The VLT-FLAMES tarantula survey:XII. Rotational velocities of the single O-type stars

Context. The 30 Doradus (30 Dor) region of the Large Magellanic Cloud, also known as the Tarantula nebula, is the nearest starburst region. It contains the richest population of massive stars in the Local Group, and it is thus the best possible laboratory to investigate open questions on the formation and evolution of massive stars. Aims. Using ground-based multi-object optical spectroscopy obtained in the framework of the VLT-FLAMES Tarantula Survey (VFTS), we aim to establish the (projected) rotational velocity distribution for a sample of 216 presumably single O-type stars in 30 Dor. The sample is large enough to obtain statistically significant information and to search for variations among subpopulations - in terms of spectral type, luminosity class, and spatial location - in the field of view. Methods. We measured projected rotational velocities, 3e sin i, by means of a Fourier transform method and a profile fitting method applied to a set of isolated spectral lines. We also used an iterative deconvolution procedure to infer the probability density, P(3e), of the equatorial rotational velocity, 3e. Results. The distribution of 3e sin i shows a two-component structure: a peak around 80 km s1 and a high-velocity tail extending up to 600 km s^-1 This structure is also present in the inferred distribution P(3e) with around 80% of the sample having 0 <3e ≤ 300 km s^-1 and the other 20% distributed in the high-velocity region. The presence of the low-velocity peak is consistent with what has been found in other studies for late O- and early B-type stars. Conclusions. Most of the stars in our sample rotate with a rate less than 20% of their break-up velocity. For the bulk of the sample, mass loss in a stellar wind and/or envelope expansion is not efficient enough to significantly spin down these stars within the first few Myr of evolution. If massive-star formation results in stars rotating at birth with a large portion of their break-up velocities, an alternative braking mechanism, possibly magnetic fields, is thus required to explain the present-day rotational properties of the O-type stars in 30 Dor. The presence of a sizeable population of fast rotators is compatible with recent population synthesis computations that investigate the influence of binary evolution on the rotation rate of massive stars. Even though we have excluded stars that show significant radial velocity variations, our sample may have remained contaminated by post-interaction binary products. That the highvelocity tail may be populated primarily (and perhaps exclusively) by post-binary interaction products has important implications for the evolutionary origin of systems that produce gamma-ray bursts. © 2013 Author(s).

The VLT-FLAMES tarantula survey:X. Evidence for a bimodal distribution of rotational velocities for the single early B-type stars

Aims. Projected rotational velocities (ve sin i) have been estimated for 334 targets in the VLT-FLAMES Tarantula Survey that do not manifest significant radial velocity variations and are not supergiants. They have spectral types from approximately O9.5 to B3. The estimates have been analysed to infer the underlying rotational velocity distribution, which is critical for understanding the evolution of massive stars. Methods. Projected rotational velocities were deduced from the Fourier transforms of spectral lines, with upper limits also being obtained from profile fitting. For the narrower lined stars, metal and non-diffuse helium lines were adopted, and for the broader lined stars, both non-diffuse and diffuse helium lines; the estimates obtained using the different sets of lines are in good agreement. The uncertainty in the mean estimates is typically 4% for most targets. The iterative deconvolution procedure of Lucy has been used to deduce the probability density distribution of the rotational velocities. Results. Projected rotational velocities range up to approximately 450 kms-1 and show a bi-modal structure. This is also present in the inferred rotational velocity distribution with 25% of the sample having 0 <ve <100 km s^-1 and the high velocity component having v_e ∼ 250 km s^-1. There is no evidence from the spatial and radial velocity distributions of the two components that they represent either field and cluster populations or different episodes of star formation. Be-type stars have also been identified. Conclusions. The bi-modal rotational velocity distribution in our sample resembles that found for late-B and early-A type stars.While magnetic braking appears to be a possible mechanism for producing the low-velocity component, we can not rule out alternative explanations. © ESO 2013.

Transcallosal connectivity of the human cortical motor network

The organizational and architectural configuration of white matter pathways connecting brain regions has ramifications for all facets of the human condition, including manifestations of incipient neurodegeneration. Although diffusion tensor imaging (DTI) has been used extensively to visualize white matter connectivity, due to the widespread presence of crossing fibres, the lateral projections of the corpus callosum are not normally detected using this methodology. Detailed knowledge of the transcallosal connectivity of the human cortical motor network has therefore remained elusive. We employed constrained spherical deconvolution (CSD) tractography - an approach that is much less susceptible to the influence of crossing fibres, in order to derive complete in-vivo characterizations of white matter pathways connecting specific motor cortical regions to their counterparts and other loci in the opposite hemisphere. The revealed patterns of connectivity closely resemble those derived from anatomical tracing in primates. It was established that dorsal premotor cortex (PMd) and supplementary motor area (SMA) have extensive interhemispheric connectivity - exhibiting both dense homologous projections, and widespread structural relations with every other region in the contralateral motor network. Through this in-vivo portrayal, the importance of non-primary motor regions for interhemispheric communication is emphasized. Additionally, distinct connectivity profiles were detected for the anterior and posterior subdivisions of primary motor cortex. The present findings provide a comprehensive representation of transcallosal white matter projections in humans, and have the potential to inform the development of models and hypotheses relating structural and functional brain connectivity.

A Bias Compensated Cross-Relation approach to Thermocouple Characterisation

The measurement of fast changing temperature fluctuations is a challenging problem due to the inherent limited bandwidth of temperature sensors. This results in a measured signal that is a lagged and attenuated version of the input. Compensation can be performed provided an accurate, parameterised sensor model is available. However, to account for the in influence of the measurement environment and changing conditions such as gas velocity, the model must be estimated in-situ. The cross-relation method of blind deconvolution is one approach for in-situ characterisation of sensors. However, a drawback with the method is that it becomes positively biased and unstable at high noise levels. In this paper, the cross-relation method is cast in the discrete-time domain and a bias compensation approach is developed. It is shown that the proposed compensation scheme is robust and yields unbiased estimates with lower estimation variance than the uncompensated version. All results are verified using Monte-Carlo simulations.

A Bias Compensated Cross-Relation approach to Thermocouple Characterisation

The measurement of fast changing temperature fluctuations is a challenging problem due to the inherent limited bandwidth of temperature sensors. This results in a measured signal that is a lagged and attenuated version of the input. Compensation can be performed provided an accurate, parameterised sensor model is available. However, to account for the influence of the measurement environment and changing conditions such as gas velocity, the model must be estimated in-situ. The cross-relation method of blind deconvolution is one approach for in-situ characterisation of sensors. However, a drawback with the method is that it becomes positively biased and unstable at high noise levels. In this paper, the cross-relation method is cast in the discrete-time domain and a bias compensation approach is developed. It is shown that the proposed compensation scheme is robust and yields unbiased estimates with lower estimation variance than the uncompensated version. All results are verified using Monte-Carlo simulations.