Collective neutrino oscillations: Many-body non-forward effects and non-classicality
集体中微子振荡:多体非前向效应与非经典性
Julien Froustey, Ermal Rrapaj, Yuhao Liu, Gushu Li, Costin Iancu, Vincenzo Cirigliano
AI总结 研究密集天体环境中中微子演化的多体非前向散射效应,通过量子动力学与完整多体哈密顿量对比,揭示时间尺度和渐近行为差异,并分析量子计算资源需求。
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- 25 pages, 12 figures
密集天体环境中中微子演化通常用量子动力学框架描述(忽略多体关联积累),或通过简化多体计算(允许显著纠缠发展)。本文在简单中微子气体构型中比较这两种方法,特别强调非前向散射过程的作用。这些效应通过动力学描述中的碰撞项或考虑完整的中微子-中微子多体哈密顿量纳入。我们突出两种描述在特征时间尺度和渐近行为上的差异。受量子计算天然适合多体计算的启发,我们进一步研究中微子演化的非经典性,讨论Trotter误差缩放,以及构建量子电路在纠缠门和非Clifford门方面的相关成本。我们发现,中微子多体演化所需的资源在典型高能物理问题中处于低端,而在量子化学问题中处于中高端。对于完整哈密顿量,资源需求相对于截断版本增加。我们强调高效费米子到量子比特编码的重要性,这对于减少此类模拟所需的大量计算资源至关重要。
Neutrino evolution in dense astrophysical environments is typically described either within a quantum kinetic framework, which neglects the build-up of multi-body correlations, or through simplified many-body calculations that allow significant entanglement to develop. In this work, we compare these two approaches in a simple neutrino-gas configuration, with particular emphasis on the role of non-forward scattering processes. These effects are incorporated either through a collision term in the kinetic description, or by considering the full neutrino-neutrino many-body Hamiltonian. We highlight differences between the two descriptions in both their characteristic timescales and asymptotic behavior. Motivated by the natural suitability of quantum computing for many-body calculations, we further investigate the non-classicality of neutrino evolution, discussing Trotter error scaling, along with the associated costs of constructing quantum circuits in terms of entangling gates and non-Clifford gates. We find that the resources needed for neutrino many-body evolution are on the low end of typical high-energy physics problems and on the mid to high end with respect to quantum chemistry problems. For the full Hamiltonian, resource requirements increase relative to the truncated version. We emphasize the importance of efficient fermion-to-qubit encodings, which are essential for reducing the substantial computational resources required for such simulations.