Low-frequency observations

Robert Laing (ESO)

Outline

A little history

Low-frequency science – emphasising the future

Technical problems: wide fields, interference, ionosphere

Current arrays: VLA, WSRT, GMRT

Overview of low-frequency data reduction

Future arrays: LOFAR

Low-frequency radio astronomy

Low frequency, somewhat arbitrarily defined as ν < 300MHz (or long wavelength, λ > 1m)

Cheap (uncooled) receivers and collecting elements (e.g. arrays of dipoles), but complex signal and data-processing

Very wide fields of view

Ionosphere

Interference

History

Reber(1937)

160 MHz

Jansky (1933) 20.5 MHz

Radio astronomy beganat low frequencies

History (2)

Earliest observations (Reber, Jansky) were at low frequency

Much early work at low frequencies (e.g. 3C 159 / 178MHz); pulsar discovery 81.5 MHz

Most aperture synthesis observations made at higher frequencies, for technical reasons and to achieve high resolution

Significant (and still useful) work on strong source spectra in 1970’s. ν down to 10 MHz – see MNRAS 190, 903 (1980) for references and flux-density scales.

Surveys: Clark Lake (26 MHz) and CLFST (38/151 MHz)

MERLIN 151 MHz

Modern era began with the 74-MHz system on the VLA

History (3)

Cygnus A MERLIN 151 MHz6C/7C151 MHz

8C38 MHz

www.mrao.cam.ac.uk/surveys

The sky at 150 MHz Landecker and Wielebinski (1970)

Low-frequency scienceEpoch of reionization, observed via redshifted neutral hydrogen. Entirely new field – a main science driver for LOFAR.Steep-spectrum synchrotron emission from low-energy (aged) electrons

Dying radio sources, cluster halos and relicsEnergy input into the intracluster mediumDistant radio galaxies with highly redshifted spectra

Surveys, selection by isotropic emissionParticle acceleration, propagation effects and turbulence in theISMAbsorption processes: free-free, synchrotron self-absorption, Razin-TsytovichCoherent emissionCosmic rays

The end of the “dark ages”

Epoch of reionization: ~halfof hydrogen neutral

When (20 > z > 6.5)?How rapid? Multiple events?Sources of ionization?

Observe redshifted HI line (z = 6 – 13 corresponds to 100 – 200 MHz)

HI and the epoch of reionization

Simulation (Furlanetto et al.): bright = neutral; dark = ionized)

Three stages: global signal (what is the redshift?)power spectrum (what is the structure?)imaging reionization

High brightness sensitivity on arcmin scales; foreground subtraction

Low-frequency synchrotron radiationCritical frequency of synchrotron radiation νc / Hz = 4.199 x 1010 γ2 (B/T)

where γ = E/mec2 is the Lorentz factor of an individual electron of energy E

Hence low-frequency implies low energy, given B

The rate of energy loss from synchrotron radiation-dE/dt = 1.058 x 10-14 (B/T)2 γ2 (v/c)2

Hence more energetic particles lose energy more rapidly and the spectrum is steeper at high frequency

The spectrum steepens with time, so steep spectrum often means older

S(ν) ∝ ν-α typically a power law with α ≥ 0.5; α > 1 - 1.5 “steep spectrum”

N(E)dE ∝ E-(2α+1) dE

Steep-spectrum synchrotron emission

Powerful radio galaxies have steep high-frequency spectra. At large distances, these are redshifted to low frequencies. Locate massive structures at high redshift.

Halo and relic sources in clusters of galaxies have steep spectra: probe very dense environments

Interaction of radio galaxies with environment dumps energy into the ICM. Important source of energy in clusters; may halt rapid cooling.

Knowledge of particle energy spectrum at lower (but still relativistic) energies is crucial to understanding jet physics, particularly composition.

Don’t forget the magnetic field.

High-redshift galaxies

HST image of the field of a radio galaxy at z= 2.2 identified by its steep spectrum radio Emission (Pentericci et al. 1999)

Probably a massive protocluster

Spectrum of a starburst galaxy at z = 4.4blueshifted to z = 0 and superimposed on that of M82

Superposition of synchrotron emission and dust emission. At very high redshifts, synchrotron emission at ν > 1 GHz may be suppressed by inverse Compton losses requiring low-frequency observations to detect this component and estimate z.

Cluster radio halos and relics

Relics in A3667 X-ray colourRadio contours

Radio relics

A cluster radio halo

Environmental impact

Perseus cluster, 74 MHz Higher-resolution imagescontours + X-ray grey-scale showing inner bubbles

Radio-source plasma forms bubbles in ICM: but (how) doesheating take place?

Low-energy electrons in radio galaxies

M87 at 74 MHz

Majority of relativistic particle energyis at low energies if the energyspectrum is steeper than E-2

(spectral index α > 0.5)

Constraints on radio-source composition depend on the measurement of the spectrum at low frequencies.

Supernova remnants and the ISM

Crab nebula

Thermal absorption by interveningHII region in W49B

Measure Galactic cosmic ray distributionby observing absorption and foreground emission for HII regions at known distances

Cas A

Some other applicationsPolarization at low frequencies: measure small Faraday rotations

Transient sources. Enormous instantaneous field of view allows efficient monitoring:

Supernova, gamma-ray burst and soft gamma-ray repeater prompt emission; afterglows

MicroquasarsGiant pulses……………..

Imaging/radar of coronal mass ejections from the Sun

Detection of coherent radio emission from secondary particle cascades generated in the atmosphere by ultra-high-energy cosmic rays – estimate direction.

The problems of low-frequency observing

Imaging wide fields

Large primary beams: the sky is full of sources

The ionosphere

Interference

Problem 1: non-coplanar baselines

Standard 2D Fourier transform relation between visibilities and image breaks down (the “w term” becomes significant)

Maximum 2πw[(1-l2-m2)1/2 -1] ≈ Bλ/D2 (B = max baseline; D = antenna diameter) – bad for long baselines and wavelengths

Possible solutions:

3D transform (impossibly slow)

Image the curved field using a number of flat facets (standard method, implemented in IMAGR)

w-projection (potentially faster and more accurate)

V (u,v,w) = I(l,m)∫ ej2π ul+vm+w 1− l2 −m2 −1( )( )dldm

Non coplanar baselines (2)

An example of image distortion caused by imaginga large field with a 2D Fouriertransform

The essence of W projection

The problem: for regular grid in (l,m) and irregularly spaced samples in (u,v)

V (u,v,w) = I(l,m)∫ ej2π ul+vm+w 1− l2 −m2 −1( )( )dldm

Image space computation

V (u,v,w) = G(l,m,w)I(l,m)∫ e j2π ul+vm( )dldm

V (u,v,w) = G(u,v,w)⊗V (u,v,w = 0)

Fourier space computation

Optics

If we had measured on planeAB then the visibility would be the 2D Fourier transform of the

sky brightness

Since we measured on AB’,we have to propagate back to plane AB, requiring the use ofFresnel diffraction theory since

the antennas are in eachothers near field

The convolution functionImage plane phase screen Fourier plane convolution function

ej2πw 1− l2 −m2 −1( ) ≈ e− jπw(u2 +v2 )

w projection in practice

Gridding kernel is a function of w.

Image to gridded visibilities.Taper image by spheroidal functionFourier transformConvolve gridded visibilities with w-dependent kernel

Ungridded visibilities to imageConvolve visibilities onto grid using w-dependent kernelInverse Fourier transformCorrect for spheroidal function

DeconvolutionMinor cycle use field-centre PSFReconcile with visibilities in major cycle

A synthetic example

Simulation of ~ typical 74MHz field

Sources from WENSS

Long integration with VLA

Single 2D Fourier transform Faceted Fourier transforms W projection

Problem 2: ionospheric phase fluctuations

Phase changes of >1 rad/minute typical on 35 km baselines at 74 MHz. Sources may be too weak and/or confused to allow self-calibration

Short integration times required, especially for arrays with long baselines (6.667s used for VLA A configuration)

Dual-frequency observing can potentially correct the phase; GPS observations useful for phase and Faraday rotation

74 MHz phase

330 MHz phase(scaled and offset)

Residual 74MHz-scaled 330 MHz

Anisoplanatism

Ionospheric isoplanatic patch = region over which signals passing through the ionosphere maintain a constant phase relation

Typically 3o – 4o at 74 MHz VLA A configuration (cf. 17o for primary beam)

Larger for more compact arrays

Analogous to the problem of adaptive optics for optical/IR telescopes

Standard phase transfer from a calibrator will not work

Dealing with anisoplanatism

Two different approaches

“Peeling” (best suited to long-baseline arrays)Separate complex gain solutions for individual bright confusing sourcesImage and subtract from uv data, then discard solutionDeal with sources in sequence

“Adaptive optics” (better for more compact arrays)Model the ionospheric wavefront error over the array as a function of

direction using orthogonal polynomials (low-order Zernikes aka – tilt, focus, astigmatism, coma)

Fit this to shifts in position of known sourcesDerive a correction as a continuous function of direction and time

No general solution combining the two approaches has yet been found.

Problem 3: interference

Natural (lightning; static discharges)

Few protected bands; FM transmission, mobile phones, ….

Sometimes local: most of the interference in the 74 MHz band at the VLA is self-generated.

Narrow spectral channels are required to identify and remove interference (hence no problem with bandwidth smearing)

Automatic recognition and removal is difficult, but absolutely required for the next generation of low-frequency arrays.

WSRT at 150 MHz (1 kHz resolution)

VLA 74 MHz

Angular resolution ≈ 24, 80, 260, 850 arcsec (A, B, C, D configurations); better with Pie Town

Low bandwidth (780 kHz) and aperture efficiency (0.15)

Noise 10-20 mJy/beam in 12 hours; depends on Galactic latitude

All-sky survey (VLSS) in progressB and BnA arrays, 80 arcsec FWHM

100 mJy/beam rms.

Entire sky N of -30o

Images + catalogue

High-resolution VLA images

Cygnus A Cas AVLA A configuration + Pie Town antenna

WSRT

Low-frequency front ends (LFFE) 115 – 180 MHz

8 x 2.5 MHz bands, each 64 channels

Maximum baseline 3 km (≈2 arcmin resolution)

Full polarization

Thermal noise 1 mJy/beam in 12 hours (higher in Galactic plane), but confusion noise higher (2-5 mJy/beam)

May be able to calibrate ionospheric Faraday rotation at these frequencies and therefore make observations in linear polarization

Some low-frequency results from WSRT

Field of 3C14710o x 10o

Single phase Solution

Average of 2 x 2.5MHzbands

Low-frequency polarization at WSRT

Polarization position angleof pulsar PSR1937+21

Off-axis polarization

Off-axis polarization (2)

GMRT

Band (MHz) 50 153 233Primary beam (deg) 3.8 1.8Beam FWHM (arcsec) total 20 13

(arcmin) compact 7 4.5

RMS thermal noise (µJy/beam) 46 1716 MHz bandwidth, 10 hours

N.B. RMS noise will always be limited by confusion,interference etc.

Some GMRT results

Abell 3562

235 MHz, 5 hours16 MHz bandwidth

18 x 12 arcsec

rms noise 0.8 mJy/beam

Tiziana Venturi

Low-frequency data reduction

PlanningInclude very bright calibrator (e.g. Cyg A) to calibrate instrumental gain

and bandpass without serious impact from RFI. Observe once/hour.

Calibrator will be resolved, so need one with a model

Avoid the Sun (scattering from solar wind)

Avoid sunrise and sunset (ionospheric ionization/recombination); prefer night-time

Consider simultaneous observations at another frequency (4P mode at the VLA) to solve for ionospheric phase

Use a short integration time (6.667s for VLA)

Initial check for RFI

Calibrate bandpass

Initial RFI check

Output fromPOSSM beforecalibration, showing “comb”of interference

Bandpass calibration

Gain calibration and RFI removal

Basic approach to gain calibration is to use a very bright source with an accurate model over a range of channels with little interference (CALIB/CLCAL).

No attempt to deal with ionospheric phase variations at this stage, as essentially all fields have enough flux to self-calibrate.

Display interference with SPFLG to set parameters for automatic flagging using a representative sample of data.

Flag on level and rms (FLGIT)

If all else fails, look at data by baseline and channel and flaginteractively (very, very boring)

Examples

time

Before AfterInteractive clip optionchannel

Example display for 3 baselines

Imaging and self-calibrationDecide whether you need to image the whole of the primary beam or just a limited area

Select facets to cover the selected area (SETFC)

Identify confusing sources from WENSS or NVSS and set small fields to cover them (also SETFC)

Image and CLEAN the selected fields (IMAGR)

Initial (phase) self-calibration options:Use model from IMAGRUse point-source models generated from WENSS/NVSS (FACES)

Iterate self-calibration in the usual way

Interpolate individual facets onto a common plane (FLATN). Beware that brightness is not conserved, although flux density is.

Peeling

If a common phase solution does not apply over the whole field, then:

Identify the brightest confusing source

Use FACES to make a point source model and scale the flux density to the correct value (usually known for these bright sources)

Run CALIB with this model

Subtract the source from the uv data (point or CLEAN model)

Discard the gain solution and move on to the next confusing source

Straightforward with multi-source files; requires CLINV to reverse the solution for single-source.

Same sources must be subtracted if combining arrays

Adaptive optics imaging

Not part of standard AIPS (Bill Cotton, VLAFM) but freely available

Filter phase solutions to derive instrumental terms (SNFLT) and apply these

Identify a grid of sources of known position around the target

Image a time-range; fit position shifts and derive form of ionospheric phase screen

Interpolate and apply to data

Image and CLEAN

VLAFM also does RFI removal

3C 31

3C31 VLSS 3C31 VLA A+BVLAFM 3C48 peeled off

(16 mJy/beam noise)

LOFAR

Under construction in the Netherlands (Phase 1 funded)

LOFAR (2)Phased array stations capable of producing one or more beams

Large collecting area – designed for EoR science

Two types of antenna, optimized for low and high frequency bands, excluding FM

Phase 1 has compact core and 45 remote stations; baselines to 100km; Phase 2 baselines to 400km

IBM BlueGene supercomputer + PC cluster + WAN

First fringes to test LOFAR stations have been obtained

Operations starting 2007

Exciting prospects for low-frequency radio astronomy in Europe