Gravity, Topology, and Complex Mathematics in the Universal Optimized Simulation
Bibliographic record
Abstract
This article appears to have started when a MicroSoftNetwork article called "Optimizing Mechanism": Physicist Claims Gravity Is Evidence We May Be In A Simulation was read. Appearances really are deceptive, however. Thoughts it contains can be traced back a few decades to musings about the Mobius strip. These thoughts took a more serious turn in 2005 when my book on Amazon (“ROD’S ROOM - A New Earth and A New Universe”) combined ideas about science with a few poems and some short stories. Ideas gradually advanced over the next decade, becoming more frequent and detailed in 2018 when something I called vector-tensor-scalar geometry popped into my head. Hypotheses regarding science and mathematics have been accelerating ever since. I’ve never felt that the source of these ideas was the reasoning in my brain. It always felt like I was a student learning things that were already common knowledge, even though the thoughts were obviously strangers to anyone living. I often find that ideas which found their way into my head in the past were made clearer by ideas that came later. For example, the geometry mentioned a few sentences ago found application years later to consciousness, topological insulators, and cosmology’s holographic principle. This latest article seeks to combine many ideas - and to explain them better than in the past. So much for personal history and self-indulgence … what are some of the scientific topics in this article? Computational or simulated universe, holographic principle, gravity, topology, real and imaginary numbers, quantum mechanics, quantum spin, mass, Higgs boson and field, gluon, Wick rotation, Riemann hypothesis, retarded and advanced waves, time, vector-tensor-scalar (VTS) geometry, elliptical VTS geometry, consciousness, single-particle universe, bosons + fermions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".