A catalogue of observed geo-effective CME/ICME characteristics

One of the goals of Space Weather studies is to achieve a better understanding of impulsive phenomena, such as Coronal Mass Ejections (CMEs), in order to improve our ability to forecast them and mitigate the risk to our technologically driven society. The essential part of achieving this goal is to assess the performance of forecasting models. To this end, the quality and availability of suitable data are of paramount importance. In this work, we have merged already publicly available data of CMEs from both in-situ and remote instrumentation in order to build a database of CME properties. To evaluate the accuracy of such a database and confirm the relationship between in-situ and remote observations, we have employed the drag-based model (DBM) due to its simplicity and inexpensive cost of computational resources. In this study, we have also explored the parameter space for the drag parameter and solar wind speed using a Monte Carlo approach to evaluate how well the DBM determines the propagation of CMEs for the events in the dataset. The dataset of geoeffective CMEs constructed as a result of this work provides validation of the initial hypothesis about DBM, and solar wind speed and also yields further insight into CME features like arrival time, arrival speed, lift-off time, etc. Using a data-driven approach, this procedure allows us to present a homogeneous, reliable, and robust dataset for the investigation of CME propagation. On the other hand, possible CME events are identified where DBM approximation is not valid due to model limitations and higher uncertainties in the input parameters, those events require more thorough investigation

Non-Gaussian bubbles in the sky

We point out a possible generation mechanism of non-Gaussian bubbles in the sky due to bubble nucleation in the early universe. We consider a curvaton scenario for inflation and assume that the curvaton field phi, whose energy density is subdominant during inflation but which is responsible for the curvature perturbation of the universe, is coupled to another field sigma which undergoes false vacuum decay through quantum tunneling. For this model, we compute the skewness of the curvaton fluctuations due to its interaction with sigma during tunneling, that is, on the background of an instanton solution that describes false vacuum decay. We find that the resulting skewness of the curvaton can become large in the spacetime region inside the bubble. We then compute the corresponding skewness in the statistical distribution of the cosmic microwave background (CMB) temperature fluctuations. We find a non-vanishing skewness in a bubble-shaped region in the sky. It can be large enough to be detected in the near future, and if detected it will bring us invaluable information about the physics in the early universe.Comment: 6 pages, 6 figure

Iterative destriping and photometric calibration for Planck-HFI, polarized, multi-detector map-making

We present an iterative scheme designed to recover calibrated I, Q, and U maps from Planck-HFI data using the orbital dipole due to the satellite motion with respect to the Solar System frame. It combines a map reconstruction, based on a destriping technique, juxtaposed with an absolute calibration algorithm. We evaluate systematic and statistical uncertainties incurred during both these steps with the help of realistic, Planck-like simulations containing CMB, foreground components and instrumental noise, and assess the accuracy of the sky map reconstruction by considering the maps of the residuals and their spectra. In particular, we discuss destriping residuals for polarization sensitive detectors similar to those of Planck-HFI under different noise hypotheses and show that these residuals are negligible (for intensity maps) or smaller than the white noise level (for Q and U Stokes maps), for l > 50. We also demonstrate that the combined level of residuals of this scheme remains comparable to those of the destriping-only case except at very low l where residuals from the calibration appear. For all the considered noise hypotheses, the relative calibration precision is on the order of a few 10e-4, with a systematic bias of the same order of magnitude.Comment: 18 pages, 21 figures. Match published versio

Comparison on map-making algorithms for CMB experiments

We have compared the cosmic microwave background (CMB) temperature anisotropy maps made from one-year time ordered data (TOD) streams that simulated observations of the originally planned 100 GHz Planck Low Frequency Instrument (LFI). The maps were made with three different codes. Two of these, ROMA and MapCUMBA, were implementations of maximum-likelihood (ML) map-making, whereas the third was an implementation of the destriping algorithm. The purpose of this paper is to compare these two methods, ML and destriping, in terms of the maps they produce and the angular power spectrum estimates derived from these maps. The difference in the maps produced by the two ML codes was found to be negligible. As expected, ML was found to produce maps with lower residual noise than destriping. In addition to residual noise, the maps also contain an error which is due to the effect of subpixel structure in the signal on the map-making method. This error is larger for ML than for destriping. If this error is not corrected a bias will be introduced in the power spectrum estimates. This study is related to Planck activities.We have compared the cosmic microwave background (CMB) temperature anisotropy maps made from one-year time ordered data (TOD) streams that simulated observations of the originally planned 100 GHz Planck Low Frequency Instrument (LFI). The maps were made with three different codes. Two of these, ROMA and MapCUMBA, were implementations of maximum-likelihood (ML) map-making, whereas the third was an implementation of the destriping algorithm. The purpose of this paper is to compare these two methods, ML and destriping, in terms of the maps they produce and the angular power spectrum estimates derived from these maps. The difference in the maps produced by the two ML codes was found to be negligible. As expected, ML was found to produce maps with lower residual noise than destriping. In addition to residual noise, the maps also contain an error which is due to the effect of subpixel structure in the signal on the map-making method. This error is larger for ML than for destriping. If this error is not corrected a bias will be introduced in the power spectrum estimates. This study is related to Planck activities.We have compared the cosmic microwave background (CMB) temperature anisotropy maps made from one-year time ordered data (TOD) streams that simulated observations of the originally planned 100 GHz Planck Low Frequency Instrument (LFI). The maps were made with three different codes. Two of these, ROMA and MapCUMBA, were implementations of maximum-likelihood (ML) map-making, whereas the third was an implementation of the destriping algorithm. The purpose of this paper is to compare these two methods, ML and destriping, in terms of the maps they produce and the angular power spectrum estimates derived from these maps. The difference in the maps produced by the two ML codes was found to be negligible. As expected, ML was found to produce maps with lower residual noise than destriping. In addition to residual noise, the maps also contain an error which is due to the effect of subpixel structure in the signal on the map-making method. This error is larger for ML than for destriping. If this error is not corrected a bias will be introduced in the power spectrum estimates. This study is related to Planck activities.Peer reviewe

Cosmological Parameters from the 2003 flight of BOOMERANG

We present the cosmological parameters from the CMB intensity and polarization power spectra of the 2003 Antarctic flight of the BOOMERANG telescope. The BOOMERANG data alone constrains the parameters of the $\Lambda$CDM model remarkably well and is consistent with constraints from a multi-experiment combined CMB data set. We add LSS data from the 2dF and SDSS redshift surveys to the combined CMB data set and test several extensions to the standard model including: running of the spectral index, curvature, tensor modes, the effect of massive neutrinos, and an effective equation of state for dark energy. We also include an analysis of constraints to a model which allows a CDM isocurvature admixture.Comment: 18 pages, 10 figures, submitted to Ap

A Measurement of the Angular Power Spectrum of the CMB Temperature Anisotropy from the 2003 Flight of Boomerang

We report on observations of the Cosmic Microwave Background (CMB) obtained during the January 2003 flight of Boomerang . These results are derived from 195 hours of observation with four 145 GHz Polarization Sensitive Bolometer (PSB) pairs, identical in design to the four 143 GHz Planck HFI polarized pixels. The data include 75 hours of observations distributed over 1.84% of the sky with an additional 120 hours concentrated on the central portion of the field, itself representing 0.22% of the full sky. From these data we derive an estimate of the angular power spectrum of temperature fluctuations of the CMB in 24 bands over the multipole range (50 < l < 1500). A series of features, consistent with those expected from acoustic oscillations in the primordial photon-baryon fluid, are clearly evident in the power spectrum, as is the exponential damping of power on scales smaller than the photon mean free path at the epoch of last scattering (l > 900). As a consistency check, the collaboration has performed two fully independent analyses of the time ordered data, which are found to be in excellent agreement.Comment: 11 pages, 7 figures, 3 tables. High resolution figures and data are available at http://cmb.phys.cwru.edu/boomerang/ and http://oberon.roma1.infn.it/boomerang/b2

Searching for non Gaussian signals in the BOOMERanG 2003 CMB maps

We analyze the BOOMERanG 2003 (B03) 145 GHz temperature map to constrain the amplitude of a non Gaussian, primordial contribution to CMB fluctuations. We perform a pixel space analysis restricted to a portion of the map chosen in view of high sensitivity, very low foreground contamination and tight control of systematic effects. We set up an estimator based on the three Minkowski functionals which relies on high quality simulated data, including non Gaussian CMB maps. We find good agreement with the Gaussian hypothesis and derive the first limits based on BOOMERanG data for the non linear coupling parameter f_NL as -300<f_NL<650 at 68% CL and -800<f_NL<1050 at 95% CL.Comment: accepted for publication in ApJ. Letter

A weighting method to improve habitat association analysis: tested on British carabids

Analysis of species’ habitat associations is important for biodiversity conservation and spatial ecology. The original phi coefficient of association is a simple method that gives both positive and negative associations of individual species with habitats. The method originates in assessing the association of plant species with habitats, sampled by quadrats. Using this method for mobile animals creates problems as records often have imprecise locations, and would require either using only records related to a single habitat or arbitrarily choosing a single habitat to assign. We propose and test a new weighted version of the index that retains more records, which improves association estimates and allows assessment of more species. It weights habitats that lie within the area covered by the species record with their certainty level, in our case study, the proportion of the grid cell covered by that habitat. We used carabid beetle data from the National Biodiversity Network atlas and CEH Land Cover Map 2015 across Great Britain to compare the original method with the weighted version. We used presence‐only data, assigning species absences using a threshold based on the number of other species found at a location, and conducted a sensitivity analysis of this threshold. Qualitative descriptions of habitat associations were used as independent validation data. The weighted index allowed the analysis of 52 additional species (19% more) and gave results with as few as 50 records. For the species we could analyse using both indices, the weighted index explained 70% of the qualitative validation data compared to 68% for the original, indicating no accuracy loss. The weighted phi coefficient of association provides an improved method for habitat analysis giving information on preferred and avoided habitats for mobile species that have limited records, and can be used in modelling and analysis that directs conservation policy and practice

A Bayesian approach to the drag-based modelling of ICMEs

Coronal Mass Ejections (CMEs) are huge clouds of magnetised plasma expelled from the solar corona that can travel towards the Earth and cause significant space weather effects. The Drag-Based Model (DBM) describes the propagation of CMEs in an ambient solar wind as analogous to an aerodynamic drag. The drag-based approximation is popular because it is a simple analytical model that depends only on two parameters, the drag parameter and the solar wind speed . DBM thus allows us to obtain reliable estimates of CME transit time at low computational cost. Previous works proposed a probabilistic version of DBM, the Probabilistic Drag Based Model (P-DBM), which enables the evaluation of the uncertainties associated with the predictions. In this work, we infer the “a-posteriori” probability distribution functions (PDFs) of the and parameters of the DBM by exploiting a well-established Bayesian inference technique: the Monte Carlo Markov Chains (MCMC) method. By utilizing this Bayesian method through two different approaches, an ensemble and an individual approach, we obtain specific DBM parameter PDFs for two ensembles of CMEs: those travelling with fast and slow solar wind, respectively. Subsequently, we assess the operational applicability of the model by forecasting the arrival time of CMEs. While the ensemble approach displays notable limitations, the individual approach yields promising results, demonstrating competitive performances compared to the current state-of-the-art, with a Mean Absolute Error (MAE) of 9.86 ± 4.07 h achieved in the best-case scenario

Images of the Early Universe from the BOOMERanG experiment

The CMB is the fundamental tool to study the properties of the early universe and of the universe at large scales. In the framework of the Hot Big Bang model, when we look to the CMB we look back in time to the end of the plasma era, at a redshift ~ 1000, when the universe was ~ 50000 times younger, ~ 1000 times hotter and ~ 10^9 times denser than today. The image of the CMB can be used to study the physical processes there, to infer what happened before, and also to study the background geometry of our Universe