47 citations · 124 across the 4 of their papers we have counts for
10 papers
Efficient sampling from shallow Gaussian quantum-optical circuits with local interactions
Haoyu Qi, Diego Cifuentes, Kamil Brádler +3
We prove that a classical computer can efficiently sample from the photon-number probability distribution of a Gaussian state prepared by using an optical circuit that is shallow a…
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…
Applications of Near-Term Photonic Quantum Computers: Software and Algorithms
Thomas R. Bromley, Juan Miguel Arrazola, Soran Jahangiri +7
Gaussian Boson Sampling (GBS) is a near-term platform for photonic quantum computing. Recent efforts have led to the discovery of GBS algorithms with applications to graph-based pr…
Understanding high gain twin beam sources using cascaded stimulated emission
Gil Triginer, Mihai D. Vidrighin, Nicolás Quesada +5
We present a new method for the spectral characterization of pulsed twin beam sources in the high gain regime, using cascaded stimulated emission. We show an implementation of this…
Point Processes with Gaussian Boson Sampling
Soran Jahangiri, Juan Miguel Arrazola, Nicolás Quesada +1
Random point patterns are ubiquitous in nature, and statistical models such as point processes, i.e., algorithms that generate stochastic collections of points, are commonly used t…
Regimes of classical simulability for noisy Gaussian boson sampling
Haoyu Qi, Daniel J. Brod, Nicolás Quesada +1
As a promising candidate for exhibiting quantum computational supremacy, Gaussian Boson Sampling (GBS) is designed to exploit the ease of experimental preparation of Gaussian state…