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Nathan Clisby

Publications and source records attributed to Nathan Clisby.

15 recordsLinked to original sources

Classical length-5 pattern-avoiding permutations

We have made a systematic numerical study of the 16 Wilf classes of length-5 classical pattern-avoiding permutations from their generating function coefficients. We have extended the number of known coefficients in fourteen of the sixteen classes. Careful analysis, including sequence extension, has allowed us to estimate the growth constant of all classes, and in some cases to estimate the sub-dominant power-law term associated with the exponential growth. In six of the sixteen classes we find the familiar power-law behaviour, so that the coefficients behave like $s_n \sim C \cdot μ^n \cdot n^g,$ while in the remaining ten cases we find a stretched exponential as the most likely sub-dominant term, so that the coefficients behave like $s_n \sim C \cdot μ^n \cdot μ_1^{n^σ} \cdot n^g,$ where $0 < σ< 1.$ We have also classified the 120 possible permutations into the 16 distinct classes. We give compelling numerical evidence, and in one case a proof, that all 16 Wilf-class generating function coefficients can be represented as moments of a non-negative measure on $[0,\infty).$ Such sequences are known as {\em Stieltjes moment sequences}. They have a number of nice properties, such as log-convexity, which can be used to provide quite strong rigorous lower bounds. Stronger bounds still can be established under plausible monotonicity assumptions about the terms in the continued-fraction expansion of the generating functions implied by the Stieltjes property. In this way we provide strong (non-rigorous) lower bounds to the growth constants, which are sometimes within a few percent of the exact value.

math.CO

High-precision estimate of the hydrodynamic radius for self-avoiding walks

The universal asymptotic amplitude ratio between the gyration radius and the hydrodynamic radius of self-avoiding walks is estimated by high-resolution Monte Carlo simulations. By studying chains of length of up to $N = 2^{25} \approx 34 \times 10^6$ monomers, we find that the ratio takes the value $R_{\mathrm{G}}/R_{\mathrm{H}} = 1.5803940(45)$, which is several orders of magnitude more accurate than the previous state of the art. This is facilitated by a sampling scheme which is quite general, and which allows for the efficient estimation of averages of a large class of observables. The competing corrections to scaling for the hydrodynamic radius are clearly discernible. We also find improved estimates for other universal properties that measure the chain dimension. In particular, a method of analysis which eliminates the leading correction to scaling results in a highly accurate estimate for the Flory exponent of $ν= 0.58759700(40)$.

cond-mat.stat-mech

Computation of the equilibrium three-particle entropy for dense atomic fluids by molecular dynamics simulation

We have computed the two and three-particle contribution to the entropy of a Weeks-Chandler-Andersen fluid via molecular dynamics simulations. The three-particle correlation function and entropy were computed with a new method which simplified calculation. Results are qualitatively similar to Lennard-Jones systems. We observed a numerical instability in the three-particle contribution. This phenomenon has been previously detected when the traditional method is used, thus it is likely to be intrinsic in the computation. While the effect of statistical fluctuations can be removed through an extrapolation procedure, the discretization error due to finite bin size is more difficult to characterize. With a correct choice of the bin size, a good estimate of the three-particle entropy contribution can be achieved at any state, even close to the freezing point. We observed that, despite the fact that the magnitude of the three-particle contribution increases significantly compared to the two-particle contribution as freezing is approached, the error induced from overestimation of the excess entropy by the two and three-body terms exceeds that induced by approximating the excess entropy with the two body term alone.

cond-mat.stat-mech

Off-lattice and parallel implementations of the pivot algorithm

The pivot algorithm is the most efficient known method for sampling polymer configurations for self-avoiding walks and related models. Here we introduce two recent improvements to an efficient binary tree implementation of the pivot algorithm: an extension to an off-lattice model, and a parallel implementation.

cond-mat.stat-mech

High resolution Monte Carlo study of the Domb-Joyce model

We study the Domb-Joyce model of weakly self-avoiding walks on the simple cubic lattice via Monte Carlo simulations. We determine to excellent accuracy the value for the interaction parameter which results in an improved model for which the leading correction-to-scaling term has zero amplitude.

cond-mat.stat-mech

Monte Carlo study of four-dimensional self-avoiding walks of up to one billion steps

We study self-avoiding walks on the four-dimensional hypercubic lattice via Monte Carlo simulations of walks with up to one billion steps. We study the expected logarithmic corrections to scaling, and find convincing evidence in support the scaling form predicted by the renormalization group, with an estimate for the power of the logarithmic factor of 0.2516(14), which is consistent with the predicted value of 1/4. We also characterize the behaviour of the pivot algorithm for sampling four-dimensional self-avoiding walks, and conjecture that the probability of a pivot move being successful for an $N$-step walk is $O([ \log N ]^{-1/4})$.

cond-mat.stat-mech

Exact enumeration of self-avoiding walks on BCC and FCC lattices

Self-avoiding walks on the body-centered-cubic (BCC) and face-centered-cubic (FCC) lattices are enumerated up to lengths 28 and 24, respectively, using the length-doubling method. Analysis of the enumeration results yields values for the exponents $γ$ and $ν$ which are in agreement with, but less accurate than those obtained earlier from enumeration results on the simple cubic lattice. The non-universal growth constant and amplitudes are accurately determined, yielding for the BCC lattice $μ=6.530520(20)$, $A=1.1785(40)$, and $D=1.0864(50)$, and for the FCC lattice $μ=10.037075(20)$, $A=1.1736(24)$, and $D=1.0460(50)$.

cond-mat.stat-mech

Scale-free Monte Carlo method for calculating the critical exponent $γ$ of self-avoiding walks

We implement a scale-free version of the pivot algorithm and use it to sample pairs of three-dimensional self-avoiding walks, for the purpose of efficiently calculating an observable that corresponds to the probability that pairs of self-avoiding walks remain self-avoiding when they are concatenated. We study the properties of this Markov chain, and then use it to find the critical exponent $γ$ for self-avoiding walks to unprecedented accuracy. Our final estimate for $γ$ is $1.15695300(95)$.

cond-mat.stat-mech

Three-dimensional terminally attached self-avoiding walks and bridges

We study terminally attached self-avoiding walks and bridges on the simple cubic lattice, both by series analysis and Monte Carlo methods. We provide strong numerical evidence supporting a scaling relation between self-avoiding walks, bridges, and terminally attached self-avoiding walks, and posit that a corresponding amplitude ratio is a universal quantity.

cond-mat.stat-mech

Endless self-avoiding walks

We introduce a self-avoiding walk model for which end-effects are completely eliminated. We enumerate the number of these walks for various lattices in dimensions two and three, and use these enumerations to study the properties of this model. We find that endless self-avoiding walks have the same connective constant as self-avoiding walks, and the same Flory exponent $ν$. However, there is no power law correction to the exponential number growth for this new model, i.e. the critical exponent $γ= 1$ exactly. In addition, we have convincing numerical evidence to support the hypothesis that the amplitude for the number growth is a universal quantity, and somewhat weaker evidence which suggests that the number growth has no analytic corrections to scaling. The technique by which end-effects are eliminated may be generalised to other models of polymers such as interacting self-avoiding walks.

cond-mat.stat-mech

A new transfer-matrix algorithm for exact enumerations: Self-avoiding polygons on the square lattice

We present a new and more efficient implementation of transfer-matrix methods for exact enumerations of lattice objects. The new method is illustrated by an application to the enumeration of self-avoiding polygons on the square lattice. A detailed comparison with the previous best algorithm shows significant improvement in the running time of the algorithm. The new algorithm is used to extend the enumeration of polygons to length 130 from the previous record of 110.

math-ph

Efficient implementation of the pivot algorithm for self-avoiding walks

The pivot algorithm for self-avoiding walks has been implemented in a manner which is dramatically faster than previous implementations, enabling extremely long walks to be efficiently simulated. We explicitly describe the data structures and algorithms used, and provide a heuristic argument that the mean time per attempted pivot for $N$-step self-avoiding walks is $O(1)$ for the square and simple cubic lattices. Numerical experiments conducted for self-avoiding walks with up to 268 million steps are consistent with $o(\log N)$ behavior for the square lattice and $O(\log N)$ behavior for the simple cubic lattice. Our method can be adapted to other models of polymers with short-range interactions, on the lattice or in the continuum, and hence promises to be widely useful.

cond-mat.stat-mech

Accurate estimate of the critical exponent $ν$ for self-avoiding walks via a fast implementation of the pivot algorithm

We introduce a fast implementation of the pivot algorithm for self-avoiding walks, which we use to obtain large samples of walks on the cubic lattice of up to $33 \times 10^6$ steps. Consequently the critical exponent $ν$ for three-dimensional self-avoiding walks is determined to great accuracy; the final estimate is $ν=0.587597(7)$. The method can be adapted to other models of polymers with short-range interactions, on the lattice or in the continuum.

cond-mat.stat-mech