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Trapped Ion Quantum Computing Quantum Simulation

Experimental demonstration of the absence of noise-induced barren plateaus using information content landscape analysis

arXiv
Authors: Sebastian Schmitt, Linus Ekstrøm, Alberto Bottarelli, Xavier Bonet-Monroig

Year

2026

Paper ID

15604

Status

Preprint

Abstract Read

~2 min

Abstract Words

239

Citations

N/A

Abstract

Variational quantum algorithms are a very promising tool for near-term quantum computing. However, despite their flexibility and wide applicability, their performance is fundamentally limited by Barren Plateaus (BP), where gradients vanish and optimization becomes intractable. Noise-Induced Barren Plateaus (NIBP) are particularly interesting, as they are predicted to arise due to noise accumulation independent of circuit structure. We experimentally study NIBP on IBM quantum hardware and demonstrate their absence under non-unital amplitude damping characterized by the qubit's T1 coherence times. We use Information Content Landscape Analysis (ICLA) to efficiently estimate gradient norms for circuits ranging from 8 to 102 qubits, with hundreds of parameters and circuit runtimes of hundreds of microseconds. Classical simulations of the 8-qubit case under noiseless, depolarizing, amplitude damping, and dephasing noise models serve as a baseline comparison. We thoroughly analyze the experimental results considering calibration data, shot-noise, and circuit structure. We robustly observe that the gradient magnitude saturates beyond a characteristic circuit runtime, in contrast with the exponential decay expected from NIBP. Using recent theoretical results, we corroborate that under T1-dominated noise NIBP do not occur and extract an effective T1eff that is significantly shorter than suggested by standard calibration data. Our results experimentally confirm recent predictions on the absence of NIBP under non-unital noise. These findings also indicate that conventional benchmarking metrics based on average values for device characteristics may be insufficient to predict variational algorithm performance, but full distributions need to be considered.

Why This Paper Matters

  • This paper contributes to the Quantum Simulation research area in the Quantum Articles archive.
  • It adds a 2026 reference point for readers tracking recent quantum research.
  • Variational quantum algorithms are a very promising tool for near-term quantum computing.

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