SlideShare uma empresa Scribd logo
1 de 32
Baixar para ler offline
Spin models on networks
revisited
Petter Holme
Tokyo Institute of Technology
Spin models of statistical physics
1. An underlying graph G.

Traditionally a d-dimensional

lattice.
2. A spin variable θi associated

with every node in the graph.
3. A function H (the “Hamiltonian”)

that maps G and {θi} to a number.

Typically (always?) ∑f(θi–θj) where the

sum is over edges (i,j).
4. The probability of {θi} is exp(–H/kBT).
↑ ↓ ↓ ↓ ↑ ↓ ↓ ↑

↑ ↑ ↓ ↑ ↑ ↓ ↑ ↑

↓ ↓ ↓ ↑ ↑ ↓ ↓ ↑

↓ ↑ ↑ ↓ ↓ ↓ ↑ ↓
Why put spin models on networks
Why put spin models on networks
Why put spin models on networks
The XY model
H(G, {θi}) = –J∑edges (i,j) cos(θi–θj), θi are angles
https://www.complexity-explorables.org/explorables/if-you-ask-your-xy/
The XY model
XY model on WS networks
Kim & al., PRE 64:056135 2001.
XY model on WS networks
Kim & al., PRE 64:056135 2001.
XY model on WS networks
Kim & al., PRE 64:056135 2001.
Dynamic XY model on WS networks
Kim & al., PRE 64:056135 2001.
The YX model
Just like XY, but keep (randomly sampled) spins fixed
and vary the links of the graph.
Holme, Wu, Minnhagen, Multiscaling in an YX model
of networks, Phys. Rev. E. 80, 036120 (2009).
Magnetic transitions no longer possible, but maybe
some transition in network structure?
The YX model
Just like XY, but keep (randomly sampled) spins fixed
and vary the links of the graph.
(a) H = −199.52
π/2
0π
−π/2
(b) H = −195.86 (c) H = −192.05
The YX model
0.4
0.6
0.8
1
1.2
1.4
10 100 103
104
TN
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
10 100 103
104
TN
DNε
δδ
10.110.1
DNε
(b)(a)
400
800
N = 1600
200
δ =1.52, ε = –0.74
The diameter of the largest connected component:
The YX model
The largest connected component:
0
0.2
0.4
0.6
0.8
1
10−5
10−4
10−3
0.01
T
1−s1
(a)
400
800
1600
N = 3200
(b)
0.05
0.1
0.15
0.2
3
10100
(1−s1)Nβ
TNα
α =1.6, β = 0.22
The YX model
The 2nd largest connected component:
10 100
TN
γ10−3
10−5
10−4
0.01 0.1
0
T
s2
0.1
0.2
(b)(a)
s2
0.1
0.2
N = 3200
1600
800
400
0
γ =1.44
The YX model
The 2nd largest connected component:
10 100
TN
γ10−3
10−5
10−4
0.01 0.1
0
T
s2
0.1
0.2
(b)(a)
s2
0.1
0.2
N = 3200
1600
800
400
0
γ =1.44
The free XY model
Magnetization (avg. degree 8).
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000
magnetization
temperature
16
32
64
128
256
The free XY model
Magnetization (avg. degree 8).
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
5.5
0.01 0.1 1
magnetization*Nnu
temperature
16
32
64
128
256
ν = 0.30
The free XY model
Magnetization (avg. degree 8).
0.0000001
0.0000010
0.0000100
0.0001000
0.0010000
0.0100000
0.1000000
1.0000000
10.0000000
0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000
8
16
32
64
128
256
The free XY model
Size of the largest component (avg. degree 8).
0.97
0.975
0.98
0.985
0.99
0.995
1
0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000
16
32
64
128
256
The free XY model
Number of components (avg. degree 8).
1
10
0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000
16
32
64
128
256
The free XY model
Magnetization (avg. degree 4).
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
0.01 0.1 1
magnetization*Nnu
temperature
8
16
32
64
128
256
ν = 0.30
The free XY model
Size of the largest component (avg. degree 4).
0.7
0.75
0.8
0.85
0.9
0.95
1
0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000
8
16
32
64
128
256
The free XY model
Number of components (avg. degree 4).
1
10
100
0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000
8
16
32
64
128
256
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
5.5
0.01 0.1 1
magnetization*Nnu
temperature
16
32
64
128
256
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
0.01 0.1 1
magnetization*Nnu
temperature
8
16
32
64
128
256
0.6
0.8
1
1.2
1.4
1.6
1.8
2
2.2
0.01 0.1
magnetization*Nnu
temperature
8
16
32
64
128
256
0.7
0.75
0.8
0.85
0.9
0.95
1
1.05
1.1
1.15
0.001 0.01 0.1
magnetization*Nnu
temperature
8
16
32
64
128
256
512
k = 8, ν = 0.30 k = 4, ν = 0.30
k = 2, ν = 0.18 k = 1, ν = 0.02
Magnetization crossing plots
0.97
0.975
0.98
0.985
0.99
0.995
1
0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000
16
32
64
128
256
0.7
0.75
0.8
0.85
0.9
0.95
1
0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000
8
16
32
64
128
256
0.45
0.5
0.55
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0.95
0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000
8
16
32
64
128
256
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
0.55
0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000
8
16
32
64
128
256
512
Size of LCC
k = 8 k = 4
k = 2 k = 1
2
2.5
3
3.5
4
4.5
5
5.5
0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000
16
32
64
128
256
2
3
4
5
6
7
8
9
0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000
8
16
32
64
128
256
2
4
6
8
10
12
14
16
18
0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000
8
16
32
64
128
256
0
2
4
6
8
10
12
14
16
18
20
22
0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000
8
16
32
64
128
256
512
Diameter
k = 8 k = 4
k = 2 k = 1
The freer XY model
Let both the links and spins be free to update; don’t
conserve the number of links.
π/23π/2
π
0
θ
T = 10–3
T = 1 T = 103
Thank you
http://petterhol.me

Mais conteúdo relacionado

Mais procurados

Comparing 3-D Interpolation Techniques
Comparing 3-D Interpolation TechniquesComparing 3-D Interpolation Techniques
Comparing 3-D Interpolation TechniquesBinu Enchakalody
 
Finite Element Analysis of Magnesium Alloys using OOF2
Finite Element Analysis of Magnesium Alloys using OOF2Finite Element Analysis of Magnesium Alloys using OOF2
Finite Element Analysis of Magnesium Alloys using OOF2jitin_22
 
1575 numerical differentiation and integration
1575 numerical differentiation and integration1575 numerical differentiation and integration
1575 numerical differentiation and integrationDr Fereidoun Dejahang
 
SPSF02 - Graphical Data Representation
SPSF02 - Graphical Data RepresentationSPSF02 - Graphical Data Representation
SPSF02 - Graphical Data RepresentationSyeilendra Pramuditya
 
Solución al ejercicio 1
Solución al ejercicio 1Solución al ejercicio 1
Solución al ejercicio 1Jesthiger Cohil
 
2016 SMU Research Day
2016 SMU Research Day2016 SMU Research Day
2016 SMU Research DayLiu Yang
 
Reliability based design Optimsation Example
Reliability based design Optimsation ExampleReliability based design Optimsation Example
Reliability based design Optimsation Examplekemo jallow
 
7 latest rangka penyelesaian
7  latest  rangka penyelesaian7  latest  rangka penyelesaian
7 latest rangka penyelesaianNorelyana Ali
 
Mpmc unit-string manipulation
Mpmc unit-string manipulationMpmc unit-string manipulation
Mpmc unit-string manipulationxyxz
 
Data Science Workflow
Data Science WorkflowData Science Workflow
Data Science WorkflowPyData
 
Vector mechanics for engineers statics 7th chapter 5
Vector mechanics for engineers statics 7th chapter 5 Vector mechanics for engineers statics 7th chapter 5
Vector mechanics for engineers statics 7th chapter 5 Nahla Hazem
 
Moment of inertia of non symmetric object
Moment of inertia of non symmetric objectMoment of inertia of non symmetric object
Moment of inertia of non symmetric objectIntishar Rahman
 

Mais procurados (19)

Ejerciciooo3
Ejerciciooo3Ejerciciooo3
Ejerciciooo3
 
Comparing 3-D Interpolation Techniques
Comparing 3-D Interpolation TechniquesComparing 3-D Interpolation Techniques
Comparing 3-D Interpolation Techniques
 
Finite Element Analysis of Magnesium Alloys using OOF2
Finite Element Analysis of Magnesium Alloys using OOF2Finite Element Analysis of Magnesium Alloys using OOF2
Finite Element Analysis of Magnesium Alloys using OOF2
 
1575 numerical differentiation and integration
1575 numerical differentiation and integration1575 numerical differentiation and integration
1575 numerical differentiation and integration
 
SPSF02 - Graphical Data Representation
SPSF02 - Graphical Data RepresentationSPSF02 - Graphical Data Representation
SPSF02 - Graphical Data Representation
 
Solución al ejercicio 1
Solución al ejercicio 1Solución al ejercicio 1
Solución al ejercicio 1
 
2016 SMU Research Day
2016 SMU Research Day2016 SMU Research Day
2016 SMU Research Day
 
Ch21 24
Ch21 24Ch21 24
Ch21 24
 
Reliability based design Optimsation Example
Reliability based design Optimsation ExampleReliability based design Optimsation Example
Reliability based design Optimsation Example
 
7 latest rangka penyelesaian
7  latest  rangka penyelesaian7  latest  rangka penyelesaian
7 latest rangka penyelesaian
 
SPSF03 - Numerical Integrations
SPSF03 - Numerical IntegrationsSPSF03 - Numerical Integrations
SPSF03 - Numerical Integrations
 
Cilindro
CilindroCilindro
Cilindro
 
Mpmc unit-string manipulation
Mpmc unit-string manipulationMpmc unit-string manipulation
Mpmc unit-string manipulation
 
Geometrical Optics QA 2
Geometrical Optics QA 2Geometrical Optics QA 2
Geometrical Optics QA 2
 
Data Science Workflow
Data Science WorkflowData Science Workflow
Data Science Workflow
 
Vector mechanics for engineers statics 7th chapter 5
Vector mechanics for engineers statics 7th chapter 5 Vector mechanics for engineers statics 7th chapter 5
Vector mechanics for engineers statics 7th chapter 5
 
303
303303
303
 
The final
The finalThe final
The final
 
Moment of inertia of non symmetric object
Moment of inertia of non symmetric objectMoment of inertia of non symmetric object
Moment of inertia of non symmetric object
 

Semelhante a Spin models on networks revisited

Computation of electromagnetic_fields_scattered_from_dielectric_objects_of_un...
Computation of electromagnetic_fields_scattered_from_dielectric_objects_of_un...Computation of electromagnetic_fields_scattered_from_dielectric_objects_of_un...
Computation of electromagnetic_fields_scattered_from_dielectric_objects_of_un...Alexander Litvinenko
 
Dynamic stiffness and eigenvalues of nonlocal nano beams
Dynamic stiffness and eigenvalues of nonlocal nano beamsDynamic stiffness and eigenvalues of nonlocal nano beams
Dynamic stiffness and eigenvalues of nonlocal nano beamsUniversity of Glasgow
 
Double Clamped and Cantilever Beam Theoretical Solution and Numerical Solutio...
Double Clamped and Cantilever Beam Theoretical Solution and Numerical Solutio...Double Clamped and Cantilever Beam Theoretical Solution and Numerical Solutio...
Double Clamped and Cantilever Beam Theoretical Solution and Numerical Solutio...Tasos Lazaridis
 
TM plane wave scattering from finite rectangular grooves in a conducting plan...
TM plane wave scattering from finite rectangular grooves in a conducting plan...TM plane wave scattering from finite rectangular grooves in a conducting plan...
TM plane wave scattering from finite rectangular grooves in a conducting plan...Yong Heui Cho
 
Magnetic hysteresis of soft magnetic material under an applied continuous ext...
Magnetic hysteresis of soft magnetic material under an applied continuous ext...Magnetic hysteresis of soft magnetic material under an applied continuous ext...
Magnetic hysteresis of soft magnetic material under an applied continuous ext...IAEME Publication
 
Magnetic hysteresis of soft magnetic material under an applied continuous ext...
Magnetic hysteresis of soft magnetic material under an applied continuous ext...Magnetic hysteresis of soft magnetic material under an applied continuous ext...
Magnetic hysteresis of soft magnetic material under an applied continuous ext...IAEME Publication
 
A common unique random fixed point theorem in hilbert space using integral ty...
A common unique random fixed point theorem in hilbert space using integral ty...A common unique random fixed point theorem in hilbert space using integral ty...
A common unique random fixed point theorem in hilbert space using integral ty...Alexander Decker
 
High gain metal only reflectarray antenna composed of multiple rectangular gr...
High gain metal only reflectarray antenna composed of multiple rectangular gr...High gain metal only reflectarray antenna composed of multiple rectangular gr...
High gain metal only reflectarray antenna composed of multiple rectangular gr...Yong Heui Cho
 
Capitulo 10, 7ma edición
Capitulo 10, 7ma ediciónCapitulo 10, 7ma edición
Capitulo 10, 7ma ediciónSohar Carr
 
Rotating machines part 1
Rotating machines part 1Rotating machines part 1
Rotating machines part 1Loki Maha
 
The Removal of Large Space Debris Using Tethered Space Tug
The Removal of Large Space Debris Using Tethered Space TugThe Removal of Large Space Debris Using Tethered Space Tug
The Removal of Large Space Debris Using Tethered Space TugTheoretical mechanics department
 
Analysis of a ridge waveguide using overlapping T-blocks
Analysis of a ridge waveguide using overlapping T-blocksAnalysis of a ridge waveguide using overlapping T-blocks
Analysis of a ridge waveguide using overlapping T-blocksYong Heui Cho
 

Semelhante a Spin models on networks revisited (20)

CMSI計算科学技術特論C (2015) ALPS と量子多体問題①
CMSI計算科学技術特論C (2015) ALPS と量子多体問題①CMSI計算科学技術特論C (2015) ALPS と量子多体問題①
CMSI計算科学技術特論C (2015) ALPS と量子多体問題①
 
Computation of electromagnetic_fields_scattered_from_dielectric_objects_of_un...
Computation of electromagnetic_fields_scattered_from_dielectric_objects_of_un...Computation of electromagnetic_fields_scattered_from_dielectric_objects_of_un...
Computation of electromagnetic_fields_scattered_from_dielectric_objects_of_un...
 
Congrès SMAI 2019
Congrès SMAI 2019Congrès SMAI 2019
Congrès SMAI 2019
 
3rd Semester Civil Engineering Question Papers June/july 2018
3rd Semester Civil Engineering Question Papers June/july 2018 3rd Semester Civil Engineering Question Papers June/july 2018
3rd Semester Civil Engineering Question Papers June/july 2018
 
1st and 2nd Semester M Tech: Structural Engineering (Dec-2015; Jan-2016) Ques...
1st and 2nd Semester M Tech: Structural Engineering (Dec-2015; Jan-2016) Ques...1st and 2nd Semester M Tech: Structural Engineering (Dec-2015; Jan-2016) Ques...
1st and 2nd Semester M Tech: Structural Engineering (Dec-2015; Jan-2016) Ques...
 
Dynamic stiffness and eigenvalues of nonlocal nano beams
Dynamic stiffness and eigenvalues of nonlocal nano beamsDynamic stiffness and eigenvalues of nonlocal nano beams
Dynamic stiffness and eigenvalues of nonlocal nano beams
 
Ch27 ssm
Ch27 ssmCh27 ssm
Ch27 ssm
 
Double Clamped and Cantilever Beam Theoretical Solution and Numerical Solutio...
Double Clamped and Cantilever Beam Theoretical Solution and Numerical Solutio...Double Clamped and Cantilever Beam Theoretical Solution and Numerical Solutio...
Double Clamped and Cantilever Beam Theoretical Solution and Numerical Solutio...
 
CMU_13
CMU_13CMU_13
CMU_13
 
TM plane wave scattering from finite rectangular grooves in a conducting plan...
TM plane wave scattering from finite rectangular grooves in a conducting plan...TM plane wave scattering from finite rectangular grooves in a conducting plan...
TM plane wave scattering from finite rectangular grooves in a conducting plan...
 
Magnetic hysteresis of soft magnetic material under an applied continuous ext...
Magnetic hysteresis of soft magnetic material under an applied continuous ext...Magnetic hysteresis of soft magnetic material under an applied continuous ext...
Magnetic hysteresis of soft magnetic material under an applied continuous ext...
 
Magnetic hysteresis of soft magnetic material under an applied continuous ext...
Magnetic hysteresis of soft magnetic material under an applied continuous ext...Magnetic hysteresis of soft magnetic material under an applied continuous ext...
Magnetic hysteresis of soft magnetic material under an applied continuous ext...
 
A common unique random fixed point theorem in hilbert space using integral ty...
A common unique random fixed point theorem in hilbert space using integral ty...A common unique random fixed point theorem in hilbert space using integral ty...
A common unique random fixed point theorem in hilbert space using integral ty...
 
cheb_conf_aksenov.pdf
cheb_conf_aksenov.pdfcheb_conf_aksenov.pdf
cheb_conf_aksenov.pdf
 
High gain metal only reflectarray antenna composed of multiple rectangular gr...
High gain metal only reflectarray antenna composed of multiple rectangular gr...High gain metal only reflectarray antenna composed of multiple rectangular gr...
High gain metal only reflectarray antenna composed of multiple rectangular gr...
 
Capitulo 10, 7ma edición
Capitulo 10, 7ma ediciónCapitulo 10, 7ma edición
Capitulo 10, 7ma edición
 
Capitulo 10 7 ed
Capitulo 10 7 edCapitulo 10 7 ed
Capitulo 10 7 ed
 
Rotating machines part 1
Rotating machines part 1Rotating machines part 1
Rotating machines part 1
 
The Removal of Large Space Debris Using Tethered Space Tug
The Removal of Large Space Debris Using Tethered Space TugThe Removal of Large Space Debris Using Tethered Space Tug
The Removal of Large Space Debris Using Tethered Space Tug
 
Analysis of a ridge waveguide using overlapping T-blocks
Analysis of a ridge waveguide using overlapping T-blocksAnalysis of a ridge waveguide using overlapping T-blocks
Analysis of a ridge waveguide using overlapping T-blocks
 

Mais de Petter Holme

Temporal network epidemiology: Subtleties and algorithms
Temporal network epidemiology: Subtleties and algorithmsTemporal network epidemiology: Subtleties and algorithms
Temporal network epidemiology: Subtleties and algorithmsPetter Holme
 
The big science of small networks
The big science of small networksThe big science of small networks
The big science of small networksPetter Holme
 
History of social simulations
History of social simulationsHistory of social simulations
History of social simulationsPetter Holme
 
Optimizing
 sentinel
 surveillance 
in
 static
 and 
temporal 
networks
Optimizing
 sentinel
 surveillance 
in
 static
 and 
temporal 
networksOptimizing
 sentinel
 surveillance 
in
 static
 and 
temporal 
networks
Optimizing
 sentinel
 surveillance 
in
 static
 and 
temporal 
networksPetter Holme
 
Important spreaders in networks: Exact results for small graphs
Important spreaders in networks: Exact results for small graphsImportant spreaders in networks: Exact results for small graphs
Important spreaders in networks: Exact results for small graphsPetter Holme
 
Important spreaders in networks: exact results on small graphs
Important spreaders in networks: exact results on small graphsImportant spreaders in networks: exact results on small graphs
Important spreaders in networks: exact results on small graphsPetter Holme
 
Spreading processes on temporal networks
Spreading processes on temporal networksSpreading processes on temporal networks
Spreading processes on temporal networksPetter Holme
 
Dynamics of Internet-mediated partnership formation
Dynamics of Internet-mediated partnership formationDynamics of Internet-mediated partnership formation
Dynamics of Internet-mediated partnership formationPetter Holme
 
Disease spreading & control in temporal networks
Disease spreading & control in temporal networksDisease spreading & control in temporal networks
Disease spreading & control in temporal networksPetter Holme
 
Modeling the evolution of the AS-level Internet: Integrating aspects of traff...
Modeling the evolution of the AS-level Internet: Integrating aspects of traff...Modeling the evolution of the AS-level Internet: Integrating aspects of traff...
Modeling the evolution of the AS-level Internet: Integrating aspects of traff...Petter Holme
 
Emergence of collective memories
Emergence of collective memoriesEmergence of collective memories
Emergence of collective memoriesPetter Holme
 
A paradox of importance in network epidemiology
A paradox of importance in network epidemiologyA paradox of importance in network epidemiology
A paradox of importance in network epidemiologyPetter Holme
 
How the information content of your contact pattern representation affects pr...
How the information content of your contact pattern representation affects pr...How the information content of your contact pattern representation affects pr...
How the information content of your contact pattern representation affects pr...Petter Holme
 
From land use to human mobility
From land use to human mobilityFrom land use to human mobility
From land use to human mobilityPetter Holme
 
Why do metabolic networks look like they do?
Why do metabolic networks look like they do?Why do metabolic networks look like they do?
Why do metabolic networks look like they do?Petter Holme
 
Temporal Networks of Human Interaction
Temporal Networks of Human InteractionTemporal Networks of Human Interaction
Temporal Networks of Human InteractionPetter Holme
 
Modeling the fat tails of size fluctuations in organizations
Modeling the fat tails of size fluctuations in organizationsModeling the fat tails of size fluctuations in organizations
Modeling the fat tails of size fluctuations in organizationsPetter Holme
 
From temporal to static networks, and back
From temporal to static networks, and backFrom temporal to static networks, and back
From temporal to static networks, and backPetter Holme
 
Exploring spatial networks with greedy navigators
Exploring spatial networks with greedy navigatorsExploring spatial networks with greedy navigators
Exploring spatial networks with greedy navigatorsPetter Holme
 

Mais de Petter Holme (20)

Temporal network epidemiology: Subtleties and algorithms
Temporal network epidemiology: Subtleties and algorithmsTemporal network epidemiology: Subtleties and algorithms
Temporal network epidemiology: Subtleties and algorithms
 
The big science of small networks
The big science of small networksThe big science of small networks
The big science of small networks
 
History of social simulations
History of social simulationsHistory of social simulations
History of social simulations
 
Optimizing
 sentinel
 surveillance 
in
 static
 and 
temporal 
networks
Optimizing
 sentinel
 surveillance 
in
 static
 and 
temporal 
networksOptimizing
 sentinel
 surveillance 
in
 static
 and 
temporal 
networks
Optimizing
 sentinel
 surveillance 
in
 static
 and 
temporal 
networks
 
Important spreaders in networks: Exact results for small graphs
Important spreaders in networks: Exact results for small graphsImportant spreaders in networks: Exact results for small graphs
Important spreaders in networks: Exact results for small graphs
 
Important spreaders in networks: exact results on small graphs
Important spreaders in networks: exact results on small graphsImportant spreaders in networks: exact results on small graphs
Important spreaders in networks: exact results on small graphs
 
Netsci 2017
Netsci 2017Netsci 2017
Netsci 2017
 
Spreading processes on temporal networks
Spreading processes on temporal networksSpreading processes on temporal networks
Spreading processes on temporal networks
 
Dynamics of Internet-mediated partnership formation
Dynamics of Internet-mediated partnership formationDynamics of Internet-mediated partnership formation
Dynamics of Internet-mediated partnership formation
 
Disease spreading & control in temporal networks
Disease spreading & control in temporal networksDisease spreading & control in temporal networks
Disease spreading & control in temporal networks
 
Modeling the evolution of the AS-level Internet: Integrating aspects of traff...
Modeling the evolution of the AS-level Internet: Integrating aspects of traff...Modeling the evolution of the AS-level Internet: Integrating aspects of traff...
Modeling the evolution of the AS-level Internet: Integrating aspects of traff...
 
Emergence of collective memories
Emergence of collective memoriesEmergence of collective memories
Emergence of collective memories
 
A paradox of importance in network epidemiology
A paradox of importance in network epidemiologyA paradox of importance in network epidemiology
A paradox of importance in network epidemiology
 
How the information content of your contact pattern representation affects pr...
How the information content of your contact pattern representation affects pr...How the information content of your contact pattern representation affects pr...
How the information content of your contact pattern representation affects pr...
 
From land use to human mobility
From land use to human mobilityFrom land use to human mobility
From land use to human mobility
 
Why do metabolic networks look like they do?
Why do metabolic networks look like they do?Why do metabolic networks look like they do?
Why do metabolic networks look like they do?
 
Temporal Networks of Human Interaction
Temporal Networks of Human InteractionTemporal Networks of Human Interaction
Temporal Networks of Human Interaction
 
Modeling the fat tails of size fluctuations in organizations
Modeling the fat tails of size fluctuations in organizationsModeling the fat tails of size fluctuations in organizations
Modeling the fat tails of size fluctuations in organizations
 
From temporal to static networks, and back
From temporal to static networks, and backFrom temporal to static networks, and back
From temporal to static networks, and back
 
Exploring spatial networks with greedy navigators
Exploring spatial networks with greedy navigatorsExploring spatial networks with greedy navigators
Exploring spatial networks with greedy navigators
 

Último

Forensic limnology of diatoms by Sanjai.pptx
Forensic limnology of diatoms by Sanjai.pptxForensic limnology of diatoms by Sanjai.pptx
Forensic limnology of diatoms by Sanjai.pptxkumarsanjai28051
 
well logging & petrophysical analysis.pptx
well logging & petrophysical analysis.pptxwell logging & petrophysical analysis.pptx
well logging & petrophysical analysis.pptxzaydmeerab121
 
Abnormal LFTs rate of deco and NAFLD.pptx
Abnormal LFTs rate of deco and NAFLD.pptxAbnormal LFTs rate of deco and NAFLD.pptx
Abnormal LFTs rate of deco and NAFLD.pptxzeus70441
 
Environmental Acoustics- Speech interference level, acoustics calibrator.pptx
Environmental Acoustics- Speech interference level, acoustics calibrator.pptxEnvironmental Acoustics- Speech interference level, acoustics calibrator.pptx
Environmental Acoustics- Speech interference level, acoustics calibrator.pptxpriyankatabhane
 
DOG BITE management in pediatrics # for Pediatric pgs# topic presentation # f...
DOG BITE management in pediatrics # for Pediatric pgs# topic presentation # f...DOG BITE management in pediatrics # for Pediatric pgs# topic presentation # f...
DOG BITE management in pediatrics # for Pediatric pgs# topic presentation # f...HafsaHussainp
 
6.2 Pests of Sesame_Identification_Binomics_Dr.UPR
6.2 Pests of Sesame_Identification_Binomics_Dr.UPR6.2 Pests of Sesame_Identification_Binomics_Dr.UPR
6.2 Pests of Sesame_Identification_Binomics_Dr.UPRPirithiRaju
 
Gas-ExchangeS-in-Plants-and-Animals.pptx
Gas-ExchangeS-in-Plants-and-Animals.pptxGas-ExchangeS-in-Plants-and-Animals.pptx
Gas-ExchangeS-in-Plants-and-Animals.pptxGiovaniTrinidad
 
DNA isolation molecular biology practical.pptx
DNA isolation molecular biology practical.pptxDNA isolation molecular biology practical.pptx
DNA isolation molecular biology practical.pptxGiDMOh
 
Q4-Mod-1c-Quiz-Projectile-333344444.pptx
Q4-Mod-1c-Quiz-Projectile-333344444.pptxQ4-Mod-1c-Quiz-Projectile-333344444.pptx
Q4-Mod-1c-Quiz-Projectile-333344444.pptxtuking87
 
How we decide powerpoint presentation.pptx
How we decide powerpoint presentation.pptxHow we decide powerpoint presentation.pptx
How we decide powerpoint presentation.pptxJosielynTars
 
final waves properties grade 7 - third quarter
final waves properties grade 7 - third quarterfinal waves properties grade 7 - third quarter
final waves properties grade 7 - third quarterHanHyoKim
 
complex analysis best book for solving questions.pdf
complex analysis best book for solving questions.pdfcomplex analysis best book for solving questions.pdf
complex analysis best book for solving questions.pdfSubhamKumar3239
 
projectile motion, impulse and moment
projectile  motion, impulse  and  momentprojectile  motion, impulse  and  moment
projectile motion, impulse and momentdonamiaquintan2
 
CHROMATOGRAPHY PALLAVI RAWAT.pptx
CHROMATOGRAPHY  PALLAVI RAWAT.pptxCHROMATOGRAPHY  PALLAVI RAWAT.pptx
CHROMATOGRAPHY PALLAVI RAWAT.pptxpallavirawat456
 
Introduction of Human Body & Structure of cell.pptx
Introduction of Human Body & Structure of cell.pptxIntroduction of Human Body & Structure of cell.pptx
Introduction of Human Body & Structure of cell.pptxMedical College
 
DECOMPOSITION PATHWAYS of TM-alkyl complexes.pdf
DECOMPOSITION PATHWAYS of TM-alkyl complexes.pdfDECOMPOSITION PATHWAYS of TM-alkyl complexes.pdf
DECOMPOSITION PATHWAYS of TM-alkyl complexes.pdfDivyaK787011
 
Science (Communication) and Wikipedia - Potentials and Pitfalls
Science (Communication) and Wikipedia - Potentials and PitfallsScience (Communication) and Wikipedia - Potentials and Pitfalls
Science (Communication) and Wikipedia - Potentials and PitfallsDobusch Leonhard
 
Immunoblott technique for protein detection.ppt
Immunoblott technique for protein detection.pptImmunoblott technique for protein detection.ppt
Immunoblott technique for protein detection.pptAmirRaziq1
 

Último (20)

Forensic limnology of diatoms by Sanjai.pptx
Forensic limnology of diatoms by Sanjai.pptxForensic limnology of diatoms by Sanjai.pptx
Forensic limnology of diatoms by Sanjai.pptx
 
well logging & petrophysical analysis.pptx
well logging & petrophysical analysis.pptxwell logging & petrophysical analysis.pptx
well logging & petrophysical analysis.pptx
 
Abnormal LFTs rate of deco and NAFLD.pptx
Abnormal LFTs rate of deco and NAFLD.pptxAbnormal LFTs rate of deco and NAFLD.pptx
Abnormal LFTs rate of deco and NAFLD.pptx
 
Environmental Acoustics- Speech interference level, acoustics calibrator.pptx
Environmental Acoustics- Speech interference level, acoustics calibrator.pptxEnvironmental Acoustics- Speech interference level, acoustics calibrator.pptx
Environmental Acoustics- Speech interference level, acoustics calibrator.pptx
 
DOG BITE management in pediatrics # for Pediatric pgs# topic presentation # f...
DOG BITE management in pediatrics # for Pediatric pgs# topic presentation # f...DOG BITE management in pediatrics # for Pediatric pgs# topic presentation # f...
DOG BITE management in pediatrics # for Pediatric pgs# topic presentation # f...
 
6.2 Pests of Sesame_Identification_Binomics_Dr.UPR
6.2 Pests of Sesame_Identification_Binomics_Dr.UPR6.2 Pests of Sesame_Identification_Binomics_Dr.UPR
6.2 Pests of Sesame_Identification_Binomics_Dr.UPR
 
Gas-ExchangeS-in-Plants-and-Animals.pptx
Gas-ExchangeS-in-Plants-and-Animals.pptxGas-ExchangeS-in-Plants-and-Animals.pptx
Gas-ExchangeS-in-Plants-and-Animals.pptx
 
DNA isolation molecular biology practical.pptx
DNA isolation molecular biology practical.pptxDNA isolation molecular biology practical.pptx
DNA isolation molecular biology practical.pptx
 
AZOTOBACTER AS BIOFERILIZER.PPTX
AZOTOBACTER AS BIOFERILIZER.PPTXAZOTOBACTER AS BIOFERILIZER.PPTX
AZOTOBACTER AS BIOFERILIZER.PPTX
 
Q4-Mod-1c-Quiz-Projectile-333344444.pptx
Q4-Mod-1c-Quiz-Projectile-333344444.pptxQ4-Mod-1c-Quiz-Projectile-333344444.pptx
Q4-Mod-1c-Quiz-Projectile-333344444.pptx
 
How we decide powerpoint presentation.pptx
How we decide powerpoint presentation.pptxHow we decide powerpoint presentation.pptx
How we decide powerpoint presentation.pptx
 
final waves properties grade 7 - third quarter
final waves properties grade 7 - third quarterfinal waves properties grade 7 - third quarter
final waves properties grade 7 - third quarter
 
complex analysis best book for solving questions.pdf
complex analysis best book for solving questions.pdfcomplex analysis best book for solving questions.pdf
complex analysis best book for solving questions.pdf
 
projectile motion, impulse and moment
projectile  motion, impulse  and  momentprojectile  motion, impulse  and  moment
projectile motion, impulse and moment
 
CHROMATOGRAPHY PALLAVI RAWAT.pptx
CHROMATOGRAPHY  PALLAVI RAWAT.pptxCHROMATOGRAPHY  PALLAVI RAWAT.pptx
CHROMATOGRAPHY PALLAVI RAWAT.pptx
 
Interferons.pptx.
Interferons.pptx.Interferons.pptx.
Interferons.pptx.
 
Introduction of Human Body & Structure of cell.pptx
Introduction of Human Body & Structure of cell.pptxIntroduction of Human Body & Structure of cell.pptx
Introduction of Human Body & Structure of cell.pptx
 
DECOMPOSITION PATHWAYS of TM-alkyl complexes.pdf
DECOMPOSITION PATHWAYS of TM-alkyl complexes.pdfDECOMPOSITION PATHWAYS of TM-alkyl complexes.pdf
DECOMPOSITION PATHWAYS of TM-alkyl complexes.pdf
 
Science (Communication) and Wikipedia - Potentials and Pitfalls
Science (Communication) and Wikipedia - Potentials and PitfallsScience (Communication) and Wikipedia - Potentials and Pitfalls
Science (Communication) and Wikipedia - Potentials and Pitfalls
 
Immunoblott technique for protein detection.ppt
Immunoblott technique for protein detection.pptImmunoblott technique for protein detection.ppt
Immunoblott technique for protein detection.ppt
 

Spin models on networks revisited

  • 1. Spin models on networks revisited Petter Holme Tokyo Institute of Technology
  • 2. Spin models of statistical physics 1. An underlying graph G.
 Traditionally a d-dimensional
 lattice. 2. A spin variable θi associated
 with every node in the graph. 3. A function H (the “Hamiltonian”)
 that maps G and {θi} to a number.
 Typically (always?) ∑f(θi–θj) where the
 sum is over edges (i,j). 4. The probability of {θi} is exp(–H/kBT). ↑ ↓ ↓ ↓ ↑ ↓ ↓ ↑
 ↑ ↑ ↓ ↑ ↑ ↓ ↑ ↑
 ↓ ↓ ↓ ↑ ↑ ↓ ↓ ↑
 ↓ ↑ ↑ ↓ ↓ ↓ ↑ ↓
  • 3. Why put spin models on networks
  • 4. Why put spin models on networks
  • 5. Why put spin models on networks
  • 6.
  • 7. The XY model H(G, {θi}) = –J∑edges (i,j) cos(θi–θj), θi are angles
  • 10. XY model on WS networks Kim & al., PRE 64:056135 2001.
  • 11. XY model on WS networks Kim & al., PRE 64:056135 2001.
  • 12. XY model on WS networks Kim & al., PRE 64:056135 2001.
  • 13. Dynamic XY model on WS networks Kim & al., PRE 64:056135 2001.
  • 14. The YX model Just like XY, but keep (randomly sampled) spins fixed and vary the links of the graph. Holme, Wu, Minnhagen, Multiscaling in an YX model of networks, Phys. Rev. E. 80, 036120 (2009). Magnetic transitions no longer possible, but maybe some transition in network structure?
  • 15. The YX model Just like XY, but keep (randomly sampled) spins fixed and vary the links of the graph. (a) H = −199.52 π/2 0π −π/2 (b) H = −195.86 (c) H = −192.05
  • 16. The YX model 0.4 0.6 0.8 1 1.2 1.4 10 100 103 104 TN 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 10 100 103 104 TN DNε δδ 10.110.1 DNε (b)(a) 400 800 N = 1600 200 δ =1.52, ε = –0.74 The diameter of the largest connected component:
  • 17. The YX model The largest connected component: 0 0.2 0.4 0.6 0.8 1 10−5 10−4 10−3 0.01 T 1−s1 (a) 400 800 1600 N = 3200 (b) 0.05 0.1 0.15 0.2 3 10100 (1−s1)Nβ TNα α =1.6, β = 0.22
  • 18. The YX model The 2nd largest connected component: 10 100 TN γ10−3 10−5 10−4 0.01 0.1 0 T s2 0.1 0.2 (b)(a) s2 0.1 0.2 N = 3200 1600 800 400 0 γ =1.44
  • 19. The YX model The 2nd largest connected component: 10 100 TN γ10−3 10−5 10−4 0.01 0.1 0 T s2 0.1 0.2 (b)(a) s2 0.1 0.2 N = 3200 1600 800 400 0 γ =1.44
  • 20. The free XY model Magnetization (avg. degree 8). 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000 magnetization temperature 16 32 64 128 256
  • 21. The free XY model Magnetization (avg. degree 8). 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 0.01 0.1 1 magnetization*Nnu temperature 16 32 64 128 256 ν = 0.30
  • 22. The free XY model Magnetization (avg. degree 8). 0.0000001 0.0000010 0.0000100 0.0001000 0.0010000 0.0100000 0.1000000 1.0000000 10.0000000 0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000 8 16 32 64 128 256
  • 23. The free XY model Size of the largest component (avg. degree 8). 0.97 0.975 0.98 0.985 0.99 0.995 1 0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000 16 32 64 128 256
  • 24. The free XY model Number of components (avg. degree 8). 1 10 0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000 16 32 64 128 256
  • 25. The free XY model Magnetization (avg. degree 4). 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 0.01 0.1 1 magnetization*Nnu temperature 8 16 32 64 128 256 ν = 0.30
  • 26. The free XY model Size of the largest component (avg. degree 4). 0.7 0.75 0.8 0.85 0.9 0.95 1 0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000 8 16 32 64 128 256
  • 27. The free XY model Number of components (avg. degree 4). 1 10 100 0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000 8 16 32 64 128 256
  • 28. 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 0.01 0.1 1 magnetization*Nnu temperature 16 32 64 128 256 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 0.01 0.1 1 magnetization*Nnu temperature 8 16 32 64 128 256 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 0.01 0.1 magnetization*Nnu temperature 8 16 32 64 128 256 0.7 0.75 0.8 0.85 0.9 0.95 1 1.05 1.1 1.15 0.001 0.01 0.1 magnetization*Nnu temperature 8 16 32 64 128 256 512 k = 8, ν = 0.30 k = 4, ν = 0.30 k = 2, ν = 0.18 k = 1, ν = 0.02 Magnetization crossing plots
  • 29. 0.97 0.975 0.98 0.985 0.99 0.995 1 0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000 16 32 64 128 256 0.7 0.75 0.8 0.85 0.9 0.95 1 0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000 8 16 32 64 128 256 0.45 0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000 8 16 32 64 128 256 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000 8 16 32 64 128 256 512 Size of LCC k = 8 k = 4 k = 2 k = 1
  • 30. 2 2.5 3 3.5 4 4.5 5 5.5 0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000 16 32 64 128 256 2 3 4 5 6 7 8 9 0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000 8 16 32 64 128 256 2 4 6 8 10 12 14 16 18 0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000 8 16 32 64 128 256 0 2 4 6 8 10 12 14 16 18 20 22 0.00001 0.00010 0.00100 0.01000 0.10000 1.00000 10.00000 100.00000 8 16 32 64 128 256 512 Diameter k = 8 k = 4 k = 2 k = 1
  • 31. The freer XY model Let both the links and spins be free to update; don’t conserve the number of links. π/23π/2 π 0 θ T = 10–3 T = 1 T = 103