getQore Blog
Insights on quantum error correction, validation, and hardware analysis
Scientific Defensibility in Hypothesis Discovery
Countering AI-driven overconfidence with three layers of scientific validation: edge case detection, multi-criteria evaluation (MDL/BIC/AIC), and bootstrap stability testing. Sprint 12 introduces tools to combat the "Illusion of Competence" where researchers trust model selection without adequate validation.
🔬 Theory ValidationValidating Non-Commuting Spectral Theory with Sprint 12
Step-by-step demonstration of Sprint 12's three-layer scientific defensibility framework validating a novel quantum theory. We test the hypothesis that surface codes have exactly 16 independent spectral modes, showing how edge detection, multi-criteria evaluation, and bootstrap stability prevent AI-driven overconfidence.
🌊 OTOC AnalysisMeasuring Error Propagation on Google Willow
Detecting the "Butterfly Velocity" of quantum errors: We analyzed temporal-spatial correlation patterns on Google Willow's d=7 surface code data and discovered 19 error propagation patterns traveling at 2.94 grid units/shot. Plus: Why hot spots can indicate physics (error convergence) rather than hardware defects.
✅ Hardware ValidationValidating Google Willow Without a Decoder
How we achieved 5.4% Lambda accuracy without running a single decoder. Using decoder-independent analysis on Google's public Willow dataset, we validated their QEC claims in seconds instead of hours. Includes platform calibration discovery: hardware syndrome density is 2× higher than simulation.