Constraining the equation of state of the Universe from Distant Type Ia Supernovae and Cosmic Microwave Background Anisotropies

We analyse the constraints that can be placed on a cosmological constant or quintessence-like component by combining observations of Type Ia supernovae with measurements of anisotropies in the cosmic microwave background. We use the recent supernovae sample of Perlmutter et al and observations of the CMB anisotropies to constraint the equation of state (w_Q = p/rho) in quintessence-like models via a likelihood analysis. The 2 sigma upper limits are w_Q < -0.6 if the Universe is assumed to be spatially flat, and w_Q < -0.4 for universes of arbitrary spatial curvature. The upper limit derived for a spatially flat Universe is close to the lower limit (w_Q approx -0.7) allowed for simple potentials, implying that additional fine tuning may be required to construct a viable quintessence model.Comment: 9 pages, 8 Postscript figures, uses mn.sty. submitted to MNRA

Power Spectrum Analysis of the Stromlo-APM Redshift Survey

We test estimators of the galaxy power spectrum $P(k)$ against simulated galaxy catalogues constructed from N-body simulations and we derive formulae to correct for biases. These estimators are then applied to compute the power spectrum of galaxies in the Stromlo-APM redshift survey. We test whether the amplitude of $P(k)$ depends on galaxy luminosity, but find no significant luminosity dependence except at absolute magnitudes brighter than M_{\bj} = -20.3, (H_{0} = 100 \kms) where there is some evidence for a rise in the amplitude of $P(k)$. By comparing the redshift space power spectrum of the Stromlo-APM survey with the real space power spectrum determined from the parent APM Galaxy Survey, we attempt to measure the distortion in the shape of $P(k)$ caused by galaxy peculiar motions. We find some evidence for an effect, but the errors are large and do not exclude a value of $\beta = \Omega^{0.6}/b = 1$, where $\Omega$ is the cosmological density parameter and $b$ is the linear biasing parameter relating galaxy fluctuations to those in the mass, $\left(\delta \rho/\rho\right)_{gal} = b \left(\delta \rho/\rho\right)_{m}$. The shape of the Stromlo-APM power spectrum is consistent with that determined from the CfA-2 survey, but has a slightly higher amplitude by a factor of about 1.4 than the power spectrum of IRAS galaxies.Comment: 14 pages, gziped and uuencoded postscript file. Submitted to MNRA

Semantic Source Code Models Using Identifier Embeddings

The emergence of online open source repositories in the recent years has led to an explosion in the volume of openly available source code, coupled with metadata that relate to a variety of software development activities. As an effect, in line with recent advances in machine learning research, software maintenance activities are switching from symbolic formal methods to data-driven methods. In this context, the rich semantics hidden in source code identifiers provide opportunities for building semantic representations of code which can assist tasks of code search and reuse. To this end, we deliver in the form of pretrained vector space models, distributed code representations for six popular programming languages, namely, Java, Python, PHP, C, C++, and C#. The models are produced using fastText, a state-of-the-art library for learning word representations. Each model is trained on data from a single programming language; the code mined for producing all models amounts to over 13.000 repositories. We indicate dissimilarities between natural language and source code, as well as variations in coding conventions in between the different programming languages we processed. We describe how these heterogeneities guided the data preprocessing decisions we took and the selection of the training parameters in the released models. Finally, we propose potential applications of the models and discuss limitations of the models.Comment: 16th International Conference on Mining Software Repositories (MSR 2019): Data Showcase Trac

The Beylkin-Cramer Summation Rule and A New Fast Algorithm of Cosmic Statistics for Large Data Sets

Based on the Beylkin-Cramer summation rule, we introduce a new fast algorithm that enable us to explore the high order statistics efficiently in large data sets. Central to this technique is to make decomposition both of fields and operators within the framework of multi-resolution analysis (MRA), and realize theirs discrete representations. Accordingly, a homogenous point process could be equivalently described by a operation of a Toeplitz matrix on a vector, which is accomplished by making use of fast Fourier transformation. The algorithm could be applied widely in the cosmic statistics to tackle large data sets. Especially, we demonstrate this novel technique using the spherical, cubic and cylinder counts in cells respectively. The numerical test shows that the algorithm produces an excellent agreement with the expected results. Moreover, the algorithm introduces naturally a sharp-filter, which is capable of suppressing shot noise in weak signals. In the numerical procedures, the algorithm is somewhat similar to particle-mesh (PM) methods in N-body simulations. As scaled with $O(N\log N)$, it is significantly faster than the current particle-based methods, and its computational cost does not relies on shape or size of sampling cells. In addition, based on this technique, we propose further a simple fast scheme to compute the second statistics for cosmic density fields and justify it using simulation samples. Hopefully, the technique developed here allows us to make a comprehensive study of non-Guassianity of the cosmic fields in high precision cosmology. A specific implementation of the algorithm is publicly available upon request to the author.Comment: 27 pages, 9 figures included. revised version, changes include (a) adding a new fast algorithm for 2nd statistics (b) more numerical tests including counts in asymmetric cells, the two-point correlation functions and 2nd variances (c) more discussions on technic

H0 Revisited

I reanalyse the Riess et al. (2011, hereafter R11) Cepheid data using the revised geometric maser distance to NGC 4258 of Humphreys et al. (2013). I explore different outlier rejection criteria designed to give a reduced chi-squared of unity and compare the results with the R11 rejection algorithm, which produces a reduced chi-squared that is substantially less than unity and, in some cases, to underestimates of the errors on parameters. I show that there are sub-luminous low metallicity Cepheids in the R11 sample that skew the global fits of the period-luminosity relation. This has a small but non-negligible impact on the global fits using NGC 4258 as a distance scale anchor, but adds a poorly constrained source of systematic error when using the Large Magellanic Cloud (LMC) as an anchor. I also show that the small Milky Way (MW) Cepheid sample with accurate parallax measurements leads to a distance to NGC 4258 that is in tension with the maser distance. I conclude that H0 based on the NGC 4258 maser distance is H0 = 70.6 +/- 3.3 km/s/Mpc compatible within 1 sigma with the recent determination from Planck for the base six-parameter LCDM cosmology. If the H-band period-luminosity relation is assumed to be independent of metallicity and the three distance anchors are combined, I find H0 = 72.5 +/- 2.5 km/s/Mpc, which differs by 1.9 sigma from the Planck value. The differences between the Planck results and these estimates of H0 are not large enough to provide compelling evidence for new physics at this stage.Comment: 14 page