mlsanityData to 7 Oct 2026

Review of Ansatz Designing Techniques for Variational Quantum Algorithms

arXiv 2212.04913 ↗First posted 7 Dec 2022quant-ph cs.LGcited by 3

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Abstract (arXiv)

For a large number of tasks, quantum computing demonstrates the potential for exponential acceleration over classical computing. In the NISQ era, variable-component subcircuits enable applications of quantum computing. To reduce the inherent noise and qubit size limitations of quantum computers, existing research has improved the accuracy and efficiency of Variational Quantum Algorithm (VQA). In this paper, we explore the various ansatz improvement methods for VQAs at the gate level and pulse level, and classify, evaluate and summarize them.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 24 of its 48 references that are in the map. First posted on arXiv 7 Dec 2022.

Builds on

24 of 48 references.

References · 24

  1. 2020Variational Quantum Algorithmscited by 687
  2. 2016Quantum Machine Learningcited by 325
  3. 2021Quantum advantage in learning from experimentscited by 186
  4. 2021QuantumNAS: Noise-Adaptive Search for Robust Quantum Circuitscited by 97
  5. 2020Quantum circuit architecture search for variational quantum algorithmscited by 81
  6. 2021Quantum Architecture Search via Deep Reinforcement Learningcited by 58
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12 more
  1. 2021Classical-to-Quantum Transfer Learning for Spoken Command Recognition Based on Quantum Neural Networkscited by 19
  2. 2021Can Noise on Qubits Be Learned in Quantum Neural Network? A Case Study on QuantumFlowcited by 13
  3. 2022Quantum Neural Network Compressioncited by 12
  4. 2021Exploration of Quantum Neural Architecture by Mixing Quantum Neuron Designscited by 11
  5. 2019Quantum-Inspired Support Vector Machinecited by 10
  6. 2020When Machine Learning Meets Quantum Computers: A Case Studycited by 9
  7. 2020Optimized Quantum Compilation for Near-Term Algorithms with OpenPulsecited by 8
  8. 2020Optimal Layout Synthesis for Quantum Computingcited by 6
  9. 2022Hybrid Gate-Pulse Model for Variational Quantum Algorithmscited by 6
  10. 2020A Hardware-Aware Heuristic for the Qubit Mapping Problem in the NISQ Eracited by 5
  11. 2022TopGen: Topology-Aware Bottom-Up Generator for Variational Quantum Circuitscited by 5
  12. 2022Improving Quantum Classifier Performance in NISQ Computers by Voting Strategy from Ensemble Learningcited by 3

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Cited by year

Citing papers per year: 2024: 2; 2025: 1.

3 papers.

  1. 2024Quantum Architecture Search: A Surveycited by 31
  2. 2024Reinforcement Learning for Variational Quantum Circuits Designcited by 8
  3. 2025Adaptive Conformal Prediction for Quantum Machine Learningcited by 0