Statistical Significance of spectral lag transition in GRB 160625B

Recently Wei et al (arXiv:1612.09425) have found evidence for a transition from positive time lags to negative time lags in the spectral lag data of GRB 160625B. They have fit these observed lags to a sum of two components: an assumed functional form for intrinsic time lag due to astrophysical mechanisms and an energy-dependent speed of light due to quadratic and linear Loren tz invariance violation (LIV) models. Here, we examine the statistical significance of the evidence for a transition to nega tive time lags. Such a transition, even if present in GRB 160625B, cannot be due to an energy dependent speed of light as th is would contradict previous limits by some 3-4 orders of magnitude, and must therefore be of intrinsic astrophysical origin . We use three different model comparison techniques: a frequentist test and two information based criteria (AIC and BIC). From the frequentist model comparison test, we find that the evidence for transition in the spectral lag data is favored at $3.05\sigma$ and $3.74\sigma$ for the linear and quadratic models respectively. We find that $\Delta$AIC and $\Delta$BIC have values $\gtrsim$ 10 for the spectral lag transition that was motivated as being due to quadratic Lorentz invariance vio lating model pointing to "decisive evidence". We note however that none of the three models (including the model of intr insic astrophysical emission) provide a good fit to the data.Comment: 6 pages, 1 figur

Non-Gaussian Error Distributions of Galactic Rotation Speed Measurements

We construct the error distributions for the galactic rotation speed ($\Theta_0$) using 137 data points from measurements compiled in De Grijs et al. (arXiv:1709.02501), with all observations normalized to the galactocentric distance of 8.3 kpc. We then checked (using the same procedures as in works by Ratra et al) if the errors constructed using the weighted mean and the median as the estimate, obey Gaussian statistics. We find using both these estimates that they have much wider tails than a Gaussian distribution. We also tried to fit the data to three other distributions: Cauchy, double-exponential, and Students-t. The best fit is obtained using the Students-$t$ distribution for $n=2$ using the median value as the central estimate, corresponding to a $p$-value of 0.1. We also calculate the median value of $\Theta_0$ using all the data as well as using the median of each set of measurements based on the tracer population used. Because of the non-gaussianity of the residuals, we point out that the subgroup median value, given by $\Theta_{med}=219.65$ km/sec should be used as the central estimate for $\Theta_0$.Comment: 7 pages, 3 figure

Bound on the graviton mass from Chandra X-ray cluster sample

We present new limits on the graviton mass using a sample of 12 relaxed galaxy clusters, for which temperature and gas density profiles were derived by Vikhlinin et al (astro-ph/0507092) using Chandra X-ray observations. These limits can be converted to a bound on the graviton mass, assuming a non-zero graviton mass would lead to a Yukawa potential at these scales. For this purpose, we first calculate the total dynamical mass from the hydrostatic equilibrium equation in Yukawa gravity and then compare it with the corresponding mass in Newtonian gravity. We calculate a 90 % c.l. lower/upper limit on the graviton Compton wavelength/ mass for each of the 12 clusters in the sample. The best limit is obtained for Abell 2390, corresponding to $\lambda_g > 3.58\times 10^{19}$ km or $m_g<3.46 \times 10^{-29}$ eV. This is the first proof of principles demonstration of setting a limit on the graviton mass using a sample of related galaxy clusters with X-ray measurements and can be easily applied to upcoming X-ray surveys such as eRosita.Comment: 6 pages, 1 figur

Separation of pulsar signals from noise with supervised machine learning algorithms

We evaluate the performance of four different machine learning (ML) algorithms: an Artificial Neural Network Multi-Layer Perceptron (ANN MLP ), Adaboost, Gradient Boosting Classifier (GBC), XGBoost, for the separation of pulsars from radio frequency interference (RFI) and other sources of noise, using a dataset obtained from the post-processing of a pulsar search pi peline. This dataset was previously used for cross-validation of the SPINN-based machine learning engine, used for the reprocessing of HTRU-S survey data arXiv:1406.3627. We have used Synthetic Minority Over-sampling Technique (SMOTE) to deal with high class imbalance in the dataset. We report a variety of quality scores from all four of these algorithms on both the non-SMOTE and SMOTE datasets. For all the above ML methods, we report high accuracy and G-mean in both the non-SMOTE and SMOTE cases. We study the feature importances using Adaboost, GBC, and XGBoost and also from the minimum Redundancy Maximum Relevance approach to report algorithm-agnostic feature ranking. From these methods, we find that the signal to noise of the folded profile to be the best feature. We find that all the ML algorithms report FPRs about an order of magnitude lower than the corresponding FPRs obtained in arXiv:1406.3627, for the same recall value.Comment: 14 pages, 2 figures. Accepted for publication in Astronomy and Computin

Generalized Lomb-Scargle analysis of 90Sr/90Y\rm{^{90}Sr/^{90}Y} decay rate measurements from the Physikalisch-Technische Bundesanstalt

We apply the generalized Lomb-Scargle (LS) periodogram to independently confirm the claim by Sturrock et al (arXiv:1605.03088) of oscillation at a frequency of 11/year in the decay rates of $\rm{^{90}Sr/^{90}Y}$ from measurements at the Physikalisch Technische Bundesanstalt (PTB), which however has been disputed by Kossert and Nahle (arXiv:1407.2493). For this analysis, we made two different {\it ansatze} for the errors. For each peak in the LS periodogram, we evaluate the statistical significance using non-parametric bootstrap resampling. We find using both of these error models evidence for ~11/year periodicity in the $\rm{^{90}Sr/^{90}Y}$ data for two of the three samples, but at a lower significance than that claimed by Sturrock et al.Comment: 9 pages, 9 figure

Classifying Exoplanets with Gaussian Mixture Model

Recently, Odrzywolek and Rafelski (arXiv:1612.03556) have found three distinct categories of exoplanets, when they are classified based on density. We first carry out a similar classification of exoplanets according to their density using the Gaussian Mixture Model, followed by information theoretic criterion (AIC and BIC) to determine the optimum number of components. Such a one-dimensional classification favors two components using AIC and three using BIC, but the statistical significance from both the tests is not significant enough to decisively pick the best model between two and three components. We then extend this GMM-based classification to two dimensions by using both the density and the Earth similarity index (arXiv:1702.03678), which is a measure of how similar each planet is compared to the Earth. For this two-dimensional classification, both AIC and BIC provide decisive evidence in favor of three components.Comment: 8 pages, 7 figure

Galactic Shapiro Delay to the Crab Pulsar and limit on Einstein's Equivalence Principle Violation

We calculate the total galactic Shapiro delay to the Crab pulsar by including the contributions from the dark matter as well as baryonic matter along the line of sight. The total delay due to dark matter potential is about 3.4 days. For baryonic matter, we included the contributions from both the bulge and the disk, which are approximately 0.12 and 0.32 days respectively. The total delay from all the matter distribution is therefore 3.84 days. We also calculate the limit on violations of Einstein's equivalence principle by using observations of "nano-shot" giant pulses from the Crab pulsar with time-delay $<0.4$~ns as well as using time differences between radio and optical photons observed from this pulsar. Using the former, we obtain a limit on violation of Einstein's equivalence principle in terms of the PPN parameter $\Delta \gamma < 2.41\times 10^{-15}$. From the time-difference between simultaneous optical and radio observations, we get $\Delta \gamma < 1.54\times 10^{-9}$. We also point out differences in our calculation of Shapiro delay and that from two recent papers (arXiv:1612.00717 and arXiv:1608.07657), which used the same observations to obtain a corresponding limit on $\Delta \gamma$.Comment: 4 pages, 1 figure. Accepted for publication in Eur. Phys. Journal