Search | Carmin.tv

2D Ising model: combinatorics, CFT/CLE description at criticality and beyond

published on May 18, 2017

2D Ising model: combinatorics, CFT/CLE description at criticality and beyond

By Dmitry Chelkak

We begin this expository talk with a discussion of the combinatorics of the nearest-neighbor Ising model in 2D - an archetypical example of a statistical physics system that admits an order-disorder phase transition - and the underlying fermionic structure, which makes it accessible for the ...

Appears in collection : Les probabilités de demain 2017

Score: 35.560863

sum of:

max of:

sum of:

weight(description:ising in 138) [PerFieldSimilarity], result of:
score(doc=138,freq=1.0 = termFreq=1.0 ), product of:

idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:

docFreq

docCount

4470

4.8938

tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:

termFreq=1.0

parameter k1

1.2

parameter b

0.75

avgFieldLength

113.6783

fieldLength

112

1.0061

4.9236

weight(description:model in 138) [PerFieldSimilarity], result of:
score(doc=138,freq=2.0 = termFreq=2.0 ), product of:

idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:

docFreq

527

docCount

4470

2.1372

tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:

termFreq=2.0

parameter k1

1.2

parameter b

0.75

avgFieldLength

113.6783

fieldLength

112

1.3807

2.9509

7.8745

sum of:

weight(tags_search:ising in 138) [PerFieldSimilarity], result of:
score(doc=138,freq=1.0 = termFreq=1.0 ), product of:

boost

1.5

idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:

docFreq

docCount

4728

5.0771

tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:

termFreq=1.0

parameter k1

1.2

parameter b

0.75

avgFieldLength

24.7225

fieldLength

0.659

5.0183

sum of:

weight(tags_search:model in 138) [PerFieldSimilarity], result of:
score(doc=138,freq=1.0 = termFreq=1.0 ), product of:

boost

1.5

idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:

docFreq

266

docCount

4728

2.8761

tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:

termFreq=1.0

parameter k1

1.2

parameter b

0.75

avgFieldLength

24.7225

fieldLength

0.659

2.8428

weight(tags_search:models in 138) [PerFieldSimilarity], result of:
score(doc=138,freq=2.0 = termFreq=2.0 ), product of:

boost

1.2

idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:

docFreq

265

docCount

4728

2.8799

tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:

termFreq=2.0

parameter k1

1.2

parameter b

0.75

avgFieldLength

24.7225

fieldLength

1.0141

3.5047

6.3475

11.3659

sum of:

weight(title:ising in 138) [PerFieldSimilarity], result of:
score(doc=138,freq=1.0 = termFreq=1.0 ), product of:

boost

1.5

idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:

docFreq

docCount

5136

7.2915

tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:

termFreq=1.0

parameter k1

1.2

parameter b

0.75

avgFieldLength

7.9529

fieldLength

0.8645

9.4552

weight(title:model in 138) [PerFieldSimilarity], result of:
score(doc=138,freq=1.0 = termFreq=1.0 ), product of:

boost

1.5

idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:

docFreq

docCount

5136

3.9747

tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:

termFreq=1.0

parameter k1

1.2

parameter b

0.75

avgFieldLength

7.9529

fieldLength

0.8645

5.1542

14.6093

weight(status:published in 138) [PerFieldSimilarity], result of:
score(doc=138,freq=1.0 = termFreq=1.0 ), product of:

idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:

docFreq

4847

docCount

5136

0.058

tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:

termFreq=1.0

parameter k1

1.2

parameter b

0.75

avgFieldLength

fieldLength

0.058

ConstantScore(DocValuesFieldExistsQuery [field=date_published])

max of:

weight(description:"ising model" in 138) [PerFieldSimilarity], result of:
score(doc=138,freq=1.0 = phraseFreq=1.0 ), product of:

idf(), sum of:

idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:

docFreq

docCount

4470

4.8938

idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:

docFreq

527

docCount

4470

2.1372

7.031

tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:

phraseFreq=1.0

parameter k1

1.2

parameter b

0.75

avgFieldLength

113.6783

fieldLength

112

1.0061

7.0738

weight(tags_search:"ising model" in 138) [PerFieldSimilarity], result of:
score(doc=138,freq=1.0 = phraseFreq=1.0 ), product of:

boost

1.5

idf(), sum of:

idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:

docFreq

docCount

4728

5.0771

idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:

docFreq

266

docCount

4728

2.8761

7.9532

tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:

phraseFreq=1.0

parameter k1

1.2

parameter b

0.75

avgFieldLength

24.7225

fieldLength

0.659

7.8612

weight(title:"ising model" in 138) [PerFieldSimilarity], result of:
score(doc=138,freq=1.0 = phraseFreq=1.0 ), product of:

boost

1.5

idf(), sum of:

idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:

docFreq

docCount

5136

7.2915

idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:

docFreq

docCount

5136

3.9747

11.2661

tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:

phraseFreq=1.0

parameter k1

1.2

parameter b

0.75

avgFieldLength

7.9529

fieldLength

0.8645

14.6093

sum of:

weight(title:ising in 138) [PerFieldSimilarity], result of:
score(doc=138,freq=1.0 = termFreq=1.0 ), product of:

boost

0.3

idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:

docFreq

docCount

5136

7.2915

tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:

termFreq=1.0

parameter k1

1.2

parameter b

0.75

avgFieldLength

7.9529

fieldLength

0.8645

1.891

weight(title:model in 138) [PerFieldSimilarity], result of:
score(doc=138,freq=1.0 = termFreq=1.0 ), product of:

boost

0.3

idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:

docFreq

docCount

5136

3.9747

tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:

termFreq=1.0

parameter k1

1.2

parameter b

0.75

avgFieldLength

7.9529

fieldLength

0.8645

1.0308

2.9219

sum of:

weight(description:ising in 138) [PerFieldSimilarity], result of:
score(doc=138,freq=1.0 = termFreq=1.0 ), product of:

boost

0.3

idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:

docFreq

docCount

4470

4.8938

tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:

termFreq=1.0

parameter k1

1.2

parameter b

0.75

avgFieldLength

113.6783

fieldLength

112

1.0061

1.4771

weight(description:model in 138) [PerFieldSimilarity], result of:
score(doc=138,freq=2.0 = termFreq=2.0 ), product of:

boost

0.3

idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:

docFreq

527

docCount

4470

2.1372

tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:

termFreq=2.0

parameter k1

1.2

parameter b

0.75

avgFieldLength

113.6783

fieldLength

112

1.3807

0.8853

2.3623

35.5609

Spectral properties of Google matrix and beyond

54:14

published on October 29, 2018

Spectral properties of Google matrix and beyond

By Klaus Frahm

IHES

https://indico.math.cnrs.fr/event/3475/attachments/2180/2564/Frahm_GomaxSlides.pdf

Appears in collection : Google matrix: fundamentals, applications and beyond

Missing fields : ~~Ising~~ ~~model~~

Score: 30.064022

Hamiltonian Simulation and Universal Quantum Hamiltonians

45:44

published on December 15, 2017

Hamiltonian Simulation and Universal Quantum Hamiltonians

By Toby Cubitt

IHP

... 1180, 2016], we used this new theoretical insight to prove for the first time that there exist universal spin models that are capable of simulating any other classical spin system, and showed that the simple 2D classical Ising model with fields is such a universal model. In recent work with Ashley ...

Appears in collection : Quantum Information Theory

Score: 29.979692

sum of:

max of:

sum of:

weight(description:ising in 302) [PerFieldSimilarity], result of:
score(doc=302,freq=1.0 = termFreq=1.0 ), product of:

idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:

docFreq

docCount

4470

4.8938

tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:

termFreq=1.0

parameter k1

1.2

parameter b

0.75

avgFieldLength

113.6783

fieldLength

280

0.6256

3.0614

sum of:

weight(description:model in 302) [PerFieldSimilarity], result of:
score(doc=302,freq=4.0 = termFreq=4.0 ), product of:

idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:

docFreq

527

docCount

4470

2.1372

tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:

termFreq=4.0

parameter k1

1.2

parameter b

0.75

avgFieldLength

113.6783

fieldLength

280

1.3504

2.886

weight(description:models in 302) [PerFieldSimilarity], result of:
score(doc=302,freq=2.0 = termFreq=2.0 ), product of:

boost

0.8

idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:

docFreq

362

docCount

4470

2.5123

tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:

termFreq=2.0

parameter k1

1.2

parameter b

0.75

avgFieldLength

113.6783

fieldLength

280

0.9741

1.9579

4.8439

7.9054

sum of:

weight(tags_search:ising in 302) [PerFieldSimilarity], result of:
score(doc=302,freq=1.0 = termFreq=1.0 ), product of:

boost

1.5

idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:

docFreq

docCount

4728

5.0771

tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:

termFreq=1.0

parameter k1

1.2

parameter b

0.75

avgFieldLength

24.7225

fieldLength

0.9339

7.1122

sum of:

weight(tags_search:model in 302) [PerFieldSimilarity], result of:
score(doc=302,freq=2.0 = termFreq=2.0 ), product of:

boost

1.5

idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:

docFreq

266

docCount

4728

2.8761

tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:

termFreq=2.0

parameter k1

1.2

parameter b

0.75

avgFieldLength

24.7225

fieldLength

1.3112

5.6567

weight(tags_search:models in 302) [PerFieldSimilarity], result of:
score(doc=302,freq=1.0 = termFreq=1.0 ), product of:

boost

1.2

idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:

docFreq

265

docCount

4728

2.8799

tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:

termFreq=1.0

parameter k1

1.2

parameter b

0.75

avgFieldLength

24.7225

fieldLength

0.9339

3.2274

8.8841

15.9963

Mathematics
and Interactions

Relative Aspects of the Langlands Program, L-Functions and Beyond Endoscopy / Aspects relatifs du programme de Langlands, fonctions L et beyond endoscopy

French computer algebra days / Journées nationales de calcul formel

Jean-Morlet Chair 2020 - Workshop: Discrepancy Theory and Applications - Part 1 / Chaire Jean-Morlet 2020 - Workshop : Théorie de la discrépance et applications - Part 1

Jean-Morlet Chair 2020 - Research School: Quasi-Monte Carlo Methods and Applications / Chaire Jean-Morlet 2020 - Ecole: Méthode de quasi-Monte-Carlo et applications

Filters

Area

Keywords

MSC

Speakers

Type

Audience

Language +

Video quality +

Institutions +

Capture date +

2D Ising model: combinatorics, CFT/CLE description at criticality and beyond

Spectral properties of Google matrix and beyond

Hamiltonian Simulation and Universal Quantum Hamiltonians

Relative Aspects of the Langlands Program, L-Functions and Beyond Endoscopy / Aspects relatifs du programme de Langlands, fonctions L et beyond endoscopy

French computer algebra days / Journées nationales de calcul formel

Jean-Morlet Chair 2020 - Workshop: Discrepancy Theory and Applications - Part 1 / Chaire Jean-Morlet 2020 - Workshop : Théorie de la discrépance et applications - Part 1

Jean-Morlet Chair 2020 - Research School: Quasi-Monte Carlo Methods and Applications / Chaire Jean-Morlet 2020 - Ecole: Méthode de quasi-Monte-Carlo et applications

Search for content

Filters

Area

Keywords

MSC

Speakers

Type

Audience

Language +

Video quality +

Institutions +

Capture date +

2D Ising model: combinatorics, CFT/CLE description at criticality and beyond

Spectral properties of Google matrix and beyond

Hamiltonian Simulation and Universal Quantum Hamiltonians