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Radio variability properties for radio sources

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arXiv:astro-ph/0701540v1 18 Jan 2007Astronomy&Astrophysicsmanuscriptno.4775textc󰀊ESO2008

February5,2008

Radiovariabilitypropertiesforradiosources

J.H.Fan1,2,Y.Liu1,Y.H.Yuan1,T.X.Hua1,H.G.Wang1,Y.X.Wang3,J.H.Yang4,A.C.Gupta5,J.Li1,J.L.Zhou1,

S.X.Xu1,andJ.L.Chen1

1CenterforAstrophysics,GuangzhouUniversity,Guangzhou510006,China2PhysicsInstitute,HunanNormalUniversity,Changsha,China3CollegeofScienceandTrade,GuangzhouUniversity,Guangzhou511442,China4DepartmentofPhysicsandElectronicsScience,HunanUniversityofArtsandScience,Changde415000,China5TataInstituteofFundamentalResearch,HomiBhabhaRoad,Colaba,Mumbai-400005,India

Received6June2006/Accepted??

ABSTRACT

Inthispaper,weusedthedatabaseoftheuniversityofMichiganRadioAstronomyObservatory(UMRAO)atthree(4.8GHz,8.0

GHZ,and14.5GHz)radiofrequencytoanalyzetheradiolightcurvesbythepowerspectralanalysismethodinsearchofpossible

periodicity.Theanalysisresultsshowedthattheradiosourcesdisplayastrophysicallymeaningfulperiodicityrangingfrom2.2to

20.8yearsintheirlightcurvesatthethreefrequencies.Wealsocalculatedthevariabilityparametersandinvestigatedthecorrelations

betweenthevariabilityparameterandthefluxdensity.Forthevariabilityparameters,wefoundthattheparametersathigherfrequency

arehigherthanthoseinthelowerfrequency.Inaddition,thevariabilityparametersofBLLacertaeobjectsarelargerthanthoseof

flat-spectrumradioquasars.suggestingthattheyaremorevariablethanflatspectrumradioquasars.

Keywords.Galaxies:blazars–radiocontinuum:general-Methods:Dataanalysis

1.Introduction

Thenatureofthecentralengineofblazarsandotherclassesof

activegalacticnuclei(AGNs)isstillanopenproblem.Blazars’

lightcurvesweregeneratedbyusingthedataoftheirmoni-

toringprogram,whichhaveyieldedveryvaluableinformation

aboutthemechanismsoperatinginthesesourcesandimpor-

tantimplicationsforquasarmodeling(Fanetal.,1998).Inthe

pasttwodecades,opticalmonitoringprogramofblazarsand

otherclassesofAGNshavebeenconductedextensivelybymany

groupsaroundtheglobe,andblazarswerereportedtodisplay

fluxvariabilityondiversetimescalesrangingfromafewmin-

utestohours,todays,tomonths,andtoevenmorethan10years

(Fan,2005b).Thevariabilitytimescaleonyearsgivesthelong-

termvariationinformationinthesourceandanimportanttool

predictingotheroutbursttimes.

RadiomonitoringprogramswerecarriedoutatBolognaat

408MHz(Bondietal.,1996),MichiganUniversityat4.8GHz,

8GHz,14.5GHz,andMets¨ahoviobservatoryat22GHz,37

GHz,87GHz,ESOsiteonCerroLaSilla,Chile,at90GHzand

230GHz(Tornikoskietal.,1996).Usingthedataofthesemon-

itoring,manygroupshaveinvestigatedthevariabilityproperties

andfoundthatblazarsshowinterestingresults.Basedonthisra-

diodatabase,Krausetal.(1999)reportthatblazars’emissionis

stronglybeamed,Lahteenmaki&Valtaoja(1999)estimatedthe

radioDopplerfactorsforasampleofradiosources,Ciaramella

etal.(2004)investigatedthepossibleperiodicityforseveralse-

lectedobjects,andAlleretal.(2003)investigatedothervariabil-

ityproperties.

Inthispaper,wemakeuseoftheUMRAOdatabasetoin-

vestigatethepossibleperiodicity,thevariabilityparameter,and

thecorrelationbetweenthesourcebrightnessandthevariability2J.H.Fanetal.:Radiovariabilitypropertiesforradiosources

First,definingtheinnerproductoftwofuncitonsfandgasthe

averagevalueoftheproductf∗govertheobservationtimes{tn},

weget

󰀋f|g󰀌=(1

2N[󰀋y|y󰀌−󰀋1|y󰀌2]/s2.(8)

Weadoptedthefalsealarmprobability,F(Horne&

Baliunas,1986),togiveaquantitativecriterionforthedetec-

tionofaperiodicsignalderivedbyDCDFT.Itwasdonewith

thefollowingsteps.First,thepowerleveloftheperiodogramis

normalizedbythetotalvariance,

PN(ω)=PX(ω)/δ2(9)

TheprobabilitythatPN(ω0)isofheightzorhigheris

Pr[PN(ω0)>z]=e−z.Supposethatzisthehighestpeakin

aperiodogramthatsamplesNiindependentfrequencies.The

probabilitythateachindependentfrequencyissmallerthanz

is1−e−z,sotheprobabilitythateachfrequencyislowerthan

zis[1−e−z]Ni.Thus,thefalsealarmprobability(FAP)canbe

defined,

F=1−[1−e−z]Ni(10)

TocomputeFAP,weneedtoknowNi,whichisnottoodifficult

toobtainbyasimpleMonteCarlomethod.TheFAPtellsus

theprobabilitythatapeakofheightzwilloccur,assumingthat

thedataarepurenoise.Consequently,thequantity1−Fisthe

probabilitythatthedatacontainasignal.

ForillustrationwepresenttheanalysisresultsinFig.1for

thestrongsignofperiodsin0605-085at8GHz,withthethe-

oreticalresultobtainedusingtwoperiods,namelya7.16-year

periodwithanamplitudeof0.582anda4.49-yearperiodwith

anamplitudeof0.168,andFig.2fortheweakestsignofperiods

in1040+123at8GHz.Fig.1.Thestrongsignofperiodsin0605-085at8GHz.Theupperpanel

isforthelightcurveat8GHz,whilethelowerpanelisthepowerspec-

tralanalysisresult.

Fig.2.Theweakestsignofperiodsin1040+123at8GHz.Theupper

panelisforthelightcurveat8GHz,whilethelowerpanelisthepower

spectralanalysisresult.

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challengesbutalsoasteptowardsamoresustainablefuture.Heresadetailedlookatthe

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Introduction

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energy,thechallengesfacedintheiradoption,andthepotentialbenefitstheyholdfora

sustainablefuture.

FormsofNewEnergy

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OECD 305

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305

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