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We use an information theoretic framework to analyze data from the Galaxy Zoo 2 project and study if there are any statistically significant correlations between the presence of bars in spiral galaxies and their environment. We measure the mutual information between the barredness of galaxies and their environments in a volume limited sample ($M_r leq -21$) and compare it with the same in datasets where (i) the bar/unbar classifications are randomized and (ii) the spatial distribution of galaxies are shuffled on different length scales. We assess the statistical significance of the differences in the mutual information using a t-test and find that both randomization of morphological classifications and shuffling of spatial distribution do not alter the mutual information in a statistically significant way. The non-zero mutual information between barredness and environment arises due to the finite and discrete nature of the dataset which can be entirely explained by mock Poisson distributions. We also separately compare the cumulative distribution functions of the barred and unbarred galaxies as a function of their local density. Using a Kolmogorov-Smirnov test, we find that the null hypothesis can not be rejected even at $75%$ confidence level. Our analysis indicates that environments do not play a significant role in the formation of a bar, which is largely determined by the internal processes of the host galaxy.
We use multi-wavelength SDSS images and Galaxy Zoo morphologies to identify a sample of $sim$$270$ late-type galaxies with an off-centre bar. We measure offsets in the range 0.2-2.5 kpc between the photometric centres of the stellar disc and stellar
We have used Galaxy Zoo DECaLS (GZD) to study strong and weak bars in disk galaxies. Out of the 314,000 galaxies in GZD, we created a volume-limited sample (0.01 < z < 0.05, Mr < -18.96) which contains 1,867 galaxies with reliable volunteer bar class
This paper presents the first results from a new citizen science project: Galaxy Zoo Supernovae. This proof of concept project uses members of the public to identify supernova candidates from the latest generation of wide-field imaging transient surv
Does the environment of a galaxy directly influence the quenching history of a galaxy? Here we investigate the detailed morphological structures and star formation histories of a sample of SDSS group galaxies with both classifications from Galaxy Zoo
Grover discovered a quantum algorithm for identifying a target element in an unstructured search universe of N items in approximately square-root of N queries to a quantum oracle, thus achieving a square-root speed-up over classical algorithms. We pr