integrability of limit shape phenomena in six vertex model
play

Integrability of Limit Shape Phenomena in Six Vertex Model Ananth - PowerPoint PPT Presentation

Integrability of Limit Shape Phenomena in Six Vertex Model Ananth Sridhar UC Berkeley Physics asridhar@berkeley.edu June 19, 2015 1 / 59 Introduction Background The six vertex model is can be reformulated as a random stepped surface


  1. Integrability of Limit Shape Phenomena in Six Vertex Model Ananth Sridhar UC Berkeley Physics asridhar@berkeley.edu June 19, 2015 1 / 59

  2. Introduction Background • The six vertex model is can be reformulated as a random stepped surface called heights. 2 / 59

  3. Introduction Background • The six vertex model is can be reformulated as a random stepped surface called heights. • In the thermodynamic limit, the limiting average height function becomes deterministic and can be found by solving a certain boundary value problem. 3 / 59

  4. Introduction Background • The six vertex model is can be reformulated as a random stepped surface called heights. • In the thermodynamic limit, the limiting average height function becomes deterministic and can be found by solving a certain boundary value problem. • The six vertex model is quantum integrable in the sense that it admits commuting transfer matrices and can be solved by Bethe ansatz. 4 / 59

  5. Introduction Background • The six vertex model is can be reformulated as a random stepped surface called heights. • In the thermodynamic limit, the limiting average height function becomes deterministic and can be found by solving a certain boundary value problem. • The six vertex model is quantum integrable in the sense that it admits commuting transfer matrices and can be solved by Bethe ansatz. • What does the quantum integrability imply for the PDE governing the limiting height function? 5 / 59

  6. Introduction Outline of Talk • Quick Review of Six Vertex Model • Thermodynamic Limit • Integrability: • Transfer Matrices • Commuting Hamiltonians • Examples • Outlook 6 / 59

  7. Review: Six Vertex Model Configurations and Weights T = ǫ Z 2 be the scaled square lattice • Let S T = [0 , T ] × [0 , 1], and let S ǫ centered inside S T . 7 / 59

  8. Review: Six Vertex Model Configurations and Weights T = ǫ Z 2 be the scaled square lattice • Let S T = [0 , T ] × [0 , 1], and let S ǫ centered inside S T . • A configuration s of the six vertex model is a set of paths that only go right and up. w 1 w 1 w 2 w 2 w 3 w 3 8 / 59

  9. Review: Six Vertex Model Configurations and Weights T = ǫ Z 2 be the scaled square lattice • Let S T = [0 , T ] × [0 , 1], and let S ǫ centered inside S T . • A configuration s of the six vertex model is a set of paths that only go right and up. w 1 w 1 w 2 w 2 w 3 w 3 • Each vertex has a weight v ( s ). • The Boltzmann weight of s : � w ( s ) = v ( s ) vertex v 9 / 59

  10. Review: Six Vertex Model Boundary Conditions • The state of s at time t is the set of horizontal edges traversed by s at t . 10 / 59

  11. Review: Six Vertex Model Boundary Conditions • The state of s at time t is the set of horizontal edges traversed by paths at t . • Fixed boundary conditions are choice initial and final states η 1 and η 2 . 11 / 59

  12. Review: Six Vertex Model Boundary Conditions • The state of s at time t is the set of horizontal edges traversed by paths at t . • Fixed boundary conditions are choice initial and final states η 1 and η 2 . • The partition function and the normalized free energy are: � Z ǫ η 1 ,η 2 , T = w ( s ) s (0)= η 1 s (1)= η 2 � � η 1 ,η 2 , T = ǫ 2 log f ǫ Z η 1 ,η 2 12 / 59

  13. Review: Six Vertex Model Height Function • A height function is a function on faces satisfying a gradient constraint: • 0 ≤ h ( x , y ) − h ( x + ǫ, y ) ≤ 1 • 0 ≤ h ( x , y + ǫ ) − h ( x , y ) ≤ 1 13 / 59

  14. Review: Six Vertex Model Height Function • A height function is a function on faces satisfying a gradient constraint: • 0 ≤ h ( x , y ) − h ( x + ǫ, y ) ≤ 1 • 0 ≤ h ( x , y + ǫ ) − h ( x , y ) ≤ 1 • Height functions are in bijection with configurations; the level curves of h are the paths of the configuration. 3 3 3 2 2 2 2 2 1 1 1 0 14 / 59

  15. Review: Six Vertex Model Height Function • A height function is a function on faces satisfying a gradient constraint: • 0 ≤ h ( x , y ) − h ( x + ǫ, y ) ≤ 1 • 0 ≤ h ( x , y + ǫ ) − h ( x , y ) ≤ 1 • Height functions are in bijection with configurations; the level curves of h are the paths of the configuration. 3 3 3 2 2 2 2 2 1 1 1 0 • The boundary conditions determine the height function at the boundary. 15 / 59

  16. Review: Six Vertex Model Height Function • A height function is a function on faces satisfying a gradient constraint: • 0 ≤ h ( x , y ) − h ( x + ǫ, y ) ≤ 1 • 0 ≤ h ( x , y + ǫ ) − h ( x , y ) ≤ 1 • Height functions are in bijection with configurations; the level curves of h are the paths of the configuration. 3 3 3 2 2 2 2 2 1 1 1 0 • The boundary conditions determine the height function at the boundary. • The normalized height function ¯ h = ǫ h . The average height function � ¯ h � is the ensemble average of the normalized height function. 16 / 59

  17. Thermodynamic Limit Thermodynamic limit • Suppose we have a sequence of six vertex models S ǫ i t and boundary 2 with ǫ i → 0. height functions η ǫ i 1 , η ǫ i 17 / 59

  18. Thermodynamic Limit Thermodynamic limit • Suppose we have a sequence of six vertex models S ǫ i t and boundary 2 with ǫ i → 0. height functions η ǫ i 1 , η ǫ i • The boundary conditions are said to be stabilizing if the normalized boundary height functions η ǫ 1 , η ǫ 2 converge to η 1 , η 2 : [0 , 1] → R in the uniform metric as ǫ → 0. 18 / 59

  19. Thermodynamic Limit Thermodynamic limit • Suppose we have a sequence of six vertex models S ǫ i t and boundary 2 with ǫ i → 0. height functions η ǫ i 1 , η ǫ i • The boundary conditions are said to be stabilizing if the normalized boundary height functions η ǫ 1 , η ǫ 2 converge to η 1 , η 2 : [0 , 1] → R in the uniform metric as ǫ → 0. • In this case, there exist limiting free energy and limiting height function: ǫ → 0 f ǫ f η 1 ,η 2 , T = lim η 1 ,η 2 , T ǫ → 0 � h � ǫ � h � = lim 19 / 59

  20. Thermodynamic Limit Variational Principle • The limiting free energy and average height function can be computed by variational principle. � 1 � T f η 1 ,η 2 , T = max σ w ( ∂ t h , ∂ y h ) dt dy h ∈H 0 0 where σ is called the surface tension function, and H is the set of limiting height functions, h : S t → R satisfying: h (0 , 0) = 0, monotonicity, and Lipschitz continuity with constant 1. 20 / 59

  21. Thermodynamic Limit Variational Principle • The limiting free energy and average height function can be computed by variational principle. � 1 � T f η 1 ,η 2 , T = max σ w ( ∂ t h , ∂ y h ) dt dy h ∈H 0 0 where σ is called the surface tension function, and H is the set of limiting height functions, h : S t → R satisfying: h (0 , 0) = 0, monotonicity, and Lipschitz continuity with constant 1. • The limiting height function � h � is the maximizer. 21 / 59

  22. Thermodynamic Limit Variational Principle • The limiting free energy and average height function can be computed by variational principle. � 1 � T f η 1 ,η 2 , T = max σ w ( ∂ t h , ∂ y h ) dt dy h ∈H 0 0 where σ is called the surface tension function, and H is the set of limiting height functions, h : S t → R satisfying: h (0 , 0) = 0, monotonicity, and Lipschitz continuity with constant 1. • The limiting height function � h � is the maximizer. • Euler Lagrange equations: ∂ 11 σ w ∂ 2 t h + 2 ∂ 12 σ w ∂ t ∂ y h + ∂ 22 σ w ∂ 2 y h = 0 22 / 59

  23. Integrability of the Six Vertex Model Transfer Matrices • Let { e 0 , e 1 } be an orthonormal basis for C 2 , and let V = ( C 2 ) ⊗⌊ 1 /ǫ ⌋ . 23 / 59

  24. Integrability of the Six Vertex Model Transfer Matrices • Let { e 0 , e 1 } be an orthonormal basis for C 2 , and let V = ( C 2 ) ⊗⌊ 1 /ǫ ⌋ . • A state s of the six vertex model corresponds to a basis vector | s � = e s 0 ⊗ e s 1 · · · e s N , where s i = 1 is the indicator of the i th edge. 24 / 59

  25. Integrability of the Six Vertex Model Transfer Matrices • Let { e 0 , e 1 } be an orthonormal basis for C 2 , and let V = ( C 2 ) ⊗⌊ 1 /ǫ ⌋ . • A state s of the six vertex model corresponds to a basis vector | s � = e s 0 ⊗ e s 1 · · · e s N , where s i = 1 is the indicator of the i th edge. • Define the transfer matrix T w : V → V by its matrix elements: � s 1 | T w | s 2 � = Z s 1 , s 2 ,ǫ (ie. the partition function for just one column). 25 / 59

  26. Integrability of the Six Vertex Model Transfer Matrices • Let { e 0 , e 1 } be an orthonormal basis for C 2 , and let V = ( C 2 ) ⊗⌊ 1 /ǫ ⌋ . • A state s of the six vertex model corresponds to a basis vector | s � = e s 0 ⊗ e s 1 · · · e s N , where s i = 1 is the indicator of the i th edge. • Define the transfer matrix T w : V → V by its matrix elements: � s 1 | T w | s 2 � = Z s 1 , s 2 ,ǫ (ie. the partition function for just one column). • Then: Z η 1 ,η 2 , t = � η 1 | T ⌊ t /ǫ ⌋ | η 2 � w 26 / 59

  27. Integrability of the Six Vertex Model Hamiltonian Formulation of Variational Principle • Recast the variational problem in the Hamiltonian formulation by Legendre transform: H w ( π, t ) = max π s − σ w ( s , t ) s The new variables are h and π , where π is conjugate to ∂ t h . 27 / 59

Download Presentation
Download Policy: The content available on the website is offered to you 'AS IS' for your personal information and use only. It cannot be commercialized, licensed, or distributed on other websites without prior consent from the author. To download a presentation, simply click this link. If you encounter any difficulties during the download process, it's possible that the publisher has removed the file from their server.

Recommend


More recommend