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

Calibrator search engine can be used for a quick search of suitable calibrator around a target with specified coordinates.

The latest catalogue of source in various formats.

The database of flux density distribution, and images of more that 4000 sources.

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.

S_corr > 50 mJy at baselines longer than 1000 km at δ > -40°
S_corr > 50 mJy at baselines longer than 6000 km at δ > -40°
S_corr > 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:

The VLBA Calibrator Survey for compact radio sources with declinations > −45°

The LBA Calibrator Survey for compact radio sources with declinations < −45°.

RDV VLBA program of geodetic and astrometric observations arXiv.org/abs/0806.0167

Some sources were observed in geodetic VLBI observations.

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

extragalactic

compact

Remember: an interferometer is a filter of spatial frequencies
We need to predict F_corr/F__tot where F_corr 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 F_corr/F__tot < 0.01

highly compact sources F_corr/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 F_corr/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 F_corr;

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:
1. to be able to solve for atmosphere path delay in zenith
2. 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 N_obs). For this same cutoff, the number of sources predicted under assumption that logN—logS dependence is a straight line (column N_{obs).
The ratio of two quantities, (column Cmpl) gives the low level of the
completeness at certain correlated flux density levels among flat spectrum sources.}

F_corr (Jy)    N_obs    N_pred 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%

Hunt for more calibrators

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 24^h 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 24^h 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 N_src 256 Mbps SNR=10 4096 Mbps SNR=10

S/X K S/X K

2^m 220 66 mJy 50 mJy 16 mJy 13 mJy

1^m 330 90 mJy 70 mJy 22 mJy 18 mJy

30^s 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 S_max > 1.4 GHz S_max > 3 GHz S_max > 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 S_max > 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 S_{1.4 GHz} > 200 mJy, were observed with VLBA. In total, 496 target objects.

S_corr > 50 mJy S_corr > 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 (S_corr > 50 mJy ) for flat-spectrum sources

With reliable spectrum: 80%

With unreliable spectrum: 50–80%

No spectrum S_1.4GHz 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 30^s, 470 sources can be observed in one 24^h 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    11^d —      —      — —      —      —

67% 8 500     9 400    28^d —      —      — —      —      —

80% 13 600    15 000    42^d 510    1 300    1.5^d–4^d —      —      —

90% 21 000     22 000    70^d 2 380    3 150        7–9^d —      —      —

95% 35 000    36 000 120^d 4 420    5 270    13–16^d —    340    1^d

Galactic plane ( |b| < 6° δ > -40° )

Radius 1° Radius 2° Radius 3°
67%    500 1^d.5 —      — —      —

80% 1 000     3^d —      — —      —

90% 1 700     6^d —      — —      —

95% 2 200     8^d 100    0^d.3 —      —

Ecliptic plane ( |β| < 7° )

Radius 1° Radius 2° Radius 3°
67% 1 200       4^d —      — —      —

80% 2 000       6^d 100    0^d.2 —      —

90% 3 200     11^d 340       1^d —      —

95% 4 300     15^d 640       2^d —      —

Estimates of the number of 24^h observing sessions at 4096 Mbps.
S_corr > 50 mJy at baselines longer than 1000 km
S_corr > 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

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%

extended sources	F_corr/F__tot < 0.01
highly compact sources	F_corr/F__tot ~0.1—0.9

near α =-1	steep spectrum
near α = 0	flat spectrum

F_corr (Jy)	N_obs	N_pred	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%

Int. time	N_src	256 Mbps SNR=10		4096 Mbps SNR=10
		S/X	K	S/X	K
2^m	220	66 mJy	50 mJy	16 mJy	13 mJy
1^m	330	90 mJy	70 mJy	22 mJy	18 mJy
30^s	470	130 mJy	100 mJy	32 mJy	26 mJy

Flux 8.6 GHz	S_max > 1.4 GHz	S_max > 3 GHz		S_max > 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)

Flux 1.4 GHz	S_max > 1.4 GHz
> 200 mJy	24 900
> 100 mJy	61 900
> 50 mJy	136 730
> 30 mJy	228 490

	S_corr > 50 mJy		S_corr > 100 mJy
Baselines < 1000 km	57	11.5%	43	8.7%
Baselines > 6000 km	38	7.7%	29	5.8%

With reliable spectrum:	80%
With unreliable spectrum:	50–80%
No spectrum S_1.4GHz	11%

	Radius 1°	Radius 2°	Radius 3°
50%	3 740 4 420 11^d	— — —	— — —
67%	8 500 9 400 28^d	— — —	— — —
80%	13 600 15 000 42^d	510 1 300 1.5^d–4^d	— — —
90%	21 000 22 000 70^d	2 380 3 150 7–9^d	— — —
95%	35 000 36 000 120^d	4 420 5 270 13–16^d	— 340 1^d