Stars interact with the surrounding interstellar medium (ISM), both through their ionizing radiation and through the mass, momentum, and energy that is transferred by way of their winds. The extreme ultraviolet radiation from hot stars leads to ionized nebulae or H II regions around young stars. In the case of low mass stars about to become white dwarfs, the radiation leads to the ionization of planetary nebulae.

The mass loss in stellar winds leads to a recycling of matter back to the interstellar medium, and because of the nuclear processing that occurs in the interiors of stars, the matter which is returned is often chemically enriched. In the cases of late type giants and carbon rich Wolf-Rayet stars, dust grains are produced in the winds, so the outflows may carry grain enriched material into the interstellar medium. These grains could play a role in the next generation of star formation. There are also dynamical effects associated with wind-interstellar medium interactions. The collisions of the winds with their surroundings produce ‘wind bubbles’, and the momentum transfer helps to maintain the random velocities of interstellar clouds that otherwise would be damped out by the dissipative effects of cloud collisions.

The winds of ‘massive stars’ tend to have the greatest effect on the ISM, because their mass loss rates are large, and the massive stars that are hot also have winds that are very fast and carry large momentum fluxes.

Introduction: outline of the chapter

In this chapter, the design of LGS AO is treated, with special emphasis on analysis tools required for predicting the expected performance of laser beacon adaptive optics on astronomical telescopes. Analytical expressions are given for estimating the most important error sources encountered in LGS AO operation. Numerical examples are given to illustrate the relative importance of various errors, and to aid in the choice of design parameters.

There have been several treatments of LGS error budget analyses (for example: Gardner et al. 1990; Kibblewhite 1992; Gavel et al. 1994; Parenti and Sasiela 1994; Olivier and Gavel 1994) each emphasizing different aspects of LGS AO, and using a wide assortment of approximations. While the tools discussed in this chapter have general applicability to LGS AO, the treatment (which parallels and extends that of Sandler et al. 1994a) is aimed at diffraction-limited imaging on astronomical telescopes, with the goal of optimizing performance for near-infrared imaging and spectroscopy for the new large telescopes, as discussed in Chapter 11. Examples are often chosen which are relevant to this problem.

We begin in Section 12.2 by decomposing the AO system error into image motion, or tilt errors and higher order wave-front errors. In the regime of diffraction-limited correction, the tilt and high order wave front errors can be treated independently, with corresponding Strehl ratios Sθ and Sφ, respectively.

In the last chapter we have seen that if a star has an open magnetic field in the equatorial region and is also rapidly rotating, a very strong stellar wind can be produced. In this chapter we consider the effects of the magnetic field in absence of rotation. If oscillations are induced in the field at the base of the wind, transverse ‘Alfvén’ waves will be generated. The dissipation of energy and momentum associated with the wave propagation can lead to the acceleration of the outer atmosphere in the form of an ‘Alfvén wave driven wind’. Open field regions can arise in a variety of configurations, depending on the circulation currents or dynamo properties of the interior of the star. Furthermore, the strength and geometry of the magnetic field can vary significantly from one location on the star to another, and the wind flow tubes will vary accordingly.

In the absence of a magnetic field, a star that has a spherically symmetric hot corona will produce a steady, radial, structureless wind, driven by the thermal gas pressure gradients in the corona (Parker, 1958), as discussed in Chapter 5. Within a few years after the solar wind was predicted by Parker, interplanetary space probes proved that indeed there is a wind from the sun that occurs at all times. However, the wind was found to be far from steady and structureless. To understand the spatial and temporal variability of the wind, Parker (1965) considered outflow in open magnetic field structures.

In this chapter we present astronomical observations obtained, at unprecedented high resolution, with the first adaptive optics systems installed on large telescopes and producing images of scientific value on a regular basis. These images cover many of the objects of interest to astronomers, from planets to quasars, and involve a number of approaches: straight imaging, spectroimaging, polaro-imaging, coronography, all being done in wide or narrow fields. These results have been obtained less than seven years after the very first astronomical AO image was taken in 1989, we hope they will convince the reader of the great future adaptive optics should have in astronomy.

Scientific programs with adaptive optics

Astronomers rightly insist upon covering various spectral ranges with similar performance in terms of sensitivity and angular resolution. On Fig. 15.1 the performance of AO is compared with that of existing or planned space-borne telescopes and ground-based telescope arrays from near ultraviolet to millimetric wavelengths. It is worth nothing the interesting match between the Hubble Space Telescope (HST) diffraction limit and the current AO systems on large telescopes, as will be demonstrated in several examples in this chapter. It is also apparent that AO observations provide the intermediate and necessary step between seeing limited images and multi-telescope interferometric observations. Optical interferometers provide the next step in improved angular resolution by one to two orders of magnitude, but require ‘identification maps’ of intermediate resolution, that AO observations can produce.

Covering all the aspects of adaptive optics (AO) in astronomy is a challenging task. Inevitably there have been omissions as well as redundancies. Moreover, the field is still rapidly evolving. Techniques which have been described in detail may become obsolete, whereas others barely mentioned in this book, may gain importance. Nevertheless, we hope this book will be found useful by both engineers who need to build AO systems for astronomy, and astronomers who want to observe with them.

A highly debated topic is the use of laser guide sources (LGS) instead of natural guide sources (NGS). We use here the word ‘sources’ rather than the more widely used word ‘stars’, because not only LGS, but also many NGS are not stars. In view of recent developments, it seems fair to say that the use of NGS has given better results than many people anticipated. Most of the astronomical results published to date have been obtained with NGS systems, and as seen in Fig. 15.2, the number of publications obtained with them is growing very rapidly. Significant image improvement can now be obtained in the infrared with guide sources as faint as V = 15 or 16. Also, – at least on good astronomical sites – the isoplanatic patch size was found to be larger than originally anticipated. At the CFH telescope, it is not uncommon to observe only a 10% loss of Strehl ratio in the H band, 20″ away from the guide star.

Introduction

This chapter presents an overview of laser guide star (LGS) AO systems which are in operation now or are under development. We will see that the systems encompass a wide range of technologies and implementation approaches. Some are built from well-tested components. Others explore new territory in terms of concepts and hardware, and are aimed at optimizing LGS AO for astronomy. As discussed in Chapter 11, one system (at the SOR 1.5-m telescope) has been operational for several years. Although it was developed for defense applications, the SOR system has been made available for astronomers to gain experience using LGS AO.

LGS AO systems are listed in Table 13.1. Included are those which exist or are under development and planned to be in operation by the year 2000. The table gives the telescope and the organization developing AO, along with: the diameter of the telescope; the number of DM actuators over the telescope pupil; the type of LGS (Rayleigh or sodium) and laser power; and the date of AO first light.

The remainder of this chapter briefly summarizes the systems in Table 13.1, emphasizing special features of each. For more detailed discussions, the reader is referred to technical papers on the systems in the proceedings of the 1994 Kona SPIE conference on AO (SPIE 1994), the 1995 Garching ESO/OSA (Garching 1995) and SPIE (SPIE 1995) conferences on AO, the 1996 OSA (OSA 1996) conference, and the 1998 SPIE and ESO/OSA meetings.

Turbulence in the Earth's atmosphere produces inhomogeneities in the air refractive index, which affect the image quality of ground-based telescopes. Adaptive optics (AO) is a means for real time compensation of the image degradation. The technique was first proposed by Babcock (1953) and later independently by Linnick (1957) to improve astronomical images. It consists of using an active optical element such as a deformable mirror to correct the instantaneous wave-front distortions. These are measured by a device called a wave-front sensor which delivers the signals necessary to drive the correcting element. Although both Babcock and Linnick described methods that could be employed to achieve this goal, development cost was too prohibitive at that time to allow the construction of an AO system for astronomy.

The invention of the laser soon triggered both experimental and theoretical work on optical propagation through the turbulent atmosphere. Studies on laser speckle led Labeyrie (1970) to propose speckle interferometry as a means to reconstruct turbulence degraded images. Following Labeyrie, astronomers focused their efforts on developing ‘post-detection’ image processing techniques to improve the resolution of astronomical images. Meanwhile, defense-oriented research started to use segmented mirrors to compensate the effect of the atmosphere in attempts to concentrate laser beams on remote targets. This was done by trial-and-error (multidither technique). As artificial satellites were sent on orbit, the need came to make images of these objects for surveillance, and attempts were made to use similar techniques for imaging (Buffington et al. 1977).

Introduction

Adaptive optics systems are often expensive and complex instruments, which need to work under a wide range of operating conditions. It therefore behooves the designer of an adaptive optics system to develop a model of the systems in order to best allocate the available resources to the project. The existence of an accurate computer model of an AO system is probably crucial for commissioning a system. Such a model helps one diagnose problems and artifacts in the system, and explore possible solutions. This chapter deals with methods for simulating the optical performance of the adaptive optical components of the system. Simulation of the mechanical aspects of the system design are not covered in this chapter.

We start the chapter with a discussion of approximate methods that can be used in the initial design phases of a project to constrain the parameters of the AO system. We then move to slightly more complex techniques, which may be used to verify results to greater accuracy. Next we discuss complete optical simulations which may be used to model the interaction of various system components, taking optical diffraction into account. Finally we discuss the problem of comparing measured results with simulation results. Measuring the performance of an AO system is a difficult undertaking, and is often poorly done.

Linear error budget analysis

A simple error budget analysis serves to elucidate the first order performance of an AO system on a given site and at a given telescope.

Stars emit not only radiation but also particles. The emission of particles is called the stellar wind.

The two most important parameters regarding a stellar wind that can be derived from the observations are the mass loss rate Ṁ, which is the amount of mass lost by the star per unit time, and the terminal velocity v∞, which is the velocity of the stellar wind at a large distance from the star. By convention, the mass loss rate Ṁ is always positive and it is expressed in units of solar masses per year, with 1 M⊙ yr-1 = 6.303 × 1025 g s-1. A star with Ṁ = 1--6M⊙ yr-1, which is not an unusual value, loses an amount of mass equal to the total mass of the earth in three years. The terminal velocity v∞ of a stellar wind ranges typically from about 10 km s-1 for a cool supergiant star to 3000 km s-1 for a luminous hot star.

The values of Ṁ and v∞ are important because

(1) Ṁ describes how much material is lost by the star per unit of time. This is important for the evolution of the stars, because stars with high mass loss rates will evolve differently from those with low mass loss rates.

(2) Different stellar wind theories predict different mass loss rates and different terminal velocities for a star. So by comparing the observed values with the predictions we can learn which mechanism is responsible for the mass loss from a star.

Coronal winds are stellar winds driven by gas pressure due to a high temperature of the gas. In the case of the sun a coronal temperature of about 2 × 106 K is reached in the outer layers of the solar atmosphere. The solar photosphere, where the visual radiation from the sun is emitted, has a temperature of about 6000 K. Above the photosphere the temperature rises with height to a few times 106 K. The temperature rise beyond the photosphere is due to the dissipation of mechanical energy or the reconnection of magnetic fields that originate in the convection zone below the photosphere. Other forces, such as those produced by Alfvén waves, may play a role in the coronal holes which are regions of lower temperatures and higher mass flux. However in this chapter on coronal winds, we will only consider the effects of gas pressure and heat conduction in the production of a stellar wind.

All non-degenerate stars with effective temperatures less than about 6500 K are expected to have a convection zone below their surface, so in principle chromospheres and coronae could exist around all cool stars. However, very luminous cool stars can also have winds driven by other mechanisms such as wave pressure or radiation pressure on dust grains. If these stars have a high mass loss rate, then the heating cannot compete with the cooling of the outflowing gas.

In this chapter, we consider how the astronomer may use an adaptive optics system, what kind of performance can be expected in a particular program, and how observations should be prepared. We also discuss what precautions must be taken during data acquisition, with special emphasis on how to keep proper track of the overall impulse response including the atmosphere. We give some advice, and discuss specific data reduction procedures.

Estimating performance

In addition to the art of imaging, well known to astronomers, the AO methodology adds the necessity of considering a constantly changing atmosphere and atmospheric seeing. Such a changeable state of affairs, departing from stationarity, is well illustrated by Fig. 14.1. Non-stationarity precludes a complete a priori knowledge of the actual performance a given system will reach at a given time: from the choice of pixel size or slit width to the selection of the operating loop frequency of the AO system or the adequacy of a given offset reference star, many observational parameters cannot be entirely pre-determined and will require real time decisions.

An a priori knowledge of the seeing at an astronomical site is therefore of importance for forecasting the atmospheric coherence time τ0 and the coherence diameter r0. At many modern observatories, programs are envisaged to deduce these values from meteorological observations, such as vertical thermal gradient and wind speed, local vorticity, etc.