论文标题

荷斯坦 - 帕里马科夫扩展和差分方程方法的准确重新调整操作员方形 - 根管

Exact resummation of the Holstein-Primakoff expansion and differential equation approach to operator square-roots

论文作者

Vogl, Michael, Laurell, Pontus, Zhang, Hao, Okamoto, Satoshi, Fiete, Gregory A.

论文摘要

操作员方形 - 根源在理论物理学中无处不在。例如,它们出现在自旋操作员的荷斯坦 - 普里马科夫(Holstein-Primakoff)和克莱恩 - 戈登方程式中。通常,使用扰动扩展是与之打交道时唯一的追索权。在这项工作中,我们表明,在某些条件下,可以得出微分方程,可用于查找与操作员方形 - 根root的近似近似值。具体而言,对于数字运算符$ \ hat n = \ hat a^†a $我们表明,平方根$ \ sqrt {\ hat n} $接近$ \ hat n = 0 $可以通过$ \ hat hat n $中的多项式近似。该结果是出乎意料的,因为泰勒的扩展失败了。 $ \ hat n $中的多项式表达是可能的,因为$ \ hat n $是运营商,其组成部分$ a $ a $ and $ a^†$具有非平凡的换向器$ [a,a^†] = 1 $,并且不表现为标准。我们将方法应用于恒定磁场中的零质量klein-gordon hamiltonian,作为主要应用,是自旋算子的荷尔斯坦 - 普里马科夫代表,在那里我们能够在玻色孔中找到新的表达式。我们证明这些新表达式完全重现了旋转算子。我们的表达显然是冬宫,它比其他方法(例如Dyson-Maleev表示)具有优势。

Operator square-roots are ubiquitous in theoretical physics. They appear, for example, in the Holstein-Primakoff representation of spin operators and in the Klein-Gordon equation. Often the use of a perturbative expansion is the only recourse when dealing with them. In this work we show that under certain conditions differential equations can be derived which can be used to find perturbatively inaccessible approximations to operator square-roots. Specifically, for the number operator $\hat n=\hat a^†a$ we show that the square-root $\sqrt{\hat n}$ near $\hat n=0$ can be approximated by a polynomial in $\hat n$. This result is unexpected because a Taylor expansion fails. A polynomial expression in $\hat n$ is possible because $\hat n$ is an operator, and its constituents $a$ and $a^†$ have a non-trivial commutator $[a,a^†]=1$ and do not behave as scalars. We apply our approach to the zero mass Klein-Gordon Hamiltonian in a constant magnetic field, and as a main application, the Holstein-Primakoff representation of spin operators, where we are able to find new expressions that are polynomial in bosonic operators. We prove that these new expressions exactly reproduce spin operators. Our expressions are manifestly Hermitian, which offer an advantage over other methods, such as the Dyson-Maleev representation.

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