Abstract Let$$\mathbb {F}_q^d$$ be thed-dimensional vector space over the finite field withqelements. For a subset$$E\subseteq \mathbb {F}_q^d$$ and a fixed nonzero$$t\in \mathbb {F}_q$$ , let$$\mathcal {H}_t(E)=\{h_y: y\in E\}$$ , where$$h_y:E\rightarrow \{0,1\}$$ is the indicator function of the set$$\{x\in E: x\cdot y=t\}$$ . Two of the authors, with Maxwell Sun, showed in the case$$d=3$$ that if$$|E|\ge Cq^{\frac{11}{4}}$$ andqis sufficiently large, then the VC-dimension of$$\mathcal {H}_t(E)$$ is 3. In this paper, we generalize the result to arbitrary dimension by showing that the VC-dimension of$$\mathcal {H}_t(E)$$ isdwhenever$$E\subseteq \mathbb {F}_q^d$$ with$$|E|\ge C_d q^{d-\frac{1}{d-1}}$$ .
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Mapping TASEP back in time
Abstract We obtain a new relation between the distributions$$\upmu _t$$ at different times$$t\ge 0$$ of the continuous-time totally asymmetric simple exclusion process (TASEP) started from the step initial configuration. Namely, we present a continuous-time Markov process with local interactions and particle-dependent rates which maps the TASEP distributions$$\upmu _t$$ backwards in time. Under the backwards process, particles jump to the left, and the dynamics can be viewed as a version of the discrete-space Hammersley process. Combined with the forward TASEP evolution, this leads to a stationary Markov dynamics preserving$$\upmu _t$$ which in turn brings new identities for expectations with respect to$$\upmu _t$$ . The construction of the backwards dynamics is based on Markov maps interchanging parameters of Schur processes, and is motivated by bijectivizations of the Yang–Baxter equation. We also present a number of corollaries, extensions, and open questions arising from our constructions.
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- Award ID(s):
- 1664617
- PAR ID:
- 10273909
- Publisher / Repository:
- Springer Science + Business Media
- Date Published:
- Journal Name:
- Probability Theory and Related Fields
- Volume:
- 182
- Issue:
- 1-2
- ISSN:
- 0178-8051
- Format(s):
- Medium: X Size: p. 481-530
- Size(s):
- p. 481-530
- Sponsoring Org:
- National Science Foundation
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