Built Google’s quantum research program around superconducting processors, quantum algorithms and error correction, helping connect experimental milestones with a sustained effort toward useful large-scale computing.
GoogleNatureNeven’s contribution is the creation and leadership of a research program that joins hardware, algorithms and error correction. His own account dates the founding of Google Quantum AI to 2012. The Willow announcement documents a later milestone: logical error rates falling as the error-correcting code grows. Together these show both institutional continuity and a technically meaningful target. The profile credits the experiments to the research team and distinguishes benchmark or error-correction demonstrations from general commercial usefulness.
Google ResearchGoogleNatureDefining contributions
Work, in context- 2012
Founding Google Quantum AI
Founded the program with the stated goal of developing a useful, large-scale quantum computer and the algorithms needed for scientific applications.
Founder of Google Quantum AI, with the founding date and program goal documented in his company-published account.
Source-supported recordGoogle - 2024
Willow and scalable error correction
Led Google Quantum AI when the team reported progressively lower logical error rates as surface-code sizes increased, a step toward scalable logical qubits.
Google Quantum AI program leader at the time of the team’s published surface-code experiment; shared technical credit.
Source-supported recordGoogleNature
Follow the evidence
3 sourcesPrimary papers, institutional records and attributed announcements. Each source supports the claims linked above.
- Google ResearchInstitutional profile
Hartmut Neven
Identity, professional identification and contribution context
Checked 2026-09-19 - GoogleCompany research announcement
Meet Willow, our state-of-the-art quantum chip
Program founding, leadership and Willow announcement
Published 2024-12-09 · Checked 2026-09-19 - NatureResearch paper
Quantum error correction below the surface code threshold
Team demonstration of decreasing logical errors with code scaling
Published 2024-12-09 · Checked 2026-09-19