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arXiv 2406.04418quant-ph
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基于水平量子门的几何量子机器学习

Geometric Quantum Machine Learning with Horizontal Quantum Gates

Roeland Wiersema, Alexander F. Kemper, Bojko N. Bakalov, Nathan Killoran

AI总结:

针对几何量子机器学习中等变电路约束过强、表达能力有限的问题,提出基于齐性空间的水平量子门新范式,可提升表达能力、实现高效分解并减少参数量。

摘要:

在当前几何量子机器学习框架下,构建满足某群作用对称性的变分拟设的标准方法是强制电路具有等变性,即与群作用对易。然而这可能是一种过于严苛的约束,会极大限制电路的表达能力,尤其是在连续对称的情况下。我们提出一种基于齐性空间的对称感知变分量子电路构建新范式,放松了等变性这一过于严格的要求。我们通过引入水平量子门实现这一目标,这类门仅沿与对称方向正交的方向变换量子态。我们证明水平量子门的表达能力远强于等变门,因此能够解决等变电路无法处理的问题。例如,由水平门构成的电路可以求解基态自旋扇区未知的SU(2)对称模型的基态——这是等变电路无法完成的任务。此外,对于一类基于对称空间的特殊水平量子门子类,我们可以通过KAK定理得到这类门的高效电路分解。最后,我们重点介绍了一类特殊的水平量子门,其行为与通用SU(4)门类似,但在通用问题上可实现参数量的二次级减少。

英文摘要:

In the current framework of Geometric Quantum Machine Learning, the canonical method for constructing a variational ansatz that respects the symmetry of some group action is by forcing the circuit to be equivariant, i.e., to commute with the action of the group. This can, however, be an overzealous constraint that greatly limits the expressivity of the circuit, especially in the case of continuous symmetries. We propose an alternative paradigm for the symmetry-informed construction of variational quantum circuits, based on homogeneous spaces, relaxing the overly stringent requirement of equivariance. We achieve this by introducing horizontal quantum gates, which only transform the state with respect to the directions orthogonal to those of the symmetry. We show that horizontal quantum gates are much more expressive than equivariant gates, and thus can solve problems that equivariant circuits cannot. For instance, a circuit comprised of horizontal gates can find the ground state of an $\mathrm{SU}(2)$-symmetric model where the ground state spin sector is unknown--a task where equivariant circuits fall short. Moreover, for a particular subclass of horizontal gates based on symmetric spaces, we can obtain efficient circuit decompositions for our gates through the KAK theorem. Finally, we highlight a particular class of horizontal quantum gates that behave similarly to general $\mathrm{SU}(4)$ gates, while achieving a quadratic reduction in the number of parameters for a generic problem.

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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