A quantum multi-level framework achieves near-optimal query complexity for q-Tsallis entropy estimation for q>1 and a speedup for q<1 over classical methods.
A quantum algorithm framework for discrete probability distributions with applications to R \'e nyi entropy estimation
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
-
Quantum Multi-Level Estimation of Functionals of Discrete Distributions
A quantum multi-level framework achieves near-optimal query complexity for q-Tsallis entropy estimation for q>1 and a speedup for q<1 over classical methods.