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Basics of Nuclear Data Evaluation and Perspectives. H. Leeb Atominstitut,TU Wien, Austria. Research at the Atominstitut. atomic physics , quantum optics (J. Schmiedmayer ). radiation physics ( Ch . Streli ). low-temperature physics , Super conductivity (H. Weber).

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Basics of nuclear data evaluation and perspectives l.jpg
Basics ofNuclear Data Evaluation andPerspectives

H. Leeb

Atominstitut,TU Wien, Austria

NuPECCMeeting,Vienna, March 13, 2009


Research at the atominstitut l.jpg
Research atthe Atominstitut

atomicphysics, quantumoptics

(J. Schmiedmayer)

radiationphysics

(Ch. Streli)

low-temperaturephysics,

Super conductivity

(H. Weber)

appliedquantumphysics

(N.N.)

neutronandquantumphysics

(H. Abele)

nuclearandparticlephysics

(H. Leeb)

NuPECC Meeting,Vienna, March 13, 2009


Nuclear and particle physics l.jpg
NuclearandParticlePhysics

NuclearPhysicsandNuclearAstrophysics(H. Leeb)

scatteringandreactiontheory, nucleardataevaluation

HadronPhysicsand Fundamental Interactions (M.Faber,

H. Markum)

exoticatoms, latticegaugetheory

Experimental ParticlePhysics(Ch. Fabjan)

detectordevelopments, dataanalysistechniques

directlylinkedtothe Institute of High EnergyPhysics

ofthe Austrian AcademyofSciences

NuPECC Meeting,Vienna, March 13, 2009


Nuclear physics and nuclear astrophysics l.jpg
NuclearPhysicsandNuclearAstrophysics

Theoreticaldescriptionofscatteringandreactionprocesses

andtheinterpretationof observables withregardtointeractions

andunderlyingstructures in basicandappliedphysics

Scatteringandreactiontheory

  • inverse scatteringtechniques

  • opticalpotentialsandspecificreactions

  • phaseproblem in quantummechanics

Neutron-inducedreactions

  • nucleardataevaluation

  • nuclearastrophysics

involvement in theexperiments

[email protected] in Geel

NuPECC Meeting,Vienna, March 13, 2009


Experiments n induced cross sections l.jpg
Experiments: n-inducedcrosssections

[email protected]

(n,g) crosssectionsfortransmutationandastrophysics

GELINA (JRC)

(n,2n) crosssections via prompt g-decay

Experiments performedwithincollaboration:

TU Wien and University of Vienna

G. Badurek, E. Jericha, H. Leeb, A. Pavlik, A. Wallner

NuPECC Meeting,Vienna, March 13, 2009


N xn cross sections l.jpg
(n,xn) crosssections

E. Jericha (TU Wien)

A. Pavlik (Univ. Wien)

GELINA (JRC)

209Bi(n,2n) crosssections

Measurement of prompt

g-raysofthe residual

nucleus (even A)

4+

2 +

0 +

Mihailescu et al. ND2007

NuPECC Meeting,Vienna, March 13, 2009


N g cross sections l.jpg
(n,g) crosssections

[email protected]

(n,g) (n,f)

4p total absorption

calorimeter (TAC)

astrophysicalrelevance

s-process

mainresponsibilityof TU Wien: proper uncertaintyanalysis

NuPECC Meeting,Vienna, March 13, 2009


Experimental uncertainties at n tof l.jpg
Experimental uncertaintiesatn_TOF

232Th(n,g)

151Sm(n,g)

E‘ MeV

E MeV

151Sm(n,g)

232Th(n,g)

E‘ MeV

E‘ MeV

normalizedcovariancematrixofthen_TOFexperiment

NuPECC Meeting,Vienna, March 13, 2009


Nuclear data evaluation l.jpg
Nucleardataevaluation

Start of Modern Data Evaluation:

recommendedvaluesof fundamental physicsconstants (c, h, af, ... )

Dunnington (1939); Du Mond and Cohen (1953)

Present Status:

AtpresentEvaluatedNuclear Data Files represent a consistentsetof

crosssectionsandassociatedquantitiesfor all relevant reaction

processes. Most datafilesare limited totheenergyregionbelow

20MeV.

Thereexistseveralnucleardatalibrarieswithevaluatedcrosssection

data, but onlyfewfilescontainuncertaintyinformation thereliability

Is still an open question.

JEFF3.1, ENDF/B-VII, JENDL, CENDL, …

NuPECC Meeting,Vienna, March 13, 2009


Concept of evaluation l.jpg
Conceptofevaluation

Nucleardataevaluationisessentially a procedurefollowing

therulesofBayesianstatisticswithin a subjectiveinterpretationtheprobabilityreflectsourexpectation no experimental verification

Evaluation isgiven in termsof

- expectationvaluesof observables- covariancematricesof observables (crosssections)

BAYESIAN STATISTICS

NuPECC Meeting,Vienna, March 13, 2009


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Bayestheorem

Bayes Theorem (1763):

p(x|s M) = p(s |xM) p(x|M) / p(s |M)

posterior = likelihood x prior / evidence

x ... model parameter s ... data M ... other information

from experiment

Choice of proper prior ?

Expectationvalue:

Covariancematrixelement:

NuPECC Meeting,Vienna, March 13, 2009


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Evaluations donebyVonach et al.

First evaluations in thefieldofnucleardatewhichincludeuncertaintieswereperformedbyVonach et al. (Univ. Vienna) about 1990

Theyconsiderednucleiwheremany experimental datahavebeenavailable

 choiceofprior not essential

S. Tagesen, H. Vonach, A. Wallner, ND2007

NuPECC Meeting,Vienna, March 13, 2009


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Developments in nucleardataevaluation

  • CurrentDemands:

  • Inclusionofuncertaintyinformation covariancematrices

  • Extension ofenergyrangeto ~150MeV

  • Challenges:

  • Evaluation processandcovariancematrices – scarcityof experimental datafor E > 20 MeV quest ofuncertaintyofnuclearmodels

  • Improvementofmodels: nuclearreactions, fission, …

NuPECC Meeting,Vienna, March 13, 2009


Bayes theorem14 l.jpg
Bayestheorem

Bayes Theorem (1763):

p(x|s M) = p(s |xM) p(x|M) / p(s |M)

posterior = likelihood x prior / evidence

x ... model parameter s ... data M ... other information

from experiment

Choice of proper prior ?

Expectationvalue:

Covariancematrixelement:

NuPECC Meeting,Vienna, March 13, 2009


Choice of proper prior l.jpg
Choice of proper prior

GOAL

quantitative estimateofthereliabilityofnuclear model

basedevaluations

  • Define an almostunbiasedprior

  • Accountfor all aprioriknowledge

  • Minimal useof experimental data

NuPECC Meeting,Vienna, March 13, 2009


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Sourcesofuncertainties

The contributions to the covariance matrix of the model are

M(mod) = M(par) + M(num) + M(def)

parameter uncertainties

Model defects

non-statistical error

numerical

implementation

error

EFFDOC-1047

NuPECC Meeting,Vienna, March 13, 2009


Parameter uncertainties l.jpg
Parameter uncertainties

For most cases where there is no obvious prior Baye proposed to apply

Laplace principle of insufficient reasoning, i.e. a uniform distribution

Main criticism from objectivist: the choice of prior is arbitrary!!!

INFORMATION THEORY(Shannon 1949)

Information entropy:

The amount of uncertainty is maximal if the entropy is maximal.

Assumption: Besides the marginalisation we know an expection value

NuPECC Meeting,Vienna, March 13, 2009


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Theoryforpriordetermination

Principleof maximal informationentropy

Information Entropy

Constraints

Determination of

Lagrange par. l

prior

partition

function

variance

Invariant measure to account for continuous parameters:

for scaling parameters:

NuPECC Meeting,Vienna, March 13, 2009


Admissible range of parameters l.jpg
Admissiblerangeofparameters

dependence on av of

admissible range in rv

admissible range in av

z defines lower boundary

NuPECC Meeting,Vienna, March 13, 2009


Parameter distribution for 208 pb l.jpg
Parameter distributionfor208Pb

potential parameters

rv(fm)

v1(MeV)

NuPECC Meeting,Vienna, March 13, 2009


Parameter uncertainties correlations l.jpg
Parameter uncertainties-correlations

stotal

selastic

phenomenologicalopticalpotentials

microscopicopticalpotentials

NuPECC Meeting,Vienna, March 13, 2009


Model defects scaling l.jpg
Model defects - scaling

Global scaling factor for

each reaction channel c

Mean value and vairance for

each energy bin Em and

isotope n

This coarse approximation provides a covariance matrix

PROBLEM: not statistically defined

NuPECC Meeting,Vienna, March 13, 2009


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Model defectsof16O

Example16O

total crosssection

experimental datafor

12C,14N,19F,20Ne,23Na,24Mg

E MeV

E‘ MeV

0

30%

relative variance in %

E MeV

20%

60 10 60

NuPECC Meeting,Vienna, March 13, 2009


Correlations comparison l.jpg
Correlations - comparison

correlationsof total crosssection uncertainties16O

cut: E+E‘=const

0.6

0.0

complete prior

E MeV

60 10 60

more details in

Final report of

EFDA-TW6-TTMN-001B-D7a

0.6

parameter uncertainties

E MeV

60 10 60

NuPECC Meeting,Vienna, March 13, 2009


Importance of uncertainty information l.jpg
Importanceofuncertaintyinformation

cross section covariances

Safetymargins – commissioning

Reducethenumberof experimental tests

 significanteconomicimpact

NuPECC Meeting,Vienna, March 13, 2009


Implementation of bayesian statistics l.jpg
ImplementationofBayesianstatistics

Bayes Theorem (1763):

p(x|s M) = p(s |xM) p(x|M) / p(s |M)

posterior = likelihood x prior/ evidence

x ... model parameters ... dataM ... otherinformation

NuPECC Meeting,Vienna, March 13, 2009


Bayesian update procedure l.jpg
Bayesian update procedure

prior

x0 M0

Exp-01

x1 M1

Exp-02

x2 M2

Exp-03

x3 M3

Exp-m

xm Mm

experiment

posterior

NuPECC Meeting,Vienna, March 13, 2009


Problem of update procedure l.jpg
Problem of update procedure

prior

systematic

error

statistical error

Bayes theorem

Bayesian update

NuPECC Meeting,Vienna, March 13, 2009


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Origin ofthedifference

The ‚experiments‘ covariance

matrix V contains all experiments

and all correlations

Standard Bayesian update procedure – no correlations

between experiments

Systematic errors are treated like a

statistical uncertainty i.e.

NuPECC Meeting,Vienna, March 13, 2009


Evaluation tool geneus l.jpg
Evaluation Tool GENEUS

still manual

semi-automatic for single

isotope and restricted

reaction channels

not available

ENDF-file

tables

graphics

PRIOR

TALYS

SC2COV

BAYES

SCALE

one-step procedure

EXFOR

Janis-Tables

EXPCOV

NuPECC Meeting,Vienna, March 13, 2009


Perspective s l.jpg
Perspectives

  • CurrentDemands:

  • Inclusionofuncertaintyinformation covariancematrices

  • Extension ofenergyrangeto ~150MeV

  • Challenges:

  • Evaluation processandcovariancematrices – scarcityof experimental datafor E > 20 MeV quest ofuncertaintyofnuclearmodels

  • Improvementofmodels: nuclearreactions, fission, …

NuPECC Meeting,Vienna, March 13, 2009


Topics in nuclear reactions l.jpg
Topics in nuclearreactions

  • Future research will focus on challenges in reactiontheory:

  • Reactionsinvolvingchargedcompositenucleiembrittlement due to gas production in structurematerials p-processreactions in nuclearastrophysics, (a,g), (p,g)

  • Reactionsinvolvingweaklyboundnucleibreak-upcontributions in deuteroninvolvingreactionsreactionprocesseswithexoticweaklyboundnuclei

  • (Microscopic) modellingofnuclearfissionmicroscopicunderstandingoffissionprocessmodellingoffissioncrosssectionsexperimentally not accessible isotopes (MA)

NuPECC Meeting,Vienna, March 13, 2009


Summary and outlook l.jpg
Summaryandoutlook

  • Summary:

  • Neutron-inducedcrosssectionmeasured

  • Well definedevaluationprocedurebased on modellingdeveloped

  • General evaluationtool GENEUS isunderconstruction

Outlook:

Focus iscurrentlychangingtotopics on reactiontheory - compositeparticlescatteringtheory - reactionsinvolvingweaklyboundnuclei

NuPECC Meeting,Vienna, March 13, 2009


Working group l.jpg
Working Group

J. Gundacker (Master)

J. Haidvogl (PhD)

D. Neudecker (PhD)

Th. Srdinko (Master)

V. Wildpaner

Former students

K. Nikolics

M.T. Pigni (PhD)

I. Raskinyte (PostDoc)

EU Research Projects:

EURATOM P&T:

n_TOF,IP_EUROTRANS

EURATOM Fusion:

EFDA-Projrects, F4E-Grants

EU I3-Project: EURONS

Strong collaborationwiththe

nucleardatacenters NEA, IAEA

NuPECC Meeting,Vienna, March 13, 2009


Slide35 l.jpg

THANK YOU FOR YOUR ATTENTION

NuPECC Meeting,Vienna, March 13, 2009


A nucleus optical potentials l.jpg
a-nucleusopticalpotentials

(semi)microscopic approach for low energies (relevant to astrophysics)

Optical Potential:

direct term

coupling term

Direct part:

evaluated within RGM in order to account

correctly for the antisymmetrisation

NuPECC Meeting,Vienna, March 13, 2009


Imaginary a nucleus optical potentials l.jpg
Imaginarya-nucleusopticalpotentials

Imaginary Part:

Intermediate states in RPA

Green functionat intermediate state

Itcanbeconsideredas a nuclearstructureapproachtoa-nucleus

optical potential, whichshouldworksatisfactoryatlowenergies

calculationsfora-16O anda-40Ca anda-208Pb are in progress

NuPECC Meeting,Vienna, March 13, 2009


Reactions of weakly bound nuclei l.jpg
Reactionsofweaklyboundnuclei

deuteron breaks up easily (EB=2,2 MeV)

breakup leads to additional flux loss

Incoming channel outgoing channel

Elastic d-A channel

Incoming

d-A channel

Breakup of the deuteron

nonelastic due to n-collision

nonelastic due to p-collision

Neglecting breakup leads to non-standard parameters in fitted potentials

Keaton, Armstrong (1973)

Ansatz of a complete wave function of the d-A system

deuteron wave function

p-n scattering wave function (continuum)

NuPECC Meeting,Vienna, March 13, 2009


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Breakupcontributionford-6Li

NuPECC Meeting,Vienna, March 13, 2009


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