Something for nothing: some consequences of the solution of the Tarski problems
Bibliographic record
Abstract
Introduction Alfred Tarski in 1940 made three well-known conjectures concerning nonabelian free groups (see Section 2). There had been various partial solutions until complete positive solutions were presented during the past 15 years by Kharlampovich and Myasnikov (see [51]–[59]) and independently by Z. Sela (see [78]–[83]). In the Kharlampovich- Myasnikov approach the proof arose from a detailed study of fully residually free groups (called limit groups in Sela's approach), the development of algebraic geometry over free groups, and an elimination process involving solutions of equations over free groups based on work of Makhanin and Razborov (see [51]–[59]). These steps were mirrored, with somewhat different terminology, by Sela, who called his approach diophantine geometry over free groups. The positive solution of the Tarski conjectures provides a straightforward proof of Magnus's theorem in surface groups which we present. This result was proved directly by J. Howie [46] and independently by O. Bogopolski [10]. We will present this proof in Section 4. This type of proof leads to several different types of questions. • Which additional nontrivial free group results are true in surface groups but difficult to obtain directly? • What first-order properties of nonabelian free groups are true beyond the class of elementary free groups? After showing a proof of Magnus's Theorem based on the solution of the Tarski problems we give several examples of other free group results holding in surface groups. Using this technique we give a proof of a theorem of D. Lee on C-test words. We then consider and prove certain other results that hold in elementary free groups, in particular surface groups, including the retract theorem of Turner [86] and the property of conjugacy separability. After this we turn to the second type of question and survey a large number of recent results. In particular we first consider groups satisfying certain quadratic properties that we call Lyndon properties and show that the class of groups satisfying these properties are closed under many amalgam constructions.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 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".