20 citations · 22 across the 2 of their papers we have counts for
2 papers
quant-ph2022★ 20 cited
Pulse-efficient quantum machine learning
André Melo, Nathan Earnest-Noble, Francesco Tacchino
Quantum machine learning algorithms based on parameterized quantum circuits are promising candidates for near-term quantum advantage. Although these algorithms are compatible with…
quant-ph2022★ 2 cited
On Hitting Times for General Quantum Markov Processes
Lorenzo Laneve, Francesco Tacchino, Ivano Tavernelli
Random walks (or Markov chains) are models extensively used in theoretical computer science. Several tools, including analysis of quantities such as hitting and mixing times, are h…