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تسجيل مستخدم جديدFrom Espresso to Codex
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CODEX and ESPRESSO are concepts for ultra-stable, high-resolution spectrographs at the E-ELT and VLT, respectively. Both instruments are well motivated by distinct sets of science drivers. However, ESPRESSO will also be a stepping stone towards CODEX both in a scientific as well as in a technical sense. Here we discuss this role of ESPRESSO with respect to one of the most exciting CODEX science cases, i.e. the dynamical determination of the cosmic expansion history.
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CODEX, a high resolution, super-stable spectrograph to be fed by the E-ELT, the most powerful telescope ever conceived, will for the first time provide the possibility of directly measuring the change of the expansion rate of the Universe with time a
nd much more, from the variability of fundamental constants to the search for other earths. A study for the implementation at the VLT of a precursor of CODEX, dubbed ESPRESSO, is presently carried out by a collaboration including ESO, IAC, INAF, IoA Cambridge and Observatoire de Geneve. The present talk is focused on the cosmological aspects of the experiment.
CoDEx is a Mathematica package that calculates the Wilson Coefficients (WCs) corresponding to effective operators up to mass dimension-6. Once the part of the Lagrangian involving single as well as multiple degenerate heavy fields, belonging to some
Beyond Standard Model (BSM) theory, is given, the package can then integrate out propagators from the tree as well as 1-loop diagrams of that BSM theory. It then computes the associated WCs up to 1-loop level, for two different bases: Warsaw and SILH. CoDEx requires only very basic information about the heavy field(s), e.g., Colour, Isospin, Hyper-charge, Mass, and Spin. The package first calculates the WCs at the high scale (mass of the heavy field(s)). We then have an option to perform the renormalisation group evolutions (RGEs) of these operators in Warsaw basis, a complete one (unlike SILH), using the anomalous dimension matrix. Thus, one can get all effective operators at the electro-weak scale, generated from any such BSM theory, containing heavy fields of spin: 0, 1/2, and 1. We have provided many example models (both here and in the package-documentation) that more or less encompass different choices of heavy fields and interactions. Relying on the status of the present day precision data, we restrict ourselves up to dimension-6 effective operators. This will be generalised for any dimensional operators in a later version. Site: https://effexteam.github.io/CoDEx
Aims. We analyze the autocorrelation function of a large contiguous sample of galaxy clusters, the Constrain Dark Energy with X-ray (CODEX) sample, in which we take particular care of cluster definition. These clusters were X-ray selected using the R
ASS survey and then identified as galaxy clusters using the code redMaPPer run on the photometry of the SDSS. We develop methods for precisely accounting for the sample selection effects on the clustering and demonstrate their robustness using numerical simulations. Methods. Using the clean CODEX sample, which was obtained by applying a redshift-dependent richness selection, we computed the two-point autocorrelation function of galaxy clusters in the $0.1<z<0.3$ and $0.3<z<0.5$ redshift bins. We compared the bias in the measured correlation function with values obtained in numerical simulations using a similar cluster mass range. Results. By fitting a power law, we measured a correlation length $r_0=18.7 pm 1.1$ and slope $gamma=1.98 pm 0.14$ for the correlation function in the full redshift range. By fixing the other cosmological parameters to their WMAP9 values, we reproduced the observed shape of the correlation function under the following cosmological conditions: $Omega_{m_0}=0.22^{+0.04}_{-0.03}$ and $S_8=sigma_8 (Omega_{m_0} /0.3)^{0.5}=0.85^{+0.10}_{-0.08}$ with estimated additional systematic errors of $sigma_{Omega_{m_0}} = 0.02$ and $sigma_{S_8} = 0.20$. We illustrate the complementarity of clustering constraints by combining them with CODEX cosmological constraints based on the X-ray luminosity function, deriving $Omega_{m_0} = 0.25 pm 0.01$ and $sigma_8 = 0.81^{+0.01}_{-0.02}$ with an estimated additional systematic error of $sigma_{Omega_{m_0}} = 0.07$ and $sigma_{sigma_8} = 0.04$. The mass calibration and statistical quality of the mass tracers are the dominant source of uncertainty.
We aim to confirm the presence of Proxima b using independent measurements obtained with the new ESPRESSO spectrograph, and refine the planetary parameters taking advantage of its improved precision. We analysed 63 spectroscopic ESPRESSO observations
of Proxima taken during 2019. We obtained radial velocity measurements with a typical radial velocity photon noise of 26 cm/s. We ran a joint MCMC analysis on the time series of the radial velocity and full-width half maximum of the cross-correlation function to model the planetary and stellar signals present in the data, applying Gaussian process regression to deal with stellar activity. We confirm the presence of Proxima b independently in the ESPRESSO data. The ESPRESSO data on its own shows Proxima b at a period of 11.218 $pm$ 0.029 days, with a minimum mass of 1.29 $pm$ 0.13 Me. In the combined dataset we measure a period of 11.18427 $pm$ 0.00070 days with a minimum mass of 1.173 $pm$ 0.086 Me. We find no evidence of stellar activity as a potential cause for the 11.2 days signal. We find some evidence for the presence of a second short-period signal, at 5.15 days with a semi-amplitude of merely 40 cm/s. If caused by a planetary companion, it would correspond to a minimum mass of 0.29 $pm$ 0.08 Me. We find that the FWHM of the CCF can be used as a proxy for the brightness changes and that its gradient with time can be used to successfully detrend the radial velocity data from part of the influence of stellar activity. The activity-induced radial velocity signal in the ESPRESSO data shows a trend in amplitude towards redder wavelengths. Velocities measured using the red end of the spectrograph are less affected by activity, suggesting that the stellar activity is spot-dominated. The data collected excludes the presence of extra companions with masses above 0.6 Me at periods shorter than 50 days.
We present Espresso, an open-source, modular, extensible end-to-end neural automatic speech recognition (ASR) toolkit based on the deep learning library PyTorch and the popular neural machine translation toolkit fairseq. Espresso supports distributed
training across GPUs and computing nodes, and features various decoding approaches commonly employed in ASR, including look-ahead word-based language model fusion, for which a fast, parallelized decoder is implemented. Espresso achieves state-of-the-art ASR performance on the WSJ, LibriSpeech, and Switchboard data sets among other end-to-end systems without data augmentation, and is 4--11x faster for decoding than similar systems (e.g. ESPnet).
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