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In this work, we study the numerical optimization of nearest-neighbor concurrence of bipartite one and two dimensional lattices, as well as non bipartite two dimensional lattices. These systems are described in the framework of a tight-binding Hamiltonian while the optimization of concurrence was performed using genetic algorithms. Our results show that the concurrence of the optimized lattice structures is considerably higher than that of non optimized systems. In the case of one dimensional chains the concurrence is maximized when the system begins to dimerize, i.e. it undergoes a structural phase transition (Peierls distortion). This result is consistent with the idea that entanglement is maximal or shows a singularity near quantum phase transitions and that quantum entanglement cannot be freely shared between many objects (monogamy property). Moreover, the optimization of concurrence in two-dimensional bipartite and non bipartite lattices is achieved when the structures break into smaller subsystems, which are arranged in geometrically distinguishable configurations. This behavior is again related to the monogamy property.
We overcome the diffraction limit in fluorescence imaging of neutral atoms in a sparsely filled one-dimensional optical lattice. At a periodicity of 433 nm, we reliably infer the separation of two atoms down to nearest neighbors. We observe light ind
Although a universal quantum computer is still far from reach, the tremendous advances in controllable quantum devices, in particular with solid-state systems, make it possible to physically implement quantum simulators. Quantum simulators are physic
The evolution of entanglement in a 3-spin chain with nearest-neighbor Heisenberg-XY interactions for different initial states is investigated here. In an NMR experimental implementation, we generate multipartite entangled states starting from initial
The subject of this paper are operators represented on Fock spaces whose behavior on one level depends only on two of its neighbors. Our initial objective was to generalize (via a common framework) the results of arXiv:math/0702158, arXiv:0709.4334,
Random walks including non-nearest-neighbor jumps appear in many real situations such as the diffusion of adatoms and have found numerous applications including PageRank search algorithm, however, related theoretical results are much less for this dy