mlsanityData to 7 Oct 2026

Evolutionary Optimization for Designing Variational Quantum Circuits with High Model Capacity

arXiv 2412.12484 ↗First posted 17 Dec 2024quant-ph cs.AI cs.ETcited by 9

Not on the map. Why?

Abstract (arXiv)

Recent advancements in quantum computing (QC) and machine learning (ML) have garnered significant attention, leading to substantial efforts toward the development of quantum machine learning (QML) algorithms to address a variety of complex challenges. The design of high-performance QML models, however, requires expert-level knowledge, posing a significant barrier to the widespread adoption of QML. Key challenges include the design of data encoding mechanisms and parameterized quantum circuits, both of which critically impact the generalization capabilities of QML models. We propose a novel method that encodes quantum circuit architecture information to enable the evolution of quantum circuit designs. In this approach, the fitness function is based on the effective dimension, allowing for the optimization of quantum circuits towards higher model capacity. Through numerical simulations, we demonstrate that the proposed method is capable of discovering variational quantum circuit architectures that offer improved learning capabilities, thereby enhancing the overall performance of QML models for complex tasks.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 31 of its 44 references that are in the map. First posted on arXiv 17 Dec 2024.

Builds on

31 of 44 references.

References · 31

  1. 2020The power of quantum neural networkscited by 377
  2. 2019Limitations of the Empirical Fisher Approximation for Natural Gradient Descentcited by 213
  3. 2019Variational Quantum Circuits for Deep Reinforcement Learningcited by 165
  4. 2020Quantum Long Short-Term Memorycited by 118
  5. 2018Universal Statistics of Fisher Information in Deep Neural Networks: Mean Field Approachcited by 89
  6. 2021Parametrized quantum policies for reinforcement learningcited by 87
  7. 2020Quantum circuit architecture search for variational quantum algorithmscited by 81
  8. 2021Reinforcement learning for optimization of variational quantum circuit architecturescited by 76
  9. 2020Reinforcement Learning with Quantum Variational Circuitscited by 74
  10. 2020Quantum Convolutional Neural Networks for High Energy Physics Data Analysiscited by 64
  11. 2021The Dawn of Quantum Natural Language Processingcited by 60
  12. 2021Quantum Architecture Search via Deep Reinforcement Learningcited by 58
19 more
  1. 2021Variational Quantum Reinforcement Learning via Evolutionary Optimizationcited by 50
  2. 2022A Survey on Quantum Reinforcement Learningcited by 50
  3. 2021An end-to-end trainable hybrid classical-quantum classifiercited by 49
  4. 2022When BERT Meets Quantum Temporal Convolution Learning for Text Classification in Heterogeneous Computingcited by 40
  5. 2021QTN-VQC: An End-to-End Learning framework for Quantum Neural Networkscited by 27
  6. 2022PQLM -- Multilingual Decentralized Portable Quantum Language Model for Privacy Protectioncited by 26
  7. 2022Quantum deep recurrent reinforcement learningcited by 23
  8. 2023Applying QNLP to sentiment analysis in financecited by 23
  9. 2021Quantum Architecture Search via Continual Reinforcement Learningcited by 22
  10. 2023Asynchronous training of quantum reinforcement learningcited by 20
  11. 2023Efficient quantum recurrent reinforcement learning via quantum reservoir computingcited by 14
  12. 2023Differentiable Quantum Architecture Search for Quantum Reinforcement Learningcited by 13
  13. 2018Approximate Fisher Information Matrix to Characterise the Training of Deep Neural Networkscited by 12
  14. 2024VQC-Based Reinforcement Learning with Data Re-uploading: Performance and Trainabilitycited by 12
  15. 2024Quantum Machine Learning Architecture Search via Deep Reinforcement Learningcited by 12
  16. 2022Monte Carlo Tree Search based Hybrid Optimization of Variational Quantum Circuitscited by 10
  17. 2022Evolutionary Quantum Architecture Search for Parametrized Quantum Circuitscited by 7
  18. 2024Quantum Architecture Search with Unsupervised Representation Learningcited by 4
  19. 2023Toward Automated Quantum Variational Machine Learningcited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 8; 2026: 1.

9 papers.

  1. 2025Learning to Measure Quantum Neural Networkscited by 15
  2. 2025Differentiable Quantum Architecture Search in Quantum-Enhanced Neural Network Parameter Generationcited by 7
  3. 2025Quantum Long Short-term Memory with Differentiable Architecture Searchcited by 4
  4. 2025Introduction to Quantum Machine Learning and Quantum Architecture Searchcited by 3
  5. 2025QuProFS: An Evolutionary Training-free Approach to Efficient Quantum Feature Map Searchcited by 1
  6. 2025Neural Architecture Search for Quantum Autoencoderscited by 1
  7. 2025Supervised Quantum Machine Learning: A Future Outlook from Qubits to Enterprise Applicationscited by 0
  8. 2025Fisher Information, Training and Bias in Fourier Regression Modelscited by 0
  9. 2026Investigating Quantum Circuit Designs Using Neuro-Evolutioncited by 0