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arxiv: 1307.8416 · v1 · pith:TI3GS5RFnew · submitted 2013-07-31 · ❄️ cond-mat.quant-gas · cond-mat.str-el· quant-ph

Improving the Gutzwiller Ansatz with Matrix Product States

classification ❄️ cond-mat.quant-gas cond-mat.str-elquant-ph
keywords algorithmgutzwillermatrixnumber-conservingcomputationalcorrelateddynamicsfact
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The Gutzwiller variational wavefunction (GVW) is commonly employed to capture correlation effects in condensed matter systems such as ferromagnets, ultracold bosonic gases, correlated superconductors, etc. By noticing that the grand-canonical and number-conserving Gutzwiller Ans\"atze are in fact the zero-order approximation of an expansion in the truncation parameter of a Matrix Product State (MPS), we argue that MPSs, and the algorithms used to operate on them, are not only flexible computational tools but also a unifying theoretical framework that can be used to generalize and improve on the GVW. In fact, we show that a number-conserving GVW is less efficient in capturing the ground state of a quantum system than a more general MPS which can be optimized with comparable computational resources. Moreover, we suggest a corrected time-dependent density matrix renormalization group algorithm that ensures the conservation of the expectation value of the number of particles when a GVW or a MPS are not explicitly number-conserving. The GVW dynamics obtained with our algorithm compares very well with the exact one in 1D. Most importantly, the algorithm works in any dimension for a GVW. We thus expect it to be of great value in the study of the dynamics of correlated quantum systems.

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