Cluster tomography in percolation
Abstract
In cluster tomography, we propose measuring the number of clusters N intersected by a line segment of length across a finite sample. As expected, the leading order of N() scales as a, where a depends on microscopic details of the system. However, at criticality, there is often an additional nonlinearity of the form b(), originating from the endpoints of the line segment. By performing large scale Monte Carlo simulations of both 2d and 3d percolation, we find that b is universal and depends only on the angles encountered at the endpoints of the line segment intersecting the sample. Our findings are further supported by analytic arguments in 2d, building on results in conformal field theory. Being broadly applicable, cluster tomography can be an efficient tool to detect phase transitions and to characterize the corresponding universality class in classical or quantum systems with a relevant cluster structure.
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