2012
DOI: 10.1088/1751-8113/45/9/095001
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Observation of SLE(κ, ρ) on the critical statistical models

Abstract: Schramm-Loewner Evolution (SLE) is a stochastic process that helps classify critical statistical models using one real parameter κ. Numerical study of SLE often involves curves that start and end on the real axis. To reduce numerical errors in studying the critical curves which start from the real axis and end on it, we have used hydrodynamically normalized SLE(κ, ρ) which is a stochastic differential equation that is hypothesized to govern such curves. In this paper we directly verify this hypothesis and nume… Show more

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Cited by 34 publications
(43 citation statements)
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“…To this end we discretize the uniformizing map g t by assuming the driving function to be partially constant, in time intervals δt n = t n − t n−1 , i.e., g t n ,ξ n = g δt n−1 ,ξ n−1 og δt n−2 ,ξ n−2 o...og δt 0 ,ξ 0 in which g δt n ,ξ n (z) is the map that uniformizes an infinitesimal vertical line [24]: One can discretize Eq. (9).…”
Section: Numerical Resultsmentioning
confidence: 99%
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“…To this end we discretize the uniformizing map g t by assuming the driving function to be partially constant, in time intervals δt n = t n − t n−1 , i.e., g t n ,ξ n = g δt n−1 ,ξ n−1 og δt n−2 ,ξ n−2 o...og δt 0 ,ξ 0 in which g δt n ,ξ n (z) is the map that uniformizes an infinitesimal vertical line [24]: One can discretize Eq. (9).…”
Section: Numerical Resultsmentioning
confidence: 99%
“…It has also been shown that SLE κ has correspondence with CFT with central charge c κ = (6−κ)(3κ−8) 2κ and at the point where the SLE curve starts a boundary changing operator with weight h 1;2 = (6 − κ)/(2κ) is sitting [18]. SLE(κ,ρ) is a variant of SLE in which the curve experiences some additional boundary changes [24]. In this theory, the parameter κ identifies the local properties of the model in hand as above, and the parameter ρ has to do with the boundary conditions (bc) imposed.…”
Section: Schramm-loewner Evolutionmentioning
confidence: 98%
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“…The first simulation has been done in 16 in which it was shown that the best values are κ = 1.95 ± 0.07 and ρ c = 3.5 ± 0.5. Our simulation for our case (which is on cylinder and the curves are rescaled) coincides with this report, i.e.…”
Section: B Calculation Of ρmentioning
confidence: 99%
“…It has been shown that this method results in more precise and reliable determination of these parameters 16 . Now consider one additional preferred point on the real axis sitting in x 0 .…”
mentioning
confidence: 99%