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Applications of Jarzynskis relation in lattice gauge theories Alessandro Nada Universit` a degli Studi di Torino INFN, Sezione di Torino 34th International Symposium on Lattice Field Theory Southampton, 24-30 July 2016 Based on: M.


  1. Applications of Jarzynski’s relation in lattice gauge theories Alessandro Nada Universit` a degli Studi di Torino INFN, Sezione di Torino 34th International Symposium on Lattice Field Theory Southampton, 24-30 July 2016 Based on: M. Caselle, G. Costagliola, A. N., M. Panero and A. Toniato arXiv:1604.05544 [hep-lat] Alessandro Nada (UniTo & INFN) Applications of Jarzynski’s relation in LGTs 26/07/2016

  2. Free-energy differences in LGTs In lattice gauge theories the expectation values of a large set of physical quantities is naturally related to the computation (via Monte Carlo simulations) of free-energy differences. For example: • equilibrium thermodynamics (pressure) • ’t Hooft loops • magnetic susceptibility In many cases the calculation of ∆ F is a computationally challenging problem: this motivates the search for new methods and algorithms. In this talk a novel (in LGTs) method to calculate directly free-energy differences based on Jarzynski’s relation is presented. In general we are interested in any case in which we compute the ratio of partition functions of physical systems , i.e. expressed in terms of well-defined fields and couplings. Alessandro Nada (UniTo & INFN) Applications of Jarzynski’s relation in LGTs 26/07/2016

  3. Free-energy differences in LGTs In lattice gauge theories the expectation values of a large set of physical quantities is naturally related to the computation (via Monte Carlo simulations) of free-energy differences. For example: • equilibrium thermodynamics (pressure) • ’t Hooft loops • magnetic susceptibility In many cases the calculation of ∆ F is a computationally challenging problem: this motivates the search for new methods and algorithms. In this talk a novel (in LGTs) method to calculate directly free-energy differences based on Jarzynski’s relation is presented. In general we are interested in any case in which we compute the ratio of partition functions of physical systems , i.e. expressed in terms of well-defined fields and couplings. Alessandro Nada (UniTo & INFN) Applications of Jarzynski’s relation in LGTs 26/07/2016

  4. Jarzynski’s relation 1 Benchmark study I: interface free energy in Z 2 gauge model 2 Benchmark study II: pressure in SU (2) gauge theory 3 Future applications 4 Alessandro Nada (UniTo & INFN) Applications of Jarzynski’s relation in LGTs 26/07/2016

  5. Jarzynski’s equality - I Jarzynski’s equality [Jarzynski, 1997] relates the exponential statistical average of the work done on a system during a non-equilibrium process with the difference between the initial and the final free energy of the system. For an isothermal transformation it can be written as � � �� � � − W ( λ i , λ f ) − ∆ F exp = exp T T The evolution of the system is performed by changing (continuously or discretely) a chosen set λ of one or more parameters, such as the couplings or the temperature of the system. In each step of the process the value of λ is changed and the system is brought out of equilibrium . Alessandro Nada (UniTo & INFN) Applications of Jarzynski’s relation in LGTs 26/07/2016

  6. Jarzynski’s equality - I Jarzynski’s equality [Jarzynski, 1997] relates the exponential statistical average of the work done on a system during a non-equilibrium process with the difference between the initial and the final free energy of the system. For an isothermal transformation it can be written as � � �� � � − W ( λ i , λ f ) − ∆ F exp = exp T T The evolution of the system is performed by changing (continuously or discretely) a chosen set λ of one or more parameters, such as the couplings or the temperature of the system. In each step of the process the value of λ is changed and the system is brought out of equilibrium . Alessandro Nada (UniTo & INFN) Applications of Jarzynski’s relation in LGTs 26/07/2016

  7. Jarzynski’s equality - II � � �� � � − W ( λ i , λ f ) − ∆ F exp = exp T T � � = Z ( T ,λ f ) − ∆ F • on the r.h.s. exp Z ( T ,λ i ) where ∆ F = F ( λ f ) − F ( λ i ) T • W ( λ i , λ f ) is the work made on the system to change the control parameter from λ i to λ f . If the transformation is discrete (like a Markov chain in MC simulations), then the process is divided into N steps and the total work is N − 1 � � � W ( λ i ≡ λ 0 , λ f ≡ λ N ) = H λ n +1 [ φ n ] − H λ n [ φ n ] n =0 where φ n is the configuration of the variables of the system at the n -th step of the transformation • the � ... � indicates the average on all possible realizations of the non-equilibrium transformation Alessandro Nada (UniTo & INFN) Applications of Jarzynski’s relation in LGTs 26/07/2016

  8. Jarzynski’s equality - II � � �� � � − W ( λ i , λ f ) − ∆ F exp = exp T T � � = Z ( T ,λ f ) − ∆ F • on the r.h.s. exp Z ( T ,λ i ) where ∆ F = F ( λ f ) − F ( λ i ) T • W ( λ i , λ f ) is the work made on the system to change the control parameter from λ i to λ f . If the transformation is discrete (like a Markov chain in MC simulations), then the process is divided into N steps and the total work is N − 1 � � � W ( λ i ≡ λ 0 , λ f ≡ λ N ) = H λ n +1 [ φ n ] − H λ n [ φ n ] n =0 where φ n is the configuration of the variables of the system at the n -th step of the transformation • the � ... � indicates the average on all possible realizations of the non-equilibrium transformation Alessandro Nada (UniTo & INFN) Applications of Jarzynski’s relation in LGTs 26/07/2016

  9. Jarzynski’s equality - II � � �� � � − W ( λ i , λ f ) − ∆ F exp = exp T T � � = Z ( T ,λ f ) − ∆ F • on the r.h.s. exp Z ( T ,λ i ) where ∆ F = F ( λ f ) − F ( λ i ) T • W ( λ i , λ f ) is the work made on the system to change the control parameter from λ i to λ f . If the transformation is discrete (like a Markov chain in MC simulations), then the process is divided into N steps and the total work is N − 1 � � � W ( λ i ≡ λ 0 , λ f ≡ λ N ) = H λ n +1 [ φ n ] − H λ n [ φ n ] n =0 where φ n is the configuration of the variables of the system at the n -th step of the transformation • the � ... � indicates the average on all possible realizations of the non-equilibrium transformation Alessandro Nada (UniTo & INFN) Applications of Jarzynski’s relation in LGTs 26/07/2016

  10. Jarzynski’s equality - Comments • The equality requires no particular assumptions and holds under very general conditions (e.g. the detailed balance condition for Markov chains) • It can be extended for non-isothermal transformations [Chatelain, 2007] • In Monte Carlo simulations we can control • N , the number of steps for each transformation between initial and final value of the parameter λ • n r , the number of “trials”, i.e. realizations of the non-equilibrium transformation • A systematic discrepancy appears between the results of the ’direct’ ( λ i → λ f ) and the ’reverse’ ( λ f → λ i ) transformation. One has to choose a suitable combination of N and n r in order to obtain convergence. Alessandro Nada (UniTo & INFN) Applications of Jarzynski’s relation in LGTs 26/07/2016

  11. Jarzynski’s equality - Comments • The equality requires no particular assumptions and holds under very general conditions (e.g. the detailed balance condition for Markov chains) • It can be extended for non-isothermal transformations [Chatelain, 2007] • In Monte Carlo simulations we can control • N , the number of steps for each transformation between initial and final value of the parameter λ • n r , the number of “trials”, i.e. realizations of the non-equilibrium transformation • A systematic discrepancy appears between the results of the ’direct’ ( λ i → λ f ) and the ’reverse’ ( λ f → λ i ) transformation. One has to choose a suitable combination of N and n r in order to obtain convergence. Alessandro Nada (UniTo & INFN) Applications of Jarzynski’s relation in LGTs 26/07/2016

  12. Jarzynski’s equality - Comments • The equality requires no particular assumptions and holds under very general conditions (e.g. the detailed balance condition for Markov chains) • It can be extended for non-isothermal transformations [Chatelain, 2007] • In Monte Carlo simulations we can control • N , the number of steps for each transformation between initial and final value of the parameter λ • n r , the number of “trials”, i.e. realizations of the non-equilibrium transformation • A systematic discrepancy appears between the results of the ’direct’ ( λ i → λ f ) and the ’reverse’ ( λ f → λ i ) transformation. One has to choose a suitable combination of N and n r in order to obtain convergence. Alessandro Nada (UniTo & INFN) Applications of Jarzynski’s relation in LGTs 26/07/2016

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