Classification of Voronoi and Delone tiles in quasicrystals: I. General method
Bibliographic record
Abstract
A new general method is presented which allows one to find all distinct Voronoi and Delone tiles in any quasicrystal from a large family. This includes the tiles which may be present with arbitrarily low density >0. At all stages, the method requires only consideration of a (possibly large) finite number of cases. Our method is applicable, in principle, to quasicrystals in any dimension and with any irrationality. This is the first of three papers where the Voronoi and Delone tilings are studied. Two-dimensional point sets, 'quasicrystals', arising from the A 4 -root lattice by means of the standard projection to a two-dimensional plane with the irrationality τ = 1/2(1 + √5), are considered. In general, we require that the acceptance window be bounded with non-empty interior. Specific results are provided here for rhombic acceptance windows of any size oriented along the direction of simple roots of the Coxeter group H 2 . Within one quasicrystal the tiles are distinguished by their shape, size and orientation. The rhombic window case is indispensable for subsequent classification of Voronoi and Delone tiles in quasicrystals with general shape of the acceptance window. Voronoi and Delone tiles of quasicrystals with circular and decagonal windows of any size are given in subsequent papers. Let VT denote the set of distinct Voronoi tiles making up a quasicrystal with a given acceptance window. There are three VT sets of the 'generic' type and three of the 'singular' type. The latter occur for one precise value of the size of the acceptance window. Any other VT set is a uniform scaling of the tiles listed here. Similar results, differing in detail, are provided for the sets of distinct Delone tiles DT . Altogether there are four different sets DT of Delone tiles.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".