Universal Markovian reduction of Brownian particle dynamics

Non-Markovian processes can often be turned Markovian by enlarging the set of variables. Here we show, by an explicit construction, how this can be done for the dynamics of a Brownian particle obeying the generalized Langevin equation. Given an arbitrary bath spectral density $J_{0}$, we introduce an orthogonal transformation of the bath variables into effective modes, leading stepwise to a semi-infinite chain with nearest-neighbor interactions. The transformation is uniquely determined by $J_{0}$ and defines a sequence $\{J_{n}\}_{n\in\mathbb{N}}$ of residual spectral densities describing the interaction of the terminal chain mode, at each step, with the remaining bath. We derive a simple, one-term recurrence relation for this sequence, and show that its limit is the quasi-Ohmic expression provided by the Rubin model of dissipation. Numerical calculations show that, irrespective of the details of $J_{0}$, convergence is fast enough to be useful in practice for an effective Markovian reduction of quantum dissipative dynamics

RNA Secondary Structures: Complex Statics and Glassy Dynamics

Models for RNA secondary structures (the topology of folded RNA) without pseudo knots are disordered systems with a complex state-space below a critical temperature. Hence, a complex dynamical (glassy) behavior can be expected, when performing Monte Carlo simulation. Interestingly, in contrast to most other complex systems, the ground states and the density of states can be computed in polynomial time exactly using transfer matrix methods. Hence, RNA secondary structure is an ideal model to study the relation between static/thermodynamic properties and dynamics of algorithms. Also they constitute an ideal benchmark system for new Monte Carlo methods. Here we considered three different recent Monte Carlo approaches: entropic sampling using flat histograms, optimized-weights ensembles, and ParQ, which estimates the density of states from transition matrices. These methods were examined by comparing the obtained density of states with the exact results. We relate the complexity seen in the dynamics of the Monte Carlo algorithms to static properties of the phase space by studying the correlations between tunneling times, sampling errors, amount of meta-stable states and degree of ultrametricity at finite temperature

Development and test results of a readout chip for the GERDA experiment

This paper describes the F-CSA104 architecture and its measurement results. The F-CSA104 is for γ spectroscopy with Ge detectors. It is a low noise, fully integrated, four channel XFAB 0.6μm CMOS technology ASIC, that has been developed for the GERDA experiment. Each channel contains a charge sensitive preamplifier (CSA) followed by a 11.7MHz differential line driver. It has been particularly designed to operate in liquid argon (T = 87K/-186°C) and to have a measuring sensitivity of 660e- with an ENC of 110e-, after offline filtering with 10μs shaping, when connected to a 30pF load. Special techniques are used to improve the SNR such as a large input PMOS FET, an integrated 500MΩ CSA feedback resistor and a noise degeneration drain resistor

RNA secondary structure design

We consider the inverse-folding problem for RNA secondary structures: for a given (pseudo-knot-free) secondary structure find a sequence that has that structure as its ground state. If such a sequence exists, the structure is called designable. We implemented a branch-and-bound algorithm that is able to do an exhaustive search within the sequence space, i.e., gives an exact answer whether such a sequence exists. The bound required by the branch-and-bound algorithm are calculated by a dynamic programming algorithm. We consider different alphabet sizes and an ensemble of random structures, which we want to design. We find that for two letters almost none of these structures are designable. The designability improves for the three-letter case, but still a significant fraction of structures is undesignable. This changes when we look at the natural four-letter case with two pairs of complementary bases: undesignable structures are the exception, although they still exist. Finally, we also study the relation between designability and the algorithmic complexity of the branch-and-bound algorithm. Within the ensemble of structures, a high average degree of undesignability is correlated to a long time to prove that a given structure is (un-)designable. In the four-letter case, where the designability is high everywhere, the algorithmic complexity is highest in the region of naturally occurring RNA.Comment: 11 pages, 10 figure

Influence of the detector's temperature on the quantum Zeno effect

In this paper we study the quantum Zeno effect using the irreversible model of the measurement. The detector is modeled as a harmonic oscillator interacting with the environment. The oscillator is subjected to the force, proportional to the energy of the measured system. We use the Lindblad-type master equation to model the interaction with the environment. The influence of the detector's temperature on the quantum Zeno effect is obtained. It is shown that the quantum Zeno effect becomes stronger (the jump probability decreases) when the detector's temperature increases

A conceptual framework for studying collective reactions to events in location-based social media

Events are a core concept of spatial information, but location-based social media (LBSM) provide information on reactions to events. Individuals have varied degrees of agency in initiating, reacting to or modifying the course of events, and reactions include observations of occurrence, expressions containing sentiment or emotions, or a call to action. Key characteristics of reactions include referent events and information about who reacted, when, where and how. Collective reactions are composed of multiple individual reactions sharing common referents. They can be characterized according to the following dimensions: spatial, temporal, social, thematic and interlinkage. We present a conceptual framework, which allows characterization and comparison of collective reactions. For a thematically well-defined class of event such as storms, we can explore differences and similarities in collective attribution of meaning across space and time. Other events may have very complex spatio-temporal signatures (e.g. political processes such as Brexit or elections), which can be decomposed into series of individual events (e.g. a temporal window around the result of a vote). The purpose of our framework is to explore ways in which collective reactions to events in LBSM can be described and underpin the development of methods for analysing and understanding collective reactions to events