The Role of Diagonalization within a Diagonalization/monte Carlo Scheme

The role of Monte Carlo within a diagonalization/Monte Carlo scheme

We review the method of stochastic error correction which eliminates the truncation error associated with any subspace diagonalization. Monte Carlo sampling is used to compute the contribution of the remaining basis vectors not included in the initial diagonalization. The method is part of a new approach to computational quantum physics which combines both diagonalization and Monte Carlo techni...

A Lattice-Based MIMO Broadcast Precoder for Multi-Stream Transmission

Precoding with block diagonalization is an attractive scheme for approaching sum capacity in multiuser multiple input multiple output (MIMO) broadcast channels. This method requires either global channel state information at every receiver or an additional training phase, which demands additional system planning. In this paper we propose a lattice based multi-user precoder that uses block diago...

Shell Model Monte Carlo method in the -formalism

The Shell model Monte Carlo (SMMC) method [1] was developed as an alternative to direct diagonalization in order to study low-energy nuclear properties. It was successfully applied to nuclear problems where large model spaces made diagonalization impractical. One calculates the thermal canonical expectation values of observables of few-body operators by representing the imaginary-time many-body...

Classical and Quantum Monte Carlo Algorithms and Exact Diagonalization

Modal Field Theory and Quasi-sparse Eigenvector Diagonalization

Of the many approaches to non-perturbative quantum field theory, we can identify two general computational strategies. The first is the method of Monte Carlo. The main advantages of this approach is that it can treat many higher dimensional field theories, requires relatively little storage, and can be performed with massively parallel computers. The other strategy is the method of explicit dia...