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Condensed Matter > Disordered Systems and Neural Networks

Title: Study of the de Almeida-Thouless (AT) line in the one-dimensional diluted power-law XY spin glass

Abstract: We study the AT line in the one-dimensional power-law diluted XY spin glass model, in which the probability that two spins separated by a distance $r$ interact with each other, decays as $1/r^{2\sigma}$. We develop a heat bath algorithm to equilibrate XY spins; using this in conjunction with the standard parallel tempering and overrelaxation sweeps, we carry out large scale Monte Carlo simulations. For $\sigma=0.6$ which is in the mean-field regime, we find clear evidence for an AT line. For $\sigma = 0.75$, there is evidence from finite size scaling studies for an AT transition but for $\sigma = 0.85$, the evidence for a transition is non-existent. We have also studied these systems at fixed temperature varying the field and discovered that at both $\sigma = 0.75$ and at $\sigma =0.85$ there is evidence of an AT transition! Confusingly, the correlation length and spin glass susceptibility as a function of the field are both entirely consistent with the predictions of the droplet picture and hence the non-existence of an AT line. The evidence from our simulations points to the complete absence of the AT line in dimensions outside the mean-field region and to the correctness of the droplet picture. Previous simulations which suggested there was an AT line can be attributed to the consequences of studying systems which are just too small. The collapse of our data to the droplet scaling form is poor for $\sigma = 0.75$ and to some extent also for $\sigma = 0.85$, when the correlation length becomes of the order of the length of the system, due to the existence of excitations which only cost a free energy of $O(1)$, just as envisaged in the TNT picture of the ordered state of spin glasses. However, for the case of $\sigma = 0.85$ we can provide evidence that for larger system sizes, droplet scaling will prevail even when the correlation length is comparable to the system size.
Comments: 24 pages, 15 figures
Subjects: Disordered Systems and Neural Networks (cond-mat.dis-nn)
Journal reference: Phys. Rev. E 108, 014116 (2023)
DOI: 10.1103/PhysRevE.108.014116
Cite as: arXiv:2301.03615 [cond-mat.dis-nn]
  (or arXiv:2301.03615v5 [cond-mat.dis-nn] for this version)

Submission history

From: Bharadwaj Vedula [view email]
[v1] Mon, 9 Jan 2023 19:00:03 GMT (5717kb,D)
[v2] Thu, 23 Mar 2023 18:00:03 GMT (2592kb,D)
[v3] Thu, 29 Jun 2023 18:00:10 GMT (2592kb,D)
[v4] Thu, 20 Jul 2023 05:03:02 GMT (2593kb,D)
[v5] Mon, 24 Jul 2023 14:23:32 GMT (2593kb,D)

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