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Leo P. Kadanoff

Publications and source records attributed to Leo P. Kadanoff.

25 records · Page 2Linked to original sources

The Loewner equation: maps and shapes

In the last few years, new insights have permitted unexpected progress in the study of fractal shapes in two dimensions. A new approach, called Schramm-Loewner evolution, or SLE, has arisen through analytic function theory and probability theory, and given a new way of calculating fractal shapes in critical phenomena, the theory of random walks, and of percolation. We present a non-technical discussion of this development aimed to attract the attention of condensed matter community to this fascinating subject.

cond-mat.stat-mech↗

Excellence in Computer Simulation

Excellent computer simulations are done for a purpose. The most valid purposes are to explore uncharted territory, to resolve a well-posed scientific or technical question, or to make a design choice. Stand-alone modeling can serve the first purpose. The other two goals need a full integration of the modeling effort into a scientific or engineering program. Some excellent work, much of it related to the Department of Energy Laboratories, is reviewed. Some less happy stories are recounted. In the past, some of the most impressive work has involved complexity and chaos. Prediction in a complex world requires a first principles understanding based upon the intersection of theory, experiment and simulation.

math.NA↗

Numerical and Theoretical Studies of Noise Effects in the Kauffman Model

In this work we analyze the stochastic dynamics of the Kauffman model evolving under the influence of noise. By considering the average crossing time between two distinct trajectories, we show that different Kauffman models exhibit a similar kind of behavior, even when the structure of their basins of attraction is quite different. This can be considered as a robust property of these models. We present numerical results for the full range of noise level and obtain approximate analytic expressions for the above crossing time as a function of the noise in the limit cases of small and large noise levels.

nlin.AO↗

A New Kind of Science?

Book Review for: "A New Kind of Science", by Stephen Wolfram (Wolfram Media, Inc. Champaign IL 2002).

nlin.CG↗

Reversible boolean networks II: Phase transition, oscillation, and local structures

We continue our consideration of a class of models describing the reversible dynamics of $N$ Boolean variables, each with $K$ inputs. We investigate in detail the behavior of the Hamming distance as well as of the distribution of orbit lengths as $N$ and $K$ are varied. We present numerical evidence for a phase transition in the behavior of the Hamming distance at a critical value $K_c\approx 1.65$ and also an analytic theory that yields the exact bounds on $1.5 \le K_c \le 2.$ We also discuss the large oscillations that we observe in the Hamming distance for $K<K_c$ as a function of time as well as in the distribution of cycle lengths as a function of cycle length for moderate $K$ both greater than and less than $K_c$. We propose that local structures, or subsets of spins whose dynamics are not fully coupled to the other spins in the system, play a crucial role in generating these oscillations. The simplest of these structures are linear chains, called linkages, and rings, called circuits. We discuss the properties of the linkages in some detail, and sketch the properties of circuits. We argue that the observed oscillation phenomena can be largely understood in terms of these local structures.

cond-mat.dis-nn↗

Reversible Boolean Networks I: Distribution of Cycle Lengths

We consider a class of models describing the dynamics of $N$ Boolean variables, where the time evolution of each depends on the values of $K$ of the other variables. Previous work has considered models with dissipative dynamics. Here we consider time-reversible models, which necessarily have the property that every possible point in the state-space is an element of one and only one cycle. As in the dissipative case, when K is large, typical orbit lengths grow exponentially with N, whereas for small enough K, typical orbit lengths grow much more slowly with N. The numerical data are consistent with the existence of a phase transition at which the average orbit length grows as a power of N at a value of K between 1.4 and 1.7. However, in the reversible models the interplay between the discrete symmetry and quenched randomness can lead to enormous fluctuations of orbit lengths and other interesting features that are unique to the reversible case. The orbits can be classified by their behavior under time reversal. The orbits that transform into themselves under time reversal have properties quite different from those that do not; in particular, a significant fraction of latter-type orbits have lengths enormously longer than orbits that are time reversal-symmetric. For large K and moderate N, the vast majority of points in the state-space are on one of the time reversal singlet orbits, and a random hopping model gives an accurate description of orbit lengths. However, for any finite K, the random hopping approximation fails qualitatively when N is large enough ($N\gg 2^{(2^K)}$).

cond-mat.dis-nn↗

Analysis of a Population Genetics Model with Mutation, Selection, and Pleiotropy

We investigate the behavior of a population genetics model introduced by Waxman and Peck incorporating mutation, selection, and pleiotropy. The population is infinite and continuous variation of genotype is allowed. Nonetheless, Waxman and Peck showed that if the degree of pleiotropy is large enough,in this model a nonzero fraction of the population can have identical alleles. This `condensed mode' behavior appears in the limit of infinite times. This paper explores the time-dependence of the distribution of alleles in this model. First, the model is analyzed using a recursion technique which enables the distribution of alleles to be calculated at finite times as well as in Waxman and Peck's infinite-time limit. Second, both Waxman and Peck's original model and a related model in which mutations occur continuously are mapped onto problems in quantum mechanics. In both cases, the long-time analysis for the biological model is equivalent to finding the nature of the eigenstates of the quantum problem. The condensed mode appears if and only if there is no bound state in the quantum problem. We compare the behavior of the discrete- and continuous-time versions of the model. The results for the two cases are qualitatively similar, though there are some quantitative differences. We also discuss our attempts to correlate the statistics of DNA sequence variations with the degree of pleiotropy of various genes.

cond-mat↗