Robust compositional data analysis

Many practical data sets contain outliers or other forms of data inhomogeneities. Robust statistics offers concepts how to deal with these situations where the data do not follow strict model assumptions. These concepts are designed for the usual Euclidean space, and they can be easily applied to compositional data if they are represented in this space as well. It turns out that the isometric logratio (ilr) transformation is best suitable in the context of robust estimation. Depending on the method applied, an interpretation of result is usually done in a back-transformed space

Analysis of compositional data using robust methods. The R-package robCompositons

The free and open-source programming language and software environment R (R Development Core Team, 2010) is currently both, the most widely used and most popular software for statistics and data analysis. In addition, R becomes quite popular as a (programming) language, ranked currently (February 2011) on place 25 at the TIOBE Programming Community Index (e.g., Matlab: 29, SAS: 30, see http://www.tiobe.com). The basic R environment can be downloaded from the comprehensive R archive network (http://cran.rproject.org). R is enhanceable via packages which consist of code and structured standard documentation including code application examples and possible further documents (so called vignettes) showing further applications of the packages. Two contributed packages for compositional data analysis comes with R, version 2.12.1.: the package compositions (van den Boogaart et al., 2010) and the package robCompositions (Templ et al., 2011). Package compositions provides functions for the consistent analysis of compositional data and positive numbers in the way proposed originally by John Aitchison (see van den Boogaart et al., 2010). In addition to the basic functionality and estimation procedures in package compositions, package robCompositions provides tools for a (classical) and robust multivariate statistical analysis of compositional data together with corresponding graphical tools. In addition, several data sets are provided as well as useful utility functions

Classical and robust imputation of missing values for compositional data using balances

Classical and Robust Imputation of Missing Values for Compositional Data using Balance

Simplicial principal component analysis for density functions in Bayes spaces

Probability density functions are frequently used to characterize the distributional properties of large-scale database systems. As functional compositions, densities primarily carry relative information. As such, standard methods of functional data analysis (FDA) are not appropriate for their statistical processing. The specific features of density functions are accounted for in Bayes spaces, which result from the generalization to the infinite dimensional setting of the Aitchison geometry for compositional data. The aim is to build up a concise methodology for functional principal component analysis of densities. A simplicial functional principal component analysis (SFPCA) is proposed, based on the geometry of the Bayes space B2 of functional compositions. SFPCA is performed by exploiting the centred log-ratio transform, an isometric isomorphism between B2 and L2 which enables one to resort to standard FDA tools. The advantages of the proposed approach with respect to existing techniques are demonstrated using simulated data and a real-world example of population pyramids in Upper Austria

Photo Thermal Effect Graphene Detector Featuring 105 Gbit s-1 NRZ and 120 Gbit s-1 PAM4 Direct Detection

The challenge of next generation datacom and telecom communication is to increase the available bandwidth while reducing the size, cost and power consumption of photonic integrated circuits. Silicon (Si) photonics has emerged as a viable solution to reach these objectives. Graphene, a single-atom thick layer of carbon5, has been recently proposed to be integrated with Si photonics because of its very high mobility, fast carrier dynamics and ultra-broadband optical properties. Here, we focus on graphene photodetectors for high speed datacom and telecom applications. High speed graphene photodetectors have been demonstrated so far, however the most are based on the photo-bolometric (PB) or photo-conductive (PC) effect. These devices are characterized by large dark current, in the order of milli-Amperes , which is an impairment in photo-receivers design, Photo-thermo-electric (PTE) effect has been identified as an alternative phenomenon for light detection. The main advantages of PTE-based photodetectors are the optical power to voltage conversion, zero-bias operation and ultra-fast response. Graphene PTE-based photodetectors have been reported in literature, however high-speed optical signal detection has not been shown. Here, we report on an optimized graphene PTE-based photodetector with flat frequency response up to 65 GHz. Thanks to the optimized design we demonstrate a system test leading to direct detection of 105 Gbit s-1 non-return to zero (NRZ) and 120 Gbit s-1 4-level pulse amplitude modulation (PAM) optical signal

Classical and robust regression analysis with compositional data

Compositional data carry their relevant information in the relationships (logratios) between the compositional parts. It is shown how this source of information can be used in regression modeling, where the composition could either form the response, or the explanatory part, or even both. An essential step to set up a regression model is the way how the composition(s) enter the model. Here, balance coordinates will be constructed that support an interpretation of the regression coefficients and allow for testing hypotheses of subcompositional independence. Both classical least-squares regression and robust MM regression are treated, and they are compared within different regression models at a real data set from a geochemical mapping project

Search for CP violating top quark couplings in pp collisions at √s = 13 TeV

A preprint version of the article is available at arXiv:2205.07434v2 [hep-ex], https://arxiv.org/abs/2205.07434. It has not been certified by peer review.Results are presented from a search for CP violation in top quark pair production, using proton-proton collisions at a center-of-mass energy of 13 TeV. The data used for this analysis consist of final states with two charged leptons collected by the CMS experiment, and correspond to an integrated luminosity of 35.9 fb−1. The search uses two observables, O1 and O3, which are Lorentz scalars. The observable O1 is constructed from the four-momenta of the charged leptons and the reconstructed top quarks, while O3 consists of the four-momenta of the charged leptons and the b quarks originating from the top quarks. Asymmetries in these observables are sensitive to CP violation, and their measurement is used to determine the chromoelectric dipole moment of the top quark. The results are consistent with the expectation from the standard model. [Figure not available: see fulltext.].SCOAP

Search for long-lived particles decaying to a pair of muons in proton-proton collisions at √s = 13 TeV

A preprint version of the article is available at arXiv:2205.08582v2 [hep-ex], https://arxiv.org/abs/2205.08582 . Comments: Replaced with the published version. Added the journal reference and the DOI. All the figures and tables, including additional supplementary figures and tables, can be found at https://cms-results.web.cern.ch/cms-results/public-results/publications/EXO-21-006 (CMS Public Pages).An inclusive search for long-lived exotic particles decaying to a pair of muons is presented. The search uses data collected by the CMS experiment at the CERN LHC in proton-proton collisions at s = 13 TeV in 2016 and 2018 and corresponding to an integrated luminosity of 97.6 fb−1. The experimental signature is a pair of oppositely charged muons originating from a common secondary vertex spatially separated from the pp interaction point by distances ranging from several hundred μm to several meters. The results are interpreted in the frameworks of the hidden Abelian Higgs model, in which the Higgs boson decays to a pair of long-lived dark photons ZD, and of a simplified model, in which long-lived particles are produced in decays of an exotic heavy neutral scalar boson. For the hidden Abelian Higgs model with m(ZD) greater than 20 GeV and less than half the mass of the Higgs boson, they provide the best limits to date on the branching fraction of the Higgs boson to dark photons for cτ(ZD) (varying with m(ZD)) between 0.03 and ≈0.5 mm, and above ≈0.5 m. Our results also yield the best constraints on long-lived particles with masses larger than 10 GeV produced in decays of an exotic scalar boson heavier than the Higgs boson and decaying to a pair of muons. [Figure not available: see fulltext.].SCOAP3