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This article studies a direct numerical approach for fractional advection-diffusion equations (ADEs). Using a set of cubic trigonometric B-splines as test functions, a differential quadrature (DQ) method is firstly proposed for the 1D and…

Numerical Analysis · Mathematics 2017-10-19 X. G. Zhu , Y. F. Nie , W. W. Zhang

We apply a recently developed quasi-diabatic (QD) scheme to the symmetric quasi-classical (SQC) approach for accurate quantum dynamics propagation. By using the adiabatic states as the quasi-diabatic states during a short-time quantum…

Chemical Physics · Physics 2018-07-11 Juan Sebastian C. Sandoval , Arkajit Mandal , Pengfei Huo

We present a distributed quasi-Newton (DQN) method, which enables a group of agents to compute an optimal solution of a separable multi-agent optimization problem locally using an approximation of the curvature of the aggregate objective…

Optimization and Control · Mathematics 2024-09-30 Ola Shorinwa , Mac Schwager

Quantum Key Distribution (QKD) offers unconditional security in principle. Many QKD protocols have been proposed and demonstrated to ensure secure communication between two authenticated users. Continuous variable (CV) QKD offers many…

We analyse and implement a quasi-Monte Carlo (QMC) finite element method (FEM) for the forward problem of uncertainty quantification (UQ) for the Helmholtz equation with random coefficients, both in the second-order and zero-order terms of…

Numerical Analysis · Mathematics 2025-11-04 Ivan G. Graham , Frances Y. Kuo , Dirk Nuyens , Ian H. Sloan , Euan A. Spence

The finite-difference time-domain (FDTD) method is a well established method for solving the time evolution of Maxwell's equations. Unfortunately the scheme introduces numerical dispersion and therefore phase and group velocities which…

Plasma Physics · Physics 2018-02-05 Alexander Blinne , David Schinkel , Stephan Kuschel , Nina Elkina , Sergey Rykovanov , Matt Zepf

Quasi-Newton (QN) methods provide an efficient alternative to second-order methods for minimizing smooth unconstrained problems. While QN methods generally compose a Hessian estimate based on one secant interpolation per iteration,…

Optimization and Control · Mathematics 2025-04-11 Mokhwa Lee , Yifan Sun

Continuous-variable quantum key distribution (CV-QKD) enables information-theoretically secure key generation between legitimate parties. To further enhance system performance, an improved two-way CV-QKD protocol has been proposed, which is…

Quantum Physics · Physics 2026-01-28 Yanhao Sun , Jiayu Ma , Xiangyu Wang , Song Yu , Ziyang Chen , Hong Guo

We define the statistical quadrature evolution (QE) method for multicarrier continuous-variable quantum key distribution (CVQKD). A multicarrier CVQKD protocol uses Gaussian subcarrier quantum continuous variables (CVs) for information…

Quantum Physics · Physics 2016-03-31 Laszlo Gyongyosi

In the present work, we investigate a model of the invasion of healthy tissue by cancer cells which is described by a system of nonlinear PDEs consisting of a cross-diffusion-reaction equation and two additional nonlinear ordinary…

Numerical Analysis · Mathematics 2023-07-18 Shahin Heydari , Petr Knobloch , Thoma Wick

Diffusion models excel at generating high-likelihood samples but often require alignment with downstream objectives. Existing fine-tuning methods for diffusion models significantly suffer from reward over-optimization, resulting in…

Machine Learning · Computer Science 2026-03-09 Hyeongyu Kang , Jaewoo Lee , Woocheol Shin , Kiyoung Om , Jinkyoo Park

Quantum key distribution (QKD) enables the establishment of secret keys between users connected via a channel vulnerable to eavesdropping, with information-theoretic security, that is, independently of the power of a malevolent party. QKD…

Continuous-variable quantum key distribution (CV-QKD) is a promising quantum-safe alternative to classical asymmetric cryptography that enables two authenticated parties to establish a shared secret over a potentially eavesdropped quantum…

Quantum Physics · Physics 2026-03-12 Jonas Berl , Utku Akin , Erdem Eray Cil , Laurent Schmalen , Tobias Fehenberger

Quantum computational fluid dynamics (QCFD) offers a promising alternative to classical computational fluid dynamics (CFD) by leveraging quantum algorithms for higher efficiency. This paper introduces a comprehensive QCFD method, including…

A method is developed for solving quasilinear convection diffusion problems starting on a coarse mesh where the data and solution-dependent coefficients are unresolved, the problem is unstable and approximation properties do not hold. The…

Numerical Analysis · Mathematics 2015-02-10 Sara Pollock

The Reynolds equation, combined with the Elrod algorithm for including the effect of cavitation, resembles a nonlinear convection-diffusion-reaction (CDR) equation. Its solution by finite elements is prone to oscillations in…

Numerical Analysis · Mathematics 2023-10-12 Hauke Gravenkamp , Simon Pfeil , Ramon Codina

For the case of approximation of convection--diffusion equations using piecewise affine continuous finite elements a new edge-based nonlinear diffusion operator is proposed that makes the scheme satisfy a discrete maximum principle. The…

Numerical Analysis · Mathematics 2015-09-30 Gabriel R. Barrenechea , Erik Burman , Fotini Karakatsani

The convergence of Boltzmann Fokker Planck solution can become arbitrarily slow with iterative procedures like source iteration. This paper derives and investigates a nonlinear diffusion acceleration scheme for the solution of the Boltzmann…

Numerical Analysis · Mathematics 2023-12-06 Japan K. Patel , Barry D. Ganapol , Martha M. Matuszak

The aim of this paper is to develop and analyze numerical schemes for approximately solving the backward problem of subdiffusion equation involving a fractional derivative in time with order $\alpha\in(0,1)$. After using quasi-boundary…

Numerical Analysis · Mathematics 2020-10-28 Zhengqi Zhang , Zhi Zhou

Standard Latent Diffusion Models rely on a complex, three-part architecture consisting of a separate encoder, decoder, and diffusion network, which are trained in multiple stages. This modular design is computationally inefficient, leads to…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Xiyuan Wang , Muhan Zhang