A local SU(2) symmetry-based product formula clusters Hamiltonian terms into at most four classes for exact two-qubit implementations, cutting commutator errors and gate count in many-body simulations.
Campbell, Random compiler for fast hamiltonian sim- ulation, Phys
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A fluctuation-guided adaptive random compiler for Hamiltonian simulation dynamically adjusts term sampling probabilities according to state sensitivity to improve fidelity over fixed randomized methods.
First end-to-end demonstration of quantum error correction integrated with quantum phase estimation to compute molecular hydrogen ground-state energy to 0.001(13) hartree accuracy on Quantinuum H2-2 hardware.
qSHIFT achieves L-independent gate complexity and O(t^{1+r}) error scaling in quantum simulation through adaptive sampling distributions updated by solving L^r classical linear equations per round.
Randomized sparse-QSVT reduces gate counts by up to 10x for inhomogeneous many-term Hamiltonians at moderate error (around 10^{-3}), but deterministic QSVT becomes cheaper for higher precision.
citing papers explorer
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Beyond Commutativity: Redesigning Trotter Decomposition via Local Symmetry
A local SU(2) symmetry-based product formula clusters Hamiltonian terms into at most four classes for exact two-qubit implementations, cutting commutator errors and gate count in many-body simulations.
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Fluctuation-guided adaptive random compiler for Hamiltonian simulation
A fluctuation-guided adaptive random compiler for Hamiltonian simulation dynamically adjusts term sampling probabilities according to state sensitivity to improve fidelity over fixed randomized methods.
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Quantum Error-Corrected Computation of Molecular Energies
First end-to-end demonstration of quantum error correction integrated with quantum phase estimation to compute molecular hydrogen ground-state energy to 0.001(13) hartree accuracy on Quantinuum H2-2 hardware.
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qSHIFT: An Adaptive Sampling Protocol for Higher-Order Quantum Simulation
qSHIFT achieves L-independent gate complexity and O(t^{1+r}) error scaling in quantum simulation through adaptive sampling distributions updated by solving L^r classical linear equations per round.
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When is randomization advantageous in quantum simulation?
Randomized sparse-QSVT reduces gate counts by up to 10x for inhomogeneous many-term Hamiltonians at moderate error (around 10^{-3}), but deterministic QSVT becomes cheaper for higher precision.