https://haifei-home.pages.dev/tags/%E7%BB%8F%E5%85%B8%E9%98%B4%E5%BD%B1/Recent content in 经典阴影 on Haifei's HomeHugozh-CNhfwang132@gmail.com (hfwang132)hfwang132@gmail.com (hfwang132)This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.Fri, 30 May 2025 02:53:53 +0800https://haifei-home.pages.dev/post_20250530_%E9%87%8F%E5%AD%90%E6%80%81%E7%9A%84%E7%BB%8F%E5%85%B8%E9%98%B4%E5%BD%B1-classical-shadows/Fri, 30 May 2025 02:53:53 +0800hfwang132@gmail.com (hfwang132)https://haifei-home.pages.dev/post_20250530_%E9%87%8F%E5%AD%90%E6%80%81%E7%9A%84%E7%BB%8F%E5%85%B8%E9%98%B4%E5%BD%B1-classical-shadows/<h2 id="一量子态层析quantum-state-tomography">一、量子态层析（Quantum State Tomography）</h2> <p>目前，人们已经可以制备由成百上千个量子比特所构成的量子态（此处省略二十个参考文献）。</p> <p>但是我们如何知道制备的量子态 \(\rho\) 的确是我们想要的 \(\rho\) ？或者更宽泛地说：如何学习一个量子态 \(\rho\) 的（部分或者所有）信息？</p>