Constraints from deuterium on the formation of icy bodies in the Jovian system and beyond

We consider the role of deuterium as a potential marker of location and ambient conditions during the formation of small bodies in our Solar system. We concentrate in particular on the formation of the regular icy satellites of Jupiter and the other giant planets, but include a discussion of the implications for the Trojan asteroids and the irregular satellites. We examine in detail the formation of regular planetary satellites within the paradigm of a circum-Jovian subnebula. Particular attention is paid to the two extreme potential subnebulae—“hot” and “cold”. In particular, we show that, for the case of the “hot” subnebula model, the D:H ratio in water ice measured from the regular satellites would be expected to be near-Solar. In contrast, satellites which formed in a “cold” subnebula would be expected to display a D:H ratio that is distinctly over-Solar. We then compare the results obtained with the enrichment regimes which could be expected for other families of icy small bodies in the outer Solar system—the Trojan asteroids and the irregular satellites. In doing so, we demonstrate how measurements by Laplace, the James Webb Space Telescope, HERSCHEL and ALMA will play an important role in determining the true formation locations and mechanisms of these objects.     

Some results from the National Observatory of Turkey, Kazan State University, and Nikolaev Astronomical Observatory on small bodies of the solar system

A scientific collaboration between TÜB?TAK National Observatory (Turkey), Kazan State University (Russia) and Nikolaev Astronomical Observatory (Ukraine) involves observations of minor planets and near-Earth asteroids (NEAs) with the 1.5 m Russian-Turkish telescope (RTT150). Regular observations of selected asteroids in the range of 11-18 magnitudes began in 2004 with the view of determining masses of selected asteroids, improving the orbits of the NEAs, and studying physical characteristics of selected asteroids from photometric observations. More than 3000 positions of 53 selected asteroids and 11 NEAs have been obtained with an internal error in the range of 30-300 mas for a single determination. Photometric reductions of more than 4000 CCD frames are in progress. Masses of 21 asteroids were estimated through dynamical method using the ground-based optical observations, mainly from the RTT150 and Minor Planet Center. A comparison of the observational results from the RTT150 in 2004-2005 with observations of the same objects at other observatories allows us to conclude that RTT150 can be used for ground-based support in astrometry for the space mission GAIA.     

Short-Period Fluctuations in Coronal Mass Ejection Activity during Solar Cycle 23

We have constructed a time series of the number of coronal mass ejections (CMEs) observed by SOHO/LASCO during solar cycle 23. Using spectral analysis techniques (the maximum entropy method and wavelet analysis) we found short-period (< one year) semiperiodic activity. Among others, we found interesting periodicities at 193, 36, 28, and 25 days. We discuss the implications of such short-period activity in terms of the emergence and escape of magnetic flux from the convection zone, through the low solar atmosphere (where these periodicities have been found for numerous activity parameters), toward interplanetary space. This analysis shows that CMEs remove the magnetic flux in a quasiperiodic process in a way similar to that of magnetic flux emergence and other solar eruptive activity.     

Forecast of the Decadal Average Sunspot Number

The forecast of the decadal average sunspot number (SN) becomes possible with an extension of telescopic observations based on proxy reconstructions using the tree ring radiocarbon data during the Holocene. These decadal numbers (SN_RC) provide a powerful statistic to verify the forecasting methods. Complicated dynamics of long-term solar activity and noise of proxy-based reconstruction make the one-step-ahead forecast challenging for any forecasting method. Here we construct a continuous data set of SN_RC which extends the group sunspot number and the international sunspot number. The known technique of nonlinear forecast, the local linear approximation, is adapted to estimate the coming SN. Both the method and the continuous data set were tested and tuned to obtain the minimum of a normalized average prediction error (E) during the last millennium using several past millennia as a training data set. E=0.58σ _D is achieved to forecast the SN successive differences whose standard deviation is σ _D=7.39 for the period of training. This corresponds to the correlation (r=0.97) between true and forecasted SN. This error is significantly smaller than the prediction error when the surrogate data were used for the training data set, and proves the nonlinearity in the decadal SN. The estimated coming SN is smaller than the previous one.     

Nonlinear Force-Free Modeling of Coronal Magnetic Fields. II. Modeling a Filament Arcade and Simulated Chromospheric and Photospheric Vector Fields

We compare a variety of nonlinear force-free field (NLFFF) extrapolation algorithms, including optimization, magneto-frictional, and Grad – Rubin-like codes, applied to a solar-like reference model. The model used to test the algorithms includes realistic photospheric Lorentz forces and a complex field including a weakly twisted, right helical flux bundle. The codes were applied to both forced “photospheric” and more force-free “chromospheric” vector magnetic field boundary data derived from the model. When applied to the chromospheric boundary data, the codes are able to recover the presence of the flux bundle and the field’s free energy, though some details of the field connectivity are lost. When the codes are applied to the forced photospheric boundary data, the reference model field is not well recovered, indicating that the combination of Lorentz forces and small spatial scale structure at the photosphere severely impact the extrapolation of the field. Preprocessing of the forced photospheric boundary does improve the extrapolations considerably for the layers above the chromosphere, but the extrapolations are sensitive to the details of the numerical codes and neither the field connectivity nor the free magnetic energy in the full volume are well recovered. The magnetic virial theorem gives a rapid measure of the total magnetic energy without extrapolation though, like the NLFFF codes, it is sensitive to the Lorentz forces in the coronal volume. Both the magnetic virial theorem and the Wiegelmann extrapolation, when applied to the preprocessed photospheric boundary, give a magnetic energy which is nearly equivalent to the value derived from the chromospheric boundary, but both underestimate the free energy above the photosphere by at least a factor of two. We discuss the interpretation of the preprocessed field in this context. When applying the NLFFF codes to solar data, the problems associated with Lorentz forces present in the low solar atmosphere must be recognized: the various codes will not necessarily converge to the correct, or even the same, solution. On 07/07/2007, the NLFFF team was saddened by the news that Tom Metcalf had died as the result of an accident. We remain grateful for having had the opportunity to benefit from his unwavering dedication to the problems encountered in attempting to understand the Sun’s magnetic field; Tom had completed this paper several months before his death, leading the team through the many steps described above.     

Automated Prediction of CMEs Using Machine Learning of CME – Flare Associations

Machine-learning algorithms are applied to explore the relation between significant flares and their associated CMEs. The NGDC flares catalogue and the SOHO/LASCO CME catalogue are processed to associate X and M-class flares with CMEs based on timing information. Automated systems are created to process and associate years of flare and CME data, which are later arranged in numerical-training vectors and fed to machine-learning algorithms to extract the embedded knowledge and provide learning rules that can be used for the automated prediction of CMEs. Properties representing the intensity, flare duration, and duration of decline and duration of growth are extracted from all the associated (A) and not-associated (NA) flares and converted to a numerical format that is suitable for machine-learning use. The machine-learning algorithms Cascade Correlation Neural Networks (CCNN) and Support Vector Machines (SVM) are used and compared in our work. The machine-learning systems predict, from the input of a flare’s properties, if the flare is likely to initiate a CME. Intensive experiments using Jack-knife techniques are carried out and the relationships between flare properties and CMEs are investigated using the results. The predictive performance of SVM and CCNN is analysed and recommendations for enhancing the performance are provided.     

Dependence of the Characteristics of Solar Wind Discontinuities and Shocks with Heliolatitude and Radial Distance

The distribution of the shocks in the heliosphere and their characteristic variations are investigated using Ulysses observations. The jumps in solar wind velocity, IMF magnitude, and proton density across the shocks and discontinuities are evaluated and used to characterize them. The distribution of these discontinuities with respect to heliolatitude ± 80° and with radial distance 1 to 5 AU are analyzed during solar minimum and solar maximum to understand their global behavior. It is noticed that the jumps in solar wind parameters associated with shocks and discontinuities are more prominent during the second orbit of Ulysses, which coincided with the maximum phase of solar activity.