Copyright (C) 2017-2024 The Simons Foundation, Inc. - All Rights Reserved.

See docs/ackn.rst for the list of code authors and contributors.

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FINUFFT is licensed under the Apache License, Version 2.0 (the
"License"); you may not use this file except in compliance with the
License.  You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

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Certain parts of this repository are contributed by others.
For their license info (which are both BSD-like), see:

fortran/cmcl_license.txt
tutorial/utils/lgwt.m

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If you find this library useful, or it helps you in creating software
or publications, please let us know, and acknowledge that fact by citing our
source repository:

  https://github.com/flatironinstitute/finufft

and the corresponding journal articles (particularly the first for the CPU
and/or the last for the GPU):

  A parallel non-uniform fast Fourier transform library based on an
  ``exponential of semicircle'' kernel. A. H. Barnett, J. F. Magland,
  and L. af Klinteberg.  SIAM J. Sci. Comput. 41(5), C479-C504 (2019).

  Aliasing error of the $\exp (\beta \sqrt{1-z^2})$ kernel in the
  nonuniform fast Fourier transform. A. H. Barnett,
  Appl. Comput. Harmon. Anal. 51, 1-16 (2021).

  cuFINUFFT: a load-balanced GPU library for general-purpose nonuniform FFTs,
  Yu-hsuan Shih, Garrett Wright, Joakim Andén, Johannes Blaschke, and
  Alex H. Barnett. PDSEC2021 workshop of the IPDPS2021 conference.
  https://arxiv.org/abs/2102.08463
