LOFAR

WEAVE-

Dutch stations: only these used for large area survey

Core 'superterp'

Core 'superterp'

HBA : 120 - 240 MHz

LBA : 30 - 80 MHz

Tier-1 : will cover whole northern hemisphere

(0.1 mJy RMS at 150 MHz)

Tier-2 :  ~100s of sq.deg to faint flux limits (25 μJy RMS @ 150 MHz)

Tier-3 : ~10s of sq.deg to sensitivities > the deepest existing imaging

(6 μJy @ 150 MHz)

Details: Röttgering et al. 2011

LOFAR Surveys KSP

LOFAR Surveys KSP

Relative to other radio surveys

LOFAR Surveys KSP

In physical terms...

LOFAR Surveys KSP

In physical terms...

Tier 1

Tier 2

Tier 3

Tier 3

Tier 2

Tier 1

LOFAR Surveys KSP

In physical terms...

Tier 1

Tier 2

Tier 3

Tier 3

Tier 2

Tier 1

-LOFAR

WEAVE

What is WEAVE?

WHT Enhanced Area Velocity Explorer

• WEAVE is a 960(/940) x 1.3” fibre multi-object spectrograph going on the 4.2m WHT
   
• First light Q1 2018
   
• 2 deg diameter field of view
   
• Complete wavelength coverage from 370–960nm at R=5000 in LR mode

WEAVE Science

• Galaxy Clusters
   
• Galaxy Evolution
  • STEPS
  • WEAVE-APERTIF


• WEAVE-LOFAR
   
• WEAVE-QSO

http://www.ing.iac.es/weave/science.html

• Archaeology
  (Gaia follow-up: radial velocity and abundances)
   
• Stellar, Circumstellar and Interstellar Physics

Galactic

Extra-galactic

What morphology problem do we want to solve?

So what's the catch?

Doubles/Triples and nice pretty jets...

The varied morphologies of radio sources

Doubles/Triples and nice pretty jets...

The varied morphologies of radio sources

6+ arcmin

~3 arcmin

~2 arcmin

~1 arcmin diameter

Bent or 'tailed' sources 

The varied morphologies of radio sources

Bent or 'tailed' sources 

Aside: automatically identifying large numbers of tailed sources will be an excellent way to find undiscovered clusters (both low-z and high-z)

The varied morphologies of radio sources

Some sources are extended and shouldn't actually have counterparts

But most sources are actually pretty nice

~3300 sources per ~10sq.deg field

92% - single component 'blobs' (some resolved)

3.4% - no obvious core (FRII type sources)

1% - classed as tailed sources

1% - radio halos and relics

Williams et al. (2015)

~3300 sources per ~10sq.deg field

92% - single component 'blobs' (some resolved)

3.4% - no obvious core (FRII type sources)

1% - classed as tailed sources

1% - radio halos and relics

Scaled to hemisphere

6 million

~250k

~70k

~70k

Williams et al. (2015)

~3300 sources per ~10sq.deg field

92% - single component 'blobs' (some resolved)

3.4% - no obvious core (FRII type sources)

1% - classed as tailed sources

1% - radio halos and relics

Scaled to hemisphere

6 million

~250k

~70k

~70k

Including deeper tiers LOFAR = 30 million sources

EMU = 70 million sources

Can we cut down number of visual classification/IDs?

Williams et al. (2015)

Size

Class 1 =  Single source (may be resolved)

Class 11 = Multiple components - clear core

Class 2 =  extended FRI or FRII type source

Analysis by W.Williams

Maybe non-parametric morphologies can help

Asymmetry?

Gini & M20?

Machine Learning

Kai Polsterer,

University of Bochum

Rotationally invariant SOMs

Machine Learning

Kai Polsterer,

University of Bochum

Credit: Tim Shimwell

Credit: Tim Shimwell