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arXiv 2104.03708hep-thquant-ph
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反线性对称性与量子场论中的鬼问题

Antilinear Symmetry and the Ghost Problem in Quantum Field Theory

Philip D. Mannheim

摘要:

如果一个非厄米哈密顿量具有像$PT$那样的反线性对称性,那么这个哈密顿量的本征值都可以是实数,这一认识激发了人们对量子力学基本结构的新认识。具体地说,它使人们认识到Hilbert空间可以比已建立的Dirac方法更丰富,即用ket向量和它们的厄米共轭bra向量构造内积。在反线性对称的情况下,我们必须用ket向量和它们的反线性共轭来构造内积,而正是这些内积在非厄米特但反线性对称的情况下是与时间无关的,即使标准狄拉克内积不是。此外,从某种意义上说,反线性对称不仅可以解决内积的时间行为,而且还可以解决它的整体符号问题,在标准狄拉克内积被发现具有幽灵般的负符号的情况下,反线性对称能够产生正的内积。因此,反线性对称解决了量子场论中的幽灵问题,它表明当一个理论有幽灵态时,它是在错误的希尔伯特空间中形成的,而反线性对称提供了一个没有幽灵的希尔伯特空间。反线性对称实际上并没有消除鬼态。相反,它表明,导致人们认为鬼魂首先存在的推理是错误的。

英文摘要:

The recognition that the eigenvalues of a non-Hermitian Hamiltonian could all be real if the Hamiltonian had an antilinear symmetry such as $PT$ stimulated new insight into the underlying structure of quantum mechanics. Specifically, it lead to the realization that Hilbert space could be richer than the established Dirac approach of constructing inner products out of ket vectors and their Hermitian conjugate bra vectors. With antilinear symmetry one must instead build inner products out of ket vectors and their antilinear conjugates, and it is these inner products that would be time independent in the non-Hermitian but antilinearly symmetric case even as the standard Dirac inner products would not be. Moreover, and in a sense quite remarkably, antilinear symmetry could address not only the temporal behavior of the inner product but also the issue of its overall sign, with antilinear symmetry being capable of yielding a positive inner product in situations where the standard Dirac inner product is found to have ghostlike negative signature. Antilinear symmetry thus solves the ghost problem in quantum field theory by showing that when a theory has ghost states it is being formulated in the wrong Hilbert space, with antilinear symmetry providing a Hilbert space that is ghost free. Antilinear symmetry does not actually get rid of the ghost states. Rather, it shows that the reasoning that led one to think that ghosts were present in the first place is faulty.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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