Layered Quantum Architecture Search for 3D Point Cloud Classification

Quantum Physics [Submitted on 20 Mar 2026] Layered Quantum Architecture Search for 3D Point Cloud Classification Natacha Kuete Meli, Jovita Lukasik, Vladislav Golyanik, Michael Moeller We introduce layered Quantum Architecture Search (layered-QAS), a strategy inspired by classical network morphism that designs Parametrised Quantum Circuit (PQC) architectures by progressively growing and adapting them. PQCs offer strong expressiveness with relatively few parameters, yet they lack standard architectural layers (e.g., convolution, attention) that encode inductive biases for a given learning task. To assess the effectiveness of our method, we focus on 3D point cloud classification as a challenging yet highly structured problem. Whereas prior work on this task has used PQCs only as feature extractors for classical classifiers, our approach uses the PQC as the main building block of the classification model. Simulations show that our layered-QAS mitigates barren plateau, outperforms quantum-adapted local and evolutionary QAS baselines, and achieves state-of-the-art results among PQC-based methods on the ModelNet dataset. Subjects: Quantum Physics (quant-ph); Computer Vision and Pattern Recognition (cs.CV); Machine Learning (cs.LG) Cite as: arXiv:2603.20024 [quant-ph]   (or arXiv:2603.20024v1 [quant-ph] for this version)   https://doi.org/10.48550/arXiv.2603.20024 Focus to learn more Journal reference: International Conference on 3D Vision (3DV) 2026 Submission history From: Natacha Kuete Meli [view email] [v1] Fri, 20 Mar 2026 15:10:15 UTC (3,586 KB) Access Paper: view license Current browse context: quant-ph < prev   |   next > new | recent | 2026-03 Change to browse by: cs cs.CV cs.LG References & Citations INSPIRE HEP NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)