QGIDC: The World's First Quantum Circuit Simulating Gravity-Induced Decoherence on Real Quantum Hardware
Bibliographic record
Abstract
First Experimental Proof of Gravity-Induced Decoherence on Quantum Hardware On May 19, 2025, Dr. Zuhair Ahmed and his team at The Centre of Excellence for Technology Quantum and AI Canada achieved a historic milestone by demonstrating gravity-induced decoherence in quantum systems for the first time using real quantum hardware. This pioneering study introduces the Quantum Gravity-Induced Decoherence Circuit (QGIDC), executed on IBM’s superconducting quantum computers—including the advanced IBM Brisbane backend—and Qiskit simulators. Building upon the theoretical foundations laid by Roger Penrose and Gerard ’t Hooft, the experiment provides empirical evidence that gravitational effects can measurably influence quantum entanglement. The study rigorously distinguishes gravitational decoherence from standard environmental noise through analysis of fidelity, entropy, purity, trace distance, measurement counts, and Bloch vector dynamics. A novel mathematical model was also developed to quantify the decoherence rate, and Bloch sphere visualizations were used to trace the evolution of quantum states under gravitational influence. This landmark result marks a breakthrough in unifying quantum mechanics with general relativity, opening new pathways in quantum gravity research and experimental quantum foundations.
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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 | 0.004 |
| 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 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".