Today's Gaia blog post is contributed by Paolo Tanga, Associate Astronomer at the Observatoire de la Côte d’Azur, Nice (France).
We tend to think that a still picture, shot with an ordinary camera, represents a subject at a given time. But this is not always the case. In some situations, a picture can show the evolution in time of the depicted subject. This is the case, for example, of the well-known “photo finish” technique widely used in athletics to record the competing athletes as they cross the arrival line at the end of the race.
How does it work? Simply, the camera aims only at a vertical strip containing the finish line and repeatedly photographs it at high speed. By putting all the strips together side-by-side, one can obtain the evolution of the image of the finish line as a function of time. As weird as it may sound, the CCD camera onboard Gaia works exactly the same way – by transforming the recorded star positions into times, the finish line being a thin strip of pixels on the edge of the detector.
Let’s imagine that we are looking at a number of athletes all running at the same speed on a straight track, but each of them having started the race at a different time: in this analogy, these are the stars, which drift across the Gaia telescopes all at the same velocity – given by the constant rotation of the satellite. If Gaia observes them several times, they will always appear spaced by the same delays.
Now, let’s add to these well-behaved competitors a different type of athlete, a rebel one who's not playing by the rules, always running either much faster or much slower than the others, and not following the direction of the track lanes but drifting as he/she pleases. Each time this eccentric athlete crosses the finish line, it will be in a different position relative to the competing runners. This is how an asteroid appears to Gaia, as its motion relative to stars makes it appear always in a different position, as a function of the time at which it is observed.
This unorthodox behaviour opens up a specific category of problems when dealing with asteroid observations. The first one is predicting when – and where – Gaia will observe a given object. In practice, it’s like predicting in advance the delays of the eccentric athlete relative to the others, when on the finish line. To perform this computation, we need to have an exact knowledge of its trajectory (the orbit of the asteroid), along with the precise speed of the “ordinary” competitors (the stars). In the case of Gaia, all these pieces of information are known, but the complexity of the scanning law, which displaces the “arrival line” in non-trivial patterns, makes the task extremely delicate. Besides, there are several “finish lines” on the Gaia focal plane (at least one per CCD), so the whole geometry of the system plays a role.
The second type of problem concerns the processing of asteroid observations, especially in the case of newly detected asteroids or of asteroids whose orbit is not yet known to great precision. In fact, each time the asteroid crosses the “finish line” it will be in a different region of the sky. Only observations that are close in time can be easily linked together, as the asteroid displacement relative to its background will be small. If the observations are performed over longer time spans, the presence of several such “rebel runners” can make things extremely complex.
These various aspects are illustrated in the following pictures. The first one (right) is a test image of the asteroid (54) Alexandra, a bright moving target. It was obtained by programming Gaia in a special imaging mode. As described before, this is a “photo finish” image. It was reconstructed by moving along the horizontal axis, which is equivalent to the observer moving in time: each pixel column represents the signal present on the “finish line” (in practice: the edge of the CCD) at a given moment. In the image, the time delay between the arrival at the finish line of the bright star and the asteroid is about 1.26 seconds. A very accurate timing of each source “arrival” is the basis of the extraordinary astrometric capabilities of Gaia.
More important, however, is the fact that in this image the predicted position of the asteroid is very close to the observed one, only a few pixels away. Given the computational difficulties involved in this process, this is an achievement with important consequences, such as the possibility to predict well enough very close “encounters” between a star and an asteroid on the plane of the sky – these are potential sources of confusion while searching for other types of anomalies (when monitoring the brightness of a star, for example). Many astronomers want to be alerted when an interesting change occurs, not when an asteroid is just passing by!
On the other hand, other astronomers (planetary scientists!) are interested in the asteroids themselves. In fact, Gaia will observe 350,000 asteroids, providing the richest sample of precise orbits and physical properties that we could dream of. Those rebel runners, containing clues about the Solar System's formation, are really interesting, and come in large quantities. Our capability to track their position is essential in the identification process.
The case of the asteroid (4997) Ksana (above) is more difficult, and showcases the capabilities of Gaia in detecting and identifying asteroids. Because it is very faint, it may have been confused with several stars – some not even present in current catalogues – making its identification more ambiguous. The presence of a source very close to the position where the asteroid was predicted to be is very encouraging, but only a comparison of data acquired over time can provide a confirmation.
The result is shown in (left), which represents an intermediate product of the processing itself: the preliminary positions of the sources seen by Gaia, as determined by the “Initial Data Treatment”. In these images, each point is a source and the point size is proportional to the source's brightness. Different colours represent the stars observed during five different sweeps of the same sky region, each lasting 6 seconds, by a single CCD.
The asteroid (4997) Ksana is now clearly seen moving from one sweep to the next (as indicated by the arrows). Checking the presence and motion of the object at the corresponding epoch provides a secure confirmation of its nature. A final remark: the observations are not equally spaced in time, and the closer couple of detections correspond to the source passing through the two telescopes (106 minutes apart) while the satellite rotates. A full rotation of the satellite (every 6 hours) separates the two detections in each pair.
Gaia asteroid observations will be processed using the software pipeline designed and implemented by Coordination Unit 4 of the DPAC, running at the CNES processing centre (Toulouse, France).
The data presented here are extracted from the results obtained by the Initial Data Treatment (IDT) pipeline, which was largely developed at the University of Barcelona and runs at the Data Processing Centre at ESAC.
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The discovery of thousands of star systems wildly different from our own has demolished ideas about how planets form. Astronomers are searching for a whole new theory.
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Guest blog post by George Seabroke, RVS Payload Expert, on behalf of the team commissioning the RVS instrument.
The Radial Velocity Spectrometer (RVS) is one of three instruments onboard Gaia (see Figure 1). It is designed to measure the line-of-sight velocity component of Gaia stars (radial velocity, RV) to complement Gaia astrometry, which measures the transverse velocity component (parallax converts proper motions to transverse velocity). Combining the radial and transverse velocities gives the 3D space velocity of Gaia stars, allowing Gaia to produce not only a map of where Gaia stars are but how they are moving.
Figure 1: Photographs of RVS components (insets) overlaid on a photograph of the Gaia Payload Module at Astrium in Toulouse. Credits: Astrium, except top left (ESA/Gaia/DPAC/Airbus DS), bottom left (ESA) and top right (Selex Galileo, Italy). Composite designed by George Seabroke, MSSL.
The accuracy that Gaia astrometry is aiming for can only be achieved above the Earth’s atmosphere. The RV accuracy that RVS is aiming for (a few km/s for bright stars) can be achieved from the ground: however, the ground-based RV follow-up of the 118,200 Hipparcos stars managed about 20,000 stars in 15 years (a remarkable effort at the time!). Therefore it was decided to include an RV instrument onboard Gaia from the beginning and thus RVS was born.
RVS is an optical module located between the last mirror (M6) and the 12 RVS CCDs at the right edge of the Gaia focal plane (see Figure 1). RVS consists of six optical elements: a transmission grating (see bottom left in Figure 1), which disperses all the light entering RVS into medium-resolution (λ/Δλ ~ 11,500) spectra; a band-pass filter, which limits the spectra to 845–872 nm (wavelengths visible to the human eye are 400-700 nm); and four lenses/prisms (see top right in Figure 1) to correct the main aberrations of the telescope.
The RVS wavelength range is chosen to include a set of three absorption lines called the calcium triplet (see top left in Figure 1; click here for enlarged version of the spectra). Calcium is made by nuclear fusion in the centre of massive stars. When they explode as supernovae, the calcium can end up in the atmospheres of the next generation of stars (or in our teeth and bones!). If the star is moving away or towards Gaia, the calcium triplet (and all spectral) lines will be shifted by the Doppler effect, compared to their rest wavelengths. The RV of each star can be determined from RVS spectra by measuring these shifts.
The RVS Payload Experts (PEs) are the team, in DPAC, supporting the commissioning of the RVS instrument. The team, geographical locations and responsibilities are mainly split between Observatoire Paris Meudon (OPM) and Mullard Space Science Laboratory (MSSL, part of University College London).
Unfortunately, at least from my personal perspective, we are PEs, rather than Payload Specialists. Payload Specialists were astronauts who flew on the Shuttle with specific payloads. Even if we wanted to visit Gaia, we would not be able to because at the second Sun–Earth Lagrangian point (L2), Gaia is much further than any astronaut has ever been, over 1 million km beyond the Moon’s orbit! Having not been selected to become an ESA astronaut in 2009 (one of my competitors, Alexander Gerst, is on the International Space Station right now!), working on commissioning the RVS is probably the closest I have come to being in space!
One recent commissioning activity that I led was when the RVS CCDs had charge injected into them to check for and calibrate any radiation damage.
The most critical issue for the RVS PEs was to check that the six optical elements of RVS are producing spectra that include the calcium triplet absorption lines, allowing us to derive RVs. If we had not seen the calcium lines, we would have had a bone to pick with RVS (English idiom!). Figure 2 shows what a 2D RVS spectrum looks like on a RVS CCD. RVS spectra are summed in the ACross Scan (AC) direction (y-axis in Figure 2) to produce 1D spectra, like the one in the top left inset of Figure 1 (see blog article “Gaia takes science measurements” for more details on this RVS spectrum – the first to go public). The calcium lines are clearly visible (so ironically no bone to pick!).
Figure 2: Example of a 2D RVS spectrum, extracted by Pasquale Panuzzo (OPM). The three dark vertical lines are where calcium atoms in the atmosphere of this particular star have blocked starlight to form absorption lines in this star’s spectrum.
The biggest surprise for the RVS PEs was finding there was a scattered light problem. The Basic Angle Monitor (BAM) has a laser at the same wavelength as RVS so there was a commissioning activity in January to check the levels of the BAM laser light leaking into RVS. Because of this, we were the first to measure the Gaia instrument background and found it to be much higher than expected from the BAM laser alone. Since then, Gaia’s instrument background has become a hot topic in commissioning and astrometric and photometric PEs have found that their instrument backgrounds are also affected. Various experiments have been conducted to understand the source of the scattered light and the Gaia PEs have been analysing the results of these experiments and feeding the results back to ESA.
OPM have developed most of the RVS offline tools. This involves downloading about 31 Gb of data per day (the total is now 7 Tb), ingesting it into local databases and generating daily “First Look” reports to allow the RVS PEs to have a first look at the data. The offline tools have been used in three other very important ways. Firstly they were used to analyse quickly the RVS spectra during the best focus commissioning activity, which were independently verified by MSSL. RVS spectra do have the required sharp absorption lines, including the calcium lines, which reduce the uncertainty on RV measurements. These spectra were also used by OPM to derive the RVS resolution. In addition, OPM are verifying and optimizing the onboard Video Processing Unit parameters, which control how well the readout windows are centred around RVS spectra to make sure we capture as much dispersed starlight as possible.
MSSL has developed a local infrastructure and integrated the official on-ground RVS data processing pipeline, which includes modules by all of Co-ordination Unit 6 (“Spectroscopic Processing”). MSSL are now running it to investigate the RVS data. The pipeline consists of more than 60,000 lines of code, described in over 800 pages of documentation (Software Design Descriptions). It has involved a lot of debugging of software to ensure the pipeline can process real RVS spectra. The commissioning period included 14 days of undisturbed data obtained between 9 and 23 May. The challenge now for MSSL, having ingested all these spectra (more than 111 million!) into our databases, is to process them through the RVS pipeline to estimate how accurate the RVS RVs will be (as a function of stellar brightness). RVS was never designed to measure the RVs of all Gaia’s 1 billion stars. We will soon know the number of stars for which RVS will be able to measure an RV and what the RV accuracy will be. Whatever the answer, it should be tens of millions, making RVS the largest RV survey in history!
I was fortunate enough to be in French Guiana to see the Gaia launch but like all the RVS PEs, we have never actually seen the completed RVS instrument with our own eyes! Now we will never see it, as Gaia will not return to Earth. Nevertheless, we have been getting to know RVS in the last six months of commissioning through the data it is returning. Over the next five years (or more) of the mission, we will get to know the instrument in ever-greater detail. This will allow us continually to optimize its operation onboard Gaia and also the on-ground algorithms that process the data, ensuring RVS reaches its enormous scientific potential.
Written by George Seabroke (MSSL) on behalf of the RVS PEs: Kevin Benson (MSSL), Mark Cropper (MSSL), Chris Dolding (MSSL), Joris Gerssen (Potsdam), Alain Guéguen (OPM), Leanne Guy (Geneva), Howard Huckle (MSSL), Katja Janssen (Potsdam), David Katz (OPM), Olivier Marchal (OPM), Pasquale Panuzzo (OPM, RVS PE Co-ordinator), Paola Sartoretti (OPM), Mike Smith (MSSL).