VLBI Calibrator list
Compact radio sources with angular sizes 0.1—10 mas with their
positions determined with sub-milliarcsec accuracy in dedicated VLBI survey
experiments can be used as target for geodetic observations and as
calibrators for imaging and differential astrometry VLBI observations.
To date, the VLBI calibrator list contains more than 6000 objects. The
catalogue is updated 2—5 times a year.
Data access
Do you need more calibrators? Refer to the
"Hunt for more calibrators" section.
Probability to find a calibrator
The probability to find a calibrator at any given direction at δ > -40°
as a function of the search radius.
Scorr > 50 mJy at baselines longer than 1000 km at δ > -40°
Scorr > 50 mJy at baselines longer than 6000 km at δ > -40°
Scorr > 30 mJy at baselines longer than 1000 km at δ < -40°
Radius |
&delta < -40° |
All sky at &delta > -40° |
Gal. plane: |b| < 6° δ > -40° |
|
Now |
Mid 2010 |
Now |
Today |
Mid 2010 |
1° |
20.0% |
28.0% |
23.0%
30.0% |
28.7% |
47.6% |
2° |
58.0% |
73.0% |
64.7%
76.9% |
76.0% |
90.3% |
3° |
84.0% |
95.0% |
90.2%
97.1% |
96.8% |
99.0% |
4° |
96.0% |
99.6% |
98.1%
99.9% |
99.9% |
100.0% |
Data
The majority of VLBI calibrators have been observed in dedicated
VLBI experiments with
VLBA and LBA:
Source Statistics by 2009.05.01
Program | Epochs | # Exp | # sources |
CDP, JPL, CRF | 1979—1994 | ~4500 | 965 |
RDV | 1994—present | 112 | 871 |
VCS, NPCS | 1994—2007 | 27 | 3575 |
LCS | 2008—present | 3 | 317 |
GaPS | 2006—present | 3 | 327 |
Some sources were observed in more than one program.
On-going analysis improvement development:
- Migration from AIPS to the custom fringing software;
- Using numerical weather models for modeling troposphere
path delay and atmospheric extinction;
- Using ionosphere models for processing single-band data.
Technology of VLBI surveys.
Source selection
- Selection of a (wide) pool of candidates;
- Computing the probability of detection of each source;
- Maximization of the target function.
The most difficult part is prediction of the correlated flux density.
We need to guess, whether a given source is
Remember: an interferometer is a filter of spatial frequencies
We need to predict Fcorr/F_tot where Fcorr is the
correlated flux density in the range of spatial frequencies, the interferometer can see
(5—500 M$λ), and F_tot is the total flux density integrated over
the source.
How to do it?
Consider two source populations:
extended sources |
Fcorr/F_tot < 0.01 |
highly compact sources |
Fcorr/F_tot ~0.1—0.9 |
These populations mostly have a distinctive spectrum index α
(F ∼ ν+α).
The distribution over spectral index has two peaks:
near α =-1 |
steep spectrum |
near α = 0 |
flat spectrum |
The source spectrum was evaluated from various catalogues collected
in the the super catalogue CATS.
To date, spectrum estimates for more than 250 000 sources are
available, although not all
spectra estimates are reliable due to source variability and errors
in source identification, especially for weak ones.
Examining plots of source spectra,
we can determine whether a given source belongs to the flat-spectrum
population or to the steep-spectrum population.
Typical source spectra from CATS.
The probability density distribution of Fcorr/F_tot at
$ |b| = R⊕ F=8 GHz among the two source populations:
Steep spectrum population
Flat spectrum population
Source selection strategy
Algorithm for predicting correlated flux density:
- gather the spectrum ( f.e. using super-catalogue
CATS);
- compute the spectral index and extrapolated flux density;
- classify a source: steep or
flat ;
- compute the cumulative probability density of Fcorr;
- compute the cumulative probability density of the SNR;
- compute the probability of detection.
Survey optimization:
- formulate the target function, for example:
- to maximize the total number of detected sources
- to fill areas with low source density;
- to reach completeness on correlated flux density
- To find such a subset of candidate sources that maximize
the target function.
Output: a source list and associated integration times.
Scheduling survey observations
- find a sequence of scans that minimizes slewing time and satisfy
antenna constraints;
- Insert every 1--1.5 hours calibrator sources. The purpose of
calibrators:
- to be able to solve for atmosphere path delay in zenith
- to tie the positions with the core of frequently observed
sources (absolutization).
NB: The source list always
must have
an overlap.
Analysis of observations
- Fringe fitting.
- Group delay ambiguity resolution.
- Outlier elimination.
- Global solution using all
available observations, including
the new one , for estimating sources, positions, station positions, EOP,
and more than 1 million nuisance parameters.
NB: VLBI source catalogues are made
incrementally.
VLBI Calibrator list statistics by May 2009.
4337 objects.
Position error distribution
formal uncertainties |
reweighted uncertainties |
|
|
Reweighting:
σ2(α)new = (rσ(α))2 + F_α(δ)2
σ2(δ)new = (rσ(δ))2 + F_δ(δ)2
Reweighted error is < 5 nrad for 83% objects, < 25 nrad for 90% objects.
Error floor is around 1 nrad.
Factors that affect errors
- whether observations at long baseline have been scheduled;
- whether observations at long baseline yield detections;
- whether a source has been observed and/or detected at one or
two bands;
- whether a source is observed predominantly at low elevations;
- how many detections have been gathered:
1 | — useless; |
2–8 | — unreliable positions due
to group delay ambiguities; |
9–50 | — moderate. Error ∼ 1/√‾ n ;
|
51–500 | — good. Error law deviates
from ∼ 1/√‾ n ;
|
> 500 | — error floor is reached.
|
Calibrator list completeness for δ >: -30° at 8.6 GHz.
Completeness is estimated by deviation from the straight line from the logN—logS
straight line. The number of sources with correlated flux density at baselines longer than
1000 km is computed for various cutoff values of the correlated flux density
(column Nobs). For this same cutoff, the number of sources predicted under
assumption that logN—logS dependence is a straight line (column Nobs).
The ratio of two quantities, (column Cmpl) gives the low level of the
completeness at certain correlated flux density levels among flat spectrum sources.
Fcorr (Jy) | Nobs | Npred | Cmpl |
0.050 | 3011 | 18700 | 16% |
0.075 | 2937 | 9800 | 30% |
0.100 | 2708 | 6100 | 44% |
0.150 | 2154 | 3200 | 67% |
0.200 | 1639 | 2000 | >86% |
0.250 | 1278 | 1350 | >96% |
Ongoing projects (observing time has been approved)
- GAIA astrometric link. 2008–? 70–200 objects. Goal: to
get absolute coordinates of radio sources associated with
optically bright quasars.
- EVN-GaPS November 2009, 2 24h sessions,
613 objects. Instrument: EVN, K-band (22 GHz). Goal: to increase the density
of astrometric catalogue at |b| < 6°
- LCS 2008—2010. Instrument: LBA, 8(3) sessions,
900(317) objects. X-band. Goal: to increase the astrometric
catalogue density at the declination zone
[-90°, -40°] in order to
match the northern hemisphere.
The text below discusses the possibilities to take more calibrators beyond these
projects.
How much observing time time is needed?
The number of target sources and the baseline sensitivity for a 24h
absolute astrometry experiment computed from trial schedules. The schedule
includes time for slewing and for observing 4 tropospheric calibrator after one
hour of observing target calibrators.
Int. time | Nsrc |
256 Mbps SNR=10 |
4096 Mbps SNR=10 |
| |
S/X | K |
S/X | K |
2m |
220 |
66 mJy |
50 mJy
| 16 mJy | 13 mJy |
1m | 330 |
90 mJy | 70 mJy |
22 mJy | 18 mJy |
30s |
470 |
130 mJy | 100 mJy |
32 mJy |
26 mJy |
How many candidate sources remained?
The number of known flat-spectrum sources α > -0.5:
the total number of sources and
the number of sources that have not yet
been observed. Three columns give the estimates of the number
of sources with the available estimates of the flux density used for deriving
spectrum, at 1.4 GHz or higher, at 3.0 GHz or higher, and at 8.0 GHz or higher.
Flux 8.6 GHz |
Smax > 1.4 GHz |
Smax > 3 GHz |
Smax > 8 GHz |
200 mJy | 4 070 |
3 900 |
( 1 400 ) |
2 980 |
(300 ) |
100 mJy | 9 170 |
8 500 |
(4 500) |
5 910 |
(2 200) |
50 mJy | 18 400 |
16 300 |
(11 250) |
9 530 |
(5 500) |
30 mJy | 29 100} |
22 500 |
(17 260) |
10 980 |
(7 100) |
For comparison: the prorated number of sources in NVSS, except |b|<6°.
(The Galaoctic plane was excluded from the count, the the number of sources
was muliplied by the factor of the ratio of the area with declination above -40°
without the Galactic plane to the area fof the total area with δ > -40°).
Flux 1.4 GHz | Smax > 1.4 GHz |
> 200 mJy | 24 900 |
> 100 mJy | 61 900 |
> 50 mJy | 136 730 |
> 30 mJy | 228 490 |
What is the calibrator search efficiency?
I. If to observe all sources.
Results of the VLBA Northern Polar Cap survey provides
a good estimate. During that experiment all sources from NVSS, regardless of their
spectra, at δ > +75^deg; with S1.4 GHz > 200 mJy,
were observed with VLBA. In total, 496 target objects.
| Scorr > 50 mJy |
Scorr > 100 mJy |
Baselines < 1000 km |
57 | 11.5% |
43 | 8.7% |
Baselines > 6000 km |
38 | 7.7% |
29 | 5.8% |
II. If to observe flat-spectrum sources.
Search efficiency (Scorr > 50 mJy ) for flat-spectrum sources
With reliable spectrum: |
80% |
With unreliable spectrum: |
50–80% |
No spectrum S1.4GHz |
11% |
The reliability of source spectra is falling with decrease of flux density.
Rough estimate of search efficiency:
next | 1000 sources | 80% |
next | 5000 sources | 70% |
next | 10000 sources | 60% |
How many new calibrators would improve the probability for find calibrator at
a given search radius?
The probability to find a calibrator at a given search radius under assumption of
uniform source distribution is a function of the number of sources. This function
can be easily evaluated using Monte Carlo simulation. Since the current number of
calibrator is known, we can get the number of new sources that are needed to reach
given level of probabilities. Then we can estimate the number of candidates one needs
to observe. Assuming recording rate 4096 Mbit/sec and integration time 30s,
470 sources can be observed in one 24h session. The number of sources
with correlated flux density > 50 mJy at baselines longer than 1000
km is greater the number of sources with the same correlated flux density
at baselines longer than 6000 km. Therefore, to estimates
of the number of new sources is given.
All sky
|
Radius 1° |
Radius 2° |
Radius 3° |
50% |
3 740
4 420
11d |
— — — |
— — — |
67% |
8 500
9 400
28d |
— — — |
— — — |
80% |
13 600
15 000
42d |
510
1 300
1.5d–4d |
— — — |
90% |
21 000
22 000
70d |
2 380
3 150
7–9d |
— — — |
95% |
35 000
36 000
120d |
4 420
5 270
13–16d |
—
340
1d |
Galactic plane ( |b| < 6° δ > -40° )
|
Radius 1° |
Radius 2° |
Radius 3° |
67% |
500
1d.5 |
— — |
— — |
80% |
1 000
3d |
— — |
— — |
90% |
1 700
6d |
— — |
— — |
95% |
2 200
8d |
100
0d.3 |
— — |
Ecliptic plane ( |β| < 7° )
|
Radius 1° |
Radius 2° |
Radius 3° |
67% |
1 200
4d |
— — |
— — |
80% |
2 000
6d |
100
0d.2 |
— — |
90% |
3 200
11d |
340
1d |
— — |
95% |
4 300
15d |
640
2d |
— — |
Estimates of the number of 24h observing
sessions at 4096 Mbps.
Scorr > 50 mJy at baselines longer than 1000 km
Scorr > 50 mJy at baselines longer than 6000 km
Back to Astrogeo Center home page.
This web page was prepared by Leonid Petrov
(
)
Last update: 2009.07.19_23:12:10