Transcript Single-Dish Continuum

Single-Dish Continuum
• Basics
• Issues
• Confusion
• gain fluctuations
• atmosphere
• Receiver architectures &
observing strategies
•The future: large arrays
Brian Mason (NRAO)
NRAO/NAIC Single-Dish Summer School
July 13, 2009
Flux Density (Jy)
ZSPEC (Caltech Submillimeter Observatory)
T 
Rotational
Transitions
Of CO
CCH,
HCN…

Thermal emission
from dust
Tsys
t
M82
Stellar death
Magnetic fields
Thermal BB
synchrotron
Stellar birth
dust
Free-Free
See Condon (1992, ARA&A)
Dust emission from galaxies at at
high redshift
• Discovered an abundant
population of submm
galaxies at z~1-3
• 50 hr map with the JCMT
at 850 m, confusion
limited
HDF-- Hughes et al. (1998)
The Sky Isn’t Empty: Confusion
NVSS (45 arcsec
FWHM) grayscale
GB6 300’ (12
arcmin FWHM)
contours
The confusion amplitude P(D) distribution
[for n(s) = dN/ds=kS-2.1]
Euclidean:
  2.5

D = image brightness (e.g., Jy/beam)
Condon (1974); Scheuer (1956)
The confusion amplitude P(D) distribution
[for n(s) = dN/ds=kS-2.1]
Euclidean:
  2.5

D = 0 mean is not a good baseline; use
running median instead
Long tail --> use at least 5 sigma threshold (src/30 beams)
The 5σ extragalactic confusion limits for
Arecibo (d = 220 m) and the GBT (d = 100 m).
Gets much weaker with
increasing frequency:
FWHM 
1

S   0.8


The noise level
won’t go below this
if you integrate for
longer.
BUT!
NRAO VLA Sky Survey (NVSS): 1.4 GHz
GB6: old 300’+7-beam receiver, 5 GHz
A Simple Picture of Gain Fluctuations
Suppose TSRC << TRX
G(t1 ){TSRC  TRX  TATM }
G(t 2 ){TRX  TATM }

On  Off  G(t1 )TSRC  G(TRX  TSKY )

Extra Noise Term
 (Contributes to baseline ripple for S.L.)
A Simple Picture of Gain Fluctuations
Flux Density (Jy)
DC Offset (e.g., Tsys)
Why not calibrate the fluctuations away?
Stability requirement in order that gain fluctuations cause
smaller changes in the output than thermal noise:
G T
1


 3 10 5
G
T

(1 sec, 1 GHz bw) - too small to be accurately measured
each second --> mitigate with instrument design
Atmospheric Emission
G{TSRC  TRX  TATM (t1 )}
G{TRX  TATM (t 2 )}

On  Off  GTSKY

Sky emission often adds noise to continuum measurements, so

you need to measure your noise instead of assuming the
radiometer equation or formal uncertainties!
How fast do G(t), TATM(t) vary?
Postdetection power spectrum of the receiver output
Atmosphere & gain
Fluctuations: 1/f
Power spectrum
Gaussian, uncorrelated
Noise (Radiometer Equation):
White (flat) power spectrum
νk
How does kdepend on bandwidth?
νk
Less bandwidth
νk
More bandwidth
Eliminate bad fluctuating signals by independently measuring the bad signal on some
timescale or shorter. Use  < 1/(2πνk): Dicke switching, chopping, multi pixel, etc..
Characteristic Timescales for
Broadband Measurements
Gain fluct. For coherent amplifiers: 100+ Hz
– receiver architecture
•incoherent (bolometer) detectors: 0.1-10 Hz
•Atmosphere 0.1-few Hz
– chopping or rapid scanning
– common mode subtraction for imaging arrays
Dicke-Switching Receiver
Rapidly alternate between feed horns to
achieve theoretical noise
performance. (old-fashioned receiver
architecture but good illustration, &
same principle as “chopping”)
G{TSRC  TRX  TATM }
G{TRX  TATM }
On  Off  GTSRC  (G  0)(TRX  TSKY )

For TSRC<<TSYS gain fluctuations don’t

contribute
significantly to the noise
P  G(V12 V22 )
Dicke-Switching Receiver
Rapidly alternate between feed horns to
achieve theoretical noise
performance
Penalty:
–Differential sky measurement
–2x higher thermal noise
T  T1  T2
RMS(T)  2  RMS(T1 )
T1
2T1
 2

1
 Tot
P  G(V12 V22 )
?
Dicke-Switching Receiver
What happens if the feeds see
slightly different things?
G {TSRC  TRX  TATM }
G {TRX  TATM  TOFF }
On
  Off  G TSRC  GTOFF
Components
before the switch must be

as identical + well matched as possible.
P  G(V12 V22 )
An Easier Way?
An Easier Way?
A  B  G1TSRC  G(TRX  TSKY )
Primarily you switch to suppress receiver effects.
Switch must be before active (unstable) components
Correlation Receiver
Receiver noise is
uncorrelated and
drops out.
Always looking at both
source & reference:
only lose one sqrt(2)
for differencing
Correlation Polarimeter
I  L2  R 2
V  L2  R 2
Q  Re( LR )
U  Im( LR )
See talk by Carl Heiles
Higher-Order Differences: Symmetric Nodding
• For sensitive photometry, one level of differencing is usually not
enough
– Gradient in sky emission, or with time
– Dual-feed systems: Slight differences in feedhorn gains or losses
Bolometers
Bolometer detectors
• Incoherent; measure
total power
• Very broad
bandwidths possible;
approach quantum limited noise.
• Can be built in very
large-format arrays!
MUSTANG (18 GHz)
Bolometers
θ
adjacent
pixels
4″
98
%
40km
Across 32″
array
98
%
5km
MUSTANG (18 GHz)
(principle also applies to dual pixel heterodyne receivers & FPAs)
Array Receivers
ALFA
ALFA on Arecibo
7-element λ = 21 cm coherent array, 3 arcmin resolution
GALFACTS:full-Stokes , sensitive, high-resolution survey of 12,000
deg^2
Galactic magnetic fields, ISM, SNR, HII regions, molecular clouds …
Large Format Heterodyne Arrays
QUIET
• 91 pixels
• I,Q,U
• 90 GHz
• integrated,
massproducable
“receiver on a
chip” (MMIC)
T. Gaier (JPL)
Large Format Heterodyne Arrays
QUIET
• 91 pixels
• I,Q,U
• 90 GHz
• integrated,
massproducable
“receiver on a
chip” (MMIC)
OCRA
• 1-cm Receiver Array
• Under construction at Jodrell Bank,
initially for Torun 30m telescope
• SZ surveys + imaging
• 16 --> 100 pixels
• correlation architecture
T. Gaier (JPL)
Millimeter
Bolocam/AZTEC
• 1-2 mm
• 144 pixels
• CSO (10m) & LMT (50m)
ACT (6m) , SPT (10M)
• 1-2 mm
• Large Area Surveys (SZ) 1000s of deg^2
• few 1000 detectors
Also IRAM 30m, APEX
Sub-millimeter
SCUBA-2
• JCMT (15m)
• ~10,000 pixels!
• SQUID-MUX’d TES
bolometers (CCD-like)
• Under commissioning now
Also: SHARC-II on CSO, 384 pixels at 350 um
MUSTANG
GBT 3.3mm Bolometer Array
Prototype for a 1000-pixel
class camera
Maping Speed
>15x ALMA
Thermal Dust + Free-Free Emission
In Orion KL/Integral Filament
Region.
MUSTANG
GBT 3.3mm Bolometer Array
Prototype for a 1000-pixel
class camera
Maping Speed
>15x ALMA
SZE in
RXJ1347-1145
User instruments
END

Performance Measures
From before:
TAnt
Aeff
TAnt Aeff

SSrc   

2k
SSrc 2k
Gain
An effective aperture of 2760 m2 is required
to give a sensitivity of 1.0 K/Jy.

SNR 
TAnt


T TSys
Units of 1/Janskys. You sometimes see
The System-Equivalent Flux Density,
SEFD (small is good)
“Mapping Speed” commonly defined as:
MappingSpeed 
Area
(noise) 2 (time)
These are single-pixel measures. For mapping, increase by Nfeeds.

Output Power
Gain Effects: deviations from linearity
Gain compression/
saturation
TRx
Input Power
Integrated power is
what usually matters
(RFI)
Output Power
Gain Effects: deviations from linearity
Gain compression/
saturation
TRx
Input Power
Integrated power is
what usually matters
(RFI)
Be aware of the limitations of the instrument
You’re using & calibrate at a similar total power
Level to what your science observations will see.
Gain Effects: fluctuations
Gain drifts over the course of an observing
Session(s) easily removed with instrumental
Calibrators (e.g., noise diodes)
Short term gain fluctuations can be more
Problematic. (see continuum lecture)
Sampling/Quantization & Dynamic
Range: Postdetection
A/D
2N levels
(N~14)
Diode or square law detector:
Turns E-field into some output
Proportional to power (E2)
P
P 

Common for continuum systems.
~1 level
Robust & simple (large dynamic range)
 2 N P
.
.
.

A/D sample time
Sampling/Quantization & Dynamic
Range: Predetection
Sample the E-field itself.
Samplers must be much faster and sample much more
corasely (typically just a few levels)
Dynamic range limitations more important
One usually requires variable attenuators
to get it right (“Balancing”).
Small # of levels increases the noise level.
(K-factor in Radiometer equation)
More levels -> greater dynamic range (RFI robustness),
greater sensitivity
Monitor levels through your observation.
Nonthermal Emission around Sgr A*
75 MHz, VLA:
330 MHz, GBT:
LaRosa, Brogan et al. (2005)
QuickTime™ and a
decompressor
are needed to see this picture.
BOOMERAnG map of CMB Anisotropies