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Metastability of Langevin dynamics : 랑주뱅 동역학의 메타안정성

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dc.contributor.advisor서인석-
dc.contributor.author이중경-
dc.date.accessioned2023-06-29T02:35:49Z-
dc.date.available2023-06-29T02:35:49Z-
dc.date.issued2023-
dc.identifier.other000000175521-
dc.identifier.urihttps://hdl.handle.net/10371/194355-
dc.identifier.urihttps://dcollection.snu.ac.kr/common/orgView/000000175521ko_KR
dc.description학위논문(박사) -- 서울대학교대학원 : 자연과학대학 수리과학부, 2023. 2. 서인석.-
dc.description.abstractIn this thesis, we investigate metastability of non-reversible Langevin dynamics. We prove the Eyring–Kramers formula, which is a precise estimation of the expectation of transition time, for non-reversible metastable diffusion processes that have Gibbs invariant measures. In addition, we further develop the Eyring–Kramers formula by proving that a suitably time-rescaled non-reversible metastable diffusion process converges to a Markov chain on the deepest metastable valleys.

Finally, we introduce the Curie–Weiss–Potts model as an example of a metastable dynamics on complex potential function so that complex metastability occurs. We analyze the energy landscape of the Curie–Weiss–Potts model and the metastable behavior of the heat-bath Glauber dynamics associated with the Curie–Weiss–Potts model.
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dc.description.abstract본 학위논문에서는 비가역적 랑주뱅 동역학의 메타안정성을 연구했다. 그 결과로 Gibbs 불변분포를 갖는 비가역적 확산확률과정의 Eyring–Kramers 공식을 증명했는데, 이 공식은 전이 시간의 기댓값을 정확히 추산하는 것이다. 이에 더해 Eyring–Kramers 공식을 발전시켜, 적절한 시간 규모에서 비가역적 확산확률과정이 최솟값 사이의 마르코프 사슬로 수렴한다는 것을 증명했다.
마지막으로, 복잡한 메타안정성을 나타내는 복잡한 잠재함수 위의 메타안정적 동역학의 예시로써 Curie–Weiss–Potts 모형을 소개한다. 이 모형의 에너지 분포와 해당 모형에 연관 된 heat-bath Glauber 동역학의 메타안정성을 연구했다.
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dc.description.tableofcontents1 Introduction 1
1.1 Mathematical study of metastability 1
1.2 Langevin dynamics 3
1.3 Main contribution of the thesis 8
1.4 General model 12

2 Model 15
2.1 Non-reversible Langevin dynamics 15
2.2 Deterministic dynamical system 19
2.3 Properties of diffusion process 26

3 Eyring–Kramers formula 29
3.1 Main result 29
3.2 Potential theory 37
3.3 Proof of Eyring–Kramers formula 40
3.4 Construction of test function around saddle point 45
3.5 Analysis of equilibrium potential 63
3.6 Construction of test function and proof of Theorem 3.3.4 72

4 Markov chain model reduction 86
4.1 Main result 86
4.2 Proof based on resolvent approach 98
4.3 Analysis of resolvent equation 104
4.4 Construction of test function 110
4.5 Proof of Proposition 4.3.7 119

5 Curie–Weiss–Potts model 131
5.1 Studies on the Curie–Weiss–Potts model 131
5.2 Model 135
5.3 Main result for energy landscape 139
5.4 Main result for metastability 151
5.5 Preliminary analysis on potential and generator 161
5.6 Investigation of critical points and temperatures 166
5.7 Critical points of Fβ 174
5.8 Analysis of energy landscape 182
5.9 Characterization of metastable sets 188
5.10 Proof of Lemma 5.8.4 194
5.11 Numerical computations 200
5.12 Proof of (5.12) 204

Abstract (in Korean) 215
Acknowledgement (in Korean) 216
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dc.format.extentiii, 218-
dc.language.isoeng-
dc.publisher서울대학교 대학원-
dc.subjectMetastability-
dc.subjectstatistical physics-
dc.subjectLangevin dynamics-
dc.subjectEyring-Kramers formula-
dc.subjectMarkov chain model reduction-
dc.subjectCurie-Weiss-Potts model-
dc.subject.ddc510-
dc.titleMetastability of Langevin dynamics-
dc.title.alternative랑주뱅 동역학의 메타안정성-
dc.typeThesis-
dc.typeDissertation-
dc.contributor.AlternativeAuthorJung-Kyoung Lee-
dc.contributor.department자연과학대학 수리과학부-
dc.description.degree박사-
dc.date.awarded2023-02-
dc.identifier.uciI804:11032-000000175521-
dc.identifier.holdings000000000049▲000000000056▲000000175521▲-
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