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20192024
most citedQuantum-inspired annealers as Boltzmann generators for machine learning and statistical physics

4 citations · 4 across the 3 of their papers we have counts for

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quant-ph2024

Spontaneous Symmetry Breaking of an Optical Polarization State in a Polarization-Selective Nonlinear Resonator

K. S. Manannikov, E. I. Mironova, A. S. Poliakov +3

We exploit polarization self-rotation in atomic rubidium vapor to observe spontaneous symmetry breaking and bistability of polarization patterns. We pump the vapor cell with horizo…

quant-ph20194 cited

Quantum-inspired annealers as Boltzmann generators for machine learning and statistical physics

Alexander E. Ulanov, Egor S. Tiunov, A. I. Lvovsky

Quantum simulators and processors are rapidly improving nowadays, but they are still not able to solve complex and multidimensional tasks of practical value. However, certain numer…

quant-ph2019

Experimental quantum homodyne tomography via machine learning

E. S. Tiunov, V. V. Tiunova, A. E. Ulanov +2

Complete characterization of states and processes that occur within quantum devices is crucial for understanding and testing their potential to outperform classical technologies fo…

quant-ph2019

Observation of Multimode Strong Coupling of Cold Atoms to a 30-m Long Optical Resonator

Aisling Johnson, Martin Blaha, Alexander E. Ulanov +3

We report on the observation of multimode strong coupling of a small ensemble of atoms interacting with the field of a 30-m long fiber resonator containing a nanofiber section. The…

quant-ph2019

Annealing by simulating the coherent Ising machine

Egor S. Tiunov, Alexander E. Ulanov, A. I. Lvovsky

The coherent Ising machine (CIM) enables efficient sampling of low-lying energy states of the Ising Hamiltonian with all-to-all connectivity by encoding the spins in the amplitudes…