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arXiv:quant-ph/0610262

An application of renormalization in Hilbert space at phase transition points in strongly interacting systems

Tarek Khalil, J. Richert

Published Oct 31, 2006• 1 citation
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Abstract

We introduce an algorithm aimed to reduce the dimensions of Hilbert space. It is used here in order to study the behaviour of low energy states of strongly interacting quantum many-body systems at first order transitions and avoided crossings. The method is tested on different frustrated quantum spin ladders with two legs. The role and importance of symmetries are investigated by using different bases of states.

DOI
10.48550/arxiv.quant-ph/0610262

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We introduce an algorithm aimed to reduce the dimensions of Hilbert space. It is used here in order to study the behaviour of low energy states of strongly interacting quantum many-body systems at first order transitions and avoided crossings. The method is tested on different frustrated quantum spin ladders with two legs. The role and importance of symmetries are investigated by using different bases of states.
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We develop a variational formalism in order to study the structure of low energy spectra of frustrated quantum spin systems. It is first applied to trial wavefunctions of ladders with one spin-1/2 on each site. We determine energy minima of these states. The variational ground state shows a finite energy gap with respect to the energies of states which span the Hilbert space and are orthogonal to it. This is the case for any size of the system. Under some justifiable approximations the argument can be extended to even-legged ladder systems in 2d and higher dimensional spaces. The Hamiltonian can contain spin-spin coupling interactions of any range. For specific values of the coupling strengths level degeneracies can occur.
Tensor network (TN) algorithms for strongly correlated electron lattice systems have become one of the most important numerical methods for studying such systems. Based on the tensor network algorithm for spin ladder systems, the study of quantum phase transitions (QPTs) in spin ladder systems through string order parameters has shown that quantum information theory provides a universal method for studying quantum phase transitions: without knowing the local or non-local order parameters of the system, or whether local or non-local order parameters exist, the ground-state wave function of the system can be obtained. If the ground-state lacks the traditional Landau long-range order and thus has no local order parameters, or if several non-local order parameters are found through other means, some topological quantum phases can be completely described, thereby greatly enriching the traditional Landau symmetry-breaking phase transition theory.
This thesis investigates the ground-state properties and quantum phase diagrams of low-dimensional spin systems, with a focus on spin–1/2 ladder chains and related models. These systems provide a fertile ground for exploring the interplay between magnetic frus- tration, quantum correlations, topology, and external fields. By combining advanced nu- merical methods, primarily the density matrix renormalization group (DMRG), with ana- lytical approaches, we analyze how different coupling geometries and magnetic fields give rise to distinct quantum phases, including magnetization plateaus, symmetry-protected and topological phases, and first-order transitions. The study covers both uniform and alternating ladders, as well as coupled ladder systems that interpolate between one- and two-dimensional behavior. In particular, we examine how frustration influences the stabil- ity of collective spin states, and how interladder couplings can drive transitions between resonating valence bond (RVB) states, Haldane phases, and trivial phases hosting collec- tive spin excitations. Although approximate analytical models, such as hard-core boson mappings and spin-wave theory, capture some qualitative aspects of these systems, our results highlight their limitations in accurately describing critical behavior and phase boundaries, reinforcing the importance of high-precision numerical analysis.