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20182026
most citedWaveguide-integrated van der Waals heterostructure photodetector at telecom band with high speed and high responsivity

343 citations · 803 across the 17 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

quant-ph2024

Quantum sensitivity of parametric oscillators

Alex Gu, Jamison Sloan, Charles Roques-Carmes +6

Many quantum systems exhibit high sensitivity to their initial conditions, where microscopic quantum fluctuations can significantly influence macroscopic observables. Understanding…

quant-ph2024

Observing the dynamics of quantum states generated inside nonlinear optical cavities

Seou Choi, Yannick Salamin, Charles Roques-Carmes +3

Quantum states at optical frequencies are often generated inside cavities to facilitate strong nonlinear interactions. However, measuring these quantum states with traditional homo…

physics.optics2024★ 1 cited

Non-reciprocal frequency conversion in a multimode nonlinear system

Sahil Pontula, Sachin Vaidya, Charles Roques-Carmes +3

Nonlinear optics has become the workhorse for countless applications in classical and quantum optics, from optical bistability to single photon pair generation. However, the intrin…

physics.optics2024★ 1 cited

Stochastic logic in biased coupled photonic probabilistic bits

Michael Horodynski, Charles Roques-Carmes, Yannick Salamin +4

Optical computing often employs tailor-made hardware to implement specific algorithms, trading generality for improved performance in key aspects like speed and power efficiency. A…

physics.optics2024★ 4 cited

Multimode amplitude squeezing through cascaded nonlinear optical processes

Sahil Pontula, Yannick Salamin, Charles Roques-Carmes +1

Multimode squeezed light is enticing for several applications, from squeezed frequency combs for spectroscopy to signal multiplexing in optical computing. To generate squeezing in…

physics.optics2024★ 3 cited

Photonic probabilistic machine learning using quantum vacuum noise

Seou Choi, Yannick Salamin, Charles Roques-Carmes +7

Probabilistic machine learning utilizes controllable sources of randomness to encode uncertainty and enable statistical modeling. Harnessing the pure randomness of quantum vacuum n…