Optimal tradeoffs for estimating Pauli observables
Sitan Chen, Weiyuan Gong, Qi Ye

TL;DR
This paper characterizes the optimal sample complexity and memory tradeoffs for estimating subsets of Pauli observables in quantum states, providing tight bounds and improved protocols for quantum shadow tomography.
Contribution
It offers a complete characterization of the optimal sample complexity for Pauli shadow tomography with various memory constraints and introduces protocols that estimate actual Pauli expectation values.
Findings
Any poly(n)-copy measurement protocol requires at least /4 measurements.
For protocols with k < n qubits of memory, 4 4 copies are necessary and sufficient.
Established tight bounds for purity testing, revealing a phase transition in the memory-sample tradeoff.
Abstract
We revisit the problem of Pauli shadow tomography: given copies of an unknown -qubit quantum state , estimate for some set of Pauli operators to within additive error . This has been a popular testbed for exploring the advantage of protocols with quantum memory over those without: with enough memory to measure two copies at a time, one can use Bell sampling to estimate for all using copies, but with qubits of memory, copies are needed. These results leave open several natural questions. How does this picture change in the physically relevant setting where one only needs to estimate a certain subset of Paulis? What is the optimal dependence on ? What is the optimal tradeoff between quantum memory and sample complexity? We answer all of these questions. For any…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsQuantum Mechanics and Applications · Markov Chains and Monte Carlo Methods · Quantum chaos and dynamical systems
