MPS TE-PAI achieves unbiased classical time evolution by averaging tensor-network representations of randomized shallow Trotter circuits, yielding lower gate counts per sample and better tolerance to bond-dimension truncation than standard methods.
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A QTT-based solver with Helmholtz-Leray penalization in Fourier space stably computes solutions and gradients for multiscale elliptic PDEs on meshes with up to 10^37 virtual degrees of freedom in 3D.
Introduces MPO encodings of the Magnus expansion and Dyson series for arbitrary-order accurate time evolution in 1D quantum lattices with time-dependent Hamiltonians, applicable to finite/infinite systems and long-range interactions.
Tailoring tensor network algorithms to the scale hierarchy in quantics representation produces faster, more robust solvers for high-dimensional linear and eigenvalue PDE problems.
Backreaction in semiclassical scalar QED in 1+1D avoids instabilities and produces over-screening at high external charges.
citing papers explorer
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Quantum-inspired classical simulation through randomized time evolution
MPS TE-PAI achieves unbiased classical time evolution by averaging tensor-network representations of randomized shallow Trotter circuits, yielding lower gate counts per sample and better tolerance to bond-dimension truncation than standard methods.
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Stable full-field simulation of a multiscale elliptic equation by means of Quantized Tensor Trains
A QTT-based solver with Helmholtz-Leray penalization in Fourier space stably computes solutions and gradients for multiscale elliptic PDEs on meshes with up to 10^37 virtual degrees of freedom in 3D.
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Matrix Product Operator Encodings of the Magnus Expansion and Dyson Series
Introduces MPO encodings of the Magnus expansion and Dyson series for arbitrary-order accurate time evolution in 1D quantum lattices with time-dependent Hamiltonians, applicable to finite/infinite systems and long-range interactions.
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Tailoring tensor network techniques to the quantics representation for highly inhomogeneous problems and few body problems
Tailoring tensor network algorithms to the scale hierarchy in quantics representation produces faster, more robust solvers for high-dimensional linear and eigenvalue PDE problems.
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Revisiting semiclassical scalar QED in 1+1 dimensions
Backreaction in semiclassical scalar QED in 1+1D avoids instabilities and produces over-screening at high external charges.