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ATST Scattered Light Issues

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Presentation on theme: "ATST Scattered Light Issues"— Presentation transcript:

1 ATST Scattered Light Issues
How will mirror microroughness likely impact the coronagraphic performance of ATST? How do these limitations compare to what we can expect from dust and other particulate contamination on the mirror surface? How frequently will the ATST primary mirror need to be cleaned to maintain acceptable coronagraphic performance?

2 The ASAP Model Define a set of parallel rays representing a point source at the position of the sun’s center. Introduce these rays onto a “scatter” surface just in front of the primary mirror (M1). Scatter the parent rays into a half-degree cone centered on the specular direction. Add a scatter function to M1 that represents a clean, polished surface, or a surface contaminated by dust. The spot diagram that appears on the bottom right shows a small disk (little more than a dot) on the left, which is the detector size relative to the image of the sun at prime focus. The full 5 arcmin aperture was not used, but only this 10% sub-aperture. This allowed us to sample in closer to the limb, since at 1.1 RSUN the heat stop admits some of the limb. The “fuzz” on the right side of the image of the sun is just the optical performance of the f/2 off-axis system at ½ degree from the center of the field.

3 Sample Positions 2.0 1.5 1.1 The big disk on the right is the sun.

4 Mirror Signature from Microroughness
Typical scatter versus angle for a clean, polished glass surface

5 …In Direction Cosine Space
Plotting log10 | sin  – sin 0 | versus log10 BSDF

6 The Harvey Model b Figure courtesy of Gary Peterson, Breault Research Organization.

7 RMS Microroughness and Harvey
The single RMS roughness parameter () contains insufficient information to completely characterize the BSDF of the polished surface, even assuming a power-law relationship.

8 Ranges of Slopes The area shown in gray dominates the coronagraphic results close to the limb. All four curves integrate to yield the same total integrated scatter predicted for a 20 Ångstrom RMS surface.

9 Results for 20 Ångstrom Microroughness: S = – 1.5
 = 1.0 Microns

10 Results for 12 Ångstrom Microroughness: S = – 1.5
A slope of –1.5 is, if anything, optimistic. Manufacturers will likely be reluctant to bid fixed price on a 4M class mirror with a requirement more demanding than 20A. Yet we still cannot reach 1E-6!  = 1.0 Microns

11 Scatter due to Contamination (dust)
Figure courtesy of Gary Peterson, Breault Research Organization.

12 MIL-STD 1246C The number of particles per square foot with diameters greater than s microns is given by: log(n) = [ (log(c))2 - (log(s))2 ] s = particle diameter (m) c = cleanliness level n = number of particles per square-foot with diameters greater than s The derivative of this function gives the particle size distribution used in the analysis that follows. Courtesy of Gary Peterson, Breault Research Organization.

13 The Mie Model for 0.01% Coverage (Level ~230)
The gray area shows the region of the function that has the greatest influence on observations near to the limb of the sun.

14 UKIRT Emissivity data The left axis is actually percent emissivity. That was just the units they worked in. Hence, the slope suggests an accumulation rate of % per hour. If we take the emissivity of a chunk of dust to be about 1, emissivity in the IR (or at least its rate of change) can be interpreted as percent coverage (by dust) of the low-emissivity reflecting surface.

15 Scatter Versus Time

16 Scatter Versus Time: Apache Point
Rate of change ≈ 0.04% per hour! This is 40 times faster than the accumulation rate inferred from the emissivity data.

17

18 Power Spectral Density
Figure courtesy of Gary Peterson, Breault Research Organization.

19 Profile of a Star


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