QSF1: The Curvature Detection: A 3-Qubit Quantum Spacetime Foam Simulation Reveals 92.7% Localized Deformation in Patch-1 (IBM Sherbrooke)
Bibliographic record
Abstract
On May 18, 2025, at precisely 08:30:07 PST, a historic scientific breakthrough was achieved: the world’s first physical measurement of quantum spacetime foam. Using IBM’s superconducting qubit hardware and Qiskit, researchers successfully mapped the elusive structure of quantum foam into executable quantum circuits and measured its entanglement entropy—providing concrete experimental evidence for a phenomenon previously limited to theory. This landmark experiment not only surpasses all earlier theoretical models and indirect simulations, but also forges a revolutionary bridge between quantum gravity and quantum computing. It positions quantum processors not just as computational tools, but as probes of the very fabric of spacetime itself. The article offers a comprehensive deep dive into this achievement, including: The scientific and philosophical significance of the result, Experimental details and histogram analysis of entropy measurements, The mathematical framework used to represent spacetime foam on quantum circuits, An overview of contributions made by the research team, A critical look at the global scientific landscape and previously bypassed nations and researchers, And a forward-looking reflection on the new frontiers this opens for physics, computation, and fundamental science. This work marks the beginning of a new era: experimental quantum gravity using quantum computers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".