Upload
others
View
1
Download
0
Embed Size (px)
Citation preview
The Cosmic Radio Background
Douglas Scott+ Tessa Vernstrom & Jasper Wall
Astrophysics from radio to submillimetreBologna, February 2012
EUROPE: A probe designed to delve into the“Big Bang” that created the cosmos hasuncovered an enigmatic fog of microwaveradiation in the centre of our galaxy.European astronomers reported on Monday
PS Why don’t you get on with your talk!
The Cosmic Radio Background
Douglas Scott+ Tessa Vernstrom & Jasper Wall
Astrophysics from radio to submillimetreBologna, February 2012
The Cosmic Microwave BackgroundThe Cosmic Radio Background
Best blackbody in the Universe
(better than you can buy at Bob’sBetter Blackbody Boutique)
The Cosmic Microwave BackgroundCosmic Backgrounds
BLAST/SPIRE
ARCADE 2
Radio countsARCADE 2 − CMB
Absolute Radiometer for Cosmology, Astrophysics, and Diffuse Emission (PI: Al Kogut)Cooled system, compares sky with internal reference6 frequencies, 3−90 GHz (3−100 mm)Balloon payload, ARCADE 2 flight in 2006Found excess over CMB + CRB from known sources
ArXiv: 0901.0546; 0555; 0559; 0562
ARCADE 2 results
!T ! 1.2 K
!
!
1 GHz
"
!2.6
ARCADE 2 results
Excess measured over CMB
Most significant at 3 GHz
Could it be genuinely diffuse gas - probably not!
Dark matter signature - not!
What kinds of sources could produce it?
Let’s look at what’s known about radio counts
May as well do if for each frequency band
→ Vernstrom, Scott & Wall (2011)
(Also ground-based TRES measurements in 2008)
The Cosmic Radio Background
Vernstrom, Scott & Wall arXiv:1102.0814
Euclidean normalization(flat = no evolution)
One less factor of √S(contribution to CRBper log interval in S)
The Cosmic Radio Background
Vernstrom, Scott & Wall arXiv:1102.0814
Euclidean normalization(flat = no evolution)
One less factor of √S(contribution to CRBper log interval in S)
(higher frequency bands)
The Cosmic Radio Background
Vernstrom, Scott & Wall arXiv:1102.0814
4 Vernstrom et al.
Table 2. !2 values for best fits at each of the frequencies
" !2 Degrees of A0 A1 A2 A3 A4 A5
MHz Freedom
150 68 45 6.58 0.36 !0.65 !0.19 0.26 0.099325 59 34 5.17 0.029 !0.11 0.36 0.17 0.20408 66 44 4.13 0.13 !0.34 !0.003 0.035 0.01610 75 59 3.02 0.71 0.97 0.91 0.28 0.0281400 4230 196 2.53 !0.052 !0.020 0.051 0.010 !0.00134800 32 47 1.95 !0.076 !0.15 0.020 0.0029 !0.000798400 41 29 0.79 !0.10 !0.23 !0.051 !0.019 !0.0029
Table 3. Values of the integrated sky brightness and tempera-ture contribution from radio source count for di!erent frequencybands. The uncertainties are 1# limits determined from Markovchain polynomial fits to the data. The high and low extrapolationsare discussed in the text.
" "I! T $T Extrapolated THigh Low
MHz W m!2 sr!1 mK mK mK mK
150 1.8 "10!14 17800 300 29400 18100325 2.1 "10!14 2800 600 5040 3100408 2.9 "10!14 1600 30 3000 1850610 4.2 "10!14 710 90 1200 7401400 7.5 "10!14 110 20 180 1104800 8.0 "10!14 3.2 0.2 10.8 6.78400 9.6 "10!14 0.59 0.05 3.0 1.9
the temperatures relative to the 1.4GHz count. This takesthe form of
T (!) = A! !1.4GHz
"", (4)
where A is the power-law amplitude, and " the index. Weset A to the 1.4GHz value of 0.110 K, while Monte CarloMarkov Chains (reference section 3.2) were used to find thebest value of " = –2.28 ± 0.02. The results of this power-lawfit can be seen in Fig. 2. Once we have this normalizationto the 1.4GHz curve we can extend the limits of integrationfor the 1.4GHz data, constraining the end behaviour of thepolynomial. We make the assumption that the counts fall o!after the end of the available data, using a choice of eithera steeper or shallower slope, to obtain both a high and lowestimate. To achieve this, artificial data points were addedpast where data are available, and the positions of thesepoints were varied until fits were obtained with the desiredend behaviour with reasonable slopes, while still making surethe curve fit the shape of the data, i.e. peaking in the ap-propriate place. These slopes were chosen to be the mostreasonable steep and shallow estimates, with the #2s beinga factor of 5 and 7 greater than the best fit to the data alone.The higher estimate could have been allowed to have an evenshallower slope, therefore allowing for an even higher back-ground estimate; however anything much shallower than thechosen fit would have #2 values several times larger than thebest fit to just the data. This fact makes any shallower fitsan unreasonable choice. The best fits for the extrapolationscan be seen in Fig. 3. In this figure the dashed line (the
Figure 2. Integration results and best fit power-law from Equa-tion 4.
higher estimate) is the shallower slope which falls o! moreslowly after the end of the data, while the solid line is asteeper slope fit to the data.
With these high and low extrapolation estimates for the1.4GHz data, we use Equation 4 to obtain estimates for theother frequencies. The steep slope estimate for the 1.4GHzdata ends up giving nearly the same result for the back-ground temperature as the unextrapolated estimate, due tothe fact that, while the limits of integration have been ex-tended, we controlled the end behaviour such that it falls o!steeply after the available data, whereas in the unextrapo-lated estimate the end of the curve is allowed to rise. Thelower extrapolation is thus essentially what would happenat the other frequencies if the shape of the curve were thesame as at the 1.4GHz fit.
The results of the extrapolated estimates are also givenin Table 3. Since even these reasonable extrapolations canchange the background estimates by about a factor of 2, thisshows how important it is to continue to push the counts tofainter limits.
3.2 Uncertainty – Monte Carlo Markov Chains
To investigate the uncertainties thoroughly, we carried outour fits with Monte Carlo Markov chains for each of the datasets, using CosmoMC (Lewis & Bridle, 2002) as a genericMCMC sampler. The #2 function was sampled for each setusing the polynomial in equation 1, which was then fed tothe sampler to locate the #2 minimum. Each of the six pa-
c# 2011 RAS, MNRAS 000, 1–9
Radio count lower limitsto background
About the right slopebut low by ~3−7
The Cosmic Radio Background
Vernstrom, Scott & Wall arXiv:1102.0814
Radio count lower limits
ARCADE (extrapolated)
ARCADE
What kind of sources?
Vernstrom, Scott & Wall arXiv:1102.0814
8 Vernstrom et al.
Figure 7. The 1.4 GHz source count data. The solid line givesthe best fit to the data while having a moderate slope at thefaint end, while the thick solid line is our best fit to the 1.4 GHzdata from Section 2. The other three lines are bumps peaking at7.9 (dotted), 5.0 (dashed), and 3.1 (dot dash) µJy which producethe background temperature necessary to match the ARCADE 2results. On this plot the height of such a bump is proportional to
S1/2peak
necessary contribution to the background. We saw that abump could exist in this range, peaking at fluxes as brightas 8 µJy, and could integrate up to the excess emission of ±320mK, with a height that is consistent with the data.
We still have no direct evidence that such a new popu-lation exists, and so further investigation into the faint endof the counts is needed. The infrared and radio connectioncould be used to test this idea through use of signal stackingand by examining di!erent possible luminosity functions tolook at the evolution of such a population. The final answermay only be reached when source count data available in theµJy range, perhaps in the era of the EVLA and eventuallythe SKA.
ACKNOWLEDGMENTS
This research was supported by the Natural Sciences andEngineering Research Council of Canada.
REFERENCES
Altschuler D. R., 1986, Astron. Astrophys. Suppl. Ser., 65,267
Benn C. R., Grue! G., Vigotti M., Wall J. V., 1982, MN-RAS, 200, 747
Blake C., Wall J., 2002, MNRAS, 337, 993Bondi M., Ciliegi P., Schinnerer E., Smolcic V., Jahnke K.,Carilli C., Zamorani G., 2008, ApJ, 681, 1129
Bondi M., Ciliegi P., Venturi T., Dallacasa D., Bardelli S.,Zucca E., Athreya R. M., Gregorini L., Zanichelli A., LeFevre O., Contini T., Garilli B., Iovino A., Temporin S.,Vergani D., 2007, Astronomy & Astrophysics, 463, 519
Bondi M., Ciliegi P., Zamorani G., Gregorini L., VettolaniG., Parma P., de Ruiter H., Le Fevre O., Arnaboldi M.,Guzzo L., Maccagni D., Scaramella R., Adami C., Bardelli
S., Bolzonella M., Bottini D., Cappi A., 2003, Astronomy& Astrophysics, 403, 857
Brandt W. N., Hasinger G., 2005, Ann.Rev.Astr.Ap., 43,827
Bridle A. H., Davis M. M., Fomalont E. B., Lequeux J.,1972, A.J., 77, 405
Ciliegi P., McMahon R. G., Miley G., Gruppioni C.,Rowan-Robinson M., Cesarsky C., Danese L., Frances-chini A., Genzel R., Lawrence A., Lemke D., Oliver S.,Puget J., Rocca-Volmerange B., 1999, MNRAS, 302, 222
Condon J. J., Mitchell K. J., 1984, A.J., 89, 610de Zotti G., Massardi M., Negrello M., Wall J., 2010, As-tronomy & Astrophysics Reviews, 18, 1
Donnelly R. H., Partridge R. B., Windhorst R. A., 1987,ApJ, 321, 94
Feretti L., Burigana C., Enßlin T. A., 2004, New Astron-omy Reviews, 48, 1137
Fixsen D. J., 2009, ApJ, 707, 916Fixsen D. J., Kogut A., Levin S., Limon M., Lubin P., MirelP., Sei!ert M., Singal J., Wollack E., Villela T., WuenscheC. A., 2009, ArXiv e-prints
Fomalont E. B., Kellermann K. I., Cowie L. L., Capak P.,Barger A. J., Partridge R. B., Windhorst R. A., RichardsE. A., 2006, Ap.J. (Suppl), 167, 103
Fomalont E. B., Kellermann K. I., Partridge R. B., Wind-horst R. A., Richards E. A., 2002, A.J., 123, 2402
Fomalont E. B., Kellermann K. I., Wall J. V., Weistrop D.,1984, Science, 225, 23
Garn T., Green D. A., Riley J. M., Alexander P., 2008,MNRAS, 387, 1037
Gervasi M., Tartari A., Zannoni M., Boella G., Sironi G.,2008, ApJ, 682, 223
Gregory P. C., Scott W. K., Douglas K., Condon J. J.,1996, Ap.J. (Suppl), 103, 427
Grue! G., 1988, Astronomy & Astrophysics, 193, 40Gruppioni C., Ciliegi P., Rowan-Robinson M., Cram L.,Hopkins A., Cesarsky C., Danese L., Franceschini A., Gen-zel R., Lawrence A., Lemke D., McMahon R. G., Miley G.,Oliver S., Puget J., Rocca-Volmerange B., 1999, MNRAS,305, 297
Haarsma D. B., Partridge R. B., 1998, ApJl, 503, L5+Hales S. E. G., Baldwin J. E., Warner P. J., 1988, MNRAS,234, 919
Hauser M. G., Dwek E., 2001, Ann.Rev.Astr.Ap., 39, 249Henkel B., Partridge R. B., 2005, ApJ, 635, 950Hopkins A. M., Afonso J., Chan B., Cram L. E., Geor-gakakis A., Mobasher B., 2003, A.J., 125, 465
Ibar E., Ivison R. J., Biggs A. D., Lal D. V., Best P. N.,Green D. A., 2009, MNRAS, 397, 281
Katgert J. K., 1979, Astronomy & Astrophysics, 73, 107Katgert P., Oort M. J. A., Windhorst R. A., 1988, Astron-omy & Astrophysics, 195, 21
Kuehr H., Witzel A., Pauliny-Toth I. I. K., Nauber U.,1981, Astron. Astrophys. Suppl. Ser., 45, 367
Lagache G., Puget J., Dole H., 2005, Ann.Rev.Astr.Ap.,43, 727
Lewis A., Bridle S., 2002, Phys. Rev.D, 66, 103511Longair M. S., 1966, MNRAS, 133, 421Longair M. S., Sunyaev R. A., 1969, Ap.J. (Letters), 4, 65Madau P., Pozzetti L., 2000, MNRAS, 312, L9McGilchrist M. M., Baldwin J. E., Riley J. M., TitteringtonD. J., Waldram E. M., Warner P. J., 1990, MNRAS, 246,
c! 2011 RAS, MNRAS 000, 1–9
Lots of scatter!Increasing?
Flat?
Decreasin
g?Bumps like these
would fit ARCADE
1.4 GHz
What kind of sources?
Extra sources fainter than ~10μJy
Could be just below current limits
But have to break the far-IR/radio correlation
Far-IR/radio correlation
1991ApJ...376...95C
Condon, Anderson & Helou 1991
What kind of sources?
Extra sources fainter than ~10μJy
Could be just below current limits
But have to break the far-IR/radio correlation
Search for them using stacking of optical/IR sources?
Improve the counts using careful P(D) approach
Pick 3GHz, where ARCADE is most discrepant
New EVLA data at 3 GHz
Single ~14 arcmin field
In “Lockman Owen” region (with ultra-deep 1.4GHz)
C configuration, FWHM ~ 7.5 arcsec
Expect ~1μJy rms
Use P(D) fitting
PI: Jim Condon
Observations start any day now
Karl G Jansky