When will quantum computers beat classical computers?

When will quantum computers beat classical computers?

by IBM Research

Formal & Physical Sciences Computing & Cybersecurity UYComputer scienceUYXNatural computing
🎙 IBM Research 👥 120K 📅 December 18, 2025 ⏱ 48 min 👁 1K 📄 expert opinion 🧭 2026-08-16
Available in: English (current) Français

Keywords

quantum advantagequantum computingerror mitigationvalidationclassical simulation

Summary

In this episode of The Coherence Times, host Ryan Mandelbaum interviews Abhinav Kandala, an experimental physicist and principal research scientist at IBM Quantum. They discuss the concept of quantum advantage, which is the point at which quantum computers outperform classical computers on specific tasks. Kandala emphasizes that quantum advantage is not just about speed but also about rigorous validation of results. He outlines three approaches to demonstrating quantum advantage: problems with efficient classical verification, variational solutions, and observable estimations. He also highlights recent progress in quantum hardware, including scaling to over 100 qubits and reducing error rates from 1% to 0.1%, which are crucial for achieving quantum advantage. The conversation covers the importance of error mitigation techniques, the role of classical resources in hybrid quantum-classical algorithms, and the collaborative efforts needed to benchmark quantum performance against classical state-of-the-art. Kandala remains optimistic about the near-term potential for quantum advantage, particularly in areas like quantum simulation and optimization.

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Critical Evaluation

Value of the Information & Strength of the Argument

The podcast provides valuable insights into the current state of quantum computing and the practical steps toward quantum advantage. Kandala’s explanations are clear and grounded in his direct experience, offering a realistic perspective on the challenges and milestones. The argumentation is solid, as he distinguishes between different types of quantum advantage and emphasizes the need for rigorous validation. He also addresses common misconceptions, such as the idea that quantum advantage must be immediately useful. The discussion is well-structured, moving from definitions to methods and finally to the current status, making it accessible to a broad audience while retaining technical depth.

Scientific Rigor, Source Quality, Title Accuracy

The podcast maintains a high level of scientific rigor, with Kandala referencing specific techniques like peaked circuits and error mitigation, and citing the work of Scott Aaronson. The sources mentioned in the description, such as the Quantum Advantage Tracker and IBM Quantum Platform, are relevant and provide additional resources for verification. The title accurately reflects the content, which focuses on the timeline and criteria for quantum advantage. The episode is part of a series by IBM Research, which lends credibility, though it is important to note the potential for bias towards IBM’s own progress and methods.

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Title / Content Match

The title accurately reflects the content, which focuses on the timeline and criteria for quantum advantage.

Quality & Reliability

8/10

The podcast features a principal research scientist from IBM Quantum, providing expert insights into quantum advantage. The discussion is grounded in current research and practical demonstrations, with references to specific techniques and error rates. However, as an IBM-affiliated source, there is potential for bias towards IBM's approach and progress.

Chapters

Cited Sources

Concurring Sources

Contribution & Novelties

The podcast offers a clear and structured overview of quantum advantage, distinguishing between different validation methods and emphasizing the importance of rigorous verification. It provides an insider’s perspective on IBM’s progress and the practical challenges involved. The discussion of error mitigation and the role of classical resources in hybrid approaches adds depth to the understanding of near-term quantum computing.

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Radar Profile

The radar profile shows high scores across all dimensions, indicating a well-rounded and reliable source. The podcast excels in providing substantial information and maintaining scientific rigor, with a strong technical level suitable for an informed audience.

Reliability 8/10