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Systematic many-fermion Hamiltonian input scheme and spectral calculations on quantum computers

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arxiv 2402.08969 v3 pith:GFLVKLZP submitted 2024-02-14 quant-ph nucl-th

classification quant-phnucl-th
keywords inputschememany-fermioncalculationsframeworkhamiltonianhybridquantum
verification ladder T0 review T1 audit T2 compute T3 formal
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abstract

We present a novel input scheme for general second-quantized Hamiltonians of relativistic or non-relativistic many-fermion systems. This input scheme incorporates the fermionic anticommutation relations, particle number variations, and respects the symmetries of the Hamiltonian. Based on our input scheme, we propose a hybrid quantum-classical framework for spectral calculations on future quantum hardwares. We provide explicit circuit designs and the associated gate cost. We demonstrate our hybrid framework by solving the low-lying spectra of ${^{42}}$Ca and ${^{46}}$Ca. Our input scheme provides new pathways to solving the spectra and dynamics of the relativistic and nonrelativistic many-fermion systems via first-principles approaches.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. High-order Magnus Expansion for Hamiltonian Simulation

    quant-ph 2025-09 conditional novelty 7.0 of 10

    Arbitrary-order Magnus expansion is shown to have commutator-scaling error bounds and a polynomial-cost quantum circuit, yielding a time-dependent Hamiltonian simulation algorithm with O~(αbar^{1+1/p} T^{1+1/p}/ε^{1/p...

  2. Ab initio many-fermion structure calculations on a quantum computer

    nucl-th 2025-05 conditional novelty 6.0 of 10

    A quantum-classical resolvent method with a new fermionic block-encoding input scheme computes the spectrum and J values of 20O in a truncated sd-shell space, matching classical diagonalization.

  3. Studying few cluster resonances with quantum neural network driven iterative Harrow-Hassidim-Lloyd algorithm

    quant-ph 2025-06 conditional novelty 4.0 of 10

    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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