A generalization of the stochastic wave function method to quantum master equations which are not in Lindblad form is developed. The proposed stochastic unravelling is based on a description of the reduced system in a doubled Hilbert space and it is shown, that this method is capable of simulating quantum master equations with negative transition rates. Non-Markovian effects in the reduced systems dynamics can be treated within this approach by employing the time-convolutionless projection operator technique. This ansatz yields a systematic perturbative expansion of the reduced systems dynamics in the coupling strength. Several examples such as the damped Jaynes Cummings model and the spontaneous decay of a two-level system into a photonic band gap are discussed. The power as well as the limitations of the method are demonstrated.

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The dynamics of atom lasers with a continuous output coupler based on two-photon Raman transitions is investigated. With the help of the time-convolutionless projection operator technique the quantum master equations for pulsed and continuous wave (cw) atom lasers are derived. In the case of the pulsed atom laser the power of the time-convolutionless projection operator technique is demonstrated through comparison with the exact solution. It is shown that in an intermediate coupling regime where the Born-Markov approximation fails the results of this algorithm agree with the exact solution. To study the dynamics of a continuous wave atom laser a pump mechanism is included in the model. Whereas the pump mechanism is treated within the Born-Markov approximation, the output coupling leads to non-Markovian effects. The solution of the master equation resulting from the time-convolutionless projection operator technique exhibits strong oscillations in the occupation number of the Bose-Einstein condensate. These oscillations are traced back to a quantum interference which is due to the non-Markovian dynamics and which decays slowly in time as a result of the dispersion relation for massive particles.

Within the framework of probability distributions on projective Hilbert space, a scheme for the calculation of multitime correlation functions is developed. The starting point is the Markovian stochastic wave-function description of an open quantum system coupled to an environment consisting of an ensemble of harmonic oscillators in arbitrary pure or mixed states. It is shown that matrix elements of reduced Heisenberg picture operators and general time-ordered correlation functions can be expressed by time-symmetric expectation values of extended operators in a doubled Hilbert space. This representation allows the construction of a stochastic process in the doubled Hilbert space which enables a determination of arbitrary matrix elements and correlation functions. The numerical efficiency of the resulting stochastic simulation algorithm is investigated and compared with an alternative Monte Carlo wave function method proposed first by Dalibard, Castin, and Mo "lmer ͓Phys. Rev. Lett. 68, 580 ͑1992͔͒. By means of a standard example the suggested algorithm is shown to be more efficient numerically and to converge faster. Finally, some specific examples from quantum optics are presented in order to illustrate the proposed method, such as the coupling of a system to a vacuum, a squeezed vacuum within a finite solid angle, and a thermal mixture of coherent states.

High‐output polymer screening (HOPS) combines automated polymerization with online reaction monitoring, rapid polymer characterization and novel fingerprint technology useful in polymer preparation as well as polymer processing and polymer additive development. Originally, HOPS was introduced to develop polymerization catalysts and polyolefin materials more effectively. In comparison to conventional high‐throughput screening, focusing on ultrahigh speed of catalyst screening using arrays of miniaturized reactors, output‐oriented, process‐relevant HOPS is aiming at generating and exploiting high information density (useful information/experiment). Catalyst systems for olefin polymerization are evaluated in automated workstations with multiparallel as well as semi‐ and fully automated, upgraded lab reactors. Automated polymerizations under standardized conditions afford large families of well‐characterized polymers which serve as calibration samples for data analysis. Data analysis, using multivariate calibration, is the key to basic correlations between spectroscopic information and catalyst and polymer properties as well as reaction parameters and processing conditions. IR spectroscopic fingerprints are used to measure chemical copolymer composition, density, molecular weight as well as thermal and even mechanical properties. This fingerprint technology can be applied in online quality control and facilitates transfer from lab results into pilot and production plants. Fingerprint methods are important components of rapid online analysis and can reduce the need for time‐ and money‐consuming polymer testing. Fingerprint technology combines spectroscopic analysis by means of “cheap” spectrometers with multivariate calibration.magnified imageFingerprint technology combines spectroscopic analysis by means of “cheap” spectrometers with multivariate calibration.