial.com/papers/6a8e9bcc451774b83f3b4b2f https://doi.org/10.5281/zenodo.22078286

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Implication

Experimental evaluation demonstrates quantum coherence extension and performance gains under capacity constraints, suggesting substrate-independent limits for computation.

Time, Capacity, and the Self-Verifying Machine

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Implication

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Time, Capacity, and the Self-Verifying Machine

Key Points

Discussion

Implication

Cite This Study

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