activity
20092026
most citedAdvances in Quantum Cryptography

1.9k citations · 7.5k across the 87 of their papers we have counts for

collaborators
Showing 2020Show all

7 papers · 1 filter

quant-ph2020★ 14 cited

How to enhance quantum generative adversarial learning of noisy information

Paolo Braccia, Filippo Caruso, Leonardo Banchi

Quantum Machine Learning is where nowadays machine learning meets quantum information science. In order to implement this new paradigm for novel quantum technologies, we still need…

quant-ph2020★ 15 cited

Ultimate Limits of Thermal Pattern Recognition

Cillian Harney, Leonardo Banchi, Stefano Pirandola

Quantum Channel Discrimination (QCD) presents a fundamental task in quantum information theory, with critical applications in quantum reading, illumination, data-readout and more.…

quant-ph2020★ 14 cited

Idler-free channel position finding

Jason L. Pereira, Leonardo Banchi, Quntao Zhuang +1

Entanglement is a powerful tool for quantum sensing, and entangled states can greatly boost the discriminative power of protocols for quantum illumination, quantum metrology, or qu…

quant-ph2020

Optimal quantum spatial search with one-dimensional long-range interactions

Dylan Lewis, Asmae Benhemou, Natasha Feinstein +2

Continuous-time quantum walks can be used to solve the spatial search problem, which is an essential component for many quantum algorithms that run quadratically faster than their…

quant-ph2020★ 28 cited

Quantum-enhanced barcode decoding and pattern recognition

Leonardo Banchi, Quntao Zhuang, Stefano Pirandola

Quantum hypothesis testing is one of the most fundamental problems in quantum information theory, with crucial implications in areas like quantum sensing, where it has been used to…

quant-ph2020★ 96 cited

Measuring Analytic Gradients of General Quantum Evolution with the Stochastic Parameter Shift Rule

Leonardo Banchi, Gavin E. Crooks

Hybrid quantum-classical optimization algorithms represent one of the most promising application for near-term quantum computers. In these algorithms the goal is to optimize an obs…

quant-ph2020★ 37 cited

Training Gaussian Boson Sampling Distributions

Leonardo Banchi, Nicolás Quesada, Juan Miguel Arrazola

Gaussian Boson Sampling (GBS) is a near-term platform for photonic quantum computing. Applications have been developed which rely on directly programming GBS devices, but the abili…