Charmed penguin versus BAU

Since the Standard Model most probably cannot explain the large value of CP asymmetries recently observed in D-meson decays we propose the fourth quark-lepton generation explanation of it. As a byproduct weakly mixed leptons of the fourth generation make it possible to save the baryon number of the Universe from erasure by sphalerons. An impact of the 4th generation on BBN is briefly discussed.Comment: 13 pages, 3 figures, version to be published in JETP Letter

Volkov solution for two laser beams and ITER

We find the solution of the Dirac equation for two plane waves (laser beams) and we determine the modified Compton formula for the scattering of two photons on an alectron. The practical meaning of the two laser beams is, that two laser beams impinging on a targed which is constituted from material in the form of a foam, can replace 100-200 laser beams impinging on a normal targed. It means that the nuclear fusion with two laser beams is realistic in combination with the nuclear reactor such as ITER.Comment: 13 page

Once more on extra quark-lepton generations and precision measurements

Precision measurements of $Z$-boson parameters and $W$-boson and $t$-quark masses put strong constraints on non $SU(2)\times U(1)$ singlet New Physics. We demonstrate that one extra generation passes electroweak constraints even when all new particle masses are well above their direct mass bounds.Comment: Dedicated to L.B. Okun's 80th birthda

Multivariate Granger Causality and Generalized Variance

Granger causality analysis is a popular method for inference on directed interactions in complex systems of many variables. A shortcoming of the standard framework for Granger causality is that it only allows for examination of interactions between single (univariate) variables within a system, perhaps conditioned on other variables. However, interactions do not necessarily take place between single variables, but may occur among groups, or "ensembles", of variables. In this study we establish a principled framework for Granger causality in the context of causal interactions among two or more multivariate sets of variables. Building on Geweke's seminal 1982 work, we offer new justifications for one particular form of multivariate Granger causality based on the generalized variances of residual errors. Taken together, our results support a comprehensive and theoretically consistent extension of Granger causality to the multivariate case. Treated individually, they highlight several specific advantages of the generalized variance measure, which we illustrate using applications in neuroscience as an example. We further show how the measure can be used to define "partial" Granger causality in the multivariate context and we also motivate reformulations of "causal density" and "Granger autonomy". Our results are directly applicable to experimental data and promise to reveal new types of functional relations in complex systems, neural and otherwise.Comment: added 1 reference, minor change to discussion, typos corrected; 28 pages, 3 figures, 1 table, LaTe

The 1986?1989 ENSO cycle in a chemical climate model

International audienceA pronounced ENSO cycle occurred from 1986 to 1989, accompanied by distinct dynamical and chemical anomalies in the global troposphere and stratosphere. Reproducing these effects with current climate models not only provides a model test but also contributes to our still limited understanding of ENSO's effect on stratosphere-troposphere coupling. We performed several sets of ensemble simulations with a chemical climate model (SOCOL) forced with global sea surface temperatures. Results were compared with observations and with large-ensemble simulations performed with an atmospheric general circulation model (MRF9). We focus our analysis on the extratropical stratosphere and its coupling with the troposphere. In this context, the circulation over the North Atlantic sector is particularly important. Observed differences between the El Niño winter 1987 and the La Niña winter 1989 include a negative North Atlantic Oscillation index with corresponding changes in temperature and precipitation patterns, a weak polar vortex, a warm Arctic middle stratosphere, negative and positive total ozone anomalies in the tropics and at middle to high latitudes, respectively, as well as anomalous upward and poleward Eliassen-Palm (EP) flux in the midlatitude lower stratosphere. Most of the tropospheric features are well reproduced in the ensemble means in both models, though the amplitudes are underestimated. In the stratosphere, the SOCOL simulations compare well with observations with respect to zonal wind, temperature, EP flux, and ozone, but magnitudes are underestimated in the middle stratosphere. The polar vortex strength is well reproduced, but within-ensemble variability is too large for obtaining a significant signal in Arctic temperature and ozone. With respect to the mechanisms relating ENSO to stratospheric circulation, the results suggest that both, upward and poleward components of anomalous EP flux are important for obtaining the stratospheric signal and that an increase in strength of the Brewer-Dobson circulation is part of that signal

Inter-model comparison of global hydroxyl radical (OH) distributions and their impact on atmospheric methane over the 2000–2016 period

The modeling study presented here aims to estimate how uncertainties in global hydroxyl radical (OH) distributions, variability, and trends may contribute to resolving discrepancies between simulated and observed methane (CH4) changes since 2000. A multi-model ensemble of 14 OH fields was analyzed and aggregated into 64 scenarios to force the offline atmospheric chemistry transport model LMDz (Laboratoire de Meteorologie Dynamique) with a standard CH4 emission scenario over the period 2000–2016. The multi-model simulated global volume-weighted tropospheric mean OH concentration ([OH]) averaged over 2000–2010 ranges between 8:7*10^5 and 12:8*10^5 molec cm-3. The inter-model differences in tropospheric OH burden and vertical distributions are mainly determined by the differences in the nitrogen oxide (NO) distributions, while the spatial discrepancies between OH fields are mostly due to differences in natural emissions and volatile organic compound (VOC) chemistry. From 2000 to 2010, most simulated OH fields show an increase of 0.1–0:3*10^5 molec cm-3 in the tropospheric mean [OH], with year-to-year variations much smaller than during the historical period 1960–2000. Once ingested into the LMDz model, these OH changes translated into a 5 to 15 ppbv reduction in the CH4 mixing ratio in 2010, which represents 7%–20% of the model-simulated CH4 increase due to surface emissions. Between 2010 and 2016, the ensemble of simulations showed that OH changes could lead to a CH4 mixing ratio uncertainty of > 30 ppbv. Over the full 2000–2016 time period, using a common stateof- the-art but nonoptimized emission scenario, the impact of [OH] changes tested here can explain up to 54% of the gap between model simulations and observations. This result emphasizes the importance of better representing OH abundance and variations in CH4 forward simulations and emission optimizations performed by atmospheric inversions

Nonlinear acoustic waves in channels with variable cross sections

The point symmetry group is studied for the generalized Webster-type equation describing non-linear acoustic waves in lossy channels with variable cross sections. It is shown that, for certain types of cross section profiles, the admitted symmetry group is extended and the invariant solutions corresponding to these profiles are obtained. Approximate analytic solutions to the generalized Webster equation are derived for channels with smoothly varying cross sections and arbitrary initial conditions.Comment: Revtex4, 10 pages, 2 figure. This is an enlarged contribution to Acoustical Physics, 2012, v.58, No.3, p.269-276 with modest stylistic corrections introduced mainly in the Introduction and References. Several typos were also correcte

Adaptive density estimation for stationary processes

We propose an algorithm to estimate the common density $s$ of a stationary process $X_1,...,X_n$. We suppose that the process is either $\beta$ or $\tau$-mixing. We provide a model selection procedure based on a generalization of Mallows' $C_p$ and we prove oracle inequalities for the selected estimator under a few prior assumptions on the collection of models and on the mixing coefficients. We prove that our estimator is adaptive over a class of Besov spaces, namely, we prove that it achieves the same rates of convergence as in the i.i.d framework

The Effect Of Microscopic Correlations On The Information Geometric Complexity Of Gaussian Statistical Models

We present an analytical computation of the asymptotic temporal behavior of the information geometric complexity (IGC) of finite-dimensional Gaussian statistical manifolds in the presence of microcorrelations (correlations between microvariables). We observe a power law decay of the IGC at a rate determined by the correlation coefficient. It is found that microcorrelations lead to the emergence of an asymptotic information geometric compression of the statistical macrostates explored by the system at a faster rate than that observed in absence of microcorrelations. This finding uncovers an important connection between (micro)-correlations and (macro)-complexity in Gaussian statistical dynamical systems.Comment: 12 pages; article in press, Physica A (2010)