2019
DOI: 10.1103/physreve.99.031301
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Bypassing sluggishness: SWAP algorithm and glassiness in high dimensions

Abstract: The recent implementation of a swap Monte Carlo algorithm (SWAP) for polydisperse mixtures fully bypasses computational sluggishness and closes the gap between experimental and simulation timescales in physical dimensions d = 2 and 3. Here, we consider suitably optimized systems in d = 2, 3, . . . , 8, to obtain insights into the performance and underlying physics of SWAP. We show that the speedup obtained decays rapidly with increasing the dimension. SWAP nonetheless delays systematically the onset of the act… Show more

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Cited by 22 publications
(15 citation statements)
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References 52 publications
(46 reference statements)
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“…Unfortunately, the obtained values fall in-between the two predictions, which are too close to be discriminated. We suggest that performing point-to-set and configurational entropy measurements in d = 4, combining recently developed tools [45, 51,87], would be very useful to conclude on this point. Indeed, when d = 4, the two In Fig.…”
Section: Resultsmentioning
confidence: 99%
“…Unfortunately, the obtained values fall in-between the two predictions, which are too close to be discriminated. We suggest that performing point-to-set and configurational entropy measurements in d = 4, combining recently developed tools [45, 51,87], would be very useful to conclude on this point. Indeed, when d = 4, the two In Fig.…”
Section: Resultsmentioning
confidence: 99%
“…VII) suggests that the analysis might not be as painful as it first seems. Thanks to the recent extension of enhanced sampling techniques to higher dimensions 75 , similar considerations in d = 4 and 5 might also be within reach. The complex criticality scenarios proposed for this transition (see Sec.…”
Section: A Gardner Transitionmentioning
confidence: 87%
“…We created glassy samples of this computer glass former in two and three dimensions (2D & 3D). Thanks to the heightened efficiency of Swap Monte Carlo in 2D [32,33], the degree of supercooling of our systems in 2D is significantly greater compared to our most deeply supercooled 3D systems: if T onset marks the onset parent temperature of the plateau of the athermal shear modulus (see, e.g., Refs. [24,34]) of underlying inherent states of equilibrium configurations, then in 2D we equilibrate supercooled samples down to 15% of T onset , whereas in 3D we only reach 33% of T onset .…”
Section: Models and Methodsmentioning
confidence: 99%