Dynamical phase transition in the occupation fraction statistics for non-crossing Brownian particles

We consider a system of $N$ non-crossing Brownian particles in one dimension. We find the exact rate function that describes the long-time large deviation statistics of their occupation fraction in a finite interval in space. Remarkably, we find that, for any general $N \geq 2$, the system undergoes $N-1$ dynamical phase transitions of second order. The $N-1$ transitions are the boundaries of $N$ phases that correspond to different numbers of particles which are in the vicinity of the interval throughout the dynamics. We achieve this by mapping the problem to that of finding the ground-state energy for $N$ noninteracting spinless fermions in a square-well potential. The phases correspond to different numbers of single-body bound states for the quantum problem. We also study the process conditioned on a given occupation fraction and the large-$N$ limiting behavior.Comment: 11 pages, 4 figure

Large deviations in statistics of the convex hull of passive and active particles: A theoretical study

We investigate analytically the distribution tails of the area A and perimeter L of a convex hull for different types of planar random walks. For N noninteracting Brownian motions of duration T we find that the large-L and A tails behave as $\mathcal{P}\left(L\right)\sim e^{-b_{N}L^{2}/DT}$ and $\mathcal{P}\left(A\right)\sim e^{-c_{N}A/DT}$, while the small-$L$ and $A$ tails behave as $\mathcal{P}\left(L\right)\sim e^{-d_{N}DT/L^{2}}$ and $\mathcal{P}\left(A\right)\sim e^{-e_{N}DT/A}$, where $D$ is the diffusion coefficient. We calculated all of the coefficients ($b_N, c_N, d_N, e_N$) exactly. Strikingly, we find that $b_N$ and $c_N$ are independent of N, for $N\geq 3$ and $N \geq 4$, respectively. We find that the large-L (A) tails are dominated by a single, most probable realization that attains the desired L (A). The left tails are dominated by the survival probability of the particles inside a circle of appropriate size. For active particles and at long times, we find that large-L and A tails are given by $\mathcal{P}\left(L\right)\sim e^{-T\Psi_{N}^{\text{per}}\left(L/T\right)}$ and $\mathcal{P}\left(A\right)\sim e^{-T\Psi_{N}^{\text{area}}\left(\sqrt{A}/T\right)}$ respectively. We calculate the large deviation functions $\Psi_N$ exactly and find that they exhibit multiple singularities. We interpret these as dynamical phase transitions of first order. We extended several of these results to dimensions $d>2$. Our analytic predictions display excellent agreement with existing results that were obtained from extensive numerical simulations.Comment: 15 pages, 9 figure

Critical behaviour near critical end points and tricritical points in disordered spin-1 ferromagnets

Critical end points and tricritical points are multicritical points that separate lines of continuous transitions from lines of first order transitions in the phase diagram of many systems. In models like the spin-1 disordered Blume-Capel model and the repulsive Blume-Emery-Griffiths model, the tricritical point splits into a critical end point and a bicritical end point with an increase in disorder and repulsive coupling strength respectively. In order to make a distinction between these two multicritical points, we investigate and contrast the behaviour of the first order phase boundary and the co-existence diameter around them.Comment: 23 pages, 28 figure

Phase transitions in the Blume-Capel model with trimodal and Gaussian random fields

We study the effect of different symmetric random field distributions: trimodal and Gaussian on the phase diagram of the infinite range Blume-Capel model. For the trimodal random field, the model has a very rich phase diagram. We find three new ordered phases, multicritical points like tricritical point (TCP), bicritical end point (BEP), critical end point (CEP) along with some multi-phase coexistence points. We also find re-entrance at low temperatures for some values of the parameters. On the other hand for the Gaussian distribution the phase diagram consists of a continuous line of transition followed by a first order transition line, meeting at a TCP. The TCP vanishes for higher strength of the random field. In contrast to the trimodal case, in Gaussian case no new phase emerges.Comment: 25 pages, 19 figures. Version accepted for publication in Journal of Statistical Physic