Worm Algorithm PIMC Application to Liquid and Solid 4 He

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Transcription:

Worm Algorithm PIMC Application to Liquid and Solid 4 He KITP - Santa Barbara, 2/8/06 Massimo Boninsegni University of Alberta Nikolay Prokof ev and Boris Svistunov University of Massachusetts

Outline of the talk Theoretical problem: investigation of superfluid behavior of matter in unusual settings Bulk solid 4 He or H 2 Interfaces, grain boundaries etc. Quantum clusters Adsorbed films Path Integral Monte Carlo: powerful numerical tool to study Bose systems (D. Ceperley, RMP 67, 279, 1995) Accurate - No adjustable parameter - no trial wave fnctn Microscopic Hamiltonian - only input is the potential Allows direct computation of ρ s (T) and n 0 (T) Problem: finite-size effects ( large system sizes needed)

Outline (cont d) Worm Algorithm: overcomes size limitation of existing PIMC technology (ρ s (T) hard to compute for N 100) Grand Canonical: allows simultaneous calculation of structural, energetic properties, as well as dynamic (imaginary-time) correlations (e.g., Matsubara Green function) Affords considerable efficiency gain in the calculation of ρ s (T) - N can be as large as several thousands (accurate determination of T c possible) Illustrative applications: superfluid transition in liquid 4 He in 2 and 3 dimensions Application to commensurate solid 4 He

Path Integral Monte Carlo Thermal averages of physical operators at finite T=1/β Ô = Tr(Ôρ) = dr O(R) ρ(r,r,β) ρ(r,r,β) many-body density matrix (unknown in general) Feynman s recipe: ρ(r,r,β) dr 0...dR P-1 { i ρ o (R i,r i+1,τ)}, τ= β/p Exact as P, τ 0 ρ o (R,R,τ) high-t approximation to exact ρ Monte Carlo scheme to path integration: Generate on a computer set of paths {X i =R 0i R 1i R...R P-1 } sampled with probability { i ρ o (R i,r i+1,τ)} Metropolis algorithm Evaluate Ô as statistical average of O(R i ) Crucial to efficiency of method is path sampling strategy

Worm Algorithm N. Prokof ev, B. Svistunov and I. Tupitsyn, Phys. Lett. A 238, 235 (1998) MB, N. Prokof ev and B. Svistunov, Phys. Rev. Lett. 96, 10212 (2006) Basic idea: work in extended configuration space Include 1 open Word Line (worm) whose head and tail can advance and recede in imaginary time Grand Canonical ensemble β M 1 2 3 4 I 0

Worm Algorithm (cont d) Local moves only-- all involving worm Head and tail of worm can swap with other World Lines efficient sampling of long permutation cycles Complementary pairs of moves Open/Close, Advance/Recede detailed balance (swap move self-complementary) k j+m _ j I M I M i k (a) (b)

Worm Algorithm (cont d) Configurations with an open WL contribute to the Matsubara Green function (G-sector) nontrivial modifications of WL Swap moves enjoy relatively high acceptance, even with hard core potentials Head and tail can reconnect, resulting in a diagonal configuration, which contributes to the partition function (Z-sector) Reconnection is attempted periodically (no need to wait for it!) Number of particles fluctuates (WLs can disappear and be recreated) -- Note, however, that canonical versions are possible General algorithm of statistical mechanics Applied to several quantum and classical lattice models No critical slowing down for Ising model

Application: SF transition in 4 He 1.0 0.8 25 200 2500 "!"!# s 0.6 0.4 0.2 0.0 2 dimensions T c =0.653(10) K 0.5 0.6 0.7 0.8 0.9 1.0!

60 50 40 30 20 10 10 20 30 40 50 60 4 He in 2 dimensions, T=0.6 K, 200 particles

Superfluid Transition in 3D 4 He n /n s 1 0.75 ρ S 0.5 NN=64 to 2048 0.25 0 1 1.5 2 T(K)

SF transition in 4 He (cont d) <W 2 >/3 1 2048 1024 3 dimensions T c =2.193(6) K 0.8 128 64 512 0.6 U(1) 0.4 T c (exp) T c (Aziz) 2.12 2.14 2.16 2.18 2.2 T(K)

OK, but...why do we need large systems? Some physical quantities require large size extrapolation Examples: T c, n 0!(r) 0.8!(r) 0.06 T = 2.14 K 0.6 0.04 0.4 0.02 0.2 0 5 10 15 20 r(a) 0 5 10 15 r(a)

Why is it important to do large systems? Some physical phenomena can only be properly formulated or studied on sufficiently large system sizes. Possible superfluid layer at solid 4 He grain boundaries Superfluidity in porous media Dislocations and extended defects in quantum crystals Polycrystalline samples (talk by B. Svistunov next week)

BEC/SF in solid 4 He? 0-2 superglass log (n(r)) 10-4 -6 ρ=0.0292 A -3-8 T=0.2 K, N=800 ρ s =0 ρ=0.0359 A -3 hcp crystal -10 0 5 10 o r (A)

Results No evidence of BEC/SF found in a perfect hcp crystal at low T Ring exchanges do occur, but long permutation cycles yielding nonzero winding (i.e., SF) are not observed Through swap type moves, worm ends can travel far apart (providing statistics for n(r) at large r). However, they almost invariably reconnect without leaving any permutation behind, unlike in the superfluid. Physical result, not artifact of computational/sampling methodology (e.g., possible lack of ergodicity) Consistent with general theoretical result for commensurate crystals N. Prokof ev and B. Svistunov, Phys. Rev. Lett. 94, 155302 (2005)

Current and future research Accurate determination of vacancy activation energy in solid 4 He Application of Green function formalism - no subtraction needed of large energies Exploration of novel phases of solid Helium Possible superglass phase Superfluidity at grain boundaries (talk by B. Svistunov) Acknowledgments NSERC (Canada) NSF NASA Sloan Foundation