一篇新的arXiv预印本探讨了在有限量子内存中进行稳定器状态测试和学习所面临的挑战。研究人员发现，当量子内存限制在 $n$ 个量子比特中的 $k$ 个时，测试和学习稳定器状态之间的区别会消失。具体来说，在非自适应框架下，测试需要 $O(n-k)$ 个副本，而学习需要 $O(n^2/k)$ 个副本，这表明有限内存使得测试和学习的难度相当。 AI
排序理由 该集群讨论了一篇详细介绍量子计算理论发现的新学术论文。[lever_c_demoted from research: ic=2 ai=0.4]
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We study stabilizer state testing and learning with limited coherent quantum memory. Here an algorithm sequentially receives copies of an unknown $n$-qubit state, but may keep only $k$ qubits of coherent quantum memory between measurements. With unrestricted memory, seminal work …
Quantum stabilizer testing fails even with 99% memory Limited quantum memory collapses the gap between stabilizer testing and learning, a new arXiv preprint shows, with both needing Theta(n) copies. https://www. notatechguy.com/quantum-stabil izer-testing-fails-even-with-99-memor…