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Quantum Machine Learning Quantum Chemistry

Variational Quantum Brushes

arXiv
Authors: Jui-Ting Lu, Henrique Ennes, Chih-Kang Huang, Ali Abbassi

Year

2025

Paper ID

36078

Status

Preprint

Abstract Read

~2 min

Abstract Words

97

Citations

N/A

Abstract

Quantum brushes are computational arts software introduced by Ferreira et al (2025) that leverage quantum behavior to generate novel artistic effects. In this outreach paper, we introduce the mathematical framework and describe the implementation of two quantum brushes based on variational quantum algorithms, Steerable and Chemical. While Steerable uses quantum geometric control theory to merge two works of art, Chemical mimics variational eigensolvers for estimating molecular ground energies to evolve colors on an underlying canvas. The implementation of both brushes is available open-source at https://github.com/moth-quantum/QuantumBrush and is fully compatible with the original quantum brushes.

Why This Paper Matters

  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
  • It adds a 2025 reference point for readers tracking recent quantum research.
  • Quantum brushes are computational arts software introduced by Ferreira et al (2025) that leverage quantum behavior to generate novel artistic effects.

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References & Citation Signals

[1] DOI https://doi.org/arXiv:2512.24173 [2] arXiv https://arxiv.org/abs/2512.24173 [3] Publisher https://arxiv.org/abs/2512.24173

Local Citation Graph (Related-Paper Links)

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