Spatial fluctuations of a surviving particle in the trapping reaction

We consider the trapping reaction, $A+B\to B$, where $A$ and $B$ particles have a diffusive dynamics characterized by diffusion constants $D_A$ and $D_B$. The interaction with $B$ particles can be formally incorporated in an effective dynamics for one $A$ particle as was recently shown by Bray {\it et al}. [Phys. Rev. E {\bf 67}, 060102 (2003)]. We use this method to compute, in space dimension $d=1$, the asymptotic behaviour of the spatial fluctuation, $^{1/2}$, for a surviving $A$ particle in the perturbative regime, $D_A/D_B\ll 1$, for the case of an initially uniform distribution of $B$ particles. We show that, for $t\gg 1$, $^{1/2} \propto t^{\phi}$ with $\phi=1/4$. By contrast, the fluctuations of paths constrained to return to their starting point at time $t$ grow with the larger exponent 1/3. Numerical tests are consistent with these predictions.Comment: 10 pages, 5 figure

An introduction to phase transitions in stochastic dynamical systems

We give an introduction to phase transitions in the steady states of systems that evolve stochastically with equilibrium and nonequilibrium dynamics, the latter defined as those that do not possess a time-reversal symmetry. We try as much as possible to discuss both cases within the same conceptual framework, focussing on dynamically attractive `peaks' in state space. A quantitative characterisation of these peaks leads to expressions for the partition function and free energy that extend from equilibrium steady states to their nonequilibrium counterparts. We show that for certain classes of nonequilibrium systems that have been exactly solved, these expressions provide precise predictions of their macroscopic phase behaviour.Comment: Pedagogical talk contributed to the "Ageing and the Glass Transition" Summer School, Luxembourg, September 2005. 12 pages, 8 figures, uses the IOP 'jpconf' document clas

Random Networks with Tunable Degree Distribution and Clustering

We present an algorithm for generating random networks with arbitrary degree distribution and Clustering (frequency of triadic closure). We use this algorithm to generate networks with exponential, power law, and poisson degree distributions with variable levels of clustering. Such networks may be used as models of social networks and as a testable null hypothesis about network structure. Finally, we explore the effects of clustering on the point of the phase transition where a giant component forms in a random network, and on the size of the giant component. Some analysis of these effects is presented.Comment: 9 pages, 13 figures corrected typos, added two references, reorganized reference

Perturbation theory for the one-dimensional trapping reaction

We consider the survival probability of a particle in the presence of a finite number of diffusing traps in one dimension. Since the general solution for this quantity is not known when the number of traps is greater than two, we devise a perturbation series expansion in the diffusion constant of the particle. We calculate the persistence exponent associated with the particle's survival probability to second order and find that it is characterised by the asymmetry in the number of traps initially positioned on each side of the particle.Comment: 18 pages, no figures. Uses IOP Latex clas

Analysis of United Kingdom Off-Highway Construction Machinery Market and Its Consumers Using New-Sales Data

The off-highway construction machinery market and its consumers have attracted minimal previous research. This study addresses that void by analyzing annual United Kingdom (UK) (volume/portfolio) new-sales data for the 10 most popular products within that market, 1990–2010 inclusive. Graphical, descriptive statistical, Pearson-correlational, autocorrelational, and elementary modeling are employed to identify contrasts in sales regarding (1) high- and low-volume items; (2) growth trends and significant recessionary effects on volumes; (3) a demand change point circa 1997, since when annual product portfolio has changed little; and (4) product associations in consumer demand. Significant association is demonstrated between demand and construction output, especially with the value of new housing. Subsequently, consumption of wheeled loaders is modeled using construction volume, and demand for mini and crawler excavators is modeled using new-housing data. Time series trends for these machinery types are presented and forecast through 2015. The primary contribution of this study is a deeper understanding of the UK new-machinery market and the predilections of its consumers over the last two decades (to present)

Magnetic and Optical properties of strained films of multiferroic GdMnO3

The effects of strain on a film of mulitferroic GdMnO3 are investigated using both magnetometry and magneto-optic spectroscopy. Optical spectra, in the energy range 1.5eV - 3.5eV, were taken in Faraday geometry in an applied magnetic field and also at remanence. This yielded rich information on the effects of strain on the spin ordering in these films. Epitaxial films of GdMnO3 were grown on SrTiO3 and LaAlO3 substrates. The LaAlO3 was twinned and so produced a highly strained film whereas the strain was less for the film grown on SrTiO3. The Ne\'el temperatures and coercive fields were measured using zero field data and hysteresis loops obtained using a SQUID magnetometer. Optical absorption data agreed with earlier work on bulk materials. The two well known features in the optical spectrum, the charge transfer transition between Mn d states at ~2eV and the band edge transition from the oxygen p band to the d states at ~3eV are observed in the magnetic circular dichroism; however they behaved very differently both as a function of magnetic field and temperature. This is interpreted in terms of the magnetic ordering of the Mn spins.Comment: 9 pages of text including figure

Free energy landscapes, dynamics and the edge of chaos in mean-field models of spin glasses

Metastable states in Ising spin-glass models are studied by finding iterative solutions of mean-field equations for the local magnetizations. Two different equations are studied: the TAP equations which are exact for the SK model, and the simpler `naive-mean-field' (NMF) equations. The free-energy landscapes that emerge are very different. For the TAP equations, the numerical studies confirm the analytical results of Aspelmeier et al., which predict that TAP states consist of close pairs of minima and index-one (one unstable direction) saddle points, while for the NMF equations saddle points with large indices are found. For TAP the barrier height between a minimum and its nearby saddle point scales as (f-f_0)^{-1/3} where f is the free energy per spin of the solution and f_0 is the equilibrium free energy per spin. This means that for `pure states', for which f-f_0 is of order 1/N, the barriers scale as N^{1/3}, but between states for which f-f_0 is of order one the barriers are finite and also small so such metastable states will be of limited physical significance. For the NMF equations there are saddles of index K and we can demonstrate that their complexity Sigma_K scales as a function of K/N. We have also employed an iterative scheme with a free parameter that can be adjusted to bring the system of equations close to the `edge of chaos'. Both for the TAP and NME equations it is possible with this approach to find metastable states whose free energy per spin is close to f_0. As N increases, it becomes harder and harder to find solutions near the edge of chaos, but nevertheless the results which can be obtained are competitive with those achieved by more time-consuming computing methods and suggest that this method may be of general utility.Comment: 13 page

Voter Model with Time dependent Flip-rates

We introduce time variation in the flip-rates of the Voter Model. This type of generalisation is relevant to models of ageing in language change, allowing the representation of changes in speakers' learning rates over their lifetime and may be applied to any other similar model in which interaction rates at the microscopic level change with time. The mean time taken to reach consensus varies in a nontrivial way with the rate of change of the flip-rates, varying between bounds given by the mean consensus times for static homogeneous (the original Voter Model) and static heterogeneous flip-rates. By considering the mean time between interactions for each agent, we derive excellent estimates of the mean consensus times and exit probabilities for any time scale of flip-rate variation. The scaling of consensus times with population size on complex networks is correctly predicted, and is as would be expected for the ordinary voter model. Heterogeneity in the initial distribution of opinions has a strong effect, considerably reducing the mean time to consensus, while increasing the probability of survival of the opinion which initially occupies the most slowly changing agents. The mean times to reach consensus for different states are very different. An opinion originally held by the fastest changing agents has a smaller chance to succeed, and takes much longer to do so than an evenly distributed opinion.Comment: 16 pages, 6 figure