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Quantum computers

Richard Feynman Peter Shor Google Quantum AI

This page delivers no verdict; it presents claims and evidence with their sources. No theory in science is absolute. Method

For everyone

Quantum computers use "qubits" with superposition and entanglement instead of bits. It has been shown theoretically that they could solve some problems, such as factoring large numbers, much faster than classical computers. Qubits are very error-prone; Google's Willow processor in 2024 was the first experiment to show error rates falling as the number of qubits grows. A useful, large-scale quantum computer does not yet exist.

For specialists

Shor's algorithm (1994) factors in polynomial time, which threatens RSA encryption. In 2019 Google claimed "quantum supremacy" with the 53-qubit Sycamore; IBM argued the same task could be done classically in days. On Willow, as the surface-code distance was raised from 3 to 5 to 7, the logical error rate fell by about 2.14 times per step; the 101-qubit distance-7 code had an error of about 0.143% per cycle.

Claims

Quantum error correction can suppress logical errors exponentially as the number of physical qubits grows (below-threshold operation).^[2]
A programmable quantum processor has performed a computation that classical supercomputers cannot practically perform.^[1]

Evidence

Supporting

Measurement

On Willow the logical error rate fell as code distance grew, and the logical qubit outlived the best physical qubit.^[2]

Challenging

Methodological critique

IBM researchers argued that the 2019 supremacy task could be done in about 2.5 days with improved classical methods.^[3]

Connections

Parent

Computing and artificial intelligence

Builds on

Quantum mechanics

Macroscopic quantum tunnelling in an electric circuit (Nobel 2025)

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Sources

ArticleArute, F. et al. (2019). Quantum supremacy using a programmable superconducting processor. Nature 574, 505–510DOI 10.1038/s41586-019-1666-5 archive
ArticleGoogle Quantum AI and Collaborators (2025). Quantum error correction below the surface code threshold. Nature 638, 920–926DOI 10.1038/s41586-024-08449-y archive
PreprintPednault, E.; Gunnels, J. A.; Nannicini, G.; Horesh, L.; Wisnieff, R. (2019). Leveraging secondary storage to simulate deep 54-qubit Sycamore circuitsarXiv:1910.09534 archive

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Cite this page

APA

Athena contributors. (2026). Quantum computers. Athena: The tree of human knowledge. Retrieved November 1, 2026, from https://latifkedi.github.io/athena/en/d/kuantum-bilgisayar/

BibTeX

@misc{athena_kuantum_bilgisayar,
  title        = {Quantum computers},
  author       = {{Athena contributors}},
  year         = {2026},
  howpublished = {\url{https://latifkedi.github.io/athena/en/d/kuantum-bilgisayar/}},
  note         = {Athena: The tree of human knowledge. Accessed: 2026-11-01}
}

Added: September 27, 2026 · Last changed: September 28, 2026 · Page history

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