We introduce a quantum information theory-inspired method to improve the characterization of many-body Hamiltonians on near-term quantum devices. We design a new class of similarity transformations that, when applied as a preprocessing step, can substantially simplify a Hamiltonian for subsequent analysis on quantum hardware. By design, these transformations can be identified and applied efficiently using purely classical resources. In practice, these transformations allow us to shorten requisite physical circuit-depths, overcoming constraints imposed by imperfect near-term hardware. Importantly, the quality of our transformations is $tunable$: we define a 'ladder' of transformations that yields increasingly simple Hamiltonians at the cost of more classical computation. Using quantum chemistry as a benchmark application, we demonstrate that our protocol leads to significant performance improvements for zero and finite temperature free energy calculations on both digital and analog quantum hardware. Specifically, our energy estimates not only outperform traditional Hartree-Fock solutions, but this performance gap also consistently widens as we tune up the quality of our transformations. In short, our quantum information-based approach opens promising new pathways to realizing useful and feasible quantum chemistry algorithms on near-term hardware.

中文翻译：

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由量子魔法提供支持的零温度和有限温度量子模拟


我们引入了一种受量子信息论启发的方法来改进近期量子设备上多体哈密顿量的表征。我们设计了一类新的相似变换，当将其用作预处理步骤时，可以大大简化哈密顿量，以便在量子硬件上进行后续分析。通过设计，可以使用纯经典资源有效地识别和应用这些转换。在实践中，这些转换使我们能够缩短必要的物理电路深度，克服不完善的近期硬件所施加的限制。重要的是，我们的变换的质量是可调的：我们定义了一个变换的“阶梯”，它以更经典的计算为代价产生越来越简单的哈密顿量。使用量子化学作为基准应用程序，我们证明我们的协议可以显着提高数字和模拟量子硬件上的零和有限温度自由能计算的性能。具体来说，我们的能源估算不仅优于传统的 Hartree-Fock 解决方案，而且随着我们调整转换质量，这种性能差距也会不断扩大。简而言之，我们基于量子信息的方法为在近期硬件上实现有用且可行的量子化学算法开辟了有前景的新途径。