论文标题
用量子进行压缩传感的合奏方法
An Ensemble Approach for Compressive Sensing with Quantum
论文作者
论文摘要
我们利用统计合奏的想法来提高基于量子退火的二元压缩感应的质量。由于在量子退火器上执行量子机说明可能会导致激发态，而不是给定的哈密顿量的基态，因此我们使用不同的惩罚参数来生成多个不同的二次不受约束的二进制优化（QUBO）函数，其基态的基态代表了原始问题的潜在解决方案。然后，我们从最小化所有相应（不同的）Qubos来估计二元压缩感应问题的解决方案中采用了已达到的样品。我们在D-WAVE 2000Q量子处理器上进行的实验表明，所提出的集合方案对控制可行性和稀疏回收率之间权衡的惩罚参数的校准敏感也较小。
We leverage the idea of a statistical ensemble to improve the quality of quantum annealing based binary compressive sensing. Since executing quantum machine instructions on a quantum annealer can result in an excited state, rather than the ground state of the given Hamiltonian, we use different penalty parameters to generate multiple distinct quadratic unconstrained binary optimization (QUBO) functions whose ground state(s) represent a potential solution of the original problem. We then employ the attained samples from minimizing all corresponding (different) QUBOs to estimate the solution of the problem of binary compressive sensing. Our experiments, on a D-Wave 2000Q quantum processor, demonstrated that the proposed ensemble scheme is notably less sensitive to the calibration of the penalty parameter that controls the trade-off between the feasibility and sparsity of recoveries.
