QumVQD enables excited-state quantum chemistry calculations on bosonic qumode hardware by enforcing particle-number symmetry and using Hamiltonian fragmentation, achieving chemical accuracy on H2 and spectroscopic accuracy on vibrational modes with far fewer entangling gates than qubit equivalents.
Qiskit nature 0.6.0
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
fields
quant-ph 3years
2026 3verdicts
UNVERDICTED 3representative citing papers
A commutativity-based dynamic ansatz within DMET enables ground-state simulations of molecules up to 144 qubits using at most 20 qubits at a time with improved accuracy and lower gate counts than standard approaches.
MonteQ applies Monte Carlo Tree Search in a two-level framework to optimize Pauli rotation orderings for Hamiltonian simulation, cutting CNOT counts by up to 53% versus prior compilers.
citing papers explorer
-
Excited-State Quantum Chemistry on Qumode-Based Processors via Variational Quantum Deflation
QumVQD enables excited-state quantum chemistry calculations on bosonic qumode hardware by enforcing particle-number symmetry and using Hamiltonian fragmentation, achieving chemical accuracy on H2 and spectroscopic accuracy on vibrational modes with far fewer entangling gates than qubit equivalents.
-
Advancing Practical Quantum Embedding Simulations via Operator Commutativity Based State Preparation for Complex Chemical Systems
A commutativity-based dynamic ansatz within DMET enables ground-state simulations of molecules up to 144 qubits using at most 20 qubits at a time with improved accuracy and lower gate counts than standard approaches.
-
MonteQ: A Monte Carlo Tree Search Based Quantum Circuit Synthesis Framework
MonteQ applies Monte Carlo Tree Search in a two-level framework to optimize Pauli rotation orderings for Hamiltonian simulation, cutting CNOT counts by up to 53% versus prior compilers.