Power, discursive space and institutional practices in the construction of housing problems

A constructionist approach to the study of social problems and housing policy provides a theoretically informed means of analysing the ways in which housing policy is formulated and implemented. Yet despite a strong commitment by housing researchers to policy-relevance, constructionist studies of how specific social problems are generated and deployed have so far made only a limited impact on housing research. The paper addresses this lacuna by first discussing important literature and the key conceptual issues in this field of study. This is followed by a discussion of two examples from recent UK housing policy (the shift in the 1980s from defining lone mothers as the victims of housing shortages to a morally questionable group subverting needs based allocation policies and the re-emergence of anti-social behaviour as a problem on housing estates). The paper's conclusion is that the 'construction of problems' provides a rich source of new material as well as offering significant opportunities to develop a more critically informed housing research agenda

Privileged or exploited council tenants?: The discursive change in Conservative housing policy from 1972 to 1980

The process of social construction in which competing and sometimes contradictory definitions contend with one another plays a decisive part in policy making. Justifications for policy intervention often require a narrative identifying villains or victims to delineate creatively a 'social problem' that needs to be addressed by appropriate measures. This article shows how contrasting political and media representations of council tenants in the 1960s and 1970s provided the emotive justifications for two distinct policies: 'Fair Rents' and the 'Right to Buy'. The article concludes that more attention should be paid to the way that the successful mobilisation of bias legitimises policy interventions

Quantum Operation Time Reversal

The dynamics of an open quantum system can be described by a quantum operation, a linear, complete positive map of operators. Here, I exhibit a compact expression for the time reversal of a quantum operation, which is closely analogous to the time reversal of a classical Markov transition matrix. Since open quantum dynamics are stochastic, and not, in general, deterministic, the time reversal is not, in general, an inversion of the dynamics. Rather, the system relaxes towards equilibrium in both the forward and reverse time directions. The probability of a quantum trajectory and the conjugate, time reversed trajectory are related by the heat exchanged with the environment.Comment: 4 page

Probability distribution of residence times of grains in models of ricepiles

We study the probability distribution of residence time of a grain at a site, and its total residence time inside a pile, in different ricepile models. The tails of these distributions are dominated by the grains that get deeply buried in the pile. We show that, for a pile of size $L$, the probabilities that the residence time at a site or the total residence time is greater than $t$, both decay as $1/t(\ln t)^x$ for $L^{\omega} \ll t \ll \exp(L^{\gamma})$ where $\gamma$ is an exponent $\ge 1$, and values of $x$ and $\omega$ in the two cases are different. In the Oslo ricepile model we find that the probability that the residence time $T_i$ at a site $i$ being greater than or equal to $t$, is a non-monotonic function of $L$ for a fixed $t$ and does not obey simple scaling. For model in $d$ dimensions, we show that the probability of minimum slope configuration in the steady state, for large $L$, varies as $\exp(-\kappa L^{d+2})$ where $\kappa$ is a constant, and hence $\gamma = d+2$.Comment: 13 pages, 23 figures, Submitted to Phys. Rev.

Spectral coarse graining for random walk in bipartite networks

Many real-world networks display a natural bipartite structure, while analyzing or visualizing large bipartite networks is one of the most challenges. As a result, it is necessary to reduce the complexity of large bipartite systems and preserve the functionality at the same time. We observe, however, the existing coarse graining methods for binary networks fail to work in the bipartite networks. In this paper, we use the spectral analysis to design a coarse graining scheme specifically for bipartite networks and keep their random walk properties unchanged. Numerical analysis on artificial and real-world bipartite networks indicates that our coarse graining scheme could obtain much smaller networks from large ones, keeping most of the relevant spectral properties. Finally, we further validate the coarse graining method by directly comparing the mean first passage time between the original network and the reduced one.Comment: 7 pages, 3 figure

Maximal-entropy random walk unifies centrality measures

In this paper analogies between different (dis)similarity matrices are derived. These matrices, which are connected to path enumeration and random walks, are used in community detection methods or in computation of centrality measures for complex networks. The focus is on a number of known centrality measures, which inherit the connections established for similarity matrices. These measures are based on the principal eigenvector of the adjacency matrix, path enumeration, as well as on the stationary state, stochastic matrix or mean first-passage times of a random walk. Particular attention is paid to the maximal-entropy random walk, which serves as a very distinct alternative to the ordinary random walk used in network analysis. The various importance measures, defined both with the use of ordinary random walk and the maximal-entropy random walk, are compared numerically on a set of benchmark graphs. It is shown that groups of centrality measures defined with the two random walks cluster into two separate families. In particular, the group of centralities for the maximal-entropy random walk, connected to the eigenvector centrality and path enumeration, is strongly distinct from all the other measures and produces largely equivalent results.Comment: 7 pages, 2 figure

Excessive functions of continuous time Markov chains

AbstractWe consider transient continuous time Markov chains P(t) with P′ij(0)=qiΠij for i≠j and −qi for i=j. We assume 0<qi<∞ for all i. Then 1/qi is the mean time the process remains in state i, and Π is the transition matrix of the imbedded jump process. We let q be a diagonal matrix with diagonal entries qi.A non-negative function h is P(t)-excessive (invariant) if h≥P(t)h, (h=P(t) h) for all t. It is Π-superregular (regular) if h≥Πh (h=Πh). Our main results characterize the excessive functions of the minimal process in terms of q and Π. These results can also be used to characterize excessive functions of certain non-minimal processes

Computing the entropy of user navigation in the web

Navigation through the web, colloquially known as "surfing", is one of the main activities of users during web interaction. When users follow a navigation trail they often tend to get disoriented in terms of the goals of their original query and thus the discovery of typical user trails could be useful in providing navigation assistance. Herein, we give a theoretical underpinning of user navigation in terms of the entropy of an underlying Markov chain modelling the web topology. We present a novel method for online incremental computation of the entropy and a large deviation result regarding the length of a trail to realize the said entropy. We provide an error analysis for our estimation of the entropy in terms of the divergence between the empirical and actual probabilities. We then indicate applications of our algorithm in the area of web data mining. Finally, we present an extension of our technique to higher-order Markov chains by a suitable reduction of a higher-order Markov chain model to a first-order one

Zero-Reachability in Probabilistic Multi-Counter Automata

We study the qualitative and quantitative zero-reachability problem in probabilistic multi-counter systems. We identify the undecidable variants of the problems, and then we concentrate on the remaining two cases. In the first case, when we are interested in the probability of all runs that visit zero in some counter, we show that the qualitative zero-reachability is decidable in time which is polynomial in the size of a given pMC and doubly exponential in the number of counters. Further, we show that the probability of all zero-reaching runs can be effectively approximated up to an arbitrarily small given error epsilon > 0 in time which is polynomial in log(epsilon), exponential in the size of a given pMC, and doubly exponential in the number of counters. In the second case, we are interested in the probability of all runs that visit zero in some counter different from the last counter. Here we show that the qualitative zero-reachability is decidable and SquareRootSum-hard, and the probability of all zero-reaching runs can be effectively approximated up to an arbitrarily small given error epsilon > 0 (these result applies to pMC satisfying a suitable technical condition that can be verified in polynomial time). The proof techniques invented in the second case allow to construct counterexamples for some classical results about ergodicity in stochastic Petri nets.Comment: 20 page

Micromagnetic understanding of stochastic resonance driven by spin-transfertorque

In this paper, we employ micromagnetic simulations to study non-adiabatic stochastic resonance (NASR) excited by spin-transfer torque in a super-paramagnetic free layer nanomagnet of a nanoscale spin valve. We find that NASR dynamics involves thermally activated transitions among two static states and a single dynamic state of the nanomagnet and can be well understood in the framework of Markov chain rate theory. Our simulations show that a direct voltage generated by the spin valve at the NASR frequency is at least one order of magnitude greater than the dc voltage generated off the NASR frequency. Our computations also reproduce the main experimentally observed features of NASR such as the resonance frequency, the temperature dependence and the current bias dependence of the resonance amplitude. We propose a simple design of a microwave signal detector based on NASR driven by spin transfer torque.Comment: 25 pages 8 figures, accepted for pubblication on Phys. Rev.