Weakly self-avoiding walk on a high-dimensional torus
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Bibliographic record
Abstract
How long does a self-avoiding walk on a discrete $d$-dimensional torus have to be before it begins to behave differently from a self-avoiding walk on $\mathbb{Z}^d$? We consider a version of this question for weakly self-avoiding walk on a torus in dimensions $d>4$. On $\mathbb{Z}^d$ for $d>4$, the partition function for $n$-step weakly self-avoiding walk is known to be asymptotically purely exponential, of the form $A\mu^n$, where $\mu$ is the growth constant for weakly self-avoiding walk on $\mathbb{Z}^d$. We prove the identical asymptotic behaviour $A\mu^n$ on the torus (with the same $A$ and $\mu$ as on $\mathbb{Z}^d$) until $n$ reaches order $V^{1/2}$, where $V$ is the number of vertices in the torus. This shows that the walk must have length of order at least $V^{1/2}$ before it "feels" the torus in its leading asymptotics. Our results support the conjecture that the behaviour of the partition function does change once $n$ reaches $V^{1/2}$, and we relate this to a conjectural critical scaling window which separates the dilute phase $n \ll V^{1/2}$ from the dense phase $n \gg V^{1/2}$. To prove the conjecture and to establish the existence of the scaling window remains a challenging open problem. The proof uses a novel lace expansion analysis based on the "plateau" for the torus two-point function obtained in previous work.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it