Quantum Generative Modeling

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Overview

Quantum generative modeling studies how to create samples from learned distributions, including images, molecules, signals, and quantum states. Its main approaches include quantum circuit Born machines and generative adversarial networks, diffusion and flow-matching models, and quantum annealing, often combined with classical neural networks. These methods are explored for sampling complex distributions, preparing quantum states, and generating data for tasks with limited training examples. A central open question is whether they offer reliable benefits over well-matched classical models, given challenges in trainability, noise, hardware scale, and fair evaluation.

Latest papers

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54 papers8 papers in the last four weeks, up 14% on the four weeks before. 0.0% of all new papers.

  1. From Characterization To Construction: Generative Quantum Circuit Synthesis from Gate Set Tomography Data

    May 2, 2026King Yiu Yu, Aritra Sarkar, Erbing Hua +3Quantum Circuit CompilationQuantum Generative Modeling

    1Quantum and Computer Engineering, Delft University of Technology, The Netherlands · 2QuTech, Delft University of Technology, The Netherlands · 3Kavli Institute of Nanoscience Delft, Delft University of Technology, The Netherlands

  2. HHL with a Coherent Fourier Oracle: A Proof-of-Concept Quantum Architecture for Joint Melody-Harmony Generation

    Apr 13, 2026Alexis KirkeMusic GenerationSymbolic Music Generation

  3. Minimizing classical resources in variational measurement-based quantum computation for generative modeling

    Apr 13, 2026Arunava Majumder, Hendrik Poulsen Nautrup, Hans J. BriegelQuantum Generative Modeling

    University of Innsbruck, Department of Theoretical Physics, Technikerstraße 21a, A-6020 Innsbruck, Austria.

  4. Learning and Generating Mixed States Prepared by Shallow Channel Circuits

    Apr 1, 2026Fangjun Hu, Christian Kokail, Milan Kornjača +5Quantum Generative ModelingQuantum State Preparation

    QuEra Computing Inc. · School of Engineering and Applied Sciences, Harvard University · JILA and Department of Physics, CU Boulder

  5. Multi-Mode Quantum Annealing for Generative Representation Learning with Boltzmann Priors

    Apr 1, 2026Gilhan Kim, Daniel K. ParkQuantum Generative ModelingVariational Autoencoders

    Department of Statistics and Data Science, Yonsei University, Seoul 03722, Republic of Korea · Department of Applied Statistics, Yonsei University, Seoul 03722, Republic of Korea · Department of Quantum Information, Yonsei University, Seoul 03722, Republic of Korea

  6. MolPaQ: Modular Quantum-Classical Patch Learning for Interpretable Molecular Generation

    Mar 27, 2026Syed Rameez Naqvi, Lu PengMolecular Graph GenerationQuantum Generative Modeling

    Department of Computer Science, Tulane University, New Orleans, LA, USA.

  7. SpinGQE: A Generative Quantum Eigensolver for Spin Hamiltonians

    Mar 25, 2026Alexander Holden, Moinul Hossain Rahat, Nii Osae Osae DadeQuantum Circuit SynthesisVariational Quantum Algorithms

    Mindbeam AI† · Department of Computer and Data Sciences, Case Western Reserve University

  8. Transcending Classical Neural Network Boundaries: A Quantum-Classical Synergistic Paradigm for Seismic Data Processing

    Mar 25, 2026Zhengyi Yuan, Xintong Dong, Xinyang Wang +2Quantum Neural NetworksHybrid Quantum-Classical ML

    College of Instrumentation and Electrical Engineering, Jilin University, Changchun 130026, China.

  9. Latent Style-based Quantum Wasserstein GAN for Drug Design

    Mar 23, 2026Julien Baglio, Yacine Haddad, Richard PolifkaMolecular GenerationQuantum Generative Modeling

    Center for Quantum Computing and Quantum Coherence (QC2), Department of Physics, University of Basel, Klingelbergstrasse 82, CH-4056 Basel, Switzerland · QuantumBasel, Schorenweg 44b, CH-4144 Arlesheim, Switzerland · Laboratory for High Energy Physics (LHEP), Physics Institute, Faculty of Sciences, University of Bern, Sidlerstrasse 5, CH-3012 Bern, Switzerland +1

  10. End-to-End QGAN-Based Image Synthesis via Neural Noise Encoding and Intensity Calibration

    Mar 19, 2026Xue Yang, Rigui Zhou, Shizheng Jia +5Quantum Generative ModelingImage Generation

    Shanghai Maritime University · Agency for Science, Technology and Research · Singapore University of Technology and Design +1

  11. Generative AI for Quantum Circuits and Quantum Code: A Technical Review and Taxonomy

    Mar 17, 2026Juhani MerilehtoQuantum Circuit SynthesisQuantum Generative Modeling

    University of Vaasa & University of Turku

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

    Mar 15, 2026Sacha Lerch, Joseph Bowles, Ricard Puig +3Quantum Circuit Born MachinesQuantum Machine Learning

    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

  13. Score Reversal Is Not Free for Quantum Diffusion Models

    Mar 6, 2026Ammar FayadQuantum Generative Modeling

    Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA

  14. Toward Generative Quantum Utility via Correlation-Complexity Map

    Mar 6, 2026Chen-Yu Liu, Leonardo Placidi, Eric Brunner +1Quantum Generative Modeling

    Quantinuum, Partnership House, London, UK · Quantinuum, Otemachi Financial City Grand Cube, Tokyo, Japan

  15. Implementation of Quantum Implicit Neural Representation in Deterministic and Probabilistic Autoencoders for Image Reconstruction/Generation Tasks

    Mar 6, 2026Saadet Müzehher ErenVariational AutoencodersQuantum Generative Modeling

    Department of Physics, Izmir Institute of Technology, Gülbahçe, Urla, 35430, Izmir, Turkey.

  16. 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

  17. Learning Quantum Data Distribution via Chaotic Quantum Diffusion Model

    Feb 25, 2026Quoc Hoan Tran, Koki Chinzei, Yasuhiro Endo +1Quantum Generative ModelingDiffusion Models

    Quantum Laboratory, Fujitsu Research, Fujitsu Limited, Kawasaki, Kanagawa 211-8588, Japan

  18. Stochastic Neural Networks for Quantum Devices

    Feb 24, 2026Bodo Rosenhahn, Tobias J. Osborne, Christoph HircheQuantum Neural NetworksHybrid Quantum-Classical ML

    Institute for Information Processing (tnt/L3S), Leibniz Universität Hannover, Germany · Institute for Theoretical Physics (ITP/L3S), Leibniz Universität Hannover, Germany

  19. Kaiwu-PyTorch-Plugin: Bridging Deep Learning and Photonic Quantum Computing for Energy-Based Models and Active Sample Selection

    Feb 22, 2026Hongdong Zhu, Qi Gao, Yin Ma +6Hybrid Quantum-Classical MLQuantum Machine Learning

    Beijing QBoson Quantum Technology Co., Ltd. · Chinese Academy of Sciences

  20. Quantum Scrambling Born Machine

    Feb 19, 2026Marcin PłodzieńQuantum Circuit Born MachinesQuantum Generative Modeling

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

  21. Molecular Design beyond Training Data with Novel Extended Objective Functionals of Generative AI Models Driven by Quantum Annealing Computer

    Feb 17, 2026Hayato Kunugi, Mohsen Rahmani, Yosuke Iyama +8Molecular GenerationQuantum Generative Modeling

    Inovation to Implementation Laboratories, Central Pharmaceutical Research Institute, Japan Tobacco Inc., 1-1 Murasaki-cho, Takatsuki, 569-1125, Japan. · D-Wave Systems Inc., 3033 Beta Ave, Burnaby, V5G 4M9, Canada.

  22. From Classical to Quantum: Extending Prometheus for Unsupervised Discovery of Phase Transitions in Three Dimensions and Quantum Systems

    Feb 16, 2026Brandon Yee, Wilson Collins, Pairie Koh +1Phase TransitionsQuantum Many-Body Physics

    Physics Lab, Yee Collins Research Group

  23. Quantum Flow Matching

    Aug 17, 2025Zidong Cui, Pan Zhang, Ying TangFlow MatchingQuantum Generative Modeling

    Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China · Institute of Theoretical Physics, Chinese Academy of Sciences, Beijing 100190, China · School of Fundamental Physics and Mathematical Sciences, Hangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China +3

  24. Physics-inspired Generative AI models via real hardware-based noisy quantum diffusion

    May 28, 2025Marco Parigi, Stefano Martina, Francesco Aldo Venturelli +1Quantum Generative ModelingDiffusion-Based Image Generation

    Department of Physics and Astronomy, University of Florence, Via Sansone 1, Sesto Fiorentino, 50019, Florence, Italy. · LENS - European Laboratory for Non-Linear Spectroscopy, University of Florence, Via Nello Carrara 1, Sesto Fiorentino, 50019, Florence, Italy. · Department of Engineering, Pompeu Fabra, T`anger 122-140, Barcelona, 08018, Barcelona, Spain.