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Flows with deformable interfaces are commonly controlled by applying an external field or modifying the boundaries that interact with the fluid, but realizing such solutions can be demanding or impractical in various scenarios. Here, we…

Soft Condensed Matter · Physics 2025-03-28 Hugo França , Maziyar Jalaal

Due to the lack of long-range order, it remains challenging to characterize the structure of disordered solids and understand the nature of the glass transition. Here we propose a new structural order parameter by taking into account…

Soft Condensed Matter · Physics 2024-08-26 Ding Xu , Qinyi Liao , Ning Xu

The hyperuniformity concept provides a unified means to classify all perfect crystals, perfect quasicrystals, and exotic amorphous states of matter according to their capacity to suppress large-scale density fluctuations. While the…

Statistical Mechanics · Physics 2021-01-27 Jaeuk Kim , Salvatore Torquato

Overcoming the detrimental effect of disorder at the nanoscale is very hard since disorder induces localization and an exponential suppression of transport efficiency. Here we unveil novel and robust quantum transport regimes achievable in…

The presence of disorder can severely impede wave transport, resulting in the famous Anderson localization. Previous theoretical studies found that Anderson transition can exist in one-dimensional (1D) non-Hermitian disordered rings with…

Applied Physics · Physics 2025-02-13 Wei Wang , Xulong Wang , Guancong Ma

Self-propelled particles with hydrodynamic interactions (microswimmers) have previously been shown to produce long-range ordering phenomena. Many theoretical explanations for these collective phenomena are connected to instabilities in the…

Soft Condensed Matter · Physics 2017-05-03 Yuzhou Qian , Peter R. Kramer , Patrick T. Underhill

Emergent order resulting from spontaneous symmetry breakings has been a central topic in statistical physics. Active matter systems composed of nonequilibrium elements exhibit a diverse range of fascinating phenomena beyond equilibrium…

Statistical Mechanics · Physics 2023-07-03 Daiki Nishiguchi

The rapid development of cloud-native architecture has promoted the widespread application of container technology, but the optimization problems in container scheduling and resource management still face many challenges. This paper…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-12-24 Xiaoye Wang

Solving inverse problems, such as parameter estimation and optimal control, is a vital part of science. Many experiments repeatedly collect data and rely on machine learning algorithms to quickly infer solutions to the associated inverse…

Machine Learning · Computer Science 2022-10-14 Philipp Holl , Vladlen Koltun , Nils Thuerey

Amorphous materials of homogeneous structures usually suffer from nonuniform deformation under shear, which can develop into shear localization and eventually destructive shear band. One approach to tackle this issue is to introduce an…

Materials Science · Physics 2019-02-01 Guo-Jie J. Gao , Yun-Jiang Wang , Shigenobu Ogata

Mixtures of active and passive particles are ubiquitous at the microscale. Many essential microbial processes involve interactions with dead or immotile cells or passive crowders. When passive objects are immersed in active baths, their…

Soft Condensed Matter · Physics 2026-02-24 Horacio Serna , C. Miguel Barriuso G. , Ignacio Pagonabarraga , Marco Polin , Chantal Valeriani

Artificial microswimmers are a new technology with promising microfluidics and biomedical applications, such as directed cargo transport, microscale assembly, and targeted drug delivery. A fundamental barrier to realising this potential is…

Fluid Dynamics · Physics 2018-06-27 Thomas D. Montenegro-Johnson

Over the past decade, Deep Learning has emerged as a useful and efficient tool to solve a wide variety of complex learning problems ranging from image classification to human pose estimation, which is challenging to solve using statistical…

Computer Vision and Pattern Recognition · Computer Science 2020-05-19 Ashutosh Chaubey , Nikhil Agrawal , Kavya Barnwal , Keerat K. Guliani , Pramod Mehta

Many of the artificial intelligence techniques developed to date rely on heuristic search through large spaces. Unfortunately, the size of these spaces and the corresponding computational effort reduce the applicability of otherwise novel…

Artificial Intelligence · Computer Science 2011-05-30 D. J. Cook , R. C. Varnell

Understanding the collective actuation of microscopic structures driven by external fields can lead to the development of next-generation autonomous machines. With this goal in mind, we investigated light-induced collective motion of…

Structured light enables the characterization of chirality of optically small nanoparticles by taking advantage of the helicity maximization concept recently introduced in[1]. By referring to fields with nonzero helicity density as chiral…

Applied Physics · Physics 2020-11-04 Mina Hanifeh , Mohammad Albooyeh , Filippo Capolino

The deep neural network has attained significant efficiency in image recognition. However, it has vulnerable recognition robustness under extensive data uncertainty in practical applications. The uncertainty is attributed to the inevitable…

Machine Learning · Computer Science 2023-08-02 Ruoxi Qin , Linyuan Wang , Xuehui Du , Xingyuan Chen , Bin Yan

This paper mainly focuses on solving the dynamic optimization of the planar controlled crowd motion models with obstacles which is an application of a class of optimal control problems governed by a general perturbed nonconvex sweeping…

Optimization and Control · Mathematics 2021-04-09 Tan Cao , Boris Mordukhovich , Dao Nguyen , Trang Nguyen

We study the emergent orientational dynamics of a dumbbell dimer -- two asymmetric monomers connected by a linking spring -- in a three-dimensional chiral environment with odd viscosity. In classical systems with conserved parity symmetry,…

Soft Condensed Matter · Physics 2025-10-23 Michalis Chatzittofi , Yuto Hosaka

Heterogeneous materials consisting of different phases are ideally suited to achieve a broad spectrum of desirable bulk physical properties by combining the best features of the constituents through the strategic spatial arrangement of the…

Materials Science · Physics 2017-10-10 Duyu Chen , Salvatore Torquato
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