mlsanityData to 7 Oct 2026

IBM Quantum Computers: Evolution, Performance, and Future Directions

arXiv 2410.00916 ↗First posted 17 Sep 2024quant-ph cs.AI cs.ARcited by 11

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Abstract (arXiv)

Quantum computers represent a transformative frontier in computational technology, promising exponential speedups beyond classical computing limits. IBM Quantum has led significant advancements in both hardware and software, providing access to quantum hardware via IBM Cloud since 2016, achieving a milestone with the world's first accessible quantum computer. This article explores IBM's quantum computing journey, focusing on the development of practical quantum computers. We summarize the evolution and advancements of IBM Quantum's processors across generations, including their recent breakthrough surpassing the 1,000-qubit barrier. The paper reviews detailed performance metrics across various hardware, tracing their evolution over time and highlighting IBM Quantum's transition from the noisy intermediate-scale quantum (NISQ) computing era towards fault-tolerant quantum computing capabilities.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 8 of its 70 references that are in the map. First posted on arXiv 17 Sep 2024.

Builds on

8 of 70 references.

References · 8

  1. 2020Variational Quantum Algorithmscited by 687
  2. 2018Supervised learning with quantum enhanced feature spacescited by 654
  3. 2020The power of quantum neural networkscited by 377
  4. 2020Power of data in quantum machine learningcited by 336
  5. 2019Learning to Prescribe Interventions for Tuberculosis Patients Using Digital Adherence Datacited by 21
  6. 2019Quantum Computing at the Frontiers of Biological Sciencescited by 8
  7. 2017Quantum Artificial Life in an IBM Quantum Computercited by 5
  8. 2024Comprehensive characterization of three-qubit Grover search algorithm on IBM's 127-qubit superconducting quantum computerscited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 8; 2026: 3.

11 papers.

  1. 2025Quantum Federated Learning: A Comprehensive Surveycited by 7
  2. 2025Quantum autoencoders for image classificationcited by 2
  3. 2025Differentially Private Federated Quantum Learning via Quantum Noisecited by 1
  4. 2025Scalable Quantum Reinforcement Learning on NISQ Devices with Dynamic-Circuit Qubit Reuse and Grover Optimizationcited by 1
  5. 2025Enhanced Prediction of CAR T-Cell Cytotoxicity with Quantum-Kernel Methodscited by 0
  6. 2025The Efficiency Frontier: Classical Shadows versus Direct Quantum Measurementcited by 0
  7. 2025Hybrid Quantum Neural Networks for Efficient Protein-Ligand Binding Affinity Predictioncited by 0
  8. 2025Data-Driven Learnability Transition of Measurement-Induced Entanglementcited by 0
  9. 2026Q-Tag: Watermarking Quantum Circuit Generative Modelscited by 0
  10. 2026Conformalized Quantum DeepONet Ensembles: Towards Scalable Operator Learning with Distribution-Free Guaranteescited by 0
  11. 2026Characterizing Privacy Risks of Quantum Machine Learning with Emergent Quantum-Native Accesscited by 0