Instrumentation for a harsh environment 

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Modelling the exosphere of Mercury: a brief history

Due to the difficulty in observing Mercury, modelling has become a major tool in the understanding of the Hermean exosphere. Since Mercury, unlike most other rocky planets in the solar system, has a clearly identified surface-bounded exosphere with multiple sources and sinks with its space environment, exospheric modelling is also a clue to the surface composition, see Figure 2.21. For example, local surface inhomogeneities are expected to directly influence the exospheric composition (Leblanc et al., 2007).
Three classes of exospheric models have been used over the past decades:
• Chamberlain analytical models: first developed for Earth’s exosphere by Chamberlain (1963), these analytical models assume gravity as the only force and a strict separation between collisional and collisionless regions.
• Boltzmann transport: these models are particularly indicated to simulate the hot component and transition regions in one dimension (1D) by solving the Boltzmann transport kinetic equation and taking into account the chemical and physical reactions at work (Nagy and Banks, 1970; Nagy et al., 1990).
• Monte Carlo simulations: they are by essence stochastic and usually used for large 3D simulations. They are equivalent to the Boltzmann approach and often deal with multiple species (Chamberlain and Campbell, 1967; Barakat and Lemaire, 1990). They also take advantage of the intrinsic nature of gas interaction and the increasing computer power available. These models have also been applied to other planets such as Mars (Nagy et al., 1981; Fox, 1993; Kim et al. 1998; Chaufray et al. 2007; Cipriani et al. 2007), Venus (Kumar et al., 1978; Bishop, 1989), Titan (Michael and Johnson, 2005), Europa (Leblanc and Johnson, 2003; Schematovich et al., 2005) and the Moon (Hodges, 1973; see Stern, 1999). Predictions derived from these models, such as the abundance of specific atoms or molecules, have been confirmed or infirmed by remote sensing measurements, showing the magnetosphere. Sources, sinks and interaction with the magnetic field are displayed schematically (Image Domingue et al. (2007)). efficient and necessary synergy between observations and modelling. The main advantages of a simulation are:
• provide spatial distributions of the species.
• separate temporal from spatial variations.
• identify physical processes responsible for the dynamic creation of a given species.

SPICAV UV spectrometer on the Venus Express mission to Venus

As a follow-up spectrometer to SPICAM, SPICAV is the acronym for ’Spectroscopy for the Investigation of the Characteristics of the Atmosphere of Venus’ (Bertaux et al., 2007). It consists of three spectrometers on board the Venus Express mission, working in the UV and IR ranges. With a total mass of 13.9 kg its scientific objective is the study of the atmosphere of Venus from the surface to the exosphere.
In addition to the original design taken from SPICAM (Service d’A´eronomie, France), a high-resolution IR spectrometer called SOIR (Solar Occultation in the InfraRed), made in Belgium at BIRA-IASB, has been included. The UV spectrometer channel (118 − 320 nm, resolution 1.5 nm) is identical to that of SPICAM. A summary of the characteristics of the SPICAV UV spectrometer with respect to SPICAM and PHEBUS is given in Table 3.1.

PHEBUS UV spectrometer on the BepiColombo mission to Mercury

The double spectrometer PHEBUS, see Figure 3.4 covers the range of Extreme Ultraviolet (55 − 155 nm) and Far Ultraviolet (145 − 315 nm). Focusing on the characterisation, composition, dynamics and surface-exosphere coupling of Mercury, PHEBUS addresses the following main scientific objectives: determination of the composition and the vertical structure of the exosphere, determination of the exospheric dynamics: day to night circulation, active to inactive regional transport, study of surface release processes, identification and characterisation of the sources of exospheric constituents, detection and evaluation of the ionosphere and its relation with the neutral atmosphere, space and time monitoring of exosphere/magnetosphere exchange and transport processes, study and quantification of escape, global scale source/sink balance and geochemical cycles synergistically with other experiments of BepiColombo (MSASI, MPPE on MMO and MIXS, SERENA on MPO).

SPICAM and SPICAV datasets

The data derived from the UV channels from both SPICAM and SPICAV consists of several observing modes with different objectives such as in Nadir, Star or Limb mode.
• In Nadir mode the line of sight is pointed directly to the planet, to analyse the solar radiation that has been filtered through the atmosphere and then reflected on the surface of the planet. These kinds of observations allow the measurement of total column abundance of atmospheric components.
• In Star or Sun mode, the instrument points tangentially through the atmosphere toward a star, or the Sun, which is observed through the atmosphere as it rises or sets. The instrument then analyses the light filtered by the atmosphere allowing derivation of vertical concentration profiles for atmospheric components. This is the mode used for occultation observations.
• Limb mode where the instrument points across the atmosphere to analyse the atmospheric glow just as in Star mode, but without a target star.

Observation of intensity decrease in high wavelengths

A common feature of instruments in space is that the detector undergoes a steady deterioration that decreases the sensitivity of the instrument. The main cause of this is the usage, the aging and the conditions in space. The instruments are constantly surrounded by radiation, the extremely low temperature in space and the atmospheric conditions around the planet or object it is observing. All of these features can have an impact on the instruments and since they are all of natural occurrence they are practically impossible to completely remove, but they can be anticipated and calculated for to a certain degree.
To envisage what could affect an instrument, knowledge on the conditions in space and the reactions of metals and electronics are crucial. Also earlier information collected from instruments already in space can give information on these reactions. It is very important to check for these occurrences since they can affect the entire calibration procedure and all other observations. One way to see if there are any changes in the detector is simply by calculating the ratio of all the observation spectra for one star and plot them in the same graph. This is done by taking one mean spectrum (any spectrum) from one observation and divide all the other mean spectra from the other observations by this reference spectra. This will yield a straight line with different height (on the y-axis) depending on the gain setting of the instrument at the time of observation, see (1) in Figure 3.18. If the spectra have all been taken in similar conditions, similar settings and of the same object they should normally show very little differences and thus give a straight line without any systematic errors. But sometimes the line can show as a leaning or other instabilities such as can be seen in Figure 3.18.
A version of this ratio can be found if the same reference spectrum is plotted straight away against the rest of spectra. This yields a leaning line with different angles from the x-axis depending on the gain setting for the instrument, just as can be seen in (2) in Figure 3.18. The two versions of these ratios were calculated for an example star from the SPICAV catalogue, HR0472 and the result can be seen in Figure 3.19, 3.20, 3.21 and 3.22.
The most striking feature in these plots is the obvious lean of all the ratio curves in Figure 3.19. The ratio was calculated using the earliest spectrum taken, with this star as object, as reference spectrum. All other spectra were observed between the 17 January 2008 and 12 September 2008 and are thus much younger than the reference spectrum.
One can easily see that the ratio gets higher and higher in the low wavelengths, and even more so for the spectra which has the highest gain settings.
The same data with the same reference spectrum is also plotted in Figure 3.21. The plot is showing lots of stray pixels and the lines are not sharp but blurry and show a slight falling of in the top and the bottom.
Figure 3.20 shows something different. Here the reference spectrum was picked to be much younger, from 17 January 2008, and the rest of the spectra are the same as earlier. Here all the lines are fairly straight and very little leaning is showing. The same trend is shown in Figure 3.22 where all the lines are very sharp and straight.The conclusion from these four figures can be interpreted as that these spectra ratios  display a decrease in sensitivity in lower wavelengths which becomes even worse with
higher gain.

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Radiometric Modelling and Scientific Perfor- mance of PHEBUS

The goal of any radiometric model is to simulate the foreseen observations as realistic as possible through a photometric model of the instrument. This is done by firstly making a photometric flux assessment of the instrument by modelling the flux of photons received by the detector. Knowing the intensities of the lines of the different species to be measured, a complete calculation of the path and transmission of photons along the full optical chain allows an estimation of the instrument’s theoretic spectral resolution and detection cabilities.
This computation combines the instruments geometric characteristics and the efficiency of the components used.
The PHEBUS radiometric model, developped by N. Rouanet, uses a combination of a raytracing software and a numerical computing software which produces a matrix representing the image recorded by the detector. A binned spectrum profile can then be calculated by summing along the spatial axis of the detector (PHEB-SC).
The radiometric model of the PHEBUS instrument has the following main objectives, which are vital for the development of the instrument:
• to calculate the instrumental response in terms of counts per second per Rayleigh of emission.
• to simulate observations of exospheric spectra and produce detector matrix images as result of this.
• to anticipate real in-flight observations in order to plan efficient observation sequences.
• to validate the scientific objectives and to prove that PHEBUS will meet the scientific requirements.
• to provide help for technological choices in the instrument for example in the choosing of the coating for the EUV photocathode and the slit width.
As always with these kinds of models it has some limits. There are large uncertainties about the expected emission lines used as reference1, because the abundance of the exospheric species to be measured are not well known and are expected to be extremely variable from time to time and from place to place. There are also some uncertainties about the efficiencies of the optical components of the instrument itself2. The straylight and noise are not well known in advance, because they are quite dependent on the details of the assembly of the final instrument and scattering by the gratings has similarly not yet been implemented. However refinement can be done with effective measurements on real optical components and with the in-flight calibrations (Chassefi`ere et al. 2010).
This chapter has been divided into two parts. The first part describes the theoretical background, scientific demands and technical details of the development of any radiometric model. The second part shows the result of the developped radiometric model applied to the instrument PHEBUS for different species and star spectra.

In-flight calibrations of stars

Regular calibration of the spectral response of detectors and optics, and its time evolution, by using stars and interplanetary medium, needs to be performed during flight. It is only the stellar calibration that will allow tracking the degradation of the channels as a function of wavelength and time. A few interplanetary lines will also be available to follow the variation of the detectors (HI Ly-α at 121.6 nm first and second order, HI Ly-α at 102.5 nm, and He resonance line at 58.4 nm).
Cruise observations will be very important to establish the absolute calibration of the instrument and make comparisons with other measurements (at Earth and Venus also). Since the number of bright hot stars is limited (about 10 to 20 according to the actual sensitivity of the instrument), a request will be put forward on off-pointing6 of the spacecraft during the ”autumn” and ”spring” seasons of the orbit to be able to point the line of sight of the instrument toward the desired stars.

Table of contents :

1 Introduction 
1.0.1 Layout of thesis
2 Mercury: History and context 
2.1 The Planet Mercury
2.1.1 Orbital parameters
2.1.2 Internal structure, the magnetic field and magnetosphere
2.1.3 Surface
2.1.4 Exosphere
2.2 History and science: Ancient
2.3 Science: In modern times
2.3.1 Early Optical observations
2.3.2 Modern ground-based observations
2.3.3 Missions
2.3.4 Modelling the exosphere of Mercury: a brief history
2.4 Summary
3 SPICAV: Differentiate ultraviolet signatures 
3.1 Stellar occultations and calibrations of the SPICAM and SPICAV instruments
3.2 The UV spectrometers on board the Mars Express and the Venus Express missions
3.2.1 General overview of the instruments
3.2.2 SPICAM and SPICAV datasets
3.3 Star calibration
3.3.1 Theoretical background
3.3.2 Observation of intensity decrease in high wavelengths
3.4 Summary
4 PHEBUS: Instrumentation for a harsh environment 
4.1 Radiometric Modelling and Scientific Performance of PHEBUS
4.2 Theoretical background
4.2.1 Instrument
4.2.2 Objectives and demands on the instrument
4.2.3 Sources
4.2.4 Optical layout
4.2.5 Photometric assessment and spectral resolution
4.3 Theoretical Results
4.3.1 Radiometric modelling of star spectra
4.3.2 In-flight calibrations of stars
4.4 Summary
5 Modelling Mercury’s hydrogen exosphere 
5.1 Introduction
5.2 SECTION I: The physics behind
5.2.1 Definitions and basic exospheric theory
5.2.2 Mechanisms of ejection from the surface: Maxwell-Boltzmann distributions
5.2.3 Temperature mapping
5.2.4 Ballistic motion of particles in the exosphere and external conditions
5.2.5 Sources of hydrogen at Mercury: Thermal processes
5.2.6 Sinks of hydrogen at Mercury: Ionisation
5.2.7 Deriving emission line brightness: radiative transfer and optical thickness (with Jean-Yves Chaufray)
5.3 SECTION II: Monte Carlo model
5.3.1 Coordinate system
5.3.2 Flow of program
5.3.3 Time evolution of the particle
5.3.4 Euler solution to ballistic motion
5.3.5 Outputs
5.4 Validation
5.4.1 Convergence criteria
5.4.2 Chamberlain
5.4.3 Thermalisation at surface
5.5 Sensitivity study
5.5.1 MB and MBF Velocity distribution functions
5.5.2 Accommodation coefficient
5.5.3 Source regions
5.5.4 Comparison to Mariner 10 data
5.5.5 Prediction of expected PHEBUS signal
5.6 Summary
6 Conclusion 
Appendices
A SPICAM star table of 39 stars with flux above 800 R at 164 nm 
B PHEBUS radiometric simulation brightness of emission lines 
C SPICAV star table of 183 stars with flux above 60 R at 164 nm 
D Short-term variations of Mercury’s sodium Na exosphere observed with very high spectral resolution 
Bibliography

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