The Energy-Advantage Frontier of Random Circuit Sampling Across the Simulability Transition

We introduce the energy-advantage frontier of random circuit sampling (RCS)—the locus in the noise-rate/size plane where the classical and quantum energy-to-solution are equal—and locate it relative to the noise-induced classical-simulability transition. Our firm, model-free result is that the classical sampling-energy floor collapses sharply across the transition, exhibiting a finite-size scaling collapse over exact systems n≤12 (with a collapse exponent of order unity). Built on it, the energy-advantage frontier is distinct from the computational (wall-clock) frontier: in the exascale-classical, few-femtojoule regime, the energy frontier is the more noise-robust, so an energy advantage can persist where a time advantage does not—a projection, not a deployment claim, whose direction reverses outside that regime. We give a conditional Landauer lower bound for sampling, RE≡Ecl/Eq≳2(1.0±0.2)n/n under standard RCS hardness, package RE as a single figure of merit computed by a released open tool (exs), and map an energy-normalized cross-entropy witness within a cost model. A run on a 156-qubit IBM Heron processor tests the fidelity model (no energy is measured on hardware) and shows real noise exceeds the depolarizing idealization, so quoted frontier locations are upper bounds.

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Publication Details

Journal
Mathematics
Published
2026-06-30
DOI
https://doi.org/10.3390/math14132314
Primary Topic
Low-power high-performance VLSI design
Type
article
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article

The Energy-Advantage Frontier of Random Circuit Sampling Across the Simulability Transition

Taiki Tanimae, Hikaru Wakaura
Mathematics
Low-power high-performance VLSI design
article

The Energy-Advantage Frontier of Random Circuit Sampling Across the Simulability Transition

Taiki Tanimae, Hikaru Wakaura
article en

Abstract

We introduce the energy-advantage frontier of random circuit sampling (RCS)—the locus in the noise-rate/size plane where the classical and quantum energy-to-solution are equal—and locate it relative to the noise-induced classical-simulability transition. Our firm, model-free result is that the classical sampling-energy floor collapses sharply across the transition, exhibiting a finite-size scaling collapse over exact systems n≤12 (with a collapse exponent of order unity). Built on it, the energy-advantage frontier is distinct from the computational (wall-clock) frontier: in the exascale-classical, few-femtojoule regime, the energy frontier is the more noise-robust, so an energy advantage can persist where a time advantage does not—a projection, not a deployment claim, whose direction reverses outside that regime. We give a conditional Landauer lower bound for sampling, RE≡Ecl/Eq≳2(1.0±0.2)n/n under standard RCS hardness, package RE as a single figure of merit computed by a released open tool (exs), and map an energy-normalized cross-entropy witness within a cost model. A run on a 156-qubit IBM Heron processor tests the fidelity model (no energy is measured on hardware) and shows real noise exceeds the depolarizing idealization, so quoted frontier locations are upper bounds.

MathematicsVol. 14(13)
Quantum Applied Science and Research (United States) (US)
Affordable and clean energy
Openalex Percentile: Top 12%
Low-power high-performance VLSI design
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