Barren Plateaus

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Overview

Barren plateaus are optimization landscapes in variational quantum circuits where gradient signals become exponentially small as systems grow, making parameter updates ineffective under finite measurement budgets. Theory connects them to random, highly expressive circuits and concentration of measure, while practical work studies gradient variance, Fisher information, and Lie-algebra structure in VQE, QAOA, and quantum-learning tasks. Mitigation approaches include local costs and readouts, symmetry- or subspace-preserving ansätze, controlled circuit growth, and informed initialization; other work learns update rules or changes objectives to amplify usable signals. The central tension is that expressivity and entanglement can improve representation while suppressing gradients, but shallow and structured circuits can have different, sometimes rugged rather than barren, landscapes—and a diagnostic alone does not establish easier end-to-end optimization.

Latest papers

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22 papers2 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

  1. Quantum-Classical Neural Networks for Solving Lindblad Master Equations

    Oct 15, 2026Rafael Florencio Díaz, Julio Guerrero García, Elvira Romera GutiérrezVariational Quantum AlgorithmsHybrid Quantum-Classical ML

    Departamento de Matem´aticas, Universidad de Ja´en, Edificio de Servicios Generales - Campus Cient´ıfico Tecnol´ogico de Linares. Avda. de la Universidad (Cintur´on Sur), s/n, Linares, 23700, Ja´en, Espa˜na. · C´atedra de Energ´ıa y Tecnolog´ıas Cu´anticas, Universidad de Granada, Spain. · Departamento de Matem´aticas, Universidad de Ja´en, Campus Las Lagunillas, Ja´en, 23071, Ja´en, Espa˜na. +1

  2. Q-Capsule: A Localized Capsule-Based Quantum Neural Architecture for Barren Plateau Mitigation

    Oct 8, 2026Awal Ahmed Fime, Tasfia Zaman Samiha, Saika Zaman +4Quantum Neural NetworksQuantum Circuit Trainability

    Florida Atlantic University, Boca Raton, Florida, USA · Khulna University of Engineering & Technology, Khulna, Bangladesh · Southern Illinois University Carbondale, Carbondale, Illinois, USA

  3. Modeling quantum neural network gradient with reinforcement learning

    Sep 25, 2026Nhan Trong Luu, Duong Trung Luu, Nam Ngoc Pham +1Quantum Neural NetworksQuantum Circuit Trainability

    College of Information and Communication Technology, Can Tho University, Can Tho, Vietnam · College of Engineering and Computer Science, VinUniversity, Hanoi, Vietnam · Center for Digital Transformation and Communications, Can Tho University, Can Tho, Vietnam +1

  4. From Trainability Diagnostics to Optimization Claims: Boundaries and Controls in Variational Quantum Optimization

    Sep 18, 2026Pilsung KangVariational Quantum AlgorithmsGradient Projection

  5. Dynamical Lie Algebras Cannot Describe Shallow QAOA: Cragged Terrains, Barren Plateaus, and Empirical Hardness Models

    Aug 4, 2026Harrison Copp, Charlton Li, Anžej Margeta-Cacace +1Barren PlateausQuantum Approximate Optimization Algorithm

    Yale University

  6. LLM-Guided Initialization for Accelerated Hybrid Quantum-Classical Medical Image Classification

    Jul 29, 2026Riza Alaudin Syah, Irwan Alnarus Kautsar, Haza Nuzly Bin Abdull HamedNeural Network InitializationHybrid Quantum-Classical ML

    Faculty of Computing Universiti Teknologi Malaysia Johor Bahru, Malaysia · Remote Student based in Jakarta, Indonesia · Informatics Department Faculty of Science and Technology Universitas Muhammadiyah Sidoarjo Sidoarjo, Indonesia

  7. Stacking the Deck: Tunable Trainability in Stacked LCUs

    Jul 27, 2026Nikhil Khatri, Stefan Zohren, Gabriel MatosBarren PlateausQuantum Circuit Simulation

    Machine Learning Research Group, University of Oxford, United Kingdom · 2Quantinuum, London, United Kingdom

  8. Breaking the One-Dimensional Expressibility-Trainability Tradeoff

    Jul 6, 2026Kyoungho Cho, Yu-Seong Jeon, Jinhyoung Lee +1Quantum Circuit ExpressibilityBarren Plateaus

    Institute for Convergence Research and Education in Advanced Technology, Yonsei University, Seoul 03722, Republic of Korea · Department of Statistics and Data Science, Yonsei University, Seoul 03722, Republic of Korea · Department of Physics, Hanyang University, Seoul 04763, Republic of Korea +2

  9. Beyond the Expressivity-Trainability Paradox: A Dynamical Lie Algebra Perspective on Navigating Barren Plateaus in Quantum Machine Learning

    Jun 30, 2026Kung-Ming Lan, Edward HuangQuantum Machine LearningBarren Plateaus

    Department of Industrial Engineering and Enterprise Information, Tunghai University, Taichung 40704, Taiwan · Department of Industrial and Systems Engineering, 3306 Shelby Center, Auburn University, Auburn, AL, USA

  10. Exponentially many initializations to avoid barren plateaus

    Jun 16, 2026Ankit Kulshrestha, Ricard Puig, Diego García-Martín +4Barren PlateausVariational Quantum Circuits

    Fujitsu Research of America, Santa Clara, CA 95054, USA · Institute of Physics, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland · Centre for Quantum Science and Engineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland +4

  11. Quantum Machine Learning for Industrial Applications

    Jun 12, 2026Léo MonbroussouQuantum Convolutional Neural NetworksQuantum Machine Learning

    Sorbonne Université, Ecole Doctorale Informatique, Télécommunications et Electronique (n° 572), Computer Science

  12. Trainability of IQP Quantum Circuit Born Machines Under Gaussian Initialization

    Jun 8, 2026Gennaro De Luca, Vinayak Sharma, Aviral ShrivastavaQuantum Generative ModelingQuantum Machine Learning

    SCAI, Arizona State University

  13. Quantum Algorithm for Distributed Reduction of Entanglements (QADR): A Trainable and Simulation-Efficient QML Framework

    May 31, 2026Syed Farhan Ahmad, Gregory T. ByrdHybrid Quantum-Classical MLBarren Plateaus

    Department of ECE, North Carolina State University, Raleigh, North Carolina, USA

  14. Latent-Conditioned Parameterized Quantum Circuits as Universal Approximators for Distributions over Quantum States

    May 27, 2026Quoc Hoan Tran, Koki Chinzei, Yasuhiro Endo +1Latent Variable ModelsQuantum Generative Modeling

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

  15. Barren Plateaus as Destructive Interference: A Diagnostic Framework and Implications for Structured Ansatzes

    May 2, 2026Pilsung KangBarren PlateausVariational Quantum Circuits

    Department of Software Science, Dankook University, Yongin, 16890, South Korea

  16. A four-player potential game for barren-plateau-aware quantum ansatz design

    Apr 23, 2026Rubén Darío GuerreroQuantum ChemistryBarren Plateaus

    Parametrized-QC-Graphs Project

  17. Trainability Beyond Linearity in Variational Quantum Objectives

    Apr 20, 2026Gordon Ma, Xiufan LiBarren PlateausVariational Quantum Circuits

    Centre for Quantum Technologies, National University of Singapore, Singapore

  18. Adaptive H-EFT-VA: A Provably Safe Trajectory Through the Trainability-Expressibility Landscape of Variational Quantum Algorithms

    Apr 12, 2026Eyad I. B. HamidQuantum Circuit ExpressibilityVariational Quantum Algorithms

    Department of Physics, International University of Africa, Khartoum, Sudan

  19. LieTrunc-QNN: Lie Algebra Truncation and Quantum Expressivity Phase Transition from LiePrune to Provably Stable Quantum Neural Networks

    Apr 3, 2026Haijian Shao, Dalong Zhao, Xing Deng +2Quantum Circuit ExpressibilityQuantum Neural Networks

    School of Computer, Jiangsu University of Science and Technology, Zhenjiang 212003, China · Department of Electrical and Computer Engineering, University of Nevada, Las Vegas, USA

  20. 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

  21. Beyond Barren Plateaus: A Scalable Quantum Convolutional Architecture for High-Fidelity Image Classification

    Mar 11, 2026Radhakrishnan DelhibabuQuantum Convolutional Neural NetworksQuantum Circuit Trainability

    School of Computing Science and Engineering (SCOPE), Vellore Institute of Technology, Vellore, 632014, India.

  22. Illustration of Barren Plateaus in Quantum Computing

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

    LMU Munich