Excited-State Quantum Chemistry on Qumode-Based Processors via Variational Quantum Deflation

• URL: http://arxiv.org/abs/2604.13457v2
• Date: Mon, 20 Apr 2026 04:26:02 GMT
• Title: Excited-State Quantum Chemistry on Qumode-Based Processors via Variational Quantum Deflation
• Abstract summary: Variational quantum algorithms on bosonic quantum processors are an emerging paradigm for quantum chemistry calculations.<n>We introduce the qumode-based variational quantum deflation framework (QumVQD) for finding both electronic and vibrational excited state energies.
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• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Variational quantum algorithms on bosonic quantum processors are an emerging paradigm for quantum chemistry calculations, exploiting the natural alignment between molecular structure and harmonic oscillator-based hardware. We introduce the qumode-based variational quantum deflation framework (QumVQD) for finding both electronic and vibrational excited state energies on qumode-based architectures. For electronic structure, we incorporated particle number conservation constraints via Fock basis Hamming weight filtering. This symmetry enforcement achieves a significant reduction in computational overhead, scaling the Hilbert space dimension as O$M \choose n_e$ rather than O$(2^M)$ for $M$ spin orbitals and $n_e$ electrons. We validate the approach through electronic structure calculations on H$_{\text{2}}$, achieving agreement with full configuration interaction (FCI) using the STO-3G basis within chemical accuracy across potential energy surfaces. Extending to vibrational structure, we combine QumVQD with Hamiltonian fragmentation based on Bogoliubov transforms, computing CO$_{\text{2}}$ and H$_{\text{2}}$S vibrational eigenstates to spectroscopic accuracy with entangling gate counts 1-2 orders of magnitude lower than analogous qubit-based algorithms. We performed noise characterization using amplitude-damping models and gate-fidelity analysis, which demonstrates enhanced error resilience due to reduced circuit depth compared to qubit-based algorithms. Together, these results highlight the potential of bosonic quantum devices for advancing computational chemistry, particularly in areas where qubit-based devices struggle.

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