Spectral Benchmarking of Holographic Quantum Simulations: A Proposed Framework for Escaping the Artifact Zone
Abstract
The simulation of quantum gravity on near-term quantum processors is hindered by a critical tension between hardware feasibility and physical fidelity, creating an “Artifact Zone” where simplified models produce misleading, non-physical results. This paper addresses this challenge by proposing a robust benchmarking framework to certify the structural integrity of holographic quantum simulations. We argue that dynamical metrics like Out-of-Time-Ordered Correlators (OTOCs) can be ambiguous in noisy systems, and advocate for the adoption of a structural metric based on Random Matrix Theory (RMT): the adjacent gap ratio, or r-statistic. Our methodology involves a computational experiment using synthetic Hamiltonians to model both integrable (artifact) and chaotic (holographic) systems. We calculate the r-statistic for these ensembles and analyze its reliability under conditions relevant to Noisy Intermediate-Scale Quantum (NISQ) hardware, including small system sizes and simulated noise. The r-statistic provides a statistically unambiguous distinction, yielding a value of ≈0.39 for integrable systems and ≈0.60 for chaotic systems, even for small numbers of qubits (N=8 to 14) and in the presence of noise. Based on this evidence, we propose a new standard for validation: a “Structural Chaos Benchmark.” We argue that future holographic simulation claims should report the r-statistic of the effective Hamiltonian to prove the system is structurally capable of chaotic evolution. This provides a clear, falsifiable method to escape the Artifact Zone, raising the standard of evidence for quantum advantage claims and guiding the development of more physically faithful quantum simulators.
Fields of Study & Subjects
Quantum chaos and dynamical systems
Quantum Computing Algorithms and Architecture
Quantum many-body systems
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 11 January 2026
- Language
- EN
- Document type
- Preprint