Polynomially trainable quantum landscapes with BQP-hard costs

Trainable quantum landscapes and computationally hard costs can coexist in near-Clifford patches, proving that avoiding flat gradients does not make a model classically easy to simulate.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-25
DOI
https://doi.org/10.5281/zenodo.22948793
Primary Topic
Quantum Computing Algorithms and Architecture
Type
preprint
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preprint

Polynomially trainable quantum landscapes with BQP-hard costs

Hyun-Ho Cha
Zenodo (CERN European Organization for Nuclear Research)
Quantum Computing Algorithms and Architecture
preprint

Polynomially trainable quantum landscapes with BQP-hard costs

Hyun-Ho Cha
preprint en

Abstract

Trainable quantum landscapes and computationally hard costs can coexist in near-Clifford patches, proving that avoiding flat gradients does not make a model classically easy to simulate.

Zenodo (CERN European Organization for Nuclear Research)
Seoul National University (KR)
Sustainable cities and communities
Quantum Computing Algorithms and Architecture
DOIOpen Access PDFOpenAlex
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Polynomially trainable quantum landscapes with BQP-hard costs — Hyun-Ho Cha · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS