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Efficient Excited-State Calculations for Molecules Based on Contextual Subspace Method and Symmetry Optimizations
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abstract
Quantum computing methods for excited-state calculations remain underexplored in Noisy Intermediate-Scale Quantum (NISQ) hardware, despite their critical role in photochemistry and material science. Herein, we propose a resource-efficient framework that integrates the contextual subspace (CS) method with the Variational Quantum Deflation (VQD) algorithm to enable systematic excited-state calculations for molecules while reducing qubit requirements. On the basis of the numerical results, we find that it is unproblematic to utilize this combination in calculating the excited state to reduce qubits. Furthermore, we demonstrate that the implementation of a spin-conserving hardware-efficient ansatz, namely the $\mathcal{N}(\theta_x,\theta_y,\theta_z)$ block ansatz, allows exploitation of spin symmetry within the projected subspace, thereby achieving further reductions in computational resource demands. Compared to the commonly used $R_{y}R_{z}$ ansatz, using the $\mathcal{N}(\theta_x,\theta_y,\theta_z)$ ansatz can reduce the number of optimization iterations by up to 3 times at a similar circuit depth.
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Cited by 1 Pith paper
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Simulating the Antiferromagnetic Heisenberg Model on a Spin-Frustrated Kagome Lattice with the Contextual Subspace Variational Quantum Eigensolver
Using contextual subspace reduction and DMRG-biased stabilizers, a 5-qubit VQE on IBM hardware estimated the Kagome Heisenberg ground state with 0.019% relative error.
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