Variational Quantum Algorithms

Overview

Variational quantum algorithms combine parameterized quantum circuits with classical optimizers to tackle tasks such as molecular ground-state estimation, combinatorial optimization, and quantum machine learning. Common approaches include VQE and QAOA, with work on circuit ansätze, gradient and measurement strategies, and automated architecture search to reduce circuit and hardware costs. Researchers test these methods on problems such as molecular Hamiltonians, spin systems, Max-Cut, and classification, using both simulations and quantum devices. A central challenge is balancing expressive circuits with trainability and noise robustness, while establishing practical benefits through fair comparisons with classical methods.

Latest papers

CardsList

28 papers4 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

  2. Measurement-Efficient Differentiable Quantum Architecture Search for Combinatorial Optimization

    Oct 7, 2026Lukas Theißinger, Thore Gerlach, Christian BauckhageQuantum Architecture SearchQuantum Machine Learning

  3. Optimization Geometry of QAOA and Variational Quantum Algorithms

    Oct 4, 2026Vojtěch Novák, Ivan Zelinka, Silvie Illésová +2Quantum Approximate Optimization AlgorithmVariational Quantum Algorithms

  4. When is global evolutionary search useful for variational quantum algorithms? A landscape-first study

    Sep 13, 2026Vojtěch Novák, Ivan ZelinkaVariational Quantum AlgorithmsEvolutionary Optimization

  5. Classical Hardware Acceleration of Quantum Autoencoders for Real-Time Anomaly Detection in Collider Experiments

    Jul 22, 2026Ivan Ge, Sagar Addepalli, Abhilasha Dave +1Online Anomaly DetectionQuantum Machine Learning

  6. Identity-Paired Progressive Depth Training: When Trainability Persists Beyond Expressibility

    Jul 18, 2026Athanasios Hadjidimoulas, Tirthak Patel, Anastasios KyrillidisQuantum Circuit ExpressibilityVariational Quantum Circuits

  7. Depth-Efficient Quantum Topological Data Analysis for Regime-Specific Detection of Financial Stress

    Jul 10, 2026Arul Rhik Mazumder, Shreyan Ronit MazumderQuantitative FinanceVariational Quantum Algorithms

  8. HamQASBench: A Hamiltonian-Informed Diagnostic Benchmark for Evaluating Quantum Architecture Search

    Jul 6, 2026Jiayang Niu, Akib Karim, Yan Wang +5Quantum Architecture SearchBenchmark Construction

  9. Ravines in quantum cost landscapes: opportunities for improved VQA predictions

    Jul 1, 2026Felix J. Beckmann, João F. BravoQuantum Machine LearningVariational Quantum Algorithms

  10. Entropy Estimation in Multi-Qutrit Systems via Variational and Classical Neural Networks

    Jun 18, 2026Sai Sakunthala Guddanti, Anil Prabhakar, Ria Rushin JosephConvolutional Neural NetworksVariational Quantum Algorithms

  11. Adaptive directional gradients for parameterised quantum circuits

    Jun 8, 2026Brian Coyle, Snehal Raj, Virag Umathe +2Variational Quantum CircuitsAdaptive Gradient Methods

  12. Classical State Preparation for Variational Quantum Algorithms via Reinforcement Learning

    May 22, 2026Gino Kwun, Dhanvi Bharadwaj, Gokul Subramanian RaviQuantum State PreparationQuantum Approximate Optimization Algorithm

  13. Diagonal Adaptive Non-local Observables on Quantum Neural Networks

    May 14, 2026Huan-Hsin Tseng, Yan Li, Hsin-Yi Lin +1Variational Quantum CircuitsVariational Quantum Algorithms

  14. Zero-shot Quantum Neural Architecture Search

    May 12, 2026Tung Dao, Son N. Tran, Huynh Thi Thanh BinhQuantum Machine LearningNeural Architecture Search

  15. Neural Quantum Spectral Operator Learning for Solving Partial Differential Equations

    May 12, 2026Chanyoung Kim, Myeonghwan Seong, Yujin Kim +2Hybrid Quantum-Classical MLPDE Operator Learning

  16. Adversarial Effects on Expressibility and Trainability in Distributed Variational Quantum Algorithms

    May 5, 2026Abhishek Sadhu, Sharu Theresa JoseQuantum Circuit ExpressibilityVariational Quantum Circuits

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

    May 2, 2026Pilsung KangBarren PlateausVariational Quantum Circuits

  18. Trainability Beyond Linearity in Variational Quantum Objectives

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

  19. Investigation of Automated Design of Quantum Circuits for Imaginary Time Evolution Methods Using Deep Reinforcement Learning

    Apr 9, 2026Ryo Suzuki, Shohei WatabeMax-CutQuantum Circuit Optimization

  20. SpinGQE: A Generative Quantum Eigensolver for Spin Hamiltonians

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

  21. The Average Relative Entropy and Transpilation Depth determines the noise robustness in Variational Quantum Classifiers

    Mar 22, 2026Aakash Ravindra Shinde, Arianne Meijer - van de Griend, Jukka K. NurminenQuantum Machine LearningVariational Quantum Algorithms

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

    Mar 15, 2026Peter Röseler, Dennis Willsch, Kristel MichielsenQuantum Circuit ExpressibilityVariational Quantum Circuits

  23. Solving Conic Programs over Sparse Graphs using a Variational Quantum Approach: The Case of the AC Optimal Power Flow

    Aug 30, 2025Thinh Viet Le, Mark M. Wilde, Vassilis KekatosOptimal Power FlowConstrained Optimization

  24. Reducing QPU Calls in Variational Quantum Algorithms via Classical Offloading of Gradient Computation

    Mar 20, 2025Rahul Bhowmick, Harsh Wadhwa, Avinash Singh +3Variational Quantum AlgorithmsQuantum Circuit Trainability

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

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