Gamma | EPFL Graph Search

Gamma (capitale Γ, minuscule γ ; en grec γάμμα), est la lettre de l'alphabet grec. Dérivée de la lettre gaml x12px de l'alphabet phénicien, elle est l'ancêtre des lettres C, G, Ɣ (gamma) de l'alphabet latin, et de la lettre Г de l'alphabet cyrillique. Usage Grec En grec ancien, gamma représente la consonne occlusive vélaire voisée . En grec moderne, elle représente une consonne fricative voisée. Elle est réalisée soit comme une palatale (devant une voyelle antérieure, /e, i/), soit une vélaire (dans les autres cas). En grec ancien comme moderne, devant une autre consonne vélaire (κ, χ, ξ, k, kh, ks), gamma représente une consonne occlusive nasale vélaire voisée . Un double gamma γγ note la séquence (variant phonétiquement en ) ou . Dans le système de numération grecque, gamma vaut 3. Dans certains styles d’écriture cursive ou dans certaines polices de caractères, comme le Grec du roi, le gamma est utilisé dans plusieurs ligatures comme gamma-epsilon-rho

Converging intracortical signatures of two separated processing timescales in human early auditory cortex

Fabiano Baroni, Arwen Blanche Giraud

Neural oscillations in auditory cortex are argued to support parsing and representing speech constituents at their corresponding temporal scales. Yet, how incoming sensory information interacts with ongoing spontaneous brain activity, what features of the neuronal microcircuitry underlie spontaneous and stimulus-evoked spectral fin-gerprints, and what these fingerprints entail for stimulus encoding, remain largely open questions. We used a combination of human invasive electrophysiology, computational modeling and decoding techniques to assess the information encoding properties of brain activity and to relate them to a plausible underlying neuronal micro -architecture. We analyzed intracortical auditory EEG activity from 10 patients while they were listening to short sentences. Pre-stimulus neural activity in early auditory cortical regions often exhibited power spectra with a shoulder in the delta range and a small bump in the beta range. Speech decreased power in the beta range, and increased power in the delta-theta and gamma ranges. Using multivariate machine learning techniques, we assessed the spectral profile of information content for two aspects of speech processing: detection and discrimination. We obtained better phase than power information decoding, and a bimodal spectral profile of information content with better decoding at low (delta-theta) and high (gamma) frequencies than at intermediate (beta) frequencies. These experimental data were reproduced by a simple rate model made of two subnetworks with different timescales, each composed of coupled excitatory and inhibitory units, and connected via a negative feedback loop. Modeling and experimental results were similar in terms of pre-stimulus spectral profile (except for the iEEG beta bump), spectral modulations with speech, and spectral profile of information content. Altogether, we provide converging evidence from both univariate spectral analysis and decoding approaches for a dual timescale processing infrastructure in human auditory cortex, and show that it is consistent with the dynamics of a simple rate model.

2020

Measurement of time-dependent CP violation in B0->Dpi decays and optimisation of flavour tagging algorithms at LHCb

Vincenzo Battista

This thesis presents the results of a time-dependent analysis of

B^0\to D^{\mp}\pi^{\pm}

decays using

3~\rm fb^{-1}

of proton-proton collision data collected with the LHCb detector at CERN's Large Hadron Collider during Run 1 with a centre-of-mass energy of

7

(2011) and

8

(2012) TeV. The LHCb experiment is dedicated to the study of the properties of

b

-flavoured hadrons, in particular

CP

violation in the

B

meson system. The Standard Model of Particle Physics describes very precisely the mechanism and the amount of

CP

violation expected in the Universe. However, the observed matter-antimatter asymmetry is larger by several order of magnitude compared to the predictions. This could be explained by the existence of a new source of

CP

violation, originating in New Physics beyond the Standard Model. The time-dependent analysis of

B^0\to D^{\mp}\pi^{\pm}

decays provides constraints on the angle

\gamma

of the Unitarity Triangle, one of the fundamental parameters of the Standard Model related to

CP

violation. Since no sizeable high-order Standard Model processes are expected to contribute, any deviation from the predictions would be an unambiguous signature of New Physics. The current experimental precision on

\gamma

is significantly lower than that of theoretical predictions. This motivates the effort for new experimental determinations of

\gamma

in order to reduce its uncertainty. The analysis of

\Bz\to\Dmp\pipm

decays, although not as sensitive as that obtained from decays of charged

B

mesons into

D^{(*)0}K^{(*)+}

final states, represents an independent and uncorrelated estimation of

\gamma

that contributes to the global combination of all

\gamma

measurements. The result obtained in this thesis is more precise than previous determinations from other experiments (BaBar, Belle) using

B^0\to D^{\mp}\pi^{\pm}

decays. Although based on a very large sample of about half a million signal events, it is still dominated by statistical uncertainties, indicating good prospects for future improvements in precision with more data from Run 2 and beyond. In addition to the

B^0\to D^{\mp}\pi^{\pm}

analysis, this thesis also summarizes the studies to improve the performances of the flavour tagging algorithms used by the LHCb collaboration to infer the flavour of neutral

B

mesons in time-dependent analyses. The performance of these algorithms, being correlated with the kinematics of the reconstructed particles as well as the complexity of the event (number of tracks and primary vertices), showed a significant decrease on Run 2 data (2015--2018), which were collected at a centre-of-mass energy of

13~\rm TeV

. Thanks to new implementations, these algorithms now have a performance similar to that obtained with Run 1 data.

EPFL2018