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We present a comprehensive investigation of polymer diffusion in the semidilute regime by fluorescence correlation spectroscopy (FCS) and dynamic light scattering (DLS). Using single-labeled polystyrene chains, FCS leads to the…

This paper is devoted to a discussion of the Discrete Fourier Transform (DFT) representation of a chaotic finite-duration sequence. This representation has the advantage that is itself a finite-duration sequence corresponding to samples…

Chaotic Dynamics · Physics 2007-05-23 Carlos R. Fadragas , Juan V. Lorenzo-Ginori , Ruben Orozco-Morales

Fourier extension is an approximation method that alleviates the periodicity requirements of Fourier series and avoids the Gibbs phenomenon when approximating functions. We describe a similar extension approach using regular wavelet bases…

Numerical Analysis · Mathematics 2020-04-08 Vincent Coppé , Daan Huybrechs

We define the notion of the Fourier transform for the rook monoid (also called the symmetric inverse semigroup) and provide two efficient divide-and-conquer algorithms (fast Fourier transforms, or FFTs) for computing it. This paper marks…

Representation Theory · Mathematics 2011-08-02 Martin Malandro , Daniel N. Rockmore

Single-shot coherent diffractive imaging (CDI) using intense XUV and soft X-ray pulses holds the promise to deliver information on the three dimensional shape as well as the optical properties of nano-scale objects in a single diffraction…

Optics · Physics 2025-11-25 Paul Tuemmler , Julia Apportin , Thomas Fennel , Christian Peltz

In the present article the author extends the Fourier transform to a more general class of functions; First to power-law functions with integer and half-integer exponents then to the widely used quantum statistics function (Fermi-Dirac and…

General Mathematics · Mathematics 2019-12-30 Cyril Belardinelli

We present a super-high-efficiency approximate computing scheme for series sum and discrete Fourier transform. The summation of a series sum or a discrete Fourier transform is approximated by summing over part of the terms multiplied by…

Numerical Analysis · Mathematics 2013-12-09 Xin-Zhong Yan

This paper addresses two interrelated problems of the nonlinear filtering mechanism and fast attitude filtering with the matrix Fisher distribution (MFD) on the special orthogonal group. By analyzing the distribution evolution along Bayes'…

Systems and Control · Electrical Eng. & Systems 2026-05-08 Shijie Wang , Haichao Gui , Rui Zhong

By formulating the inverse problem of partial differential equations (PDEs) as a statistical inference problem, the Bayesian approach provides a general framework for quantifying uncertainties. In the inverse problem of PDEs, parameters are…

Numerical Analysis · Mathematics 2026-02-10 Haoyu Lu , Junxiong Jia , Deyu Meng

In this paper a sublinear time algorithm is presented for the reconstruction of functions that can be represented by just few out of a potentially large candidate set of Fourier basis functions in high spatial dimensions, a so-called…

Numerical Analysis · Mathematics 2020-06-24 Lutz Kämmerer , Felix Krahmer , Toni Volkmer

We prove pointwise convergence for the scattering data of a Dirac system of differential equations. Equivalently, we prove an analog of Carleson's theorem on almost everywhere convergence of Fourier series for a version of the non-linear…

Complex Variables · Mathematics 2025-12-22 Alexei Poltoratski

We present an approach to computing spatial information based on Fourier coefficient distributions. The Fourier transform (FT) of an image contains a complete description of the image, and the values of the FT coefficients are uniquely…

Quantitative Methods · Quantitative Biology 2009-12-09 William F. Heinz , Jeffrey L. Werbin , Eaton Lattman , Jan H. Hoh

For a sample set of 1024 values, the FFT is 102.4 times faster than the discrete Fourier transform (DFT). The basis for this remarkable speed advantage is the `bit-reversal' scheme of the Cooley-Tukey algorithm. Eliminating the burden of…

History and Overview · Mathematics 2007-05-23 Randall D. Peters

We establish a general Bernstein--von Mises theorem for approximately linear semiparametric functionals of fractional posterior distributions based on nonparametric priors. This is illustrated in a number of nonparametric settings and for…

Statistics Theory · Mathematics 2025-08-12 Alice L'Huillier , Luke Travis , Ismaël Castillo , Kolyan Ray

The Fourier-based diffraction approach is an established method to extract order and symmetry propertiesfrom a given point set. We want to investigate a different method for planar sets which works in direct spaceand relies on reduction of…

Dynamical Systems · Mathematics 2023-07-19 Tobias Jakobi

Based on the discrete fractional random transform (DFRNT), we present the discrete fractional random cosine and sine transforms (DFRNCT and DFRNST). We demonstrate that the DFRNCT and DFRNST can be regarded as special kinds of DFRNT and…

Mathematical Physics · Physics 2009-11-11 Zhengjun Liu , Qing Guo , Shutian Liu

We employ concepts and tools from the theory of finite permutation groups in order to analyse the Hidden Subgroup Problem via Quantum Fourier Sampling (QFS) for the symmetric group. We show that under very general conditions both the weak…

Quantum Physics · Physics 2007-05-23 Julia Kempe , Aner Shalev

This paper develops a constructive numerical scheme for Fourier-Bessel approximations on disks compatible with convolutions supported on disks. We address accurate finite Fourier-Bessel transforms (FFBT) and inverse finite Fourier-Bessel…

Numerical Analysis · Mathematics 2023-11-08 Arash Ghaani Farashahi , Gregory S. Chirikjian

The direct Gaussian copula model with discrete marginal distributions is an appealing data-analytic tool but poses difficult computational challenges due to its intractable likelihood. A number of approximations/surrogates for the…

Methodology · Statistics 2021-03-08 John Hughes

Diffusion models have gained prominence as powerful generative tools for solving inverse problems due to their ability to model complex data distributions. However, existing methods typically rely on complete knowledge of the forward…

Machine Learning · Computer Science 2026-03-03 Hongkun Dou , Zike Chen , Zeyu Li , Hongjue Li , Lijun Yang , Yue Deng