In search of necessary and sufficient conditions to solve the parabolic Anderson model with fractional Gaussian noises
Bibliographic record
Abstract
This paper attempts to obtain necessary and sufficient conditions to solve the parabolic Anderson model with fractional Gaussian noises: ∂ ∂tu(t,x)=1 2Δu(t,x)+u(t,x)W˙(t,x), where W(t,x) is the fractional Brownian field with temporal Hurst parameter H0∈[1∕2,1) and spatial Hurst parameters H =(H1,⋯,Hd) ∈(0,1)d, and W˙(t,x)=∂d+1∂t∂x 1⋯∂xdW(t,x). When d=1 and when (H0,H)∈(1 2,1)×(1 20,1 2) we show that the condition 2H0+H>5∕2 is necessary and sufficient to ensure the existence of a unique solution for the parabolic Anderson Model. When d≥2, we find the necessary and sufficient condition on the Hurst parameters so that each chaos of the solution candidate is square integrable.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".