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Spontaneous phase coordination and fluid pumping in model ciliary carpets

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arXiv 2022年

作者： Kanale, Anup V. Ling, Feng Guo, Hanliang Fürthauer, Sebastian Kanso, Eva Aerospace and Mechanical Engineering University of Southern California Los AngelesCA90089 United States Department of Mathematics University of Michigan Ann ArborMI48109 United States Department of Mathematics and Computer Science Ohio Wesleyan University DelawareOH43015 United States Center for Computational Biology Flatiron Institute New YorkNY10010 United States Institute for Applied Physics TU Wien Wien1050 Austria

Ciliated tissues such as in the mammalian lungs, brains, and reproductive tracts, are specialized to pump fluid. They generate flows by the collective activity of hundreds of thousands of individual cilia that beat in a striking metachronal wave pattern. Despite progress in analyzing cilia coordination, a general theory that links coordination and fluid pumping in the limit of large arrays of cilia remains lacking. Here, we conduct in-silico experiments with thousands of hydrodynamically-interacting cilia, and we develop a continuum theory in the limit of infinitely-many independently beating cilia by combining tools from active matter and classical Stokes flow. We find, in both simulations and theory, that isotropic and synchronized ciliary states are unstable. Traveling waves emerge regardless of initial conditions, but the characteristics of the wave and net flows depend on cilia and tissue properties. That is, metachronal phase coordination is a stable global attractor in large ciliary carpets, even under finite perturbations to cilia and tissue properties. These results support the notion that functional specificity of ciliated tissues is interlaced with the tissue architecture and cilia beat kinematics and open up the prospect of establishing structure-to-function maps from cilium-level beat to tissue-level coordination and fluid pumping. Copyright © 2022, The Authors. All rights reserved.

关键词： Tissue

Surface Coverage Dynamics for Reversible Dissociative Adsorption on Finite Linear Lattices

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arXiv 2022年

作者： Mercado, Enrique Jung, Hyun Tae Kim, Changho Garcia, Alejandro L. Nonaka, Andy J. Bell, John B. Department of Applied Mathematics University of California MercedCA95343 United States Department of Chemistry Korea Advanced Institute of Science and Technology Daejeon34141 Korea Republic of Department of Physics and Astronomy San Jose State University San JoseCA95192 United States Center for Computational Sciences and Engineering Lawrence Berkeley National Laboratory BerkeleyCA94720 United States

Dissociative adsorption onto a surface introduces dynamic correlations between neighboring sites not found in non-dissociative absorption. We study surface coverage dynamics where reversible dissociative adsorption of dimers occurs on a finite linear lattice. We derive analytic expressions for the equilibrium surface coverage as a function of the number of reactive sites, N, and the ratio of the adsorption and desorption rates. Using these results, we characterize the finite size effect on the equilibrium surface coverage. For comparable N’s, the finite size effect is significantly larger when N is even than when N is odd. Moreover, as N increases, the size effect decays more slowly in the even case than in the odd case. The finite-size effect becomes significant when adsorption and desorption rates are considerably different. These finite-size effects are related to the number of accessible configurations in a finite system where the odd-even dependence arises from the limited number of accessible configurations in the even case. We confirm our analytical results with kinetic Monte Carlo simulations. We also analyze the surface-diffusion case where adsorbed atoms can hop into neighboring sites. As expected, the odd-even dependence disappears because more configurations are accessible in the even case due to surface diffusion. Copyright © 2022, The Authors. All rights reserved.

关键词： Surface diffusion

Machine learning based non-Newtonian fluid model with molecular fidelity

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arXiv 2020年

作者： Lei, Huan Wu, Lei Weinan, E. Department of Computational Mathematics Science & Engineering Department of Statistics & Probability Michigan State University MI48824 United States Department of Mathematics and Program in Applied and Computational Mathematics Princeton University NJ08544 United States

We introduce a machine-learning-based framework for constructing continuum non-Newtonian fluid dynamics model directly from a micro-scale description. Polymer solution is used as an example to demonstrate the essential ideas. To faithfully retain molecular fidelity, we establish a micro-macro correspondence via a set of encoders for the micro-scale polymer configurations and their macro-scale counterparts, a set of nonlinear conformation tensors. The dynamics of these conformation tensors can be derived from the micro-scale model and the relevant terms can be parametrized using machine learning. The final model, named the deep non-Newtonian model (DeePN2), takes the form of conventional non-Newtonian fluid dynamics models, with a new form of the objective tensor derivative. Numerical results demonstrate the accuracy of DeePN2. Copyright © 2020, The Authors. All rights reserved.

关键词： Viscous flow

DP Compress: a Model Compression Scheme for Generating Efficient Deep Potential Models

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arXiv 2021年

作者： Lu, Denghui Jiang, Wanrun Chen, Yixiao Zhang, Linfeng Jia, Weile Wang, Han Chen, Mohan HEDPS CAPT College of Engineering Peking University Beijing100871 China Songshan Lake Materials Laboratory Guangdong Dongguan523808 China Institute of Physics Chinese Academy of Sciences Beijing100190 China Program in Applied and Computational Mathematics Princeton University PrincetonNJ United States Beijing Institute of Big Data Research Beijing100871 China Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Fenghao East Road 2 Beijing100094 China

Machine-learning-based interatomic potential energy surface (PES) models are revolutionizing the field of molecular modeling. However, although much faster than electronic structure schemes, these models suffer from costly computations via deep neural networks to predict the energy and atomic forces, resulting in lower running efficiency as compared to the typical empirical force fields. Herein, we report a model compression scheme for boosting the performance of the Deep Potential (DP) model, a deep learning based PES model. This scheme, we call DP Compress, is an efficient post-processing step after the training of DP models (DP Train). DP Compress combines several DP-specific compression techniques, which typically speed up DP-based molecular dynamics simulations by an order of magnitude faster, and consume an order of magnitude less memory. We demonstrate that DP Compress is sufficiently accurate by testing a variety of physical properties of Cu, H2O, and Al-Cu-Mg systems. DP Compress applies to both CPU and GPU machines and is publicly available online. Copyright © 2021, The Authors. All rights reserved.

关键词： Molecular dynamics

A Beginner’s Guide to Black Hole Imaging and Associated Tests of General Relativity

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arXiv 2024年

作者： Lupsasca, Alexandru Mayerson, Daniel R. Ripperda, Bart Staelens, Seppe Department of Physics and Astronomy Vanderbilt University NashvilleTN37212 United States Institute for Theoretical Physics KU Leuven Celestijnenlaan 200D LeuvenB-3001 Belgium Canadian Institute for Theoretical Astrophysics TorontoONM5S 3H8 Canada Department of Physics University of Toronto TorontoONM5S 1A7 Canada D. A. Dunlap Department of Astronomy University of Toronto TorontoONM5S 3H4 Canada Perimeter Institute for Theoretical Physics WaterlooONN2L 2Y5 Canada Flatiron Institute Center for Computational Astrophysics New YorkNY10010 United States Department of Applied Mathematics and Theoretical Physics Centre for Mathematical Sciences University of Cambridge Wilberforce Road CambridgeCB3 0WA United Kingdom

Following the 2019 release by the Event Horizon Telescope Collaboration of the first pictures of a supermassive black hole, there has been an explosion of interest in black hole images, their theoretical interpretation, and their potential use in tests of general relativity. The literature on the subject has now become so vast that an introductory guide for newcomers would appear welcome. Here, we aim to provide an accessible entry point to this growing field, with a particular focus on the black hole "photon ring": the bright, narrow ring of light that dominates images of a black hole and belongs to the black hole itself, rather than to its surrounding plasma. Far from an exhaustive review, this beginner’s guide offers a pedagogical review of the key basic concepts and a brief summary of some results at the research frontier. Copyright © 2024, The Authors. All rights reserved.

关键词： Black holes

Isotope effects in x-ray absorption spectra of liquid water

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arXiv 2020年

作者： Zhang, Chunyi Zhang, Linfeng Xu, Jianhang Tang, Fujie Santra, Biswajit Wu, Xifan Department of Physics Temple University PhiladelphiaPA19122 United States Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States

The isotope effects in x-ray absorption spectra of liquid water are studied by a many-body approach within electron-hole excitation theory. The molecular structures of both light and heavy water are modeled by path-integral molecular dynamics based on the advanced deep-learning technique. The neural network is trained on ab initio data obtained with SCAN density functional theory. The experimentally observed isotope effect in x-ray absorption spectra is reproduced semi-quantitatively in theory. Compared to the spectrum in normal water, the blueshifted and less pronounced pre- and main-edge in heavy water reflect that the heavy water is more structured at short- and intermediate-range of the hydrogen-bond network. In contrast, the isotope effect on the spectrum is negligible at post-edge, which is consistent with the identical long-range ordering in both liquids as observed in the diffraction experiment. Copyright © 2020, The Authors. All rights reserved.

关键词： Heavy water

Time-energy analysis of the photoionization process in a double-XUV pulse combined with a few-cycle IR field

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Chinese Optics Letters 2021年第12期19卷 116-123页

作者： Yi Jia Li Guo Shilin Hu Xinyan Jia Daihe Fan Ronghua Lu Shensheng Han Jing Chen School of Physics Southwest Jiaotong UniversityChengdu 610031China Department of Physics Shanghai Normal UniversityShanghai 200234China Guangdong Provincial Key Laboratory of Quantum Metrology and Sensing&School of Physics and Astronomy Sun Yat-sen University(Zhuhai Campus)Zhuhai 519082China Key Laboratory for Quantum Optics Shanghai Institute of Optics and Fine MechanicsChinese Academy of SciencesShanghai 201800China Institute of Applied Physics and Computational Mathematics Beijing 100088China Center for Advanced Material Diagnostic Technology College of Engineering PhysicsShenzhen Technology UniversityShenzhen 518118China

We calculate the time-energy distribution(TED)and ionization time distribution(ITD)of photoelectrons emitted by a doubleextreme-ultraviolet(XUV)pulse and a two-color XUV-IR pulse using the Wigner distribution-like function based on the strong field *** a double-XUV pulse,besides two identical broad distributions generated by two XUV pulses,many interference fringes resulting from the interference between electrons generated,respectively,by two pulses appear in the *** adding an IR field,the TED intuitively exhibits the effect of the IR field on the electron *** ITDs during two XUV pulses are no longer the same and show the different changes for the different two-color fields,the origin of which is attributed to the change of the electric field induced by the IR *** analysis shows that the emission time of electrons ionized during two XUV pulses mainly depends on the electric field of the combined XUV pulse and IR pulse.

关键词： Wigner distribution two-color field time-energy distribution attosecond physics strong field approximation

Extending the computational Reach of a Superconducting Qutrit Processor

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arXiv 2023年

作者： Goss, Noah Ferracin, Samuele Hashim, Akel Carignan-Dugas, Arnaud Kreikebaum, John Mark Naik, Ravi K. Santiago, David I. Siddiqi, Irfan Quantum Nanoelectronics Laboratory Department of Physics University of California at Berkeley BerkeleyCA94720 United States Applied Mathematics and Computational Research Division Lawrence Berkeley National Lab BerkeleyCA94720 United States Keysight Technologies Canada ON KanataK2K 2W5 Canada Materials Sciences Division Lawrence Berkeley National Lab BerkeleyCA94720 United States

Quantum computing with qudits is an emerging approach that exploits a larger, more-connected computational space, providing advantages for many applications, including quantum simulation and quantum error correction. Nonetheless, qudits are typically afflicted by more complex errors and suffer greater noise sensitivity which renders their scaling difficult. In this work, we introduce techniques to tailor and mitigate arbitrary Markovian noise in qudit circuits. We experimentally demonstrate these methods on a superconducting transmon qutrit processor, and benchmark their effectiveness for multipartite qutrit entanglement and random circuit sampling, obtaining up to 3x improvement in our results. To the best of our knowledge, this constitutes the first ever error mitigation experiment performed on qutrits. Our work shows that despite the intrinsic complexity of manipulating higher-dimensional quantum systems, noise tailoring and error mitigation can significantly extend the computational reach of today's qudit processors. Copyright © 2023, The Authors. All rights reserved.

关键词： Quantum chemistry

Blockchain Platforms as a Tool for Resolving Contradictions in the Labor Market and Improving the Interaction of the Applicant and Employer

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Blockchain Platforms as a Tool for Resolving Contradictions ...

2022 Conference of Russian Young Researchers in Electrical and Electronic Engineering, ElConRus 2022

作者： Levitskaya, Aleksandra N. Pokrovskaia, Nadezhda N. Rodionova, Elena A. St. Petersburg University of Management Technologies and Economics Department of Economics and Management of Socio-Economic Systems Saint Petersburg Russia Saint Petersburg Electrotechnical University Innovation Management Department Higher School of Mediacommunications Pr Peter the Great St.Petersburg Polytechnic University Economics and Management of Socio-Economic Systems Leti St. Petersburg University of Management Technologies and Economics St. Petersburg Russia School of Applied Mathematics and Computational Physics of the Physic-Mechanic Institute St. Petersburg University of Management Technologies and Economics Peter the Great St.Petersburg Polytechnic University Saint Petersburg Russia

ISBN: (纸本)9781665409933

The article provides a comparative analysis of blockchain platforms for creation, storage and trusted access to personalized documents for labor market participants. A project is discussed for creating reputation tokens as a crypto-currency of public trust, or as NFT, unique non-fungible assets of brand competency certificates. The paper investigates a number of problems arising in the interaction of employers and applicants, in particular, cybersecurity and reliability of certification, security of data and information flows, reconciliation of information about real work experience and obtained qualifications with employers' requests. The problems of the younger generation in the search for work and obtaining the desired positions are noted, i.e., the lack of data on competencies acquired, portfolio, previous experience. The blockchain platforms can help with solving tasks of HR service in the search and selection of candidates. The digitalization of social and economic life in Russia, in particular, labor market, is influenced with the cultural inertia and chasm of confidence between individuals, organizations and public administrations, the advantages of the use of blockchain technologies opens up in the field of recruiting and building a career path are shown on the basis of the enhancement of the mutual trust within the networks of distributed ledgers. © 2022 IEEE.

关键词： Blockchain