Phase diagram of the $J$-$J_d$ Heisenberg Model on the Maple-Leaf Lattice: Neural networks and density matrix renormalization group

We microscopically analyze the nearest neighbor Heisenberg model on the maple-leaf lattice through neural quantum states (NQS) and infinite density matrix renormalization group (iDMRG). Embarking to parameter regimes beyond the exact dimer singlet ground state with a dimer bond spin exchange coupling $J_{d}$ varied against the exchange strength $J$ of all other bonds, iDMRG (NQS) finds a dimer state paramagnetic phase for $J_{d} / J > 1.464$ ( $J_{d} / J > 1.39$ ) and a canted $120^{\circ}$ magnetic order for $J_{d} / J < 1.419$ ( $J_{d} / J < 1.23$ ). Assessing training convergence inaccuracies of NQS and the influence of finite cylindric circumference for iDMRG, we discuss the possible existence of an intermediate phase between magnet and dimer paramagnet.

Phase diagram of the $J$ - $J_{d}$ Heisenberg Model on the Maple-Leaf Lattice: Neural networks and density matrix renormalization group

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Phase diagram of the $J$ - $J_{d}$ Heisenberg Model on the Maple-Leaf Lattice: Neural networks and density matrix renormalization group

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Phase diagram of the JJ-JdJd​ Heisenberg Model on the Maple-Leaf Lattice: Neural networks and density matrix renormalization group

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Phase diagram of the JJ-JdJd​ Heisenberg Model on the Maple-Leaf Lattice: Neural networks and density matrix renormalization group

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Phase diagram of the $J$ - $J_{d}$ Heisenberg Model on the Maple-Leaf Lattice: Neural networks and density matrix renormalization group

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Phase diagram of the $J$ - $J_{d}$ Heisenberg Model on the Maple-Leaf Lattice: Neural networks and density matrix renormalization group

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