Structural f-divergence yields tight trade-off inequalities bounding gradient magnitudes and cost moments in parameterized quantum circuits, with equality for a minimal one-qubit ansatz.
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σ-VQE uses low-depth circuits and an energy-selective cost function to preferentially prepare quantum many-body scar states on NISQ devices.
Hybrid generative quantum circuits guided by local observable correlators sample diverse ensembles whose span reproduces degenerate ground spaces in Majumdar-Ghosh, AKLT, and XXZ models.
A variational framework assisted by matrix product states prepares approximate thermal Gibbs states for 1D lattices up to 30 sites and 2D lattices up to 6x6 using up to 44 qubits, with a demonstration on IBM Heron hardware.
citing papers explorer
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Structural $f$-divergence: Tight universal bounds for cost function moments and gradients in parameterized quantum circuits
Structural f-divergence yields tight trade-off inequalities bounding gradient magnitudes and cost moments in parameterized quantum circuits, with equality for a minimal one-qubit ansatz.
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$\sigma$-VQE: Excited-state preparation of quantum many-body scars with shallow circuits
σ-VQE uses low-depth circuits and an energy-selective cost function to preferentially prepare quantum many-body scar states on NISQ devices.
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Local-Observable-Guided Generative Quantum Circuits for Degenerate Ground Spaces
Hybrid generative quantum circuits guided by local observable correlators sample diverse ensembles whose span reproduces degenerate ground spaces in Majumdar-Ghosh, AKLT, and XXZ models.
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Variational Thermal State Preparation on Digital Quantum Processors Assisted by Matrix Product States
A variational framework assisted by matrix product states prepares approximate thermal Gibbs states for 1D lattices up to 30 sites and 2D lattices up to 6x6 using up to 44 qubits, with a demonstration on IBM Heron hardware.