| _version_ | 1866901280358662144 |
|---|---|
| author | Ryo, Minegishi |
| author_facet | Ryo, Minegishi |
| contents | <p><strong>We present the first deep-learning verification of the Non-Commutative Kolmogorov–Arnold Theory (NKAT), a candidate for ultimate unification of quantum fields, gravity and information.</strong><br>Using a GPU-accelerated spectral-triple simulator with kernel-adapting neural networks, we drive the spectral-dimension error on 64³ lattices down to <span><span>4.34×10−54.34\times10^{-5}</span><span><span><span>4.34</span><span>×</span></span><span><span>1</span><span>0<span><span><span><span><span><span>−5</span></span></span></span></span></span></span></span></span></span>.<br>We show that (i) Moyal and <span><span>κ\kappa</span><span><span><span>κ</span></span></span></span>-Minkowski star products satisfy Jacobi consistency and yield indistinguishable physics, (ii) the θ-running remains finite and smooth over 20 orders of energy, and (iii) the Connes distance reproduces an almost flat emergent metric.<br>Compactifying eleven-dimensional M-theory on a seven-dimensional Calabi–Yau manifold reproduces the NKAT parameter set within <span><span><0.1%<0.1\%</span><span><span><span><</span></span><span><span>0.1%</span></span></span></span>.<br>The resulting predictions—γ-ray time-delay ≤ <span><span>1.6×10−191.6\times10^{-19}</span><span><span><span>1.6</span><span>×</span></span><span><span>1</span><span>0<span><span><span><span><span><span>−19</span></span></span></span></span></span></span></span></span></span> s (CTA), vacuum birefringence ≤ <span><span>10−1310^{-13}</span><span><span><span>1</span><span>0<span><span><span><span><span><span>−13</span></span></span></span></span></span></span></span></span></span> rad km<span><span>−1^{-1}</span><span><span><span><span><span><span><span><span><span>−1</span></span></span></span></span></span></span></span></span></span> (PVLAS-II) and atomic-interferometer phase shift <span><span>Δϕ∼10−7Δ\phi\sim10^{-7}</span><span><span><span>Δ</span><span>ϕ</span><span>∼</span></span><span><span>1</span><span>0<span><span><span><span><span><span>−7</span></span></span></span></span></span></span></span></span></span> rad (MAGIS-100)—are testable with current or near-future experiments.<br>All code, data and trained checkpoints (47 MB) are released under CC-BY-4.0.<br>Our results demonstrate that modern machine-learning pipelines can rigorously validate non-perturbative quantum-gravity candidates and deliver concrete experimental targets.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_15496874 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | NKAT-Ultimate-Unification Ryo, Minegishi <p><strong>We present the first deep-learning verification of the Non-Commutative Kolmogorov–Arnold Theory (NKAT), a candidate for ultimate unification of quantum fields, gravity and information.</strong><br>Using a GPU-accelerated spectral-triple simulator with kernel-adapting neural networks, we drive the spectral-dimension error on 64³ lattices down to <span><span>4.34×10−54.34\times10^{-5}</span><span><span><span>4.34</span><span>×</span></span><span><span>1</span><span>0<span><span><span><span><span><span>−5</span></span></span></span></span></span></span></span></span></span>.<br>We show that (i) Moyal and <span><span>κ\kappa</span><span><span><span>κ</span></span></span></span>-Minkowski star products satisfy Jacobi consistency and yield indistinguishable physics, (ii) the θ-running remains finite and smooth over 20 orders of energy, and (iii) the Connes distance reproduces an almost flat emergent metric.<br>Compactifying eleven-dimensional M-theory on a seven-dimensional Calabi–Yau manifold reproduces the NKAT parameter set within <span><span><0.1%<0.1\%</span><span><span><span><</span></span><span><span>0.1%</span></span></span></span>.<br>The resulting predictions—γ-ray time-delay ≤ <span><span>1.6×10−191.6\times10^{-19}</span><span><span><span>1.6</span><span>×</span></span><span><span>1</span><span>0<span><span><span><span><span><span>−19</span></span></span></span></span></span></span></span></span></span> s (CTA), vacuum birefringence ≤ <span><span>10−1310^{-13}</span><span><span><span>1</span><span>0<span><span><span><span><span><span>−13</span></span></span></span></span></span></span></span></span></span> rad km<span><span>−1^{-1}</span><span><span><span><span><span><span><span><span><span>−1</span></span></span></span></span></span></span></span></span></span> (PVLAS-II) and atomic-interferometer phase shift <span><span>Δϕ∼10−7Δ\phi\sim10^{-7}</span><span><span><span>Δ</span><span>ϕ</span><span>∼</span></span><span><span>1</span><span>0<span><span><span><span><span><span>−7</span></span></span></span></span></span></span></span></span></span> rad (MAGIS-100)—are testable with current or near-future experiments.<br>All code, data and trained checkpoints (47 MB) are released under CC-BY-4.0.<br>Our results demonstrate that modern machine-learning pipelines can rigorously validate non-perturbative quantum-gravity candidates and deliver concrete experimental targets.</p> |
| title | NKAT-Ultimate-Unification |
| url | https://doi.org/10.5281/zenodo.15496874 |