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Optimal Low-Rank Quantum State Tomography with Bounded-Sample Joint Measurements

Paper recorded by Signals 4 on 2026-09-09 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-09 on arXiv · recorded by Signals 4 on 2026-09-10

Category: cs.LG · 机器学习 · first seen 2026-09-10

Abstract

We determine the optimal sample complexity of low-rank quantum state tomography when each measurement may act jointly on at most $t$ samples. For sufficiently small $\varepsilon$, estimating an unknown state on $\mathbb{C}^d$ of rank at most $r$ to trace norm error $\varepsilon$ with constant success probability requires, and is achievable with, $$ Θ\left( \frac{dr}{\varepsilon^2} \max\left\

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#82 most recent of 215 cs.LG papers we have recorded · ↑ newer: Characterizing Language Generation in the Limit: Finite Witnesses and · ↓ older: Quantum Feature Engineering for Credit Default Prediction: When and Wh
Cite this page: Optimal Low-Rank Quantum State Tomography with Bounded-Sample Joint Measurements: the #82 most recent of 215 cs.LG papers we have recorded (as of 2026-09-09). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/optimal-low-rank-quantum-state-tomography-with-bounded-sample-joint-measurements.html
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