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Quantum computing for extracting nuclear resonances
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abstract
Quantum computing has been increasingly applied in nuclear physics. In this work, we combine quantum computing with the complex scaling method to address the resonance problem. Due to the non-Hermiticity introduced by complex scaling, standard quantum computing cannot solve for complex eigenvalues directly. Therefore, it is necessary to embed the non-Hermitian operator into a larger dimensional unitary operator. Additionally, for the case of two basis vectors, we improve the traditional direct measurement method and optimize the quantum circuit. Ultimately, using the $\alpha+\alpha$ system as an example, we obtain the complex eigenenergies from the quantum computer that are consistent with those obtained from direct Hamiltonian diagonalization.
Forward citations
Cited by 2 Pith papers
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Data-driven trap theory for nuclear scattering
A data-calibrated quantization condition is proposed to extract nuclear scattering phase shifts from harmonic-trap spectra for neutral and charged particles.
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Studying few cluster resonances with quantum neural network driven iterative Harrow-Hassidim-Lloyd algorithm
A quantum neural network generates eigenvector-continuation basis states, and an iterative HHL routine solves the resulting generalized eigenvalue problem for the 4+ resonance of 9ΛBe.
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