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MKrbm edited this page Jan 7, 2024
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Shastry–Sutherland Model
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- discuss about exact ground state
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Quantum Criticality and Spin Liquid Phase in the Shastry-Sutherland model
- focusing on the
$g = J_D/J_{\times}, g \in [0.7, 0.9]$ , with DMRG calculation.
- focusing on the
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Tensor network study of the Shastry-Sutherland model in zero magnetic field
- tensor network study
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- use canonical thermal pure quantum (TPQ)
- also, The ground state phase diagram is listed.
- apply magnetic field
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Thermodynamic properties of the Shastry-Sutherland model from quantum Monte Carlo simulations
- Check "negative sign problem" part.
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Majumder-gohsh
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ladder model
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- can remove negative sign at fully frustrated parameter point (
$J_\times = J_\parallel$ ) by local unitary transformation.
- can remove negative sign at fully frustrated parameter point (
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Kitaev model
- original paper of kitaev.
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Theory of the Kitaev model in a [111] magnetic field
- summerizing several methods for simulating Kitaev model (DMRG, tensor-network)
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- simulate with QMC.
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pyrochlore lattice
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Negative sign problem
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Symmetry-protected topological order and negative-sign problem for SO(N) bilinear-biquadratic chains
- With a generalized Jordan-Wigner transformation, bilinear-biquadratic(BLBQ) spin chain could be negative-sign free
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Sign-Problem-Free Monte Carlo Simulation of Certain Frustrated Quantum Magnets
- The scheme uses the basis of total spin eigenstates of clusters of spins to avoid the severe sign problem faced by other QMC methods.
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Thermodynamic properties of the Shastry-Sutherland model from quantum Monte Carlo simulations
- Also discuss about Shastry-Surtherland model
- If the Hamiltonian of interest and the sign-problem-free Hamiltonian have the same ground state and this state is a member of the computational basis, then the average sign returns to one as the temperature goes to zero.
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Reduction of the sign problem near T = 0 in quantum Monte Carlo simulations
- solve negative-sign problem near T = 0 using the above rule.
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Mitigating the Sign Problem through Basis Rotations
- optimize over the choice of basis for sign-free quantum Monte-Carlo simulations using the idea of (ⅲ).
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cluster algorithm
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Markov Chain Monte Carlo Method without Detailed Balance
- As name suggests, this algorithm minimize the average rejection rate, and even reduced to zero in many relevant cases.
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Geometric Allocation Approach for Transition Kernel of Markov Chain
- algorithm for constructing rejection free transition kernel that satisfies detai balance condition. Just symmetric version of
$\rm(ii)$
- algorithm for constructing rejection free transition kernel that satisfies detai balance condition. Just symmetric version of
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frustration-free model
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Multiple magnetization plateaus induced by farther neighbor interaction in an $S = 1$ two-leg Heisenberg spin ladder
- Consider the interaction that couples up to the nextnearest neighbor rungs and find an exactly solvable regime where the ground states become product states.
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Multiple magnetization plateaus induced by farther neighbor interaction in an $S = 1$ two-leg Heisenberg spin ladder
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reweighting
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Nakamura, Tota, Naomichi Hatano, and Hidetoshi Nishimori. 1992. “Reweighting Method for Quantum Monte Carlo Simulations with the Negative-Sign Problem.” Journal of the Physical Society of Japan 61 (10): 3494–3502.
- Studying J1J2 model with quantum monte carlo algorithm. Note that trotter number is finite here, which means there is systematical bias for calculation.
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Hatano, Naomichi. 1994. “Data Analysis for Quantum Monte Carlo Simulations with the Negative-Sign Problem.” Journal of the Physical Society of Japan 63 (5): 1691–97.
- Data analysis for reweighting method. Particulally this paper refer to the distribution of ratio of expectation value.
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Nakamura, Tota, Naomichi Hatano, and Hidetoshi Nishimori. 1992. “Reweighting Method for Quantum Monte Carlo Simulations with the Negative-Sign Problem.” Journal of the Physical Society of Japan 61 (10): 3494–3502.