Discrete Green’s functions and spectral graph theory for computationally efficient thermal modeling

Approximate spectral functions in thermal field theory.

Causality requires that the ~anti!commutator of two interacting field operators vanishes for spacelike coordinate differences. This implies that the Fourier transform of the spectral function of this quantum field should vanish in the spacelike domain. We find that this requirement imposes some constraints on the use of resummed propagators in high temperature gauge theory. @S0556-2821~96!02418-6#

Retarded Greens Functions and Forward Scattering Amplitudes in Thermal Field Theory

In this paper, we give a simple diagrammatic identification of the unique combination of the causal n-point vertex functions in the real time formalism that would coincide with the corresponding functions obtained in the imaginary time formalism. Furthermore, we give a simple calculational method for evaluating the temperature dependent parts of the retarded vertex functions, to one loop, by id...

Computationally efficient 2-D spectral estimation

We present an efficient implementation of the 2-D Amplitude Spectrum Capon (ASC) estimator, denoted the 2-D Burg-Based ASC (BASC) estimator. The algorithm, which will depend only on the (forward) linear prediction matrices and the (forward) prediction error covariance matrices, can be implemented using the 2-D Fast Fourier Transform. To compute the needed prediction matrices, we make use of a r...

Kubelka-Munk theory for efficient spectral printer modeling

Spectral graph theory

With every graph (or digraph) one can associate several different matrices. We have already seen the vertex-edge incidence matrix, the Laplacian and the adjacency matrix of a graph. Here we shall concentrate mainly on the adjacency matrix of (undirected) graphs, and also discuss briefly the Laplacian. We shall show that spectral properies (the eigenvalues and eigenvectors) of these matrices pro...