langevin molecular dynamics of driven magnetic flux lines
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Langevin Molecular Dynamics of Driven Magnetic Flux Lines Ulrich Dobramysl, Michel Pleimling and Uwe C. T auber Department of Physics, Virginia Tech, Blacksburg, VA, USA SESAPS Meeting, Roanoke, VA, October 22, 2011 Motivation Type II


  1. Langevin Molecular Dynamics of Driven Magnetic Flux Lines Ulrich Dobramysl, Michel Pleimling and Uwe C. T¨ auber Department of Physics, Virginia Tech, Blacksburg, VA, USA SESAPS Meeting, Roanoke, VA, October 22, 2011

  2. Motivation ◮ Type II superconductors exhibit a second order phase transition from superconducting to normal state ◮ Magnetic flux penetrates above critical field H c 1 through vortex lines - each one carries a flux quantum ◮ Vortex lines movement generates dissipation ◮ Pinning by (artificially introduced) defect sites - optimization ◮ Complex and rich system that is accessible in experiments ◮ High T C SC - interesting for technology and applications

  3. Elastic Line Model After coarse graining: Vortex lines are interacting elastic lines †   � L N N 2 � �  ǫ 1 d � r + 1 � � � � F el = V I ( | � r ij | ) + V D ( � r j ) dz � �  2 dz 2 � � 0 j =1 i � = j ◮ Elastic energy ǫ 1 (stiffness) ◮ Line interaction energy V I ( | � r ij | ) ∝ K 0 ( | � r ij | ) ◮ Defects potential V D ( � r ) due to pin sites ◮ This work: only random point defects Discretize lines into connected particles → simulations † D.R. Nelson and VM Vinokur PRB 48 13060 (1993), T. Klongcheongsan, TJ Bullard, and UC T¨ auber, Supercond Sci Tech 23 025023 (2010)

  4. Visualization LMD simulation of interacting vortex lines in clean system → form hexagonal lattice t = 0

  5. Methods Monte Carlo Find steady state by performing a biased random walk on the energy landscape ◮ Problem: external drive enters energy - not well defined for relaxation into non-equilibrium steady-state Langevin Molecular Dynamics Algorithm Solve the system of coupled Langevin equations r i = − ζ ˙ ¨ r i + � 2 ζ k B T � � � � F ( { � r j } ) + R ( t ) ◮ Additional random force term � η describing fast degrees of freedom - temperature bath ◮ Gaussian white noise � R i ( t ) R j ( t ′ ) � = δ ij δ ( t − t ′ ) ◮ Problem: also not well defined for non-equilibrium (driven) systems

  6. Time regimes Transient regime Steady state ◮ Dependent on inital ◮ Time translation invariance conditions recovered ◮ Dynamical scaling - aging ◮ No dependence on initial conditions ◮ Time translation invariance ◮ All quantities stationary in broken thermodynamic limit ◮ Need two-time quantities to characterize

  7. Driven system results 1.00 10 16 lines 16 lines Normalized velocity v/v 0 32 lines 32 lines 8 Gyration radius r g 64 lines 64 lines 0.75 LMD LMD MC MC 6 0.50 4 0.25 2 0.00 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 Driving force F d Driving force F d ◮ 16, 32 or 64 initially straight lines placed at random positions ◮ 34200 randomly distributed point defects ◮ Driven system, allowed to relax into steady state ◮ Agreement between MC and LMD good

  8. Two-time height-height autocorrelation LMD yields similar results as previously performed MC simulations † No defect sites Disordered system 10 0 1.1 4 8 16 32 64 10 -1 1.0 C ( t,s ) 0.9 10 -2 C ( t,s ) /C ( s,s ) 0.8 10 -3 10 -1 10 0 10 1 10 2 10 3 10 4 t − s 0.7 5.5 ln( s − 0 . 5 C ( t,s )) 128 256 512 1024 0.6 6.0 0.5 6.5 0.4 7.0 0.3 0.0 0.5 1.0 1.5 2.0 10 -1 10 0 10 1 10 2 10 3 10 4 ln( t/s ) t − s ◮ Dynamical scaling - aging ◮ Disorder leads to glass-like exponent ≈ 0 . 5 relaxation † M. Pleimling and U.C. T¨ auber, arXiv :1106.1130 (2011)

  9. Summary Conclusion ◮ Complex out-of-equilibrium system ◮ Important to understand vortex dynamics to optimize technological applications ◮ Both methods yield comparable results - complementary to each other ◮ LMD is much more efficient Outlook ◮ Aging regime – universality/scaling ◮ Correlated defects ◮ Thin films ◮ Relaxation of driven systems

  10. Thank you for your attention! References ◮ D.R. Nelson and VM Vinokur PRB 48 13060 (1993) ◮ T. Klongcheongsan, TJ Bullard, and UC T¨ auber, Supercond Sci Tech 23 025023 (2010) ◮ M. Pleimling and U.C. T¨ auber, arXiv :1106.1130 (2011) This research was funded by the Department of Energy, grant number BES DE-FG02-09ER46613.

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