论文标题
在量子计算机上自动区分统一耦合群集的可行方法
A Feasible Approach for Automatically Differentiable Unitary Coupled-Cluster on Quantum Computers
论文作者
论文摘要
我们为适用于量子计算机的单一耦合群集类型运算符开发计算负担得起的独立梯度评估程序。我们表明，在我们的框架内，相对于参数化的n折口激发的期望值梯度可以通过四个相似形式和大小的期望值来评估，而大多数标准方法基于参数转换规则的直接应用，与o（2^（2n））期望值相关的成本。对于真实的波形，可以将此成本进一步降低到两个期望值。我们的策略是在开源软件包龙舌兰酒中实施的，并允许黑板样式的可区分目标功能构建。我们说明了电子地面和激发状态的初始应用。
We develop computationally affordable and encoding independent gradient evaluation procedures for unitary coupled-cluster type operators, applicable on quantum computers. We show that, within our framework, the gradient of an expectation value with respect to a parameterized n-fold fermionic excitation can be evaluated by four expectation values of similar form and size, whereas most standard approaches based on the direct application of the parameter-shift-rule come with an associated cost of O(2^(2n)) expectation values. For real wavefunctions, this cost can be further reduced to two expectation values. Our strategies are implemented within the open-source package tequila and allow blackboard style construction of differentiable objective functions. We illustrate initial applications for electronic ground and excited states.
