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1 2005 년 년년년년 년년년 ( 년년년년년 ) Mass distribution in a model with aggregation and chipping processes on complex networks I. Introduct ion II. Motivatio n III. Model IV. Results Sungmin Lee, Sungchul Kwon and Yup Kim Kyung Hee Univ.

Mass distribution in a model with aggregation and chipping processes on complex networks

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Mass distribution in a model with aggregation and chipping processes on complex networks. I. Introduction II. Motivation III. Model IV. Results V. Argument VI. Summary. Sungmin Lee, Sungchul Kwon and Yup Kim. Kyung Hee Univ. I. Introduction. Diffusion, aggregation - PowerPoint PPT Presentation

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Page 1: Mass distribution in a model with aggregation and chipping processes on complex networks

12005 년 통계물리 워크샵 ( 경기대학교 )

Mass distribution in a model with aggregation and chipping processes on complex networks

I. Introduction

II. Motivation

III. Model

IV. Results

V. Argument

VI. Summary

Sungmin Lee, Sungchul Kwon and Yup KimKyung Hee Univ.

Page 2: Mass distribution in a model with aggregation and chipping processes on complex networks

22005 년 통계물리 워크샵 ( 경기대학교 )

I. Introduction

Conserved mass aggregation (CMA) model Diffusion Chipping

Diffusion, aggregation and fragmentation

colloidal suspensionpolymer gelsaerosols and cloudsetc…

Page 3: Mass distribution in a model with aggregation and chipping processes on complex networks

32005 년 통계물리 워크샵 ( 경기대학교 )

Mean field results

Numerical simulation results J.Stat.Phys. 99,1(2000)

Page 4: Mass distribution in a model with aggregation and chipping processes on complex networks

42005 년 통계물리 워크샵 ( 경기대학교 )

Zero Range Process (ZRP)

- A particle jumps out of the site at the rate , and

Hopping

- hops to a neighboring site with the probability

A condensed state arises or not

according to ,

CMA model with

ZRP

No condensatio

n

M.R.Evans, Braz.J.Phys. 30,42 (2000)

Jumping

Diffusion Chipping

Page 5: Mass distribution in a model with aggregation and chipping processes on complex networks

52005 년 통계물리 워크샵 ( 경기대학교 )

II. Motivation

Phase Diagram

Page 6: Mass distribution in a model with aggregation and chipping processes on complex networks

62005 년 통계물리 워크샵 ( 경기대학교 )

III. Model

Diffusion

Chipping

ChippingDiffusion

Measurement

Page 7: Mass distribution in a model with aggregation and chipping processes on complex networks

72005 년 통계물리 워크샵 ( 경기대학교 )

IV. Results

1 10 100 1000 1000010-8

10-7

10-6

10-5

10-4

10-3

10-2

10-1

100

=0.01 =3.0

P

(m)

m

=0.1

P(m)~m-1.55e-m/m*

P(m)~m-2.33

1 10 100 1000 1000010-8

10-7

10-6

10-5

10-4

10-3

10-2

10-1

100

P(m)~m-1.65e-m/m*

P(m)~m-2.38

=0.1 =3.0

P

(m)

m

=1

Random network

1 10 100 1000 1000010-8

10-7

10-6

10-5

10-4

10-3

10-2

10-1

100

P(m)~m-1.5e-m/m*

P(m)~m-2.33

=0.1 =3.0

P

(m)

m

=10

0 1 2 3 4 5 6 7 8 9 10 110.0

0.5

1.0

1.5

2.0

2.5

Page 8: Mass distribution in a model with aggregation and chipping processes on complex networks

82005 년 통계물리 워크샵 ( 경기대학교 )

SFN

1 10 100 1000 1000010-8

10-7

10-6

10-5

10-4

10-3

10-2

10-1

100

P(m)~m-1.65e-m/m*

P(m)~m-2.33

=0.01 =3.0

P(m

)

m

=0.1

1 10 100 1000 1000010-8

10-7

10-6

10-5

10-4

10-3

10-2

10-1

100

P(m)~m-1.75e-m/m*

P(m)~m-2.33

=0.1 =3.0

P

(m)

m

=1

1 10 100 1000 1000010-8

10-7

10-6

10-5

10-4

10-3

10-2

10-1

100

P(m)~m-1.5e-m/m*

P(m)~m-2.30

=0.1 =3.0

P

(m)

m

=10

0 1 2 3 4 5 6 7 8 9 10 110.0

0.5

1.0

1.5

Page 9: Mass distribution in a model with aggregation and chipping processes on complex networks

92005 년 통계물리 워크샵 ( 경기대학교 )

SFN

1 10 100 1000 1000010-9

10-8

10-7

10-6

10-5

10-4

10-3

10-2

10-1

100

=0.2 =3.0

P(m)~m-1.9e-m/m*

P

(m)

m

=0.1

1 10 100 1000 1000010-9

10-8

10-7

10-6

10-5

10-4

10-3

10-2

10-1

100

1 10 100 1000 10000

10-9

10-8

10-7

10-6

10-5

10-4

10-3

10-2

10-1

100

=0.2 =3.0

P

(m)

m

=1

N=105 =1 =0.2

P(m

)

m

1 10 100 1000 1000010-9

10-8

10-7

10-6

10-5

10-4

10-3

10-2

10-1

100

=0.2 =3.0

P

(m)

m

=10

Page 10: Mass distribution in a model with aggregation and chipping processes on complex networks

102005 년 통계물리 워크샵 ( 경기대학교 )

SFN

1 10 100 1000 1000010-9

10-8

10-7

10-6

10-5

10-4

10-3

10-2

10-1

100

=0.2 =3.0

P(m)~m-1.7e-m/m*

P

(m)

m

=0.1

1 10 100 1000 1000010-9

10-8

10-7

10-6

10-5

10-4

10-3

10-2

10-1

100

=0.2 =3.0

P

(m)

m

=1

0 1 2 3 4 5 6 7 8 9 10 110.0

0.5

1.0

1.5

2.0

1 10 100 1000 10000

10-9

10-8

10-7

10-6

10-5

10-4

10-3

10-2

10-1

100

1 10 100 1000 10000

10-9

10-8

10-7

10-6

10-5

10-4

10-3

10-2

10-1

100

=0.2 =3.0

P(m

)

m

=10

P(m

)

m

N=105 =10 =0.2

Page 11: Mass distribution in a model with aggregation and chipping processes on complex networks

112005 년 통계물리 워크샵 ( 경기대학교 )

Zero range process

condensation

Noh at el.,PRL 94,198701

(2005)

1 10 10010-2

10-1

100

101

102

103

104

105

106

=0.2 =3.0

mk

k1 10

10-2

10-1

100

101

102

103

104

105

=0.4 =3.0

mk

k

CMA model with

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

1000

2000

3000

k

t=2*105

t=4*105

t=6*105

t=8*105

Mk

N=103

=1=3.0

1 2 3 4 5 6 7 8 9 10

1000

2000

3000

mm

ax

k

t=2*105

t=4*105

t=6*105

t=8*105

N=103

=1=3.0

1 10 100

1

10

100

k

mk

N=103

=1=3.0

1 10

1

10

k

m

k

N=103

=1=3.0

Page 12: Mass distribution in a model with aggregation and chipping processes on complex networks

122005 년 통계물리 워크샵 ( 경기대학교 )

V. Argument

10-6 10-5 10-4 10-3

0.0

5.0x105

1.0x106

1.5x106

RG SFN=4.3 SFN=3.0 SFN=2.4 SFN=2.15

1/N

<T>

<T>~N0.99

<T>~N0.98

Maintain? or not?

<T> : average life time

Maintain !!

Maintain

Page 13: Mass distribution in a model with aggregation and chipping processes on complex networks

132005 년 통계물리 워크샵 ( 경기대학교 )

VI. Summary◆ We study conserved mass aggregation model on

networks.

◆ In case, there is no exponential phase because the big mass is maintained at low density.

◆ Phase diagram