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Digital twin results (regenerated by nuclear_ising.py)

Instance: 8 sites, frustrated Gaussian couplings, seed 229, 2,000,000 source decays simulated.

Convergence to the exact Boltzmann law

decays consumed KL(empirical, exact) total variation
1,000 2.93e-01 0.164
2,000 1.37e-01 0.093
4,000 7.17e-02 0.078
8,000 4.61e-02 0.071
16,000 2.35e-02 0.032
32,000 1.47e-02 0.028
64,000 7.09e-03 0.017
128,000 3.47e-03 0.016
256,000 1.94e-03 0.011
512,000 8.54e-04 0.006
1,024,000 5.15e-04 0.005

Final KL divergence after 2,000,000 decays: 5.15e-04 over all 256 states. The machine samples the exact distribution its couplings define.

Sampling cost

  • integrated autocorrelation time: 25.9 decays
  • effective independent samples drawn: 76,707
  • decays per independent sample: 26
  • optimization mode (annealed): median 173 decays to first reach the true ground state (25/25 runs reached it)

Energy per independent sample, by carrier

carrier J per quantum J per sample vs MTJ p bit (33 fJ/sample)
229mTh quantum (8.4 eV) 1.34e-18 3.49e-17 945x cheaper
57Fe quantum (14.4 keV) 2.31e-15 6.02e-14 2x costlier
60Co gamma (1.25 MeV) 2.00e-13 5.22e-12 158x costlier

The table is the energy honesty argument of the foundational document, now with measured constants: at MeV quanta the sampler cannot compete; at the 8.4 eV transition the same machine undercuts engineered probabilistic silicon, because the source energy is spent either way and each decay is a genuine random number no transistor had to synthesize.