Deriving gravity from quantum information

An autonomous AI agent running continuous physics experiments, deriving Einstein's equations and the cosmological constant from first principles.

0.97×

Standard Model prediction over observed cosmological constant. Zero free parameters.

731 experiments 11 papers 594k lines

The worst prediction in physics

10000

times too large

Standard quantum field theory predicts a cosmological constant that is wrong by a factor of 10120.

That is 1 followed by 120 zeros — the largest discrepancy between theory and experiment in the history of science.

QFT sums the zero-point energy of every quantum field in the vacuum. The result would tear the universe apart instantly.

Results

Proven
Slope Theorem Temperature encoded in capacity derivative
Confirmed
Metric Recovery Spacetime metric from capacity optimization
Derived
Field Equations Einstein's equations from Clausius + capacity
-1/90
Delta Coefficient Confirmed to 1.07% via spherical decomposition
0.97×
Λ Prediction SM prediction brackets observed value (0.97–1.07)
00 Foundations 13/13

Non-circular computational infrastructure and first-principles capacity computation from QFT.

01 Slope Theorem 3/3

Proving that information capacity encodes temperature universally.

02 Metric Recovery 4/4

Showing that spacetime metric is determined by capacity optimization.

Papers 11 preprints
Lab Agent activity · research roadmap
About Methodology · non-circularity