We investigate the equilibrium dynamics of our recently proposed toy model of dense fluid in the infinite damping limit. Contrary to naive expectation, the correlators involving the velocity-like variables do not quickly relax away. Instead, after a very fast transient relaxation, they exhibit rather slow relaxations due to the coupling to the density-like variable. Hence, the so-called "hopping" processes are not suppressed even in the large damping limit. These hopping processes can only be controlled by tuning the parameter delta, which is the ratio of the numbers of the components of the velocity-like and the density-like variables in the model. We analytically prove that there must exist an ergodic-to-nonergodic phase transition for delta such that 0 < delta < 1. The slow dynamics and the dynamic transition in the model are distinct from those in the idealized mode coupling theory.
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Chem Soc Rev
January 2025
Faculty of Chemistry and Food Chemistry, TU Dresden, Bergstrasse 66, 01062 Dresden, Germany.
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Department of Electrical and Computer Engineering, and Department of Physics and Astronomy, University of California, Los Angeles, CA, 90095, USA.
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Department of Mechanical Engineering, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia.
Metamaterials are pushing the limits of traditional materials and are fascinating frontiers in scientific innovation. Mechanical metamaterials (MMs) are a category of metamaterials that display properties and performances that cannot be realized in conventional materials. Exploring the mechanical properties and various aspects of vibration and damping control is becoming a crucial research area.
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December 2024
College of Computer and Data Science, Fuzhou University, Fuzhou, 350108, China; Key Laboratory of Intelligent Metro, Fujian Province University, Fuzhou, 350108, China. Electronic address:
Graph convolutional networks have achieved remarkable success in the field of multi-view learning. Unfortunately, most graph convolutional network-based multi-view learning methods fail to capture long-range dependencies due to the over-smoothing problem. Many studies have attempted to mitigate this issue by decoupling graph convolution operations.
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January 2025
Department of Ecology and Conservation Biology, Texas A&M University, College Station, TX, United States of America.
Matrix population models are essential tools in conservation biology, offering key metrics to guide species management and conservation planning. However, the development of these models is often limited by insufficient life history data, particularly for non-charismatic species. This study addresses this gap by using life history data from FishBase and the FishLife R package, complemented by size-dependent natural mortality estimates, to parameterize age-structured matrix population models applicable to most fish species.
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