Dark matter density profiles: A comparison of nonextensive theory with N-body simulations

Density profiles of simulated galaxy cluster-sized dark matter haloes are analysed in the context of a recently introduced nonextensive theory of dark matter and gas density distributions. Nonextensive statistics accounts for long-range interactions in gravitationally coupled systems and is derived from the fundamental concept of entropy generalisation. The simulated profiles are determined down to radii of ~1% of R_200. The general trend of the relaxed, spherically averaged profiles is accurately reproduced by the theory. For the main free parameter kappa, measuring the degree of coupling within the system, and linked to physical quantities as the heat capacity and the polytropic index of the self-gravitating ensembles, we find a value of -15. The significant advantage over empirical fitting functions is provided by the physical content of the nonextensive approach.Comment: 6 pages, 3 figures, accepted for publication in A&

Cooperative protein transport in cellular organelles

Compartmentalization into biochemically distinct organelles constantly exchanging material is one of the hallmarks of eukaryotic cells. In the most naive picture of inter-organelle transport driven by concentration gradients, concentration differences between organelles should relax. We determine the conditions under which cooperative transport, i.e. based on molecular recognition, allows for the existence and maintenance of distinct organelle identities. Cooperative transport is also shown to control the flux of material transiting through a compartmentalized system, dramatically increasing the transit time under high incoming flux. By including chemical processing of the transported species, we show that this property provides a strong functional advantage to a system responsible for protein maturation and sorting.Comment: 9 pages, 5 figure

Fidelity of holonomic quantum computations in the case of random errors in the values of control parameters

We investigate the influence of random errors in external control parameters on the stability of holonomic quantum computation in the case of arbitrary loops and adiabatic connections. A simple expression is obtained for the case of small random uncorrelated errors. Due to universality of mathematical description our results are valid for any physical system which can be described in terms of holonomies. Theoretical results are confirmed by numerical simulations.Comment: 7 pages, 3 figure

Phenomenological approach to non-linear Langevin equations

In this paper we address the problem of consistently construct Langevin equations to describe fluctuations in non-linear systems. Detailed balance severely restricts the choice of the random force, but we prove that this property together with the macroscopic knowledge of the system is not enough to determine all the properties of the random force. If the cause of the fluctuations is weakly coupled to the fluctuating variable, then the statistical properties of the random force can be completely specified. For variables odd under time-reversal, microscopic reversibility and weak coupling impose symmetry relations on the variable-dependent Onsager coefficients. We then analyze the fluctuations in two cases: Brownian motion in position space and an asymmetric diode, for which the analysis based in the master equation approach is known. We find that, to the order of validity of the Langevin equation proposed here, the phenomenological theory is in agreement with the results predicted by more microscopic models.Comment: LaTex file, 2 figures available upon request, to appear in Phys.Rev.

Markov Chain Modeling of Polymer Translocation Through Pores

We solve the Chapman-Kolmogorov equation and study the exact splitting probabilities of the general stochastic process which describes polymer translocation through membrane pores within the broad class of Markov chains. Transition probabilities which satisfy a specific balance constraint provide a refinement of the Chuang-Kantor-Kardar relaxation picture of translocation, allowing us to investigate finite size effects in the evaluation of dynamical scaling exponents. We find that (i) previous Langevin simulation results can be recovered only if corrections to the polymer mobility exponent are taken into account and that (ii) the dynamical scaling exponents have a slow approach to their predicted asymptotic values as the polymer's length increases. We also address, along with strong support from additional numerical simulations, a critical discussion which points in a clear way the viability of the Markov chain approach put forward in this work.Comment: 17 pages, 5 figure

Conservation, Dissipation, and Ballistics: Mesoscopic Physics beyond the Landauer-Buettiker Theory

The standard physical model of contemporary mesoscopic noise and transport consists in a phenomenologically based approach, proposed originally by Landauer and since continued and amplified by Buettiker (and others). Throughout all the years of its gestation and growth, it is surprising that the Landauer-Buettiker approach to mesoscopics has matured with scant attention to the conservation properties lying at its roots: that is, at the level of actual microscopic principles. We systematically apply the conserving sum rules for the electron gas to clarify this fundamental issue within the standard phenomenology of mesoscopic conduction. Noise, as observed in quantum point contacts, provides the vital clue.Comment: 10 pp 3 figs, RevTe

Turing's model for biological pattern formation and the robustness problem

One of the fundamental questions in developmental biology is how the vast range of pattern and structure we observe in nature emerges from an almost uniformly homogeneous fertilized egg. In particular, the mechanisms by which biological systems maintain robustness, despite being subject to numerous sources of noise, are shrouded in mystery. Postulating plausible theoretical models of biological heterogeneity is not only difficult, but it is also further complicated by the problem of generating robustness, i.e. once we can generate a pattern, how do we ensure that this pattern is consistently reproducible in the face of perturbations to the domain, reaction time scale, boundary conditions and so forth. In this paper, not only do we review the basic properties of Turing's theory, we highlight the successes and pitfalls of using it as a model for biological systems, and discuss emerging developments in the area