Tuning of MC generator MPI models

MC models of multiple partonic scattering inevitably introduce many free parameters, either fundamental to the models or from their integration with MC treatments of primary-scattering evolution. This non-perturbative and non-factorisable physics in particular cannot currently be constrained from theoretical principles, and hence parameter optimisation against experimental data is required. This process is commonly referred to as MC tuning. We summarise the principles, problems and history of MC tuning, and the still-evolving modern approach to both model optimisation and estimation of modelling uncertainties.Comment: Contributed chapter to "Multiple Parton Interactions at the LHC", World Scientific 201

Simulation of vector boson plus many jet final states at the high luminosity LHC

We present a novel event generation framework for the efficient simulation of vector boson plus multi-jet backgrounds at the high-luminosity LHC and at possible future hadron colliders. MPI parallelization of parton-level and particle-level event generation and storage of parton-level event information using the HDF5 data format allow us to obtain leading-order merged Monte-Carlo predictions with up to nine jets in the final state. The parton-level event samples generated in this manner correspond to an integrated luminosity of 3ab-1 and are made publicly available for future phenomenological studies.Comment: 10 pages, 8 figures, 5 table

Heterogeneous diffusion in comb and fractal grid structures

We give an exact analytical results for diffusion with a power-law position dependent diffusion coefficient along the main channel (backbone) on a comb and grid comb structures. For the mean square displacement along the backbone of the comb we obtain behavior $\langle x^2(t)\rangle\sim t^{1/(2-\alpha)}$, where $\alpha$ is the power-law exponent of the position dependent diffusion coefficient $D(x)\sim |x|^{\alpha}$. Depending on the value of $\alpha$ we observe different regimes, from anomalous subdiffusion, superdiffusion, and hyperdiffusion. For the case of the fractal grid we observe the mean square displacement, which depends on the fractal dimension of the structure of the backbones, i.e., $\langle x^2(t)\rangle\sim t^{(1+\nu)/(2-\alpha)}$, where $0<\nu<1$ is the fractal dimension of the backbones structure. The reduced probability distribution functions for both cases are obtained by help of the Fox $H$-functions

Content-Aware DataGuides for Indexing Large Collections of XML Documents

XML is well-suited for modelling structured data with textual content. However, most indexing approaches perform structure and content matching independently, combining the retrieved path and keyword occurrences in a third step. This paper shows that retrieval in XML documents can be accelerated significantly by processing text and structure simultaneously during all retrieval phases. To this end, the Content-Aware DataGuide (CADG) enhances the wellknown DataGuide with (1) simultaneous keyword and path matching and (2) a precomputed content/structure join. Extensive experiments prove the CADG to be 50-90% faster than the DataGuide for various sorts of query and document, including difficult cases such as poorly structured queries and recursive document paths. A new query classification scheme identifies precise query characteristics with a predominant influence on the performance of the individual indices. The experiments show that the CADG is applicable to many real-world applications, in particular large collections of heterogeneously structured XML documents

Constraining A4A_4 Leptonic Flavour Model Parameters at Colliders and Beyond

The observed pattern of mixing in the neutrino sector may be explained by the presence of a non-Abelian, discrete flavour symmetry broken into residual subgroups at low energies. Many flavour models require the presence of Standard Model singlet scalars which can promptly decay to charged leptons in a flavour-violating manner. We constrain the model parameters of a generic $A_4$ leptonic flavour model using a synergy of experimental data including limits from charged lepton flavour conversion, an 8 TeV collider analysis and constraints from the anomalous magnetic moment of the muon. The most powerful constraints derive from the MEG collaborations' limit on Br$\left(\mu\to e\gamma\right)$ and the reinterpretation of an 8 TeV ATLAS search for anomalous productions of multi-leptonic final states. We quantify the exclusionary power of each of these experiments and identify regions where the constraints from collider and MEG experimental data are complementary.Comment: v1: 28 + 9 pages, 8 figures. v2: 30 + 10 pages, 10 figures. v2 consistent with JHEP accepted version where further discussion of results and several more references were adde

New developments in event generator tuning techniques

Data analyses in hadron collider physics depend on background simulations performed by Monte Carlo (MC) event generators. However, calculational limitations and non-perturbative effects require approximate models with adjustable parameters. In fact, we need to simultaneously tune many phenomenological parameters in a high-dimensional parameter-space in order to make the MC generator predictions fit the data. It is desirable to achieve this goal without spending too much time or computing resources iterating parameter settings and comparing the same set of plots over and over again. We present extensions and improvements to the MC tuning system, Professor, which addresses the aforementioned problems by constructing a fast analytic model of a MC generator which can then be easily fitted to data. Using this procedure it is for the first time possible to get a robust estimate of the uncertainty of generator tunings. Furthermore, we can use these uncertainty estimates to study the effect of new (pseudo-) data on the quality of tunings and therefore decide if a measurement is worthwhile in the prospect of generator tuning. The potential of the Professor method outside the MC tuning area is presented as well.Comment: To appear in the proceedings of the 13th International Workshop on Advanced Computing and Analysis Techniques in Physics Research, ACAT2010, Jaipur, India, February 22-27, 201

Vantagens e limitações das ontologias formais na área biomédica

Propomos uma tipologia dos artefatos de representação para as áreas de saúde e ciências biológicas, e a associação dessa tipologia com diferentes tipos de ontologia formal e lógica, chegando a conclusões quanto aos pontos fortes e limitações da ontologia de diferentes tipos de recursos lógicos, enquanto mantemos o foco na lógica descritiva. Consideramos quatro tipos de representação de área: (i) representação léxico-semântica, (ii) representação de tipos de entidades, (iii) representação de conhecimento prévio, e (iv) representação de indivíduos. Defendemos uma clara distinção entre os quatro tipos de representação, de forma a oferecer uma base mais racional para o uso das ontologias e artefatos relacionados no avanço da integração de dados e interoperabilidade de sistemas de raciocínio associados. Destacamos que apenas uma pequena porção de fatos cientificamente relevantes em áreas como a biomedicina pode ser adequadamente representada por ontologias formais, quando estas últimas são concebidas como representações de tipos de entidades. Particularmente, a tentativa de codificar conhecimento padrão ou probabilístico pela utilização de ontologias assim concebidas é fadada à produção de modelos não intencionais e errôneos