Leggett's bound for amorphous solids

We investigate the constraints on the superfluid fraction of an amorphous solid following from an upper bound derived by Leggett. In order to accomplish this, we use as input density profiles generated for amorphous solids in a variety of different manners including by investigating Gaussian fluctuations around classical results. These rough estimates suggest that, at least at the level of the upper bound, there is not much difference in terms of superfluidity between a glass and a crystal characterized by the same Lindemann ratio. Moreover, we perform Path Integral Monte Carlo simulations of distinguishable Helium 4 rapidly quenched from the liquid phase to very lower temperature, at the density of the freezing transition. We find that the system crystallizes very quickly, without any sign of intermediate glassiness. Overall our results suggest that the experimental observations of large superfluid fractions in Helium 4 after a rapid quench correspond to samples evolving far from equilibrium, instead of being in a stable glass phase. Other scenarios and comparisons to other results on the super-glass phase are also discussed.Comment: 11 pages, 5 figure

Yielding and plasticity in amorphous solids

The physics of disordered media, from metallic glasses to colloidal suspensions, granular matter and biological tissues, offers difficult challenges because it often occurs far from equilibrium, in materials lacking symmetries and evolving through complex energy landscapes. Here, we review recent theoretical efforts to provide microscopic insights into the mechanical properties of amorphous media using approaches from statistical mechanics as unifying frameworks. We cover both the initial regime corresponding to small deformations, and the yielding transition marking a change between elastic response and plastic flow. We discuss the specific features arising for systems evolving near a jamming transition, and extend our discussion to recent studies of the rheology of dense biological and active materials.Comment: 20 pages, 7 figure

Body composition assessment: comparison of quantitative values between magnetic resonance imaging and computed tomography.

Background The primary objective of this study was to compare measurements of skeletal muscle index (SMI), visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) at the level of L3, on subjects who underwent computed tomography (CT) and magnetic resonance imaging (MRI) examinations within a three-month period. The secondary objective was to compare the automatic and semi-automatic quantifications of the same values for CT images. Methods Among subjects who underwent CT and MRI at our Institution between 2011 and 2020, exclusion criteria were: presence of extensive artifacts; images not including the whole waist circumference; CT acquired with low-dose technique and lack of non-contrast images. A set of three axial images (CT, MRI T1-weighted and T2-weighted) were used to extract the following measurements with semi-automatic segmentations: SMI [calculated normalizing skeletal muscle area (SMA) by the square height], SAT, VAT. For the CT images only, the same values were also calculated by using automatic segmentation. Statistical analysis was performed comparing quantitative MRI and CT measurements by Pearson correlation analysis and by Bland-Altman agreement analysis. Results A total of 123 patients were included. By performing linear regression analysis, CT and MRI measurements of SMI showed a high correlation (r2=0.81 for T1, r2=0.89 for T2), with a mean logarithmic difference between CT and MRI quantitative values of 0.041 for T1-weighted and 0.072 for T2-weighted images. CT and MRI measurements of SAT showed high correlation (r2=0.81 for T1; r2=0.81 for T2), with a mean logarithmic difference between CT and MRI values of 0.0174 for T1-weighted and 0.201 for T2-weighted images. CT and MRI measurements of VAT showed high correlation (r2=0.94 for T1; r2=0.93 for T2), with a mean logarithmic difference of 0.040 for T1-weighted and -0.084 for T2-weighted images. The comparison of values extracted by semi-automatic and automatic segmentations were highly correlated. Conclusions Quantification of body composition values at MRI from T1-weighted and T2-weighted images was highly correlated to same values at CT, therefore quantitative values of body composition among patients who underwent either one of the examinations may be compared. CT body composition values extracted by semi-automatic and automatic segmentations showed high correlation

Experimental Determination of Configurational Entropy in a Two-Dimensional Liquid under Random Pinning

A quasi two-dimensional colloidal suspension is studied under the influence of immobilisation (pinning) of a random fraction of its particles. We introduce a novel experimental method to perform random pinning and, with the support of numerical simulation, we find that increasing the pinning concentration smoothly arrests the system, with a cross-over from a regime of high mobility and high entropy to a regime of low mobility and low entropy. At the local level, we study fluctuations in area fraction and concentration of pins and map them to entropic structural signatures and local mobility, obtaining a measure for the local entropic fluctuations of the experimental system

Roadmap on machine learning glassy liquids

Unraveling the connections between microscopic structure, emergent physical properties, and slow dynamics has long been a challenge in the field of the glass transition. The absence of clear visible structural order in amorphous configurations complicates the identification of the key features related to structural relaxation and transport properties. The difficulty in sampling equilibrated configurations at low temperatures hampers thorough numerical and theoretical investigations. This roadmap article explores the potential of machine learning (ML) techniques to face these challenges, building on the algorithms that have revolutionized computer vision and image recognition. We present successful ML applications, as well as many open problems for the future, such as transferability and interpretability of ML approaches. We highlight new ideas and directions in which ML could provide breakthroughs to better understand glassy liquids. To foster a collaborative community effort, the article introduces the "GlassBench" dataset, providing simulation data and benchmarks for both two-dimensional and three-dimensional glass-formers. Emphasizing the importance of benchmarks, we identify critical metrics for comparing the performance of emerging ML methodologies, in line with benchmarking practices in image and text recognition. The goal of this roadmap is to provide guidelines for the development of ML techniques in systems displaying slow dynamics, while inspiring new directions to improve our understanding of glassy liquids

Can the jamming transition be described using equilibrium statistical mechanics?

When materials such as foams or emulsions are compressed, they display solid behaviour above the so-called `jamming' transition. Because compression is done out-of-equilibrium in the absence of thermal fluctuations, jamming appears as a new kind of a nonequilibrium phase transition. In this proceeding paper, we suggest that tools from equilibrium statistical mechanics can in fact be used to describe many specific features of the jamming transition. Our strategy is to introduce thermal fluctuations and use statistical mechanics to describe the complex phase behaviour of systems of soft repulsive particles, before sending temperature to zero at the end of the calculation. We show that currently available implementations of standard tools such as integral equations, mode-coupling theory, or replica calculations all break down at low temperature and large density, but we suggest that new analytical schemes can be developed to provide a fully microscopic, quantitative description of the jamming transition.Comment: 8 pages, 6 figs. Talk presented at Statphys24 (July 2010, Cairns, Australia

Theory of the superglass phase

A superglass is a phase of matter which is characterized at the same time by superfluidity and a frozen amorphous structure. We introduce a model of interacting bosons in three dimensions that displays this phase unambiguously and that can be analyzed exactly or using controlled approximations. Employing a mapping between quantum Hamiltonians and classical Fokker-Planck operators, we show that the ground state wavefunction of the quantum model is proportional to the Boltzmann measure of classical hard spheres. This connection allows us to obtain quantitative results on static and dynamic quantum correlation functions. In particular, by translating known results on the glassy dynamics of Brownian hard spheres we work out the properties of the superglass phase and of the quantum phase transition between the superfluid and the superglass phase.Comment: 23 pages, 7 figure