A layer-by-layer classical variational disentanglement algorithm compiles preparation circuits for matrix product states by minimizing bipartite entanglement to reduce bond dimensions.
and Akhriev, Albert and Vala, Jiri and Zhuk, Sergiy , date =
4 Pith papers cite this work, alongside 4 external citations. Polarity classification is still indexing.
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Introduces a parallelizable hybrid tensor network algorithm for time-evolving matrix product states that combines classical BUG integration with quantum methods without synchronization barriers.
Bowtie VarQTE is a hybrid classical-quantum variational time evolution method that exploits causal light-cones to reduce quantum resource use for state preparation while achieving fidelities comparable to approximate quantum compilation.
Quantum simulation finds SU(2)-symmetric 2D interactions most resilient to superdiffusion breakdown in generalized Heisenberg models.
citing papers explorer
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Preparation Circuits for Matrix Product States by Classical Variational Disentanglement
A layer-by-layer classical variational disentanglement algorithm compiles preparation circuits for matrix product states by minimizing bipartite entanglement to reduce bond dimensions.
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Time Evolution on Hybrid Tensor Networks -- A Novel and Parallelizable Algorithm
Introduces a parallelizable hybrid tensor network algorithm for time-evolving matrix product states that combines classical BUG integration with quantum methods without synchronization barriers.
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Bowtie VarQTE: A Resource-Efficient Quantum State Preparation Primitive
Bowtie VarQTE is a hybrid classical-quantum variational time evolution method that exploits causal light-cones to reduce quantum resource use for state preparation while achieving fidelities comparable to approximate quantum compilation.
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Superdiffusion resilience in Heisenberg Chains with 2D interactions on a quantum processor
Quantum simulation finds SU(2)-symmetric 2D interactions most resilient to superdiffusion breakdown in generalized Heisenberg models.