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Neill E. Bowler

Publications and source records attributed to Neill E. Bowler.

6 recordsLinked to original sources
arXiv2026

Remote sensing of the temporal and spatial variability of atmospheric refractivity using ADS-B interferometry (ADSBi)

The extreme variability of humidity in the lower atmosphere over short spatial and temporal scales presents an enormous challenge for existing observing systems. Variations in humidity can be detected due to changes in the refractive properties of the atmosphere, which influence the propagation of electromagnetic radiation. We demonstrate the ability to retrieve high-resolution refractivity gradient measurements using an interferometer to measure the refraction of the Automatic Dependent Surveillance-Broadcast (ADS-B) radio transmission routinely broadcast by commercial aircraft. The ADS-B interferometry (ADSBi) technique is sensitive to small-scale spatial and temporal variability in the refractivity gradient due to changes in humidity. We demonstrate how the retrieval of refractivity profiles is possible exploiting the differences in the observed refraction of radio transmissions broadcast by aircraft at different distances and altitudes.

physics.ao-ph↗
arXiv2004

Off-lattice Noise Reduced Diffusion-limited Aggregation in Three Dimensions

Using off-lattice noise reduction it is possible to estimate the asymptotic properties of diffusion-limited aggregation clusters grown in three dimensions with greater accuracy than would otherwise be possible. The fractal dimension of these aggregates is found to be 2.50 +/- 0.01, in agreement with earlier studies, and the asymptotic value of the relative penetration depth is 0.122 +/- 0.002. The multipole powers of the growth measure also exhibit universal asymptotes. The fixed point noise reduction is estimated to be ε= 0.0035 meaning that large clusters can be identified with a low noise regime. The slowest correction to scaling exponents are measured for a number of properties of the clusters, and the exponent for the relative penetration depth and quadrupole moment are found to be significantly different from each other. The relative penetration depth exhibits the slowest correction to scaling of all quantities, which is consistent with a theoretical result derived in two dimensions.

cond-mat.stat-mech↗
arXiv2003

Characterisation of the probabilistic travelling salesman problem

We show that Stochastic Annealing can be successfully applied to gain new results on the Probabilistic Traveling Salesman Problem (PTSP). The probabilistic "traveling salesman" must decide on an a priori order in which to visit n cities (randomly distributed over a unit square) before learning that some cities can be omitted. We find the optimized average length of the pruned tour follows E(\bar{L}_{pruned}) = \sqrt{np} (0.872-0.105p) f(np) where p is the probability of a city needing to be visited, and f(np) -> 1 as np -> infinity. The average length of the a priori tour (before omitting any cities) is found to follow E(L_{a priori}) =\sqrt{n/p}β(p) where β(p)=1/(1.25-0.82 ln(p)) is measured for 0.05 < p < 0.6. Scaling arguments and indirect measurements suggest that β(p) tends towards a constant for p<0.03. Our stochastic annealing algorithm is based on limited sampling of the pruned tour lengths, exploiting the sampling error to provide the analogue of thermal fluctuations in simulated (thermal) annealing. The method has general application to the optimization of functions whose cost to evaluate rises with the precision required.

physics.comp-ph↗
arXiv2003

Stochastic Annealing

We demonstrate that is it possible to simulate a system in thermal equilibrium even when the energy cannot be evaluated exactly, provided the error distribution is known. This leads to an effective optimisation strategy for problems where the evaluation of each design can only be sampled statistically.

cond-mat.stat-mech↗
arXiv2002

Off-lattice noise reduction and the ultimate scaling of DLA in two dimensions

Off-lattice DLA clusters grown with different levels of noise reduction are found to be consistent with a simple fractal fixed point. Cluster shapes and their ensemble variation exhibit a dominant slowest correction to scaling, and this also accounts for the apparent ``multiscaling'' in the DLA mass distribution. We interpret the correction to scaling in terms of renormalized noise. The limiting value of this variable is strikingly small and is dominated by fluctuations in cluster shape. Earlier claims of anomalous scaling in DLA were misled by the slow approach to this small fixed point value.

cond-mat.stat-mech↗