相关论文: A conjugate gradient algorithm for the astrometric…

We investigated the reliability of the genetic algorithm which will be used to invert the photometric measurements of asteroids collected by the European Space Agency Gaia mission. To do that, we performed several sets of simulations for 10…

A fundamental task in numerical computation is the solution of large linear systems. The conjugate gradient method is an iterative method which offers rapid convergence to the solution, particularly when an effective preconditioner is…

In practical computations, the (preconditioned) conjugate gradient (P)CG method is the iterative method of choice for solving systems of linear algebraic equations $Ax=b$ with a real symmetric positive definite matrix $A$. During the…

Solving large-scale linear systems problems is a cornerstone in scientific and industrial computing. Classical iterative solvers face increasing difficulty as the number of unknowns becomes large, while fully quantum linear solvers require…

This thesis investigates algorithms regarding their applicability for highly nonlinear model fitting on big datasets. Various mathematical methods are presented with which a model fit using the least squares criterion is possible. Special…

Gaia is an all sky, high precision astrometric and photometric satellite of the European Space Agency (ESA) due for launch in 2010-2011. Its primary mission is to study the composition, formation and evolution of our Galaxy. Gaia will…

Astrometric missions like Gaia provide exceptionally precise measurements of stellar positions and proper motions. Gravitational waves traveling between the observer and distant stars can induce small, correlated shifts in these apparent…

Major advancements in space science and detector technology brought about a revolution in global astrometry, the science of measuring distances and motions of stars in the Milky Way and in the local universe. From the first ESA astrometric…

We present an iterative method to diagonalise large matrices. The basic idea is the same as the conjugated gradient (CG) method, i.e, minimizing the Rayleigh quotient via its gradient and avoiding reintroduce errors to the directions of…

The conjugate gradient method is a widely used algorithm for the numerical solution of a system of linear equations. It is particularly attractive because it allows one to take advantage of sparse matrices and produces (in case of infinite…

In its all-sky survey, the ESA global astrometry mission Gaia will perform high-precision astrometry and photometry for 1 billion stars down to $V = 20$ mag. The data collected in the Gaia catalogue, to be published by the end of the next…

The ESA global astrometry space mission Gaia has been monitoring the position of a billion stars since 2014. The analysis of such a massive dataset is challenging in terms of the data processing involved. In particular, the blind detection…

The Advanced Gamma-ray Imaging System (AGIS) is a next-generation ground-based gamma-ray observatory being planned in the U.S. The anticipated sensitivity of AGIS is about one order of magnitude better than the sensitivity of current…

The adaptive $s$-step CG algorithm is a solver for sparse, symmetric positive definite linear systems designed to reduce the synchronization cost per iteration while still achieving a user-specified accuracy requirement. In this work, we…

We propose a new algorithm for finite sum optimization which we call the curvature-aided incremental aggregated gradient (CIAG) method. Motivated by the problem of training a classifier for a d-dimensional problem, where the number of…

This paper presents the analytical solution of the inverse ray tracing problem for photons emitted by a star and collected by an observer located in the gravitational field of the Solar System. This solution has been conceived to suit the…

Mapping the Earth's gravity field from space offers valuable insights into climate change, hydro- and biosphere evolution, and seismic activity. Current satellite gravimetry missions have demonstrated the utility of gravity data in…

We present the development and benchmarking of Poisson solvers for graphics processing units (GPUs). Implemented in the Astaroth platform, the solvers feature high computational efficiency. We present novel combinations of discretizations…

Gaia Data Release 2 (Gaia DR2) provides high accuracy and precision astrometric parameters (position, parallax, and proper motion) for more than 1 billion sources and is revolutionizing astrometry. For a fast-moving target such as an…

The Bayesian Conjugate Gradient method (BayesCG) is a probabilistic generalization of the Conjugate Gradient method (CG) for solving linear systems with real symmetric positive definite coefficient matrices. Our CG-based implementation of…