Abstract This article revisits the problem of global well-posedness for the generalized parabolic Anderson model on$$\mathbb {R}^+\times \mathbb {T}^2$$ within the framework of paracontrolled calculus (Gubinelli et al. in Forum Math, 2015). The model is given by the equation:$$\begin{aligned} (\partial _t-\Delta ) u=F(u)\eta \end{aligned}$$ where$$\eta \in C^{-1-\kappa }$$ with$$1/6>\kappa >0$$ , and$$F\in C_b^2(\mathbb {R})$$ . Assume that$$\eta \in C^{-1-\kappa }$$ and can be lifted to enhanced noise, we derive new a priori bounds. The key idea follows from the recent work by Chandra et al. (A priori bounds for 2-d generalised Parabolic Anderson Model,,2024), to represent the leading error term as a transport type term, and our techniques encompass the paracontrolled calculus, the maximum principle, and the localization approach (i.e. high-low frequency argument).
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This content will become publicly available on March 1, 2026
Fast and fair randomized wait-free locks
Abstract We present a randomized approach for wait-free locks with strong bounds on time and fairness in a context in which any process can be arbitrarily delayed. Our approach supports a tryLock operation that is given a set of locks, and code to run when all the locks are acquired. A tryLock operation may fail if there is contention on the locks, in which case the code is not run. Given an upper bound$$\kappa $$ known to the algorithm on the point contention of any lock, and an upper boundLon the number of locks in a tryLock’s set, a tryLock will succeed in acquiring its locks and running the code with probability at least$$1/(\kappa L)$$ . It is thus fair. Furthermore, if the maximum step complexity for the code in any lock isT, the operation will take$$O(\kappa ^2 L^2 T)$$ steps, regardless of whether it succeeds or fails. The operations are independent, thus if the tryLock is repeatedly retried on failure, it will succeed in$$O(\kappa ^3 L^3 T)$$ expected steps. If the algorithm does not know the bounds$$\kappa $$ andL, we present a variant that can guarantee a probability of at least$$1/\kappa L\log (\kappa L T)$$ of success. We assume an oblivious adversarial scheduler, which does not make decisions based on the operations, but can predetermine any schedule for the processes, which is unknown to our algorithm. Furthermore, to account for applications that change their future requests based on the results of previous tryLock operations, we strengthen the adversary by allowing decisions of the start times and lock sets of tryLock operations to be made adaptively, given the history of the execution so far.
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- Award ID(s):
- 2119352
- PAR ID:
- 10639091
- Publisher / Repository:
- Springer
- Date Published:
- Journal Name:
- Distributed Computing
- Volume:
- 38
- Issue:
- 1
- ISSN:
- 0178-2770
- Page Range / eLocation ID:
- 51 to 72
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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