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Highly optimized tolerance

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In applied mathematics, highly optimized tolerance (HOT) is a method of generating power law behavior in systems by including a global optimization principle. It was developed by Jean M. Carlson and John Doyle in the early 2000s. For some systems that display a characteristic scale, a global optimization term could potentially be added that would then yield power law behavior. It has been used to generate and describe internet-like graphs, forest fire models and may also apply to biological systems.

Example

The following is taken from Sornette's book.

Consider a random variable, X {\displaystyle X} , that takes on values x i {\displaystyle x_{i}} with probability p i {\displaystyle p_{i}} . Furthermore, let’s assume for another parameter r i {\displaystyle r_{i}}

x i = r i β {\displaystyle x_{i}=r_{i}^{-\beta }}

for some fixed β {\displaystyle \beta } . We then want to minimize

L = i = 0 N 1 p i x i {\displaystyle L=\sum _{i=0}^{N-1}p_{i}x_{i}}

subject to the constraint

i = 0 N 1 r i = κ {\displaystyle \sum _{i=0}^{N-1}r_{i}=\kappa }

Using Lagrange multipliers, this gives

p i x i ( 1 + 1 / β ) {\displaystyle p_{i}\propto x_{i}^{-(1+1/\beta )}}

giving us a power law. The global optimization of minimizing the energy along with the power law dependence between x i {\displaystyle x_{i}} and r i {\displaystyle r_{i}} gives us a power law distribution in probability.

See also

References

  1. Carlson, null; Doyle, null (2000-03-13). "Highly optimized tolerance: robustness and design in complex systems" (PDF). Physical Review Letters. 84 (11): 2529–2532. Bibcode:2000PhRvL..84.2529C. doi:10.1103/PhysRevLett.84.2529. ISSN 1079-7114. PMID 11018927.


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