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2016-2017 SAMSI Program on �Sta$s$cal,Mathema$calandComputa$onalMethods
forAstronomy(ASTRO)
G. Jogesh Babu
Sta$s$calandAppliedMathema$calSciencesIns$tute
Whyastrosta$s$cs?Astronomersencounterasurprisingvarietyofsta$s$calproblemsintheirresearch:
– Theskyhasvastnumbersofstars&galaxiesandgasonallscales.– Moststarshaveorbi$ngplanets,mostgalaxieshaveamassiveblackhole– Astronomersacquirehugedatasetsofimages,spectra&$meseriesof
planets,stars,galaxies,quasars,supernovae,etc.– Variousproper$esofcosmicpopula$onsobservedandempiricallystudied
withallkindsoftelescopes(n>>p)– Proper$esaremeasuredrepeatedlybutwithirregularspacing.– Spa$aldistribu$onsinsky(2D),space(3D),andparameterspace(pD)is
complex(MVNassump$onusuallyinapplicable)EricFeigelsonandIstartedcollabora$nginlate1980sandtheterm`Astrosta$s$cs’wascoinedinmid1990s,whenwepublishedabookbythesamename.
Astrosta$s$csatSAMSIAstrostatistics Program at SAMSI January 2006�
• Opening workshop January18-20,2006– Bayesian astrostatistics– Nonparametric inference– Astronomy for Statisticians
• Working groups – Exoplanets, Surveys & Population studies– Gravitational Lensing, – Source detection & feature detection– Particle Physics
• Concluded with SCMA IV at Penn State in June 2006
Astrosta$s$csatSAMSIAstrostatistics sub Program Fall 2012
Statistical and Computational Methodology for Massive Datasets • Workshop September19-21,2012– Thesearchfortransients– Missions(Fermi,SDSS.DES,Plank,LSST,LIGO)– Sparsity(high-dimensionaldata,butlow-dimsignal)– DataMining
• Working groups – Discovery&Classifica$oninSynop$cSurveys;– Inference&Simula$oninComplexModels,– Stochas$cProcesses&AstrophysicalInference– GraphicalModels&GraphicsProcessors
Astrosta$s$csatSAMSI
Exoplanets Summer 2013
ModernSta$s$calandComputa$onalMethodsforAnalysisofKeplerData
June10-28,2013
Astrosta$s$csatSAMSI
Sta4s4cal,Mathema4calandComputa4onalMethodsforAstronomy 2016-2017�
• Opening workshop August22-26,2016– TimeDomainAstronomy– ExoplanetDataanalysis,HierarchicalModeling– Uncer$nity,selec$oneffectsetc.,inGW– PulsarTimingArraysandDetec$onofGWs– Non-sta$onary,non-Gaussian,Irregularlysampledprocesses.– Sta$s$alissuesinCosmology
SAMSIASTROProgramis$mely
• Gravita$onalWavesDetected100yearsaeerEinstein’sPredic$on
• FirstGW(GW150914)wasdetectedbyLaserInterferometerGravita$onal-WaveObservatory(LIGO)Confirmingamajorpredic$onofAlbertEinstein’s1915generaltheoryofrela$vity.(GWfromcollidingBlackHoles).
• Theplanningmee$ngonSeptember21,2015includedLIGOscien$stswhohadonlyjustlearnedofthecandidatedetec$on,andhadtokeepitsecretun$lconfirmedandannouncedonFebruary11,2016.AsecondGWevent(GW151226)wasannouncedonJune15,2016.ItwasrecordedonDecember26,2015.
WorkingGroups
I. UncertaintyQuan$fica$onandAstrophysicalEmula$on
II. Synop$cTimeDomainSurveys
III. Mul$variateandIrregularlySampledTimeSeries
IV. AstrophysicalPopula$ons
V. Sta$s$cs,computa$on,andmodelingincosmology
UncertaintyQuan$fica$onandAstrophysicalEmula$on
• UncertaintyQuan$fica$on(UQ)andReducedOrderModeling(ROM)areatthecoreofmanyproblemsingravita$onandcosmology,fromdirectsimula$onsoftheEinsteinequa$onstotheinverseproblem(inferenceproblem).
• Thegoalofthisworkinggroupistoleverageexper$sefromareassuchasgeneralizedpolynomialchaosandsimulatoremula$onbasedonstochas$cprocesses,anddomain-areassuchasgravita$on,astrophysics,andcosmology.GroupLeaders:DerekBingham(SimonFraser),EarlLawrence(LANL)
Synop$cTimeDomainSurveys• TDAhasbeengekngricherintermsofdatasetsthatspanseveral
years,manybands,andincludedenseandsparselight-curvesforhundredsofmillionsofsources.
• Thevariety,volumeetc.squarelyfallinBigDataregime.• Thelight-curvesoeenhavelargegaps,areheteroskedas$c,and
theintrinsicvariability–oeenpoorlyunderstood–addsanelementofuncertaintywhenmul$-banddataarenotobtainedsimultaneously.– Kepler-typeplanetsearch/characteriza$on(alsoinotherWGs)
– binaryblack-holesearchesfromCRTTransientSurvey
GroupLeaders:AshishMahabal(Astro,Caltech),G.JogeshBabu(Stat,PSU)
AshishMahabalwilldiscusssomeoftheworkundervarioussubgroupsofthisWG.
Mul$variateandIrregularlySampledTimeSeries• Ground-basedphotometricsurveys,withbillionsofirregularlightcurves,detectstellarvariabilityfromamul$tudeofsources,fromplanetarytransits,tosupernovae.Howdoweeffec$velyseparatetheseclassesinirregularlysampleddata?
• Howcanwemaximizethesensi$vityofspace-basedphotometricsurveysfordetec$ngsmallplanetsinthepresenceofstellarac$vity?
• Howcanwemeasureplanetmassesrobustlydespiteobserva$onaldatawithoutliers(duetostellarac$vityaffec$ngeitherDopplerdataortransit$mes)?GroupLeaders:BenFarr(Astro,U.Chicago),SoumenLahiri(Stat,NCSU)
Sta$s$cs,Computa$on,andModelingin
Cosmology• Willbringtogetherleadingresearchersin
cosmology,computa$onalspa$alandBayesiansta$s$cs,experimentaldesign,andcomputermodelingtodevelopmethodologynecessaryforansweringfundamentalques$onsabouttheoriginandlargescalestructureoftheuniverse.
• Howcanwemakeinferencesfordeterminis$cnonlineardynamicalsystems(inferenceofini$alcondi$onsandmodelparameters)?
GroupLeaders:JeffJewell(Astro,JPL),JoeGuinness(Stat,NCSU)
JeffJewellwilldiscusstheapplica4onsareasunderthisWG.
AstrophysicalPopula$ons• Improvethesta$s$calmethodologyforinterpre$ngdetec$onsof
exoplanets,gravita$onalwaves(GW),aswellasusingthosetoinfertheunderlyingpopula$onofplanetarysystemsandGWsources.
• Theexoplanetscommunityispar$cularlyinterestedindevelopingtechniquestorobustlydetectandcharacterizeplanetsinthepresenceofstellarac$vityfromDopplerSurveysforwhichwedonothaveafirstprinciplesmodel.
• TheGWcommunityisinterestedindetec$nggravita$onalwavesourcesforwhichthedetailsoftheprimaryGWsignaland/orbackgroundsareunknown.
• Bothapplica$onsrequiredevelopingalgorithmstoefficientlyexplorehigh-dimensionalparameterspacesandtoestablishconfidenceindetec$ons,despitecomplexandunknownsourcesofbackgroundsignalsthat“noise”.
GroupLeaders:JessiCisewski(Stat,Yale);EricFord(Astro,PennState)JessiCisewskiwillnowdiscusssomeoftheprogressmadeunderthisWG.