A superfluid hydrodynamic model for the enhanced moments of inertia of molecules in liquid 4He

We present a superfluid hydrodynamic model for the increase in moment of inertia, $\Delta I$, of molecules rotating in liquid $^4$He. The static inhomogeneous He density around each molecule (calculated using the Orsay-Paris liquid $^4$He density functional) is assumed to adiabatically follow the rotation of the molecule. We find that the $\Delta I$ values created by the viscousless and irrotational flow are in good agreement with the observed increases for several molecules [ OCS, (HCN)$_2$, HCCCN, and HCCCH$_3$ ]. For HCN and HCCH, our model substantially overestimates $\Delta I$. This is likely to result from a (partial) breakdown of the adiabatic following approximation.Comment: 4 pages, 1 eps figure, corrected version of published paper. Erratum has been submitted for change

The Liquid Argon Jet Trigger of the H1 Experiment at HERA

We report on a novel trigger for the liquid argon calorimeter which was installed in the H1 Experiment at HERA.This trigger, called the “Jet Trigger”, was running at level 1 and implemented a real-time cluster algorithm. Within only 800 ns, the Jet Trigger algorithm found local energy maxima in the calorimeter, summed their immediate neighbors, sorted the resulting jets by energy, and applied topological conditions for the final level 1 trigger decision. The Jet Trigger was in operation from the year 2006 until the end of the HERA running in the summer of 2007. With the Jet Trigger it was possible to substantially reduce the thresholds for triggering on electronsand jets, giving access to a largely extended phase space for physical observables which could not have been reached in H1 before. The concepts of the Jet Trigger may be an interesting upgrade option for the LHC experiments

A Neural Network Second Level Trigger for the H1-Experiment at HERA

At the HERA ep collider the expected machine background rates exceed by several orders of magnitude the typical collision rates from ep physics reactions. One of the great challenges for the ep experiments at HERA is therefore to find methods suppressing the high rate machine background efficiently without cutting heavily into the physics. We present here the concept, the design, and the status for a second level hardware trigger based on the neural network architecture. We address the problems of efficiently selecting "known" physics as well as preparing such a trigger for "new" physics never presented to the network and give a few examples for networks specifically trained for physical reactions close to the background. The training is done with real data and the corresponding nets are ready for installation in the network trigger, which is expected to start operation in the fall of 1995. 1 Introduction At full luminosity, the HERA Electron-Proton-Collider at DESY will challenge e..