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The performance of quantum algorithms for ground-state energy estimation is directly impacted by the quality of the initial state, where quality is traditionally defined in terms of the overlap of the input state with the target state. An ideal state preparation protocol can be characterized by being easily generated classically and can be transformed to a quantum circuit with minimal overhead while having a significant overlap with the targeted eigenstate of a given Hamiltonian. We propose a method that meets these requirements by introducing a variant of the iterative qubit coupled cluster (iQCC) approach, which exclusively uses Clifford circuits. These circuits can be efficiently simulated on a classical computer, with polynomial scaling according to the Gottesman-Knill theorem. Since the iQCC method has been developed as a quantum algorithm firstly, our variant can be mapped naturally to quantum hardware. We additionally implemented several optimizations to the algorithm enhancing its scalability. We demonstrate the algorithm's correctness in ground-state simulations for small molecules such as H2, LiH, and H2O, and extend our study to complex systems like the titanium-based compound Ti(C5H5)(CH3)3 with a (20, 20) active space, requiring 40 qubits. Results show that the convergence of the algorithm is well-behaved, and the ground state can be represented accurately. Moreover, we show an automated workflow for restricting the qubit active space, thus relieving computational resources by considering only qubits affected by non-trivial operations.