5 papers · 1 filter
Quantum Bayesian Networks Can Speed up Reinforcement Learning in Partially Observable Environments
Gilberto Cunha, Alexandra Ramôa, André Sequeira +2
Reinforcement learning (RL) provides a principled framework for decision-making in partially observable environments, which can be modeled as Markov decision processes and compactl…
Worst-case depth hierarchy for shallow quantum circuits
Min-Hsiu Hsieh, Michael de Oliveira, Sathyawageeswar Subramanian +1
Circuit depth is a central resource in complexity theory. While bounded-depth classical circuits admit well-understood hierarchy theorems, the internal structure of constant-depth…
The Power of Shallow-depth Toffoli and Qudit Quantum Circuits
Alex Bredariol Grilo, Elham Kashefi, Damian Markham +1
The relevance of shallow-depth quantum circuits has recently increased, mainly due to their applicability to near-term devices. In this context, one of the main goals of quantum ci…
Learning depth-3 circuits via quantum agnostic boosting
Srinivasan Arunachalam, Arkopal Dutt, Alexandru Gheorghiu +1
We initiate the study of quantum agnostic learning of phase states with respect to a function class : given copies of an unk…
Bridging Resource Theory and Quantum Key Distribution: Geometric Analysis and Statistical Testing
Andrea D'Urbano, Michael de Oliveira, LuÃs Soares Barbosa
Discerning between quantum and classical correlations is of great importance. Bell polytopes are well established as a fundamental tool. In this paper, we extend this line of inqui…