The work proves a worst-case sample complexity of O(sqrt(4.5^n)) for distributed inner product estimation with local Clifford sampling on n-qubit states, with a conjectured O(sqrt(3.6^n)) for Haar sampling.
Now the shared variable iss j, whilet k andt k′ are independent conditioned onU
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
quant-ph 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Worst-Case Sample Complexity Bounds for Distributed Inner Product Estimation with Local Randomized Measurements
The work proves a worst-case sample complexity of O(sqrt(4.5^n)) for distributed inner product estimation with local Clifford sampling on n-qubit states, with a conjectured O(sqrt(3.6^n)) for Haar sampling.