Variational Quantum Circuits

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Overview

Variational quantum circuits use adjustable gate parameters to prepare quantum states or make predictions, with a classical optimizer typically updating those parameters from measured outcomes. Common approaches include hardware-efficient and problem-inspired ansätze, data re-uploading, quantum kernels, and hybrid models for tasks such as classification, forecasting, and molecular simulation. Work studies how circuit depth, entanglement, initialization, gradient methods, and measurement choices affect expressivity and trainability, especially under barren plateaus and hardware noise. Compact circuits have shown promise on selected benchmarks, but broad practical advantage remains unsettled: results depend on task and hardware, and careful comparisons with tuned, capacity-matched classical models are essential.

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14 papers in the last four weeks, up 75% on the four weeks before. 0.1% of all new papers.

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  1. Layered Quantum Architecture Search for 3D Point Cloud Classification

    Mar 20, 2026Natacha Kuete Meli, Jovita Lukasik, Vladislav Golyanik +1Quantum Neural NetworksPoint Cloud Classification

    University of Siegen · MPI for Informatics, SIC

  2. Hybrid Classical-Quantum Transfer Learning with Noisy Quantum Circuits

    Mar 17, 2026D. Martín-Pérez, F. Rodríguez-Díaz, D. Gutiérrez-Avilés +2Quantum Machine LearningHybrid Quantum-Classical ML

    Data Science and Big Data Lab, Pablo de Olavide University, Seville, Spain · Department of Computer Science, University of Seville, Seville, Spain

  3. IQP Born Machines under Data-dependent and Agnostic Initialization Strategies

    Mar 15, 2026Sacha Lerch, Joseph Bowles, Ricard Puig +3Quantum Machine LearningQuantum Generative Modeling

    Institute of Physics, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland · Centre for Quantum Science and Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland · Xanadu, Toronto, ON, M5G 2C8, Canada +3

  4. How to find expressible and trainable parameterized quantum circuits?

    Mar 15, 2026Peter Röseler, Dennis Willsch, Kristel MichielsenVariational Quantum CircuitsQuantum Circuit Trainability

    Jülich Supercomputing Centre, Forschungszentrum Jülich, 52425 Jülich, Germany · Universität zu Köln, 50923 Köln, Germany · Faculty of Medical Engineering and Technomathematics, University of Applied Sciences Aachen, 52428 Jülich, Germany +1

  5. Scaling Quantum Machine Learning without Tricks: Full-Resolution and Diverse Image Generation

    Feb 27, 2026Jonas Jäger, Florian J. Kiwit, Carlos A. RiofríoQuantum Generative ModelingImage Generation

    BMW Group, Munich, Germany · Department of Computer Science and Institute of Applied Mathematics, University of British Columbia (UBC), Vancouver, Canada · Stewart Blusson Quantum Matter Institute (QMI), Vancouver, Canada +1

  6. Comparing Classical and Quantum Variational Classifiers on the XOR Problem

    Feb 27, 2026Miras Seilkhan, Adilbek TaizhanovQuantum Machine LearningVariational Quantum Circuits

  7. Long Range Frequency Tuning for QML

    Feb 26, 2026Michael Poppel, Markus Baumann, Sebastian Wölckert +2Quantum Machine LearningVariational Quantum Circuits

    LMU Munich & Aqarios GmbH, Munich, Germany · LMU Munich, Munich, Germany

  8. Quantum Scrambling Born Machine

    Feb 19, 2026Marcin PłodzieńQuantum Generative ModelingVariational Quantum Circuits

    Qilimanjaro Quantum Tech, Carrer de Veneçuela 74, 08019 Barcelona, Spain

  9. Illustration of Barren Plateaus in Quantum Computing

    Feb 18, 2026Gerhard Stenzel, Tobias Rohe, Michael Kölle +3Variational Quantum CircuitsQuantum Circuit Trainability

    LMU Munich

  10. Reinforcement Learning for Parameterized Quantum State Preparation: A Comparative Study

    Feb 18, 2026Gerhard Stenzel, Isabella Debelic, Michael Kölle +4Quantum State PreparationQuantum RL

    LMU Munich Department of Computer Science Chair of Mobile and Distributed Systems

  11. Quantum Attention by Overlap Interference: Predicting Classical and Many-Body Quantum Sequences

    Feb 6, 2026Alessio Pecilli, Matteo RosatiSelf-AttentionTransformer Attention

    Dipartimento di Ingegneria Civile, Informatica e delle Tecnologie Aeronautiche, Universit`a degli Studi Roma Tre, Via della Vasca Navale 79, 00146 Rome, Italy

  12. Trainability-Oriented Hybrid Quantum Regression via Geometric Preconditioning and Curriculum Optimization

    Jan 17, 2026Qingyu Meng, Yangshuai WangQuantum Machine LearningHybrid Quantum-Classical ML

    Shanghai Jiao Tong University-Chongqing Institute of Artificial Intelligence, Chongqing 401329, China. · Department of Mathematics, National University of Singapore, 10 Lower Kent Ridge Road, Singapore.

  13. Graph-Based Bayesian Optimization for Quantum Circuit Architecture Search with Uncertainty Calibrated Surrogates

    Dec 10, 2025Prashant Kumar Choudhary, Nouhaila Innan, Muhammad Shafique +1Bayesian OptimizationVariational Quantum Circuits

    Department of Physics, Indian Institute of Technology (BHU), Varanasi, Uttar Pradesh, India · eBRAIN Lab, Division of Engineering, New York University Abu Dhabi (NYUAD), Abu Dhabi, UAE · Center for Quantum and Topological Systems (CQTS), NYUAD Research Institute, NYUAD, Abu Dhabi, UAE

  14. A Versatile Variational Quantum Kernel Framework for Non-Trivial Classification

    Nov 13, 2025Jiang Yuhan, Matthew OttenQuantum Kernel MethodsVariational Quantum Circuits

    Department of Physics, University of Wisconsin–Madison, Madison, WI 53706, USA · Department of Chemistry, University of Wisconsin–Madison, Madison, WI 53706, USA

  15. Quantum Variational Activation Functions Empower Kolmogorov-Arnold Networks

    Sep 17, 2025Jiun-Cheng Jiang, Morris Yu-Chao Huang, Tianlong Chen +1Quantum Machine LearningQuantum-Inspired ML

    Department of Physics and Center for Theoretical Physics, National Taiwan University, Taipei 106319, Taiwan · Physics Division, National Center for Theoretical Sciences, National Taiwan University, Taipei 106319, Taiwan · Department of Computer Science, University of North Carolina at Chapel Hill, NC 27514, USA +1

  16. Quantum Adaptive Self-Attention for Quantum Transformer Models

    Apr 5, 2025Chi-Sheng Chen, En-Jui KuoHybrid Quantum-Classical MLTransformer Attention

    Department of Electrophysics, National Yang Ming Chiao Tung University, Hsinchu, Taiwan

  17. Quantum State Preparation with the QNN-based SRBB Algorithm

    Mar 17, 2025Marco Mordacci, Giacomo Belli, Michele AmorettiVariational Quantum CircuitsQuantum State Preparation

    Quantum Software Laboratory University of Parma Parma, Italy