论文标题
用于模型无关的量子算法搜索新物理
A Quantum Algorithm for Model-Independent Searches for New Physics
论文作者
论文摘要
我们提出了一种新型的量子技术，以在多维BINNED撞机数据中搜索未建模的异常。我们提出将Ising晶格旋转位点与每个垃圾箱相关联，并根据观察到的数据和相应的理论期望适当地构建了Ising Hamiltonian。为了捕获数据中的空间相关异常，我们引入了相邻站点之间的自旋旋转相互作用以及自相互作用。由此产生的伊斯汀汉密尔顿的基态能量可以用作新的测试统计量，可以通过经典或通过绝热量子优化计算。我们证明，我们的测试统计量优于一些最常用的合适性测试。新方法通过利用统计噪声和真正的新物理信号之间的典型差异来大大降低了查找效果。
We propose a novel quantum technique to search for unmodeled anomalies in multidimensional binned collider data. We propose associating an Ising lattice spin site with each bin, with the Ising Hamiltonian suitably constructed from the observed data and a corresponding theoretical expectation. In order to capture spatially correlated anomalies in the data, we introduce spin-spin interactions between neighboring sites, as well as self-interactions. The ground state energy of the resulting Ising Hamiltonian can be used as a new test statistic, which can be computed either classically or via adiabatic quantum optimization. We demonstrate that our test statistic outperforms some of the most commonly used goodness-of-fit tests. The new approach greatly reduces the look-elsewhere effect by exploiting the typical differences between statistical noise and genuine new physics signals.
