Homogenization Approach to Smoothed Molecular Dynamics

In classical Molecular Dynamics a molecular system is modelled by classi-cal Hamiltonian equations of motion. The potential part of the correspond-ing energy function of the system includes contributions of several types of atomic interaction. Among these, some interactions represent the bond structure of the molecule. Particularly these interactions lead to extremely stiff potentials which force the solution of the equations of motion to oscil late on a very small time scale. There is a strong need for eliminating the smallest time scales because they are a severe restriction for numerical long-term simulations of macromolecules. This leads to the idea of just freezing the high frequency degrees of freedom (bond stretching and bond angles) via increasing the stiffness of the strong part of the potential to infinity However, the naive way of doing this via holonomic constraints mistakenly ignores the energy contribution of the fast oscillations. The paper presents a mathematically rigorous discussion of the limit situation of infinite stiffnes

Utilizing weak pump depletion to stabilize squeezed vacuum states

We propose and demonstrate a pump-phase locking technique that makes use of weak pump depletion (WPD) - an unavoidable effect that is usually neglected - in a sub-threshold optical parametric oscillator (OPO). We show that the phase difference between seed and pump beam is imprinted on both light fields by the non-linear interaction in the crystal and can be read out without disturbing the squeezed output. Our new locking technique allows for the first experimental realization of a pump-phase lock by reading out the pre-existing phase information in the pump field. There is no degradation of the detected squeezed states required to implement this scheme.Comment: 11 pages, 7 figure

Eigenvalue Bounds on Restrictions of Reversible Nearly Uncoupled Markov Chains

AbstractIn this paper we analyze decompositions of reversible nearly uncoupled Markov chains into rapidly mixing subchains. We state upper bounds on the 2nd eigenvalue for restriction and stochastic complementation chains of reversible Markov chains, as well as a relation between them. We illustrate the obtained bounds analytically for bunkbed graphs, and furthermore apply them to restricted Markov chains that arise when analyzing conformation dynamics of a small biomolecule

Political will, work values, and objective career success: A novel approach – The Trait-Reputation-Identity Model

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordIndividual-level political will in organizations and careers is recognized by many scholars as an important yet under-investigated construct. Only recently has a scale directly assessing political will been developed, and its validation process has just begun (Kapoutsis, Papalexandris, Treadway, & Bentley, 2017). We used the Trait-Reputation-Identity Model (McAbee & Connelly, 2016) and a triadic multisource design to explore and elucidate the nomological network of political will, including its link to objective career success. We found supporting empirical evidence for the construct (power striving) and criterion validity (hierarchical position and income) of the self-serving political will scale. However, our findings did not support the multi-rater convergence and the interpretation of the benevolent political will scale as representing an altruistic political motive. Hence, we suggest the development and validation of new items that directly relate to benevolence toward others at work. We further encourage researchers to develop and validate an additional scale assessing altruistic political will above and beyond self-serving and benevolent political will. We discuss additional implications, limitations, and directions for future research

Automated Model Reduction for Complex Systems exhibiting Metastability

We present a novel method for the identification of the most important metastable states of a system with complicated dynamical behavior from time series information. The novel approach represents the effective dynamics of the full system by a Markov jump process between metastable states and the dynamics within each of these metastable states by rather simple stochastic differential equations (SDEs). Its algorithmic realization exploits the concept of hidden Markov models with output behavior given by SDEs. The numerical effort of the method is linear in the length of the given time series and quadratic in terms of the number of metastable states. The performance of the resulting method is illustrated by numerical tests and by application to molecular dynamics time series of a trialanine molecule