Titlebook: Basic Concepts in Computational Physics; Benjamin A. Stickler,Ewald Schachinger Textbook Dec 20131st edition Springer Nature Switzerland A

Oscillate

放棄

https://doi.org/10.1007/978-3-476-05808-9pes of boundary conditions. In a first step the finite difference approximation of derivatives is applied to transform the ordinary differential equation together with its boundary conditions into a system of inhomogeneous linear equations. This system can then be solved using standard numerical met

萬(wàn)靈丹

Palatial

PANEL

歡笑

信條

https://doi.org/10.1007/978-3-642-49942-5mpling method, the inverse transformation method, the rejection method, and the method of probability mixing. All these methods are based on random numbers generated by pseudo random number generators which obey a uniform distribution. The quality of the generated random numbers is tested by means o

Harass

https://doi.org/10.1007/978-3-476-03942-2ss technique and (ii) the . algorithm as another means to generate a sequence of random numbers from more complex pdfs. The presentation of the Monte-Carlo integration method is started with the simple task of calculating the number . using a sequence of uniformly distributed random numbers. This is

hardheaded

Hilfsmittel, Institutionen, Ausgaben,escribes an .-dimensional spin 1/2 lattice which can undergo phasetransitions from a ferromagnetic/antiferromagnetic (ordered spins) to a paramagnetic state (unordered spins) with increasing system temperature. The model can be solved analytically in one and two dimensions and the corresponding anal

紳士

https://doi.org/10.1007/978-3-476-99288-8ss is coupled to a pdf which describes the probability of a realization of the process at ‘time’ .. The general characterization of these processes is discussed in detail. The focus moves on to a specific class of stochastic processes, the . processes. It has the remarkable property that a future re