A Study of Full Scale CMS Tracker Alignment using High Momentum Muons and Cosmics

The positions of the silicon modules of the CMS tracker will be known to $O(100$ $\mu$m) from survey measurements, mounting precision and the laser alignment system. However, in order to fully exploit the capabilities of the tracker, these positions need to be known to a precision of a few $\mu$m. Only a track-based alignment procedure can reach this required precision. Such an alignment procedure is a major challenge given that about 50000 geometry constants need to be measured. Making use of the novel $\chi^2$ minimization program Millepede II an alignment strategy has been developed in which all detector components are aligned simultaneously and all correlations between their position parameters taken into account. Different datasets, such as Z$^0$ decays and cosmic muons, plus information about the mechanical structure of the tracker, and initial position uncertainties have been used as input for the alignment procedure. A proof of concept of this alignment strategy is demonstrated using simulated data

Refining fast simulation using machine learning

At the CMS experiment, a growing reliance on the fast Monte Carlo application (FastSim) will accompany the high luminosity and detector granularity expected in Phase 2. The FastSim chain is roughly 10 times faster than the application based on the GEANT4 detector simulation and full reconstruction referred to as FullSim. However, this advantage comes at the price of decreased accuracy in some of the final analysis observables. In this contribution, a machine learning-based technique to refine those observables is presented. We employ a regression neural network trained with a sophisticated combination of multiple loss functions to provide post-hoc corrections to samples produced by the FastSim chain. The results show considerably improved agreement with the FullSim output and an improvement in correlations among output observables and external parameters. This technique is a promising replacement for existing correction factors, providing higher accuracy and thus contributing to the wider usage of FastSim.Comment: 8 pages, 4 figures, CHEP2023 proceedings, submitted to EPJ Web of Conference

Radio Galaxy Classification with wGAN-Supported Augmentation

Novel techniques are indispensable to process the flood of data from the new generation of radio telescopes. In particular, the classification of astronomical sources in images is challenging. Morphological classification of radio galaxies could be automated with deep learning models that require large sets of labelled training data. Here, we demonstrate the use of generative models, specifically Wasserstein GANs (wGAN), to generate artificial data for different classes of radio galaxies. Subsequently, we augment the training data with images from our wGAN. We find that a simple fully-connected neural network for classification can be improved significantly by including generated images into the training set.Comment: 10 pages, 6 figures; accepted to ml.astro; v2: matches published versio

Refining fast simulation using machine learning

At the CMS experiment, a growing reliance on the fast Monte Carlo application (FastSim) will accompany the high luminosity and detector granularity expected in Phase 2. The FastSim chain is roughly 10 times faster than the application based on the Geant4 detector simulation and full reconstruction referred to as FullSim. However, this advantage comes at the price of decreased accuracy in some of the final analysis observables. In this contribution, a machine learning-based technique to refine those observables is presented. We employ a regression neural network trained with a sophisticated combination of multiple loss functions to provide post-hoc corrections to samples produced by the FastSim chain. The results show considerably improved agreement with the FullSim output and an improvement in correlations among output observables and external parameters. This technique is a promising replacement for existing correction factors, providing higher accuracy and thus contributing to the wider usage of FastSim

Forward pi^0 Production and Associated Transverse Energy Flow in Deep-Inelastic Scattering at HERA

Deep-inelastic positron-proton interactions at low values of Bjorken-x down to x \approx 4.10^-5 which give rise to high transverse momentum pi^0 mesons are studied with the H1 experiment at HERA. The inclusive cross section for pi^0 mesons produced at small angles with respect to the proton remnant (the forward region) is presented as a function of the transverse momentum and energy of the pi^0 and of the four-momentum transfer Q^2 and Bjorken-x. Measurements are also presented of the transverse energy flow in events containing a forward pi^0 meson. Hadronic final state calculations based on QCD models implementing different parton evolution schemes are confronted with the data.Comment: 27 pages, 8 figures and 3 table

Multi-Jet Event Rates in Deep Inelastic Scattering and Determination of the Strong Coupling Constant

Jet event rates in deep inelastic ep scattering at HERA are investigated applying the modified JADE jet algorithm. The analysis uses data taken with the H1 detector in 1994 and 1995. The data are corrected for detector and hadronization effects and then compared with perturbative QCD predictions using next-to-leading order calculations. The strong coupling constant alpha_S(M_Z^2) is determined evaluating the jet event rates. Values of alpha_S(Q^2) are extracted in four different bins of the negative squared momentum transfer~\qq in the range from 40 GeV2 to 4000 GeV2. A combined fit of the renormalization group equation to these several alpha_S(Q^2) values results in alpha_S(M_Z^2) = 0.117+-0.003(stat)+0.009-0.013(syst)+0.006(jet algorithm).Comment: 17 pages, 4 figures, 3 tables, this version to appear in Eur. Phys. J.; it replaces first posted hep-ex/9807019 which had incorrect figure 4

“Hot standards” for the thermoacidophilic archaeon Sulfolobus solfataricus

Within the archaea, the thermoacidophilic crenarchaeote Sulfolobus solfataricus has become an important model organism for physiology and biochemistry, comparative and functional genomics, as well as, more recently also for systems biology approaches. Within the Sulfolobus Systems Biology (“SulfoSYS”)-project the effect of changing growth temperatures on a metabolic network is investigated at the systems level by integrating genomic, transcriptomic, proteomic, metabolomic and enzymatic information for production of a silicon cell-model. The network under investigation is the central carbohydrate metabolism. The generation of high-quality quantitative data, which is critical for the investigation of biological systems and the successful integration of the different datasets, derived for example from high-throughput approaches (e.g., transcriptome or proteome analyses), requires the application and compliance of uniform standard protocols, e.g., for growth and handling of the organism as well as the “–omics” approaches. Here, we report on the establishment and implementation of standard operating procedures for the different wet-lab and in silico techniques that are applied within the SulfoSYS-project and that we believe can be useful for future projects on Sulfolobus or (hyper)thermophiles in general. Beside established techniques, it includes new methodologies like strain surveillance, the improved identification of membrane proteins and the application of crenarchaeal metabolomics

Measurement of Leading Proton and Neutron Production in Deep Inelastic Scattering at HERA

Deep--inelastic scattering events with a leading baryon have been detected by the H1 experiment at HERA using a forward proton spectrometer and a forward neutron calorimeter. Semi--inclusive cross sections have been measured in the kinematic region 2 <= Q^2 <= 50 GeV^2, 6.10^-5 <= x <= 6.10^-3 and baryon p_T <= MeV, for events with a final state proton with energy 580 <= E' <= 740 GeV, or a neutron with energy E' >= 160 GeV. The measurements are used to test production models and factorization hypotheses. A Regge model of leading baryon production which consists of pion, pomeron and secondary reggeon exchanges gives an acceptable description of both semi-inclusive cross sections in the region 0.7 <= E'/E_p <= 0.9, where E_p is the proton beam energy. The leading neutron data are used to estimate for the first time the structure function of the pion at small Bjorken--x.Comment: 30 pages, 9 figures, 2 tables, submitted to Eur. Phys.