Renormalization Group Results for Random Resistor Networks

1987 ◽  
pp. 471-480
Author(s):  
A. B. Harris
Keyword(s):  
Renormalization Group ◽  
Resistor Networks

scholarly journals HIERARCHY OF CRITICAL EXPONENTS ON SIERPINSKI FRACTAL RESISTOR NETWORKS

2009 ◽  
Vol 23 (18) ◽  
pp. 2293-2310
Author(s):  
M. MIRZAEE ◽  
M. A. JAFARIZADEH
Keyword(s):  
Renormalization Group ◽  
Current Distribution ◽  
Critical Exponents ◽  
Real Space ◽  
Invariant Polynomials ◽  
The Real ◽  
Resistor Networks ◽  
Real Space Renormalization Group ◽  
Group Technique

Using the S3-symmetry of Sierpinski fractal resistor networks we determine the current distribution as well as the multifractals spectrum of moments of current distribution by using the real space renormalization group technique based on ([q/4]+1) independent Schure's invariant polynomials of inwards flowing currents.

The renormalization group and ultraviolet asymptotics

1979 ◽  
Vol 129 (11) ◽  
pp. 407 ◽  
Author(s):  
A.A. Vladimirov ◽  
D.V. Shirkov
Keyword(s):  
Renormalization Group

Phenomenological Renormalization Group and Cluster Approximation

2014 ◽  
Vol 59 (7) ◽  
pp. 655-662
Author(s):  
O. Borisenko ◽  
◽  
V. Chelnokov ◽  
V. Kushnir ◽  
◽  
...  
Keyword(s):  
Renormalization Group ◽  
Cluster Approximation ◽  
Phenomenological Renormalization

Renormalization Group

2020 ◽  
Author(s):  
Giuseppe Benfatto ◽  
Giovanni Gallavotti
Keyword(s):  
Renormalization Group

The Non-Causal Character of Renormalization Group Explanations

2018 ◽  
Author(s):  
Margaret Morrison
Keyword(s):  
Probability Theory ◽  
Renormalization Group ◽  
Dynamical Systems ◽  
Recent Literature ◽  
Mathematical Explanation ◽  
Causal Status ◽  
Physical Information ◽  
The Relationship ◽  
Structural Aspects

After reviewing some of the recent literature on non-causal and mathematical explanation, this chapter develops an argument as to why renormalization group (RG) methods should be seen as providing non-causal, yet physical, information about certain kinds of systems/phenomena. The argument centres on the structural character of RG explanations and the relationship between RG and probability theory. These features are crucial for the claim that the non-causal status of RG explanations involves something different from simply ignoring or “averaging over” microphysical details—the kind of explanations common to statistical mechanics. The chapter concludes with a discussion of the role of RG in treating dynamical systems and how that role exemplifies the structural aspects of RG explanations which in turn exemplifies the non-causal features.

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