Matrix product state algorithms must enlarge their bond spaces as entanglement grows and compress them to control cost. We formulate basis-update and Galerkin (BUG) time integration as a sequence of canonical MPS sweeps for Hamiltonians represented as matrix product operators. We show when two natural basis updates pro...
Maximilian Fröhlich, Richard M. Milbradt, Martin Eigel et al.· 0 citations
A tensor network approach for simulating dynamic circuits is developed by extending a DMRG-based method for quantum circuit simulation to support dynamic circuit operations and explores the trade-offs between simulation accuracy and computational efficiency.
Innocenzo Fulginiti, Alessandro Poggiali, C. Mendl· 0 citations
Tensor networks have attracted much attention as a powerful tool for modeling quantum many-body systems. Their contraction is a significant challenge, however, especially in highly connected networks, as memory requirements become prohibitive and the optimal contraction order is increasingly hard to find. The belief pr...
The hybrid tensor network (hTN) abstraction is introduced—a unified representation capturing quantum-classical computation—realized in qTPU, an end-to-end sys-tem comprising: the qTPU programming model for declarative hybrid computation specification; the qTPU compiler for holistic hTN optimization balancing classical...
Nathaniel Tornow, Emmanouil Giortamis, Dennis Sprokholt et al.· 1 citation
A low-overhead fidelity-aware scheduling framework for multi-QPU systems based on a Graph Neural Network that estimates, before compilation, the expected fidelity of each circuit on each available QPU, and a tunable scheduler uses these estimates to control the trade-off between execution fidelity and parallelism.
Innocenzo Fulginiti, Antonio Tudisco, Salvatore Zammuto et al.· 0 citations
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