Stephen White

Space Vehicles Directorate Air Force Research Laboratory

Observing the Sun with a Millimeter Interferometer

Introduction

This talk will review observations of the Sun at millimeter wavelengths. It will cover:

• telescope hardware issues • the problem of deconvolving quiet sun images • issues for observing with ALMA

The quiet Sun is the worst possible target for ALMA (flares OK)

• Low contrast emission fills the field of view • Therefore must sample large spatial scales, which means short

baselines: most telescopes don’t do short and long simultaneously • Dynamic: highly time variable in most pixels

BIMA millimeter array

An interferometer can map the entire field of view of one of its dishes at a resolution corresponding to the maximum size of the array.

CARMA array: merger of OVRO + BIMA

The Sun at microwaves: large contrast

VLA observation

VAL 1981 model of the chrom-osphere Heights of diff-erent diag- nostics

Fontenla et al 1999

The Solar Chromosphere (Hinode)

“the Hα chromosphere is a seething, oscillating mass of fibrils” (Zirin)

Spicules probably define the radio limb.

High Resolution Millimeter-

Interferometer Observations of

the Solar Chromosphere

with

Maria Loukitcheva

& Sami Solanki

Target regions for BIMA

observations

Making images of the chromosphere

• Need information on largest spatial scales: most compact array configuration

• Information deficit: BIMA has only 9 antennas in this observation, 45 “measurements” per snapshot

• But field of view is 2 arcmin, resolution 10 arcsec, need several hundred pieces of information to reconstruct sky brightness

• Chromosphere is dynamic: is it sufficiently stable? • Low contrast (fluctuations of hundreds of K on a

base of 7000 K) • Conventional “CLEAN” does not work.

Overall map: active region

Images are filled with low contrast emission, very difficult to map. Range in millimeter image from 0 to 2000 K.

Active region: comparison with Ca K

Quiet Sun: comparison with Ca K

Deconvolution: CLEAN vs MEM

CLEAN: • Represents everything as a point source • Very good for bright compact sources • Very poor for extended diffuse emission

Maximum entropy (MEM): • Mathematically defined minimization procedure: convolve

brightness model with telescope response, change model to improve agreement with dirty map

• Usually implemented with smoothness and positivity constraints: good for extended diffuse emission

• Mosaics allow you to get information on scales larger than a single field

• But it’s a diva to run

CLEAN vs MEM for the chromosphere

OST Simulation (M. Loukitcheva)

Better with multi-resolution clean?

Snapshot mapping issues • Time-dependent imaging requires snapshot mapping but

a single snapshot does not contain enough information to reconstruct the sky

• Small number of antennas (10 at best, often 9) results in snapshot maps with poor point response, sidelobes up to 50% of maximum

• Need to use a priori information: start with a default image that is the all-day map, and use maximum entropy to look for (a small number of) departures from this map required by the data (CLEAN does not use a priori information, fails miserably)

• Map with 15 second cadence, 10 arcsec beam to be sensitive to oscillation power

Quiet Sun movie: 30 minute scan

Imaging tests: add an oscillating source

Add oscillating sources at different locations in the image, subtract original and fit.

Find that recover flux down to 100 K temperature in regions of bright emission in the default map, but not in regions dark to start with.

Imaging tests: add an oscillating source

Add sources in pairs at different locations with different periods, see how well they are recovered as a function of the flux in the default image.

Network

Internetwork

Individual pixels from internetwork (cell interior, low in both Ca K and millimeter) and network (cell boundaries, high in both Ca K and millimeter)

Snapshot mapping issues

• Find that changes that would create negatives in the image are not well reproduced, changes that add to image are well reproduced

• Maximum entropy has a positivity constraint: forces the zero level in the map to be the lowest point in the image

• This affects reconstruction: changes that would add a negative to the map and force the entire map to shift down are not well reconstructed because they require changes in many pixels, but small number of positive changes are OK. With a small number of dishes this is a limiting factor to the effective size of oscillations that can be imaged.

• Oscillations in bright regions may be well reproduced • Only the brightest changes are likely to be reproduced because

of the limitations of the data (small no of antennas)

CARMA map of the chromosphere

2008 Sep 26 data: in conjunction with TRACE UV observations. CARMA image with 10” beam (two dish sizes!)

Use of dishes with different primary beams is OK

Mapping the chromosphere with ALMA • Exciting for chromospheric work because we measure

temperatures directly, no NLTE to worry about, and can measure POLARIZATION for the first time, potential for magnetic field measurements (but optically thick – some work required)

• I expect that we will need the 12m dishes, 7m dishes and single dish mapping simultaneously to optimize imaging of the chromosphere – can combine all with MEM

• The fast mapping with the single dishes allows options that we have never had before for filling in short spacings and getting the absolute temperature scale

• But it will take some time to figure out the best way to use single dish data – issue with calibration relative to interferometer?

• Can we get to subarcsecond resolution? Possible with all the dishes.

• If we could do snapshot mapping with BIMA, should work with ALMA: necessary because all the small features will be variable.

Year GOES C M X 1997 286 20 3 1998 1194 95 14 1999 1855 170 4 2000 2263 215 17 2001 2103 311 21 2002 2319 219 12 2003 1316 160 20 2004 913 122 12 2005 578 103 18 2006 153 10 4 2007 73 10 0 2008 8 1 0 2009 28 0 0 2010 170 23 0 2011 1200 111 8 2012 1337 129 7