Applied Mathematics and Computational Science Program

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Recent Submissions

Now showing 1 - 5 of 1999
  • Preprint

    Multidimensional deconvolution with shared bases

    (arXiv, 2024-04-02) Sushnikova, Daria; Ravasi, Matteo; Keyes, David E.; Computer, Electrical and Mathematical Sciences and Engineering; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division; Earth Science and Engineering; Earth Science and Engineering Program; Physical Sciences and Engineering; Physical Science and Engineering (PSE) Division; Applied Mathematics and Computational Science; Applied Mathematics and Computational Science Program; Extreme Computing Research Center; Office of the President

    We address the estimation of seismic wavefields by means of Multidimensional Deconvolution (MDD) for various redatuming applications. While offering more accuracy than conventional correlation-based redatuming methods, MDD faces challenges due to the ill-posed nature of the underlying inverse problem and the requirement to handle large, dense, complex-valued matrices. These obstacles have long limited the adoption of MDD in the geophysical community. Recent interest in this technology has spurred the development of new strategies to enhance the robustness of the inversion process and reduce its computational overhead. We present a novel approach that extends the concept of block low-rank approximations, usually applied to linear operators, to simultaneously compress the operator, right-hand side, and unknowns. This technique greatly alleviates the data-heavy nature of MDD. Moreover, since in 3d applications the matrices do not lend themselves to global low rank approximations, we introduce a novel H2-like approximation. We aim to streamline MDD implementations, fostering efficiency and controlling accuracy in wavefield reconstruction. This innovation holds potential for broader applications in the geophysical domain, possibly revolutionizing the analysis of multi-dimensional seismic datasets.

  • Conference Paper

    Snapshot hyperspectral imaging via learned metasurface encoders

    (META Conference, 2022-01-01) Maksim, Makarenko; Getman, Fedor; Burguete-Lopez, Arturo; Wang, Qizhou; Giancola, Silvio; Ghanem, Bernard; Fratalocchi, Andrea; PRIMALIGHT, Faculty of Electrical Engineering;, Applied Mathematics and Computational Science, King Abdullah University of Science and Technology, Thuwal, 23955-6900; Electrical and Computer Engineering; Electrical and Computer Engineering Program; Computer, Electrical and Mathematical Sciences and Engineering; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division; Visual Computing Center (VCC); Applied Mathematics and Computational Science; Applied Mathematics and Computational Science Program

    In this work, we present Hyplex™ system, a real-time high-resolution hyperspectral camera based on a combination of hardware metasurface encoders and software decoders.

  • Conference Paper

    Designing robust flat-optics for flexible substrates and their performance under stress

    (META Conference, 2022-01-01) Getman, Fedor; Maksim, Makarenko; Wang, Q.; Burguete-Lopez, Arturo; Fratalocchi, Andrea; PRIMALIGHT, Faculty of Electrical Engineering; Applied Mathematics and Computational Science, King Abdullah University of Science and Technology, Thuwal, 23955-6900; Electrical and Computer Engineering; Electrical and Computer Engineering Program; Computer, Electrical and Mathematical Sciences and Engineering; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division; Applied Mathematics and Computational Science; Applied Mathematics and Computational Science Program

    We present an inverse design platform that enables the fast design of flexible flat-optics that maintain high performance under deformations and are tolerant to fabrication errors. The platform is based on evolutionary large-scale optimizers, and neural network predictors.We demonstrate both the of the design methods and the experimental performance of fabricated evices, over a 200nm bandwidth in the visible under mechanical deformations.

  • Conference Paper

    Controlling Sound Wave via Spinning Media

    (META Conference, 2022-01-01) Farhat, Mohamed; Wu, Ying; Computer, Electrical and Mathematical Sciences and Engineering; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division; Applied Mathematics and Computational Science; Applied Mathematics and Computational Science Program

    In this talk, we will discuss our recent advances on controlling sound wave via spinning media. First, we study the torque and force a spinning cylindrical column of fluid experiences in evanescent acoustic fields, and show that the resulting discontinuity can scatter sound in unusual ways, e.g., a negative radiation force. In another example, we develop a generalized scattering cancellation theory (SCT) to cloak spinning objects from static observers. Our work extends the applicable realms of SCT to moving objects.

  • Conference Paper

    Inversely designed ultrahigh refractive index metamaterial for compact sensing

    (META Conference, 2022-01-01) Elizarov, Maxim; Fratalocchi, Andrea; PRIMALIGHT, Faculty of Electrical Engineering, Applied Mathematics and Computational Science, KAUST, Thuwal, 23955-6900; Material Science and Engineering; Material Science and Engineering Program; Physical Sciences and Engineering; Physical Science and Engineering (PSE) Division; Electrical and Computer Engineering; Electrical and Computer Engineering Program; Computer, Electrical and Mathematical Sciences and Engineering; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division; Applied Mathematics and Computational Science; Applied Mathematics and Computational Science Program

    We propose optical RI sensor with sensitivity of 350 nm/RIU for the micrometer footprint. The advantage of this sensor is the ability to sustain air-confined high-Q modes which probe the analyte material with entire energy distribution of the mode. The device is based on artificial material which can emulate non-dispersive ultra-high refractive index (n≈100) capable of strong localization of incoming radiation. This is achieved by suitable deformation of a reflective substrate by applying inverse design to transformation optics approach.