Seite - 26 - in Differential Geometrical Theory of Statistics
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Entropy2016,18, 370
Withx= ρ1(z)andx0= ρb(z),zbeinganyelement inM, that inequalitybecomes
h (
ρ1(z) )
= ρ1(z) log (
1
ρ1(z) )
≤ ρb(z)− (
1+ logρb(z) )
ρ1(z) .
ByintegrationoverM,usingthefact thatρb is theprobabilitydensityof theGibbsstateassociated
tob,weobtain
s(ρ1)≤1−1− ∫
M ρ1 logρbdλω= s(ρb) .
Wehaveproventhe inequality s(ρ1)≤ s(ρb). Ifρ1= ρb,wehaveofcourse theequality s(ρ1)= s(ρb).
Conversely if s(ρ1)= s(ρb), the functionsdefinedonM
z →ϕ1(z)= ρ1(z) log (
1
ρ1(z) )
and z →ϕ(z)= ρb(z)− (
1+ logρb(z) )
ρ1(z)
arecontinuousonMexcept,maybe, forϕ, atpointszatwhichρb(z)=0andρ1(z) =0,but thesetof
suchpoints isofmeasure0sinceϕ is integrable. Theysatisfytheinequalityϕ1≤ϕ. Bothare integrable
onMandhavethesameintegral. Thefunctionϕ−ϕ1 iseverywhere≥0, is integrableonMandits
integral is0. That function is thereforeeverywhereequal to0onM.Wecanwrite, for anyz∈M,
ρ1(z) log (
1
ρ1(z) )
= ρb(z)− (
1+ logρb(z) )
ρ1(z) . (6)
Foreachz∈M suchthatρ1(z) =0,wecandivide thatequalitybyρ1(z).Weobtain
ρb(z)
ρ1(z) − log (
ρb(z)
ρ1(z) )
=1.
Since the function x → x− logx reaches itsminimum,equal to1, forauniquevalueof x> 0,
thatvaluebeing1,wesee that foreach z∈Matwhichρ1(z)>0,wehaveρ1(z)= ρb(z). Atpoints
z∈Matwhichρ1(z)=0,Equation(6) showsthatρb(z)=0. Thereforeρ1= ρb.
Remark14. Themaximality property of the entropy functionρ → s(ρ) at aGibbs state densityρb proven
inProposition9of course implies the stationarity of that functionatρb with respect to smooth infinitesimal
variationsofρwithfixedmeanvalueofH,proven inProposition8. ThatProposition therefore couldbeomitted.
Wechose tokeep it because itsproof ismucheasier than that ofProposition9, andexplainswhy it is interesting
to lookatprobabilitydensitiesproportional to exp(−bH) for someb∈R.
ThefollowingpropositionshowsthataGibbsstatistical state remains invariantunder theflowof
theHamiltonianvectorfieldXH.OnecanthereforesaythataGibbsstate isastatisticalequilibrium
state.Ofcourse thereexist statisticalequilibriumstatesother thanGibbsstates.
Proposition10. LetHbeasmoothHamiltonianboundedbybelowonasymplecticmanifold (M,ω), b∈R
be such that the integral defining the value P(b) of the partition functionPat b converges. TheGibbs state
associated tob remains invariantunder theflowofof theHamiltonianvectorfieldXH.
Proof. Thedensityρbof theGibbsstateassociatedtob,withrespect to theLiouvillemeasureλω, is
ρb= 1
P(b) exp(−bH) .
SinceH is constantalongeach integral curveofXH,ρb too isconstantalongeach integral curve
ofXH. Moreover, theLiouvillemeasureλω remains invariantunder theflowofXH. Therefore the
Gibbsprobabilitymeasureassociatedtob tooremains invariantunder thatflow.
26
Differential Geometrical Theory of Statistics
- Titel
- Differential Geometrical Theory of Statistics
- Autoren
- Frédéric Barbaresco
- Frank Nielsen
- Herausgeber
- MDPI
- Ort
- Basel
- Datum
- 2017
- Sprache
- englisch
- Lizenz
- CC BY-NC-ND 4.0
- ISBN
- 978-3-03842-425-3
- Abmessungen
- 17.0 x 24.4 cm
- Seiten
- 476
- Schlagwörter
- Entropy, Coding Theory, Maximum entropy, Information geometry, Computational Information Geometry, Hessian Geometry, Divergence Geometry, Information topology, Cohomology, Shape Space, Statistical physics, Thermodynamics
- Kategorien
- Naturwissenschaften Physik