Bernoulli TASEP — Empirical Density Profile     TASEPs

Leonid Petrov


Simulation Info

Bernoulli TASEP — Empirical Density Profile     TASEPs

Leonid Petrov

Simulation of Bernoulli TASEP with step initial condition. Particles at sites {-r+1,...,0} each flip a biased coin and (if heads) attempt to jump right by one site; exclusion prevents two particles from occupying the same site. Two update rules: parallel (snapshot-based, simultaneous) and sequential (right-to-left cascading, allowing chains of jumps). Outputs are the averaged empirical density profile as a function of xi = x/T, and the fraction of active particles A_n/n vs time.

Definitions, stationary currents, and limit shapes

Setup. State space $\{0,1\}^{\mathbb{Z}}$; write $\eta_t(x) \in \{0,1\}$ for the occupancy of site $x \in \mathbb{Z}$ at time $t \in \mathbb{Z}_{\ge 0}$. Fix $r \in \mathbb{Z}_{\ge 1}$ and $p \in (0,1]$. Step initial condition: $\eta_0(x) = \mathbf{1}_{-r < x \le 0}$. Let $(\xi_{t,x})_{t \ge 0,\, x \in \mathbb{Z}}$ be i.i.d. $\mathrm{Bernoulli}(p)$.

Definition 1 (parallel update). $\eta_{t+1}$ is obtained from $\eta_t$ by moving, simultaneously, every particle at $x$ with $\xi_{t,x} = 1$ and $\eta_t(x+1) = 0$.

Definition 2 (right-to-left sequential update). $\eta_{t+1}$ is obtained from $\eta_t$ by processing sites in strict decreasing order of $x$: apply $(\eta(x), \eta(x+1)) \mapsto (0,1)$ whenever the current configuration satisfies $\eta(x) = 1$, $\eta(x+1) = 0$, and $\xi_{t,x} = 1$.

Proposition 1 (Evans–Rajewsky–Speer [2]). The stationary current of Definition 1 on $\mathbb{Z}/N\mathbb{Z}$ at density $\rho \in [0,1]$ is $$j_{\mathrm{par}}(\rho) = \tfrac{1}{2}\!\left(1 - \sqrt{1 - 4p\rho(1-\rho)}\,\right).$$

Proposition 2 (Rajewsky–Santen–Schadschneider–Schreckenberg [1]). The stationary current of Definition 2 on $\mathbb{Z}/N\mathbb{Z}$ at density $\rho \in [0,1]$ is $$j_{\mathrm{seq}}(\rho) = \frac{p\,\rho(1-\rho)}{1 - p\rho}.$$

Both currents are strictly concave on $[0,1]$ for $p \in (0,1)$. At the deterministic boundary $p = 1$ one has $j_{\mathrm{par}}(\rho) = \min(\rho, 1-\rho)$ and $j_{\mathrm{seq}}(\rho) = \rho$.

Scaling limit under step initial condition. Under Eulerian scaling $\xi = x/T$, the empirical measure $T^{-1}\sum_k \delta_{x_k(T)/T}$ is expected to converge in probability to $\rho_\infty(\xi)\, d\xi$, where $\rho_\infty$ is the entropy solution of $\partial_t \rho + \partial_x j(\rho) = 0$ with initial data $\rho_0(\xi) = \mathbf{1}_{\xi \le 0}$; see Kipnis–Landim [4]. For a strictly concave flux this yields the rarefaction $$\rho_\infty(\xi) = \begin{cases} 1, & \xi \le j'(1), \\ (j')^{-1}(\xi), & j'(1) < \xi < j'(0), \\ 0, & \xi \ge j'(0). \end{cases}$$

Corollary (explicit fans).

Parallel. $j_{\mathrm{par}}'(0) = p$, $j_{\mathrm{par}}'(1) = -p$; on $\xi \in (-p, p)$, $$\rho_\infty^{\mathrm{par}}(\xi) = \tfrac{1}{2}\!\left(1 - \mathrm{sgn}(\xi)\sqrt{\tfrac{\xi^2(1-p)}{p\,(p - \xi^2)}}\right).$$

Sequential. $j_{\mathrm{seq}}'(0) = p$, $j_{\mathrm{seq}}'(1) = -p/(1-p)$; on $\xi \in \bigl(-\tfrac{p}{1-p},\, p\bigr)$, $$\rho_\infty^{\mathrm{seq}}(\xi) = \tfrac{1}{p}\!\left(1 - \sqrt{\tfrac{1-p}{1 - \xi}}\,\right).$$

References

  1. N. Rajewsky, L. Santen, A. Schadschneider, M. Schreckenberg. The asymmetric exclusion process: Comparison of update procedures. J. Stat. Phys. 92 (1998), 151–194.
  2. M. R. Evans, N. Rajewsky, E. R. Speer. Exact solution of a cellular automaton for traffic. J. Stat. Phys. 95 (1999), 45–96. arXiv:cond-mat/9903287.
  3. A. M. Povolotsky, V. B. Priezzhev. Determinant solution for the totally asymmetric exclusion process with parallel update. J. Stat. Mech. (2006), P07002.
  4. C. Kipnis, C. Landim. Scaling Limits of Interacting Particle Systems. Grundlehren der mathematischen Wissenschaften 320, Springer, 1999.
  5. A. Borodin, P. L. Ferrari, M. Prähofer, T. Sasamoto. Fluctuation properties of the TASEP with periodic initial configuration. J. Stat. Phys. 129 (2007), 1055–1080. arXiv:math-ph/0608056.

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code

(note: parameters in the code might differ from the ones in simulation results below)

Dear colleagues:

Feel free to use code (unless otherwise specified next to the corresponding link), data, and visualizations to illustrate your research in talks and papers, with attribution (CC BY-SA 4.0 (opens in new tab)). Some images are available in very high resolution upon request. I can also produce other simulations upon request - email me at lenia.petrov@gmail.com
This material is based upon work supported by the National Science Foundation under Grant DMS-2153869