Stability of travelling-wave solutions for reaction-diffusion-convection systems

We are concerned with the asymptotic behaviour of classical solutions of systems of the form u_t = Au_xx + f(u, u_x), x in R, t>0, u(x,t) a vector in RN, with u(x,0)= U(x), where A is a positive-definite diagonal matrix and f is a 'bistable' nonlinearity satisfying conditions which guarantee the existence of a comparison principle. Suppose that there is a travelling-front solution w with velocity c, that connects two stable equilibria of f. We show that if U is bounded, uniformly continuously differentiable and such that w(x) - U(x) is small when the modulus of x is large, then there exists y in R such that u(., t) converges to w(.+y-ct) in the C1 norm at an exponential rate as t tends to infinity. Our approach extends an idea developed by Roquejoffre, Terman and Volpert in the convectionless case, where f is independent of u_x.Comment: 23 pages. To appear in Topological Methods in Nonlinear Analysi

Protein secondary structure: Entropy, correlations and prediction

Is protein secondary structure primarily determined by local interactions between residues closely spaced along the amino acid backbone, or by non-local tertiary interactions? To answer this question we have measured the entropy densities of primary structure and secondary structure sequences, and the local inter-sequence mutual information density. We find that the important inter-sequence interactions are short ranged, that correlations between neighboring amino acids are essentially uninformative, and that only 1/4 of the total information needed to determine the secondary structure is available from local inter-sequence correlations. Since the remaining information must come from non-local interactions, this observation supports the view that the majority of most proteins fold via a cooperative process where secondary and tertiary structure form concurrently. To provide a more direct comparison to existing secondary structure prediction methods, we construct a simple hidden Markov model (HMM) of the sequences. This HMM achieves a prediction accuracy comparable to other single sequence secondary structure prediction algorithms, and can extract almost all of the inter-sequence mutual information. This suggests that these algorithms are almost optimal, and that we should not expect a dramatic improvement in prediction accuracy. However, local correlations between secondary and primary structure are probably of under-appreciated importance in many tertiary structure prediction methods, such as threading.Comment: 8 pages, 5 figure

On the Quantum Jarzynski Identity

In this note, we will discuss how to compactly express and prove the Jarzynski identity for an open quantum system with dissipative dynamics. We will avoid explicitly measuring the work directly, which is tantamount to continuously monitoring the system, and instead measure the heat flow from the environment. We represent the measurement of heat flow with Hermitian map superoperators that act on the system density matrix. Hermitian maps provide a convenient and compact representation of sequential measurement and correlation functions.Comment: 4 page