Results 11 to 20 of about 18,207 (135)
Dynamic multi‐objective optimisation of complex networks based on evolutionary computation
IET Networks, EarlyView., 2022 Abstract As the problems concerning the number of information to be optimised is increasing, the optimisation level is getting higher, the target information is more diversified, and the algorithms are becoming more complex; the traditional algorithms such as particle swarm and differential evolution are far from being able to deal with this situation ...
Linfeng Huang
wiley +1 more source
A geometric protocol for a robust Majorana magic gate [PDF]
, 2016 A universal quantum computer requires a full set of basic quantum gates. With Majorana bound states one can form all necessary quantum gates in a topologically protected way, bar one. In this manuscript we present a protocol that achieves the missing, so
Freedman, Michael H. +3 more
core +3 more sources
On the parallel solution of parabolic equations [PDF]
, 1989 Parallel algorithms for the solution of linear parabolic problems are proposed. The first of these methods is based on using polynomial approximation to the exponential. It does not require solving any linear systems and is highly parallelizable. The two
Gallopoulos, E., Saad, Youcef
core +2 more sources
Some Remarks on Relative Chebyshev Centers
Journal of Approximation Theory, 1997 Let \(X\) be a Hilbert space with \(F(X)\) as the set of all closed nonempty convex subsets of \(X\). Suppose that \(Y\), \(K\in F(X)\) and \(K\) is bounded. Then the author shows that the set of all relative Chebyshev centres of \(K\) with respect to \(Y\) is a subset of \(P_Y(K)\), where \(P_Y\) is the metric projection onto \(Y\).
openaire +1 more source
A Multiscale Butterfly Algorithm for Multidimensional Fourier Integral Operators
, 2015 This paper presents an efficient multiscale butterfly algorithm for computing Fourier integral operators (FIOs) of the form $(\mathcal{L} f)(x) = \int_{R^d}a(x,\xi) e^{2\pi \i \Phi(x,\xi)}\hat{f}(\xi) d\xi$, where $\Phi(x,\xi)$ is a phase function, $a(x,\
Li, Yingzhou +2 more
core +1 more source
A new tool for image analysis based on Chebyshev rational functions: CHEF functions
, 2011 We introduce a new approach to the modelling of the light distribution of galaxies, an orthonormal polar base formed by a combination of Chebyshev rational functions and Fourier polynomials that we call CHEF functions, or CHEFs.
Benítez, N., Jiménez-Teja, Y.
core +1 more source
An evaluation of best compromise search in graphs [PDF]
, 2013 This work evaluates two different approaches for multicriteria graph search problems using compromise preferences. This approach focuses search on a single solution that represents a balanced tradeoff between objectives, rather than on the whole set ...
Galand, Lucie +2 more
core +4 more sources
Improved Chebyshev series ephemeris generation capability of GTDS [PDF]
, 1980 An improved implementation of the Chebyshev ephemeris generation capability in the operational version of the Goddard Trajectory Determination System (GTDS) is described.
Jacintho, J. J., Liu, S. Y., Rogers, J.
core +1 more source
Bottom‐Up Programming of Cell States in Cancer Organoids with Defined Synthetic Adhesion Cues
Advanced Materials, EarlyView.A bottom‐up biomaterial platform is developed to program transcriptomic states in pancreatic cancer organoids by tuning adhesion cues within synthetic matrices. By combining a Design of Experiments framework with multiobjective optimization, matrix compositions are identified that enrich specific cellular programs like EMT.
Ali Nadernezhad +6 more
wiley +1 more source
Two-level Chebyshev filter based complementary subspace method: pushing the envelope of large-scale electronic structure calculations [PDF]
, 2018 We describe a novel iterative strategy for Kohn-Sham density functional theory calculations aimed at large systems (> 1000 electrons), applicable to metals and insulators alike.
Banerjee, Amartya S. +4 more
core +2 more sources