principle of equal a priori probability principle of equal a priori probabilities: an isolated...

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Principle of equal a priori probabilities: An isolated system, with N,V,E, has equal probability to be in any of the (N,V,E) quantum states or Each and every one of the (N,V,E) quantum states is represented with equally probability The probability offinding a state 1 P (, is , ) NV E nd S (N ,V ,E ;int.constr)<S (N 2 Law ,V,E) (1) (1) (1) (2) (2) (2) states states int.constr.N ,V ,E ,V ,E & ,V ,E # obeying the int.c (N ,V ,E ;int.co onstr.<# w ith n nstr.) (N ,V ,E ;int.constr.) o int.constr. N N Maxim um Maxim um S

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Page 1: Principle of equal a priori probability Principle of equal a priori probabilities: An isolated system, with N,V,E, has equal probability to be in any of

Principle of equal a priori probability

Principle of equal a priori probabilities:

An isolated system, with N,V,E, has equal probability to be in any of the (N,V,E) quantum states or

Each and every one of the (N,V,E) quantum states is represented with equally probability

The probability of finding a state 1

P( ,

is ,

)N V E

nd S(N,V,E;int.constr)<S(N 2 Law ,V,E)

(1) (1) (1) (2) (2) (2)

states states

int. constr. N,V,E ,V ,E & ,V ,E

# obeying the int. c

(N,V,E; int.co

onstr.<# with n

nstr.) (N,V,E; int.constr.)

o int. constr.

N N

Maximum

Maxim

um S

Page 2: Principle of equal a priori probability Principle of equal a priori probabilities: An isolated system, with N,V,E, has equal probability to be in any of

,

ln ( , , ) We define

1

B

N V

ST

E

N V E

T

S k

, ,

1 ln ( , )

T

Since 0 ( , , ) when E

BN V N V

S N Vk

E E

T N V E

Page 3: Principle of equal a priori probability Principle of equal a priori probabilities: An isolated system, with N,V,E, has equal probability to be in any of

Canonical ensembles

Canonical N,V,T

I II III AThere are A identical replicas

with same N,V, and T

V=AxV N=AxN EEach microsystem has an energy value Ej(N,V).Each Ej is (Ej) times degenerate

al number of systems in state l , occupation number

heat bath(T)

Set of {al } = distribution = a describes the state of the Ensemble

A=j aj

E=j aj Ej

One possible state of ensemble{ 1 2 3 lEl E1 E2 … El

al a1 a2…al

Page 4: Principle of equal a priori probability Principle of equal a priori probabilities: An isolated system, with N,V,E, has equal probability to be in any of

Canonical as subsystem of microcanocal

heat bath(T)EB

Ej(N,V)

N,V,E E=Ej+EB

Page 5: Principle of equal a priori probability Principle of equal a priori probabilities: An isolated system, with N,V,E, has equal probability to be in any of

Distributions

Principle of equal priori probability every {a} is equally probable

Since there are A systems (each with energy Ej)

there are A number distinguishable particles that can be

distributed according to their al value

a1 in group 1, a2 in group 2, al in group l…

How many times a particular distribution can be found in the ENSEMBLE?

We know the answer to this one, right?

! ( )

!kk

W {a}Aa

fraction systems with in any particular microsate is jE ja

A

Page 6: Principle of equal a priori probability Principle of equal a priori probabilities: An isolated system, with N,V,E, has equal probability to be in any of

Consider 3 oscillators, with 3TE

0 ,1 ,2 ,3

For this ,

there are 10 states of the en

canonic

emble w

al en

ith

semble

=3

jE

Esame distributa group of states can have the with

What is the # of states in each distributi

ion

on?

IIII II

distribution IThere are 3 2 1 6 possible states for

of those, some are equivalent example

3!

# of nonequivalent states in distribution I 32!1!

3 systems

Page 7: Principle of equal a priori probability Principle of equal a priori probabilities: An isolated system, with N,V,E, has equal probability to be in any of

Example (Nash)II

0

1

2

3

2 oscillators in E 0

0 oscillators in E 1distribution with 3 times

0 oscillators in{2,

E 2

1 os

0,0,1};

cillators in E 3

the other two distributions are

3!=6 times

1!1!1!

3! =1 time

3!

{1,1,1,0}

{0,3,0,0}

10 states in 3 different distribution

( ) 3; ( ) 6; ( ) 1

3 3

s

W I W II W III

Eii i

i ia EaA

Page 8: Principle of equal a priori probability Principle of equal a priori probabilities: An isolated system, with N,V,E, has equal probability to be in any of

If we increase to 5 8

there are 7 different distributions

E A=

8 ! 8 ! 8 ! ( ) 8 ( ) 56 ( ) 56

1! 7 ! 6 ! 1! 1! 6 ! 1! 1!

8 ! 8 ! 8 !( ) 168 ( ) 168 ( ) 280

5 ! 2 ! 1! 5 ! 2 ! 4 ! 3 !

8 !( )

5 ! 3 !

792 states

W I W II W III

W IV W V W VI

W VII W0 2 4 6

W

B

systems

For E=1000 and A=1000 W=10600

there are 1070 atoms in the galaxyFor larger and larger A values, the ratioWn/ Wmax=An 0 20 40 60 80 100

An

B

( ) is a function which sharply peaks at * ( )W W{a} {a}

Page 9: Principle of equal a priori probability Principle of equal a priori probabilities: An isolated system, with N,V,E, has equal probability to be in any of

Probability of finding a system in Ej is obtained by

j

WP

Wa

a

j {a}{a}

{a}

( )×A

( )

a ( )aA

k

Since W( )= is a multinomial coeff., the

which maximizes ( ) is = which maximizes ln ( )

!

W W

kk

k

{a}

{a} {a}

aa

a

A!

knd

If there is a single constraint , the max of W( )will

happen for { } .

But with a 2 constraint

( )

=

E

will maximize for { }W

a

k

k

k

1 2

k

k

k

k

{a}

a

Aa a a

=A

= =...=

E

ak

a

a

=

Page 10: Principle of equal a priori probability Principle of equal a priori probabilities: An isolated system, with N,V,E, has equal probability to be in any of

Distribution for max W(a)

j(to find P we find which maximizes W( ) j {a } {a}a

( ) is a function which sharply peaks at * ( )

( ) ( )

all ( ) ( ) can be neglected in the sum

W W

W W

W W

{a} {a}

{a} {a }

{a} {a }

1

=

where = in the

j

WW

PW W

a

a

j

j j

j j

{a}{a}

{a }

{a} {a }

{a }

( )× ( )A( )

a ( )a

a a

A A

a

( )

Having 2 constraints, we need to use Lagrange multipliers

Page 11: Principle of equal a priori probability Principle of equal a priori probabilities: An isolated system, with N,V,E, has equal probability to be in any of

Maximazing lnW(a)

n f ln ( ) undetermined multipliers: ,

constraints:

W

Ek k kk k

{a}

a =A a =E

for each given 1,2,...

ln 0

j k

W Ek k kk kj

a a aa

0 ln ! ln ! Ek k k kk k kj

A a a aa

0 lnj

A A- Aa

lnk k kk

a a a

Ek k kk k k

a a

10 0 ln Ej j j

j

a aa

1

ln 1 0

for every j

= 1,2,...k

jEe

E

e

j

*j

ja +

a

Page 12: Principle of equal a priori probability Principle of equal a priori probabilities: An isolated system, with N,V,E, has equal probability to be in any of

Evaluating the multiplier

1constraint #1 jEe e*j

j j

a =A=

1

jEe

e j

A

( 1)

jE

j

e eP

*ja

A A

1

j

j

j

j

E

j

E

E

E

e

e

e

P

ej

*j

j

Aa

A A

From here we can calculate all othermechanical thermodynamic properties

Probability of finding the quantum state with Ej at a given N,V

j

j

E

j j jEj

eP M P M

ej