Optical frequency transfer via telecommunication fiber links for metrological applications

[no abstract

Weighted Operator Precedence Languages

In the last years renewed investigation of operator precedence languages (OPL) led to discover important properties thereof: OPL are closed with respect to all major operations, are characterized, besides the original grammar family, in terms of an automata family (OPA) and an MSO logic; furthermore they significantly generalize the well-known visibly pushdown languages (VPL). In another area of research, quantitative models of systems are also greatly in demand. In this paper, we lay the foundation to marry these two research fields. We introduce weighted operator precedence automata and show how they are both strict extensions of OPA and weighted visibly pushdown automata. We prove a Nivat-like result which shows that quantitative OPL can be described by unweighted OPA and very particular weighted OPA. In a Büchi-like theorem, we show that weighted OPA are expressively equivalent to a weighted MSO-logic for OPL

Characterization of a 450-km Baseline GPS Carrier-Phase Link using an Optical Fiber Link

A GPS carrier-phase frequency transfer link along a baseline of 450 km has been established and is characterized by comparing it to a phase-stabilized optical fiber link of 920 km length, established between the two endpoints, the Max-Planck-Institut f\"ur Quantenoptik in Garching and the Physikalisch-Technische Bundesanstalt in Braunschweig. The characterization is accomplished by comparing two active hydrogen masers operated at both institutes. The masers serve as local oscillators and cancel out when the double differences are calculated, such that they do not constitute a limitation for the GPS link characterization. We achieve a frequency instability of 3 x 10^(-13) in 30 s and 5 x 10^(-16) for long averaging times. Frequency comparison results obtained via both links show no deviation larger than the statistical uncertainty of 6 x 10^(-16). These results can be interpreted as a successful cross-check of the measurement uncertainty of a truly remote end fiber link.Comment: 14 pages, 6 figure

On the AAVenue to success: Advances in technologies for AAV production

Please click Additional Files below to see the full abstract

Micro shape and rough surface analysis by fringe projection

A new microscopic fringe projection system is described. Projection of the grating and imaging of the fringes is accomplished by the same objective. The spectrum of the binary grating is spatially filtered and projected into the aperture with a lateral shift. This leads to telecentric projection and imaging under oblique incidence. Topographies of specularely as well as diffusely reflecting surfaces can be obtained. The measurement of rough, technical surfaces is demonstrated

On the impact of the cutoff time on the performance of algorithm configurators

Algorithm conigurators are automated methods to optimise the parameters of an algorithm for a class of problems. We evaluate the performance of a simple random local search conigurator (Param- RLS) for tuning the neighbourhood size k of the RLS k algorithm. We measure performance as the expected number of coniguration evaluations required to identify the optimal value for the parameter. We analyse the impact of the cutof time κ (the time spent evaluat- ing a coniguration for a problem instance) on the expected number of coniguration evaluations required to ind the optimal parameter value, where we compare conigurations using either best found itness values (ParamRLS-F) or optimisation times (ParamRLS-T). We consider tuning RLS k for a variant of the Ridge function class ( Ridge* ), where the performance of each parameter value does not change during the run, and for the OneMax function class, where longer runs favour smaller k . We rigorously prove that ParamRLS- F eiciently tunes RLS k for Ridge* for any κ while ParamRLS-T requires at least quadratic κ . For OneMax ParamRLS-F identiies k = 1 as optimal with linear κ while ParamRLS-T requires a κ of at least Ω ( n log n ) . For smaller κ ParamRLS-F identiies that k > 1 performs better while ParamRLS-T returns k chosen uniformly at random