Circumstellar emission in Be/X-ray binaries of the Magellanic Clouds and the Milky Way

Aims. We study the optical and near-infrared colour excesses produced by circumstellar emission in a sample of Be/X-ray binaries. Our main goals are exploring whether previously published relations, valid for isolated Be stars, are applicable to Be/X-ray binaries and computing the distance to these systems after correcting for the effects of the circumstellar contamination. Methods. Simultaneous UBVRI photometry and spectra in the 3500−7000 Å spectral range were obtained for 11 optical counterparts to Be/X-ray binaries in the LMC, 5 in the SMC and 12 in the Milky Way. As a measure of the amount of circumstellar emission we used the Hα equivalent width corrected for photospheric absorption. Results. We find a linear relationship between the strength of the Hα emission line and the component of E(B − V) originating from the circumstellar disk. This relationship is valid for stars with emission lines weaker than EW ≈ −15   Å. Beyond this point, the circumstellar contribution to E(B − V) saturates at a value ≈0.17   mag. A similar relationship is found for the (V − I) near infrared colour excess, albeit with a steeper slope and saturation level. The circumstellar excess in (B − V) is found to be about five times higher for Be/X-ray binaries than for isolated Be stars with the same equivalent width EW(Hα), implying significant differences in the physical properties of their circumstellar envelopes. The distance to Be/X-ray binaries (with non-shell Be star companions) can only be correctly estimated by taking into account the excess emission in the V band produced by free-free and free-bound transitions in the circumstellar envelope. We provide a simple method to determine the distances that includes this effect.

A new approach for semi-automatic rock mass joints recognition from 3D point clouds

Rock mass characterization requires a deep geometric understanding of the discontinuity sets affecting rock exposures. Recent advances in Light Detection and Ranging (LiDAR) instrumentation currently allow quick and accurate 3D data acquisition, yielding on the development of new methodologies for the automatic characterization of rock mass discontinuities. This paper presents a methodology for the identification and analysis of flat surfaces outcropping in a rocky slope using the 3D data obtained with LiDAR. This method identifies and defines the algebraic equations of the different planes of the rock slope surface by applying an analysis based on a neighbouring points coplanarity test, finding principal orientations by Kernel Density Estimation and identifying clusters by the Density-Based Scan Algorithm with Noise. Different sources of information —synthetic and 3D scanned data— were employed, performing a complete sensitivity analysis of the parameters in order to identify the optimal value of the variables of the proposed method. In addition, raw source files and obtained results are freely provided in order to allow to a more straightforward method comparison aiming to a more reproducible research.

A new survey of cool supergiants in the Magellanic Clouds

Aims. In this study we conduct a pilot program aimed at the red supergiant population of the Magellanic Clouds. We intend to extend the current known sample to the unexplored low end of the brightness distribution of these stars, building a more representative dataset with which to extrapolate their behaviour to other Galactic and extra-galactic environments. Methods. We select candidates using only near infrared photometry, and with medium resolution multi-object spectroscopy, we perform spectral classification and derive their line-of-sight velocities, confirming the nature of the candidates and their membership in the clouds. Results. Around two hundred new red supergiants have been detected, hinting at a yet to be observed large population. Using near- and mid-infrared photometry we study the brightness distribution of these stars, the onset of mass-loss, and the effect of dust in their atmospheres. Based on this sample, new a priori classification criteria are investigated, combining mid- and near-infrared photometry to improve the observational efficiency of similar programs to this.

Discontinuity spacing analysis in rock masses using 3D point clouds

The complete characterization of rock masses implies the acquisition of information of both, the materials which compose the rock mass and the discontinuities which divide the outcrop. Recent advances in the use of remote sensing techniques – such as Light Detection and Ranging (LiDAR) – allow the accurate and dense acquisition of 3D information that can be used for the characterization of discontinuities. This work presents a novel methodology which allows the calculation of the normal spacing of persistent and non-persistent discontinuity sets using 3D point cloud datasets considering the three dimensional relationships between clusters. This approach requires that the 3D dataset has been previously classified. This implies that discontinuity sets are previously extracted, every single point is labeled with its corresponding discontinuity set and every exposed planar surface is analytically calculated. Then, for each discontinuity set the method calculates the normal spacing between an exposed plane and its nearest one considering 3D space relationship. This link between planes is obtained calculating for every point its nearest point member of the same discontinuity set, which provides its nearest plane. This allows calculating the normal spacing for every plane. Finally, the normal spacing is calculated as the mean value of all the normal spacings for each discontinuity set. The methodology is validated through three cases of study using synthetic data and 3D laser scanning datasets. The first case illustrates the fundamentals and the performance of the proposed methodology. The second and the third cases of study correspond to two rock slopes for which datasets were acquired using a 3D laser scanner. The second case study has shown that results obtained from the traditional and the proposed approaches are reasonably similar. Nevertheless, a discrepancy between both approaches has been found when the exposed planes members of a discontinuity set were hard to identify and when the planes pairing was difficult to establish during the fieldwork campaign. The third case study also has evidenced that when the number of identified exposed planes is high, the calculated normal spacing using the proposed approach is minor than those using the traditional approach.

Datasets and results of the research [Discontinuity spacing analysis in rock masses using 3D point clouds]

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Characterization of rock slopes through slope mass rating using 3D point clouds

Rock mass classification systems are widely used tools for assessing the stability of rock slopes. Their calculation requires the prior quantification of several parameters during conventional fieldwork campaigns, such as the orientation of the discontinuity sets, the main properties of the existing discontinuities and the geo-mechanical characterization of the intact rock mass, which can be time-consuming and an often risky task. Conversely, the use of relatively new remote sensing data for modelling the rock mass surface by means of 3D point clouds is changing the current investigation strategies in different rock slope engineering applications. In this paper, the main practical issues affecting the application of Slope Mass Rating (SMR) for the characterization of rock slopes from 3D point clouds are reviewed, using three case studies from an end-user point of view. To this end, the SMR adjustment factors, which were calculated from different sources of information and processes, using the different softwares, are compared with those calculated using conventional fieldwork data. In the presented analysis, special attention is paid to the differences between the SMR indexes derived from the 3D point cloud and conventional field work approaches, the main factors that determine the quality of the data and some recognized practical issues. Finally, the reliability of Slope Mass Rating for the characterization of rocky slopes is highlighted.

A three-dimensional representation method for noisy point clouds based on growing self-organizing maps accelerated on GPUs

The research described in this thesis was motivated by the need of a robust model capable of representing 3D data obtained with 3D sensors, which are inherently noisy. In addition, time constraints have to be considered as these sensors are capable of providing a 3D data stream in real time. This thesis proposed the use of Self-Organizing Maps (SOMs) as a 3D representation model. In particular, we proposed the use of the Growing Neural Gas (GNG) network, which has been successfully used for clustering, pattern recognition and topology representation of multi-dimensional data. Until now, Self-Organizing Maps have been primarily computed offline and their application in 3D data has mainly focused on free noise models, without considering time constraints. It is proposed a hardware implementation leveraging the computing power of modern GPUs, which takes advantage of a new paradigm coined as General-Purpose Computing on Graphics Processing Units (GPGPU). The proposed methods were applied to different problem and applications in the area of computer vision such as the recognition and localization of objects, visual surveillance or 3D reconstruction.

A strongly magnetized pulsar within the grasp of the milky way’s supermassive black hole

The center of our Galaxy hosts a supermassive black hole, Sagittarius (Sgr) A∗. Young, massive stars within 0.5 pc of Sgr A∗ are evidence of an episode of intense star formation near the black hole a few million years ago, which might have left behind a young neutron star traveling deep into Sgr A∗’s gravitational potential. On 2013 April 25, a short X-ray burst was observed from the direction of the Galactic center. With a series of observations with the Chandra and the Swift satellites, we pinpoint the associated magnetar at an angular distance of 2.4±0.3 arcsec from Sgr A∗, and refine the source spin period and its derivative (P = 3.7635537(2) s and ˙ P = 6.61(4) × 10−12 s s−1), confirmed by quasi simultaneous radio observations performed with the Green Bank Telescope and Parkes Radio Telescope, which also constrain a dispersion measure of DM = 1750 ± 50 pc cm−3, the highest ever observed for a radio pulsar. We have found that this X-ray source is a young magnetar at ≈0.07–2 pc from Sgr A∗. Simulations of its possible motion around Sgr A∗ show that it is likely (∼90% probability) in a bound orbit around the black hole. The radiation front produced by the past activity from the magnetar passing through the molecular clouds surrounding the Galactic center region might be responsible for a large fraction of the light echoes observed in the Fe fluorescence features.

An obscured cluster associated with the H II region RCW173

Context. The discovery of several clusters of red supergiants towards l = 24°−30° has triggered interest in this area of the Galactic plane, where lines of sight are very complex and previous explorations of the stellar content were very preliminary. Aims. We attempt to characterise the stellar population associated with the H ii region RCW 173 (=Sh2-60), located at, as previous studies have suggested that this population could be beyond the Sagittarius arm. Methods. We obtained UBV photometry of a stellar field to the south of the brightest part of RCW 173, as well as spectroscopy of about twenty stars in the area. We combined our new data with archival 2MASS near-infrared photometry and Spitzer/GLIMPSE imaging and photometry, to achieve a more accurate characterisation of the stellar sources and the associated cloud. Results. We find a significant population of early-type stars located at d = 3.0 kpc, in good agreement with the “near” dynamical distance to the H ii region. This population should be located at the near intersection of the Scutum-Crux arm. A luminous O7 II star is likely to be the main source of ionisation. Many stars are concentrated around the bright nebulosity, where GLIMPSE images in the mid infrared show the presence of a bubble of excited material surrounding a cavity that coincides spatially with a number of B0-1 V stars. We interpret this as an emerging cluster, perhaps triggered by the nearby O7 II star. We also find a number of B-type giants. Some of them are located at approximately the same distance, and may be part of an older population in the same area, characterised by much lower reddening. A few have shorter distance moduli and are likely to be located in the Sagittarius arm. Conclusions. The line of sight in this direction is very complex. Optically visible tracers delineate two spiral arms, but seem to be absent beyond d ≈ 3 kpc. Several H ii regions in this area suggest that the Scutum-Crux arm contains thick clouds actively forming stars. All these populations are projected on top of the major stellar complex signposted by the clusters of red supergiants.

Portable 3D laser-camera calibration system with color fusion for SLAM

Nowadays, the use of RGB-D sensors have focused a lot of research in computer vision and robotics. These kinds of sensors, like Kinect, allow to obtain 3D data together with color information. However, their working range is limited to less than 10 meters, making them useless in some robotics applications, like outdoor mapping. In these environments, 3D lasers, working in ranges of 20-80 meters, are better. But 3D lasers do not usually provide color information. A simple 2D camera can be used to provide color information to the point cloud, but a calibration process between camera and laser must be done. In this paper we present a portable calibration system to calibrate any traditional camera with a 3D laser in order to assign color information to the 3D points obtained. Thus, we can use laser precision and simultaneously make use of color information. Unlike other techniques that make use of a three-dimensional body of known dimensions in the calibration process, this system is highly portable because it makes use of small catadioptrics that can be placed in a simple manner in the environment. We use our calibration system in a 3D mapping system, including Simultaneous Location and Mapping (SLAM), in order to get a 3D colored map which can be used in different tasks. We show that an additional problem arises: 2D cameras information is different when lighting conditions change. So when we merge 3D point clouds from two different views, several points in a given neighborhood could have different color information. A new method for color fusion is presented, obtaining correct colored maps. The system will be tested by applying it to 3D reconstruction.

Portable 3D laser-camera calibration system with color fusion for SLAM

Paper submitted to the 43rd International Symposium on Robotics (ISR2012), Taipei, Taiwan, Aug. 29-31, 2012.

3D visual sensing of human hand for remote operation of a robotic hand

New low cost sensors and open free libraries for 3D image processing are making important advances in robot vision applications possible, such as three-dimensional object recognition, semantic mapping, navigation and localization of robots, human detection and/or gesture recognition for human-machine interaction. In this paper, a novel method for recognizing and tracking the fingers of a human hand is presented. This method is based on point clouds from range images captured by a RGBD sensor. It works in real time and it does not require visual marks, camera calibration or previous knowledge of the environment. Moreover, it works successfully even when multiple objects appear in the scene or when the ambient light is changed. Furthermore, this method was designed to develop a human interface to control domestic or industrial devices, remotely. In this paper, the method was tested by operating a robotic hand. Firstly, the human hand was recognized and the fingers were detected. Secondly, the movement of the fingers was analysed and mapped to be imitated by a robotic hand.

RGBD Human-Hand recognition for the Interaction with Robot-Hand

New low cost sensors and the new open free libraries for 3D image processing are permitting to achieve important advances for robot vision applications such as tridimensional object recognition, semantic mapping, navigation and localization of robots, human detection and/or gesture recognition for human-machine interaction. In this paper, a method to recognize the human hand and to track the fingers is proposed. This new method is based on point clouds from range images, RGBD. It does not require visual marks, camera calibration, environment knowledge and complex expensive acquisition systems. Furthermore, this method has been implemented to create a human interface in order to move a robot hand. The human hand is recognized and the movement of the fingers is analyzed. Afterwards, it is imitated from a Barret hand, using communication events programmed from ROS.

Three-dimensional planar model estimation using multi-constraint knowledge based on k-means and RANSAC

Plane model extraction from three-dimensional point clouds is a necessary step in many different applications such as planar object reconstruction, indoor mapping and indoor localization. Different RANdom SAmple Consensus (RANSAC)-based methods have been proposed for this purpose in recent years. In this study, we propose a novel method-based on RANSAC called Multiplane Model Estimation, which can estimate multiple plane models simultaneously from a noisy point cloud using the knowledge extracted from a scene (or an object) in order to reconstruct it accurately. This method comprises two steps: first, it clusters the data into planar faces that preserve some constraints defined by knowledge related to the object (e.g., the angles between faces); and second, the models of the planes are estimated based on these data using a novel multi-constraint RANSAC. We performed experiments in the clustering and RANSAC stages, which showed that the proposed method performed better than state-of-the-art methods.

Magnetars: Properties, Origin and Evolution

Magnetars are neutron stars in which a strong magnetic field is the main energy source. About two dozens of magnetars, plus several candidates, are currently known in our Galaxy and in the Magellanic Clouds. They appear as highly variable X-ray sources and, in some cases, also as radio and/or optical pulsars. Their spin periods (2–12 s) and spin-down rates (∼10−13–10−10 s s−1) indicate external dipole fields of ∼1013−15 G, and there is evidence that even stronger magnetic fields are present inside the star and in non-dipolar magnetospheric components. Here we review the observed properties of the persistent emission from magnetars, discuss the main models proposed to explain the origin of their magnetic field and present recent developments in the study of their evolution and connection with other classes of neutron stars.