Matt Jarvis - Recent results from the Herschel-ATLAS

Recent results from the Herschel-ATLAS

Matt Jarvis

University of the Western Cape &

University of Hertfordshire

Herschel

3.5m primary

Launched in May 2009

Continuum capabilities from 70-550 microns

•  Contains as much energy as the optical / UV background

•  Half the energy emitted by stars and AGN since the Big Bang has been absorbed by dust and re-emitted at longer wavelengths

•  Herschel presents the first opportunity to study large samples of galaxies selected near the peak

Dole et al. 2006

The Cosmic IR background

Planck Herschel

GOODS North / HDF North

GOODS South CDFS ECDFS

Lockman wide & deep

Extended Groth Strip

Bootes

XMM/VVDS

SWIRE fields (EN1, EN2, ES1)

Spitzer-FLS

AKARI SEP

Courtesy of S. Oliver

HerMES+PEP

•  The widest area extragalactic survey with Herschel (~ 570 sq deg)

•  Consortium of 150+ astronomers worldwide led by Nottingham (Dunne) and Cardiff (Eales)

•  Covering 5 bands with PACS and SPIRE (100 – 500 microns) in fast parallel mode

•  5 sigma sensitivities of 132, 126, 33, 36 and 45 mJy / beam from 100-500µm

•  Detect ~105 sources to z~3

•  SDP = 3% of data = 7000 galaxies = 16 hrs!

The Herschel ATLAS

•  Chosen to maximize overlap with existing & planned survey data: GALEX, 2dF, SDSS, GAMA, UKIDSS, KIDS, VIKING, PanSTARRS, DES, MeerKAT, LOFAR , ASKAP etc

NGP & Equatorial

SGP

Fields

GAMA 9hr field (Driver et al. 2011)

•  250/350/500um •  no filtering •  cirrus background •  almost confused

Pascale et al 2010 The Herschel ATLAS

•  Sensitive to cold and warm dust giving the total mass of dust (and gas)

•  At high redshift, the shape of the curve means that galaxies don’t get much fainter at larger distances.

•  Study evolution of dusty star forming galaxies over the past 10 billion years of cosmic history

•  The sub-mm colours of the galaxies will give us clues to their redshifts

z=0 The dust SED

•  250um: –  beam 18.1” –  positional uncertainty ~2.4” –  minimal z info –  probes dust properties

•  SDSS r band: –  PSF ~1-2” –  positional uncertainty ~0.1” –  redshift & colour

information –  probes starlight/AGN

Smith et al. 2011

Cross-matching: the problem

(Smith et al. 2011) •  Likelihood ratio technique (e.g. Sutherland &

Saunders 1992)

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f (r) =1

2πσ pos

exp −r2

2σ pos

⎛

⎝ ⎜ ⎜

⎞

⎠ ⎟ ⎟

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n(m) = Probability density of possible counterparts i.e. SDSS r band number counts

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q(m) = Probability density of true counterparts – statistical excess

“The ratio of the probability that two sources are associated to the probability that the same two sources are unrelated”

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LR =f (r)q(m)n(m)

Radial probability density – estimate from comparing HATLAS & SDSS positions

Identifying counterparts

“The ratio of the probability that two sources are associated to the probability that the same two sources are unrelated”

Radial probability density – estimate from comparing HATLAS & SDSS positions

Introduce the Reliability:

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Ri =Li

L j + 1−Q0( )j∑

Can define a catalogue of 5sigma 250um sources with R>0.8 optical counterparts.

Smith et al. (2011)


•  LR method allows for the fact that not all 250um galaxies are detected in Sloan r band:

•  Q0 = ~63% of 250um sources have an r band counterpart in SDSS

Smith et al. (2011)


•  LR method allows for the fact that not all 250um galaxies are detected in Sloan r band:

•  Q0 = ~63% of 250um sources have an r band counterpart in SDSS

Smith et al. (2011)


•  Smith et al., submitted

H-ATLAS: Complete SEDs

Chary & Elbaz (2001) vs Smith et al. 2011

• Normalised to LFir

• Binned according to matched luminosities

• 1sigma uncertainty regions shown in grey hatchings

• CE01 models too hot for 250um selected galaxies

Comparisons with other models

H-ATLAS: The luminosity function

Dye et al. 2010

Dust mass varies by factor of 5 - not T

High z SMGs @ z~2.5(Dunne 2003) T=25K

Dunne et al. 2011

H-ATLAS: Evolution of dust

Herschel sources in and around galaxy clusters

Coppin et al. 2011

Excess of far-infrared sources towards the centre of galaxy clusters in the local Universe

H-ATLAS: Environments of dusty galaxies

Burton, MJJ, et al. in prep.

Herschel sources in and around galaxy clusters H-ATLAS: Environments of dusty galaxies

Optical sources

Far-IR bright sources

Find a tendency for far-IR bright galaxies to reside in less dense environments that a matched sample of non-far-IR galaxies

Suggests that gas is stripped out of galaxies in dense environments, thus hindering star-formation activity

Negrello et al., 2010, Science

H-ATLAS: lenses in the SDP field


Negrello et al. in prep.



Negrello et al. in prep.




Flux @ 1.6 µm ~ 10 µJy

CREDITS: Rosalind Hopwood

Lens subtraction @ F160W


To extract the maximum amount of science from these lenses, accurate redshifts of both the lens and the lensed source are required.

SALT is going to be the leading telescope to obtain accurate redshifts of the lenses in the southern hemisphere (PI Leeuw).

Redshifts for the lensed sources requires mm-wavelength observations of redshift CO. ALMA and ATCA will do this in the southern hemisphere.

H-ATLAS: High-z galaxies

Isolating high-dusty galaxies (Negrello et al. 2010)

2.5 < z < 5

Lensing in HerMES

Isolating high-dusty galaxies (Negrello et al. 2010)

2.5 < z < 5

Wang et al. 2011

Wang et al. 2011

Evidence for lensing induced cross-correlations between background (high-z) far-IR sources and foreground (low-z) optical galaxies

Lensing in HerMES

H-ATLAS: Galaxy Clustering

Maddox et al. 2010

van Kampen et al. submitted

Clustering as a function of z by combining H-ATLAS with GAMA

H-ATLAS: Galaxy Clustering

Amblard et al. 2011, Nature Brightness fluctuation

analysis of two HerMES fields

H-ATLAS fluctuation

analysis to follow this year, over ~30

degree scale!

HerMES: Fluctuation Analysis

One of the key unknowns in astrophysics is how active galactic nuclei influence the formation and evolution of galaxies.

H-ATLAS: AGN-star formation

Luminosity

Benson et al. (2003)

Den

sity

of g

alax

ies

/mag

nitu

de

One of the key unknowns in astrophysics is how active galactic nuclei influence the formation and evolution of galaxies.


Luminosity

Benson et al. 2003

Den

sity

of g

alax

ies

/mag

nitu

de

Feedback is not understood in models of galaxy formation.

2 mechanisms proposed to stop

gas cooling to form stars

Active Galaxies

Supernovae

Cao Orjales, Stevens, MJJ et al., in prep

Long standing issue as to whether BAL QSOs are an early stage in QSO evolution when the outflow terminates a period of star formation, or just a simple orientation effect

H-ATLAS: BAL QSOs and unification

Cao Orjales, Stevens, MJJ et al., in prep

Long standing issue as to whether BAL QSOs are an early stage in QSO evolution when the outflow terminates a period of star formation, or just a simple orientation effect

H-ATLAS: BAL QSOs and unification

•  Hardcastle, Virdee, MJJ, et al. 2010


•  Hardcastle, Virdee, MJJ, et al. 2010


Virdee, Hardcastle, MJJ, et al. in prep. Hardcastle, Ching, MJJ et al. in prep.


With the larger sample we see a higher star-formation rate associated with more powerful radio galaxies.

In line with current views that powerful AGN are fueled by the influx of cold gas via galaxy mergers, whereas lower power radio sources are fueled by the hotter ICM


One of the key unknowns is accurate redshifts at high-z and optical emission-line classification of AGN and star-forming galaxies

SALT observations are going to address this issue (PI MJJ)

Virdee, Hardcastle, MJJ, et al. in prep. Hardcastle, Ching, MJJ et al. in prep.

•  The far-infrared—radio correlation is key to using future radio surveys to measure the star-formation history of the Universe

•  FIRC looks to be very similar at low and high redshift

•  Puzzling - as would expect evolution!

H-ATLAS: Far-IR—radio correlation

Jarvis et al. 2010, MNRAS, 409, 92

•  The far-infrared—radio correlation is key to using future radio surveys to measure the star-formation history of the Universe

•  FIRC looks to be very similar at low and high redshift

•  Puzzling - as would expect evolution!

H-ATLAS: Far-IR—radio correlation

Jarvis et al. 2010, MNRAS, 409, 92

(a factor of ~10 shallower than LOFAR deep field data and 100 times shallower than MIGHTEE Tier 3)

McAlpine & MJJ in prep.

10 arcmin

The new generation of radio surveys

McAlpine, Smith, MJJ, Bonfield in prep.

The likelihood ratio on the new radio surveys

WODAN

EVLA B-array

ASKAP-EMU

Resolution does matter in continuum radio surveys for X-matching.

Key to almost all science!

MeerKAT will excel at this compared to ASKAP and APERTIF!

Currently extending to fainter fluxes using COSMOS data.



WODAN

EVLA B-array

ASKAP-EMU

Depth of optical/nearIR data also crucial!

Again the MeerKAT-MIGHTEE deep fields will have the best optical/near-IR data available!

K=22.6 K=20



WODAN

EVLA B-array

ASKAP-EMU

Depth of optical/nearIR data also crucial!

Again the MeerKAT-MIGHTEE deep fields will have the best optical/near-IR data available!

K=22.6 K=20

Redshifts are also important for science exploitation.

SALT-MOS observations will provide these (PI McAlpine)

Radio surveys with SKA precursors Constraints on the evolution of star-forming galaxies

Radio surveys with SKA precursors Constraints on the evolution of AGN

Raccanelli et al. (2011) present several predictions of the constraints that can be obtained on modified gravity and the cosmology using the new generation of wide-area radio continuum surveys.

The link to cosmology

Cosmology with the radio continuum surveys requires information from most of the science I have presented.


The redshift distribution of radio sources is fundamental to many tests, such as ISW, lensing etc

The new surveys will be dominated by star-forming galaxies and low luminosity AGN.

We know the least about the redshift evolution of these objects!

Herschel gives us information on the evolution of the SFGs

Nikhita & Kim both working on this

Wilman, MJJ et al. 2010 Raccenelli et al. 2011



The evolution of bias is also key.

This is one of the most uncertain factors in the prediction presented in Raccanelli et al. (2011)

Using GAMA+FIRST and SDSS-Stripe82+EVLA data we can pin this down to z~0.7 (Lindsay, MJJ & Percival in prep) Wilman, Miller, MJJ et al. 2008

Raccanelli et al. 2011



The evolution of bias is also key.

This is one of the most uncertain factors in the prediction presented in Raccanelli et al. (2011)

Using GAMA+FIRST and SDSS-Stripe82+EVLA data we can pin this down to z~0.7 (Lindsay, MJJ & Percival in prep) Wilman, Miller, MJJ et al. 2008

Raccanelli et al. 2011

But for SFGs and starbursts can use the measurements from Herschel surveys

•  Herschel is providing new and important insights into the evolution of galaxies, from the star-formation history of the Universe, the evolution of dust, the influence of AGN activity etc.

•  Over the next year or so, Herschel will also be working in pinning down the shape of dark matter haloes through strong lensing, magnification bias over ~500 sq.deg and clustering of starburst galaxies at z~2.

•  We are using the techniques developed for Herschel and the science results from Herschel to input into the design and implementation of the new generation of radio continuum surveys.

•  All of this information is key for our understanding of both galaxy evolution and cosmology

Summary

Matt Jarvis - Recent results from the Herschel-ATLAS

Technology

um galaxies

r band counterpart

sloan r band

sdp field negrello

probability lr

radial probability density

unrelatednm1 r

galaxies dont