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pdf, 9 MiB - Infoscience - EPFL

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34 CHAPTER 2. NUMERICAL METHODS<br />

Since P (α) is a positive function, the sum can be sampled by Monte Carlo calculations<br />

and no spurious sign problem occurs. The probability of a transition<br />

from state X toanewstateX ′ is given by:<br />

(<br />

)<br />

P (X → X ′ )=min 1, |det(A(X′ ))| 2<br />

|det(A(X))| 2 (2.20)<br />

Therefore, during a simulation the main task consists in calculating ratios of<br />

determinants. Although the brute force calculation of a determinant scales like<br />

N 3 numerical operations, we can reduce it to N operations [42] by considering<br />

optimized formulae that allow to compute directly ratios of determinants of two<br />

matrices A ′ /A, where the two matrices A and A ′ differ only the column j:<br />

w j = det(A′ )<br />

det(A) = ∑ k<br />

A −1<br />

j,k v k (2.21)<br />

where v is the column j of the new matrix A ′ . Similar formula can be obtained<br />

when several lines and columns are updated at the same time in the new matrix<br />

A ′ (for further details see ref. [45]). However, the formula (2.21) involves the<br />

inverse of the matrix A. The matrix A −1 can be updated when a set of rows<br />

and/or columns are changed in the matrix A 1 each time that a Monte Carlo<br />

move is accepted, and the update can be done in N 2 numerical operation [42].<br />

In the simple implementation of the Metropolis algorithm, the moves are often<br />

rejected and therefore the formula 2.21 is the bottleneck of the simulation. A<br />

even much improved algorithm, that updates directly the weights w j and does<br />

not compute the inverse of the matrix A, is currently used by Sandro Sorella and<br />

collaborators. This latter algorithm computes the weight w j in a single operation.<br />

However, the implementation of such an algorithm is much more involved and is<br />

beyond the scope of this dissertation.<br />

2.1.1 Degenerate open shell<br />

As discussed in the previous section, the variational wavefunction is built by<br />

piling the quasi-particle states up to the Fermi energy, in the case of a tightbinding<br />

wavefunction, or up to the chemical potential µ when the BCS pairing<br />

is considered. When the energy of the single-particle state is non-degenerate<br />

the resulting wavefunction is well defined. However, the wavefunction becomes<br />

ambiguous when the energies are degenerate. This happens in finite size clusters,<br />

due to the symmetry of the lattice: The k points are lying on shells of same energy.<br />

This gives artificial degeneracies related to the different filling possibilities.<br />

1 The hopping of one particle involves a change of row or a column in A, andtheswapof<br />

an up and down particles involves the change of both a row and a column in A.

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