Coherence properties of microcavity polaritons : from parametric scattering to Bose-Einstein condensation

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\gamma

and momentum parameter

\beta

that allows u ...

While momentum-based accelerated variants of stochastic gradient descent (SGD) are widely used when training machine learning models, there is little theoretical understanding on the generalization error of such methods. In this work, we first show that th ...

Coherence properties of microcavity polaritons : from parametric scattering to Bose-Einstein condensation

Chattez avec Graph Search

Light Emission and Conductance Fluctuations in Electrically Driven and Plasmonically Enhanced Molecular Junctions

Fair real-time control of energy storage systems in active distribution networks in the presence of uncertainties

Dataset to accompany publication "Quantum-mechanical effects in photoluminescence from thin crystalline gold films"

Thermo-optic epsilon-near-zero effects

Lithium tantalate photonic integrated circuits for volume manufacturing

Dissipative Kerr soliton generation at 2μm in a silicon nitride microresonator

Frustrated magnets in the limit of infinite dimensions: Dynamics and disorder-free glass transition

Wave-momentum shaping for moving objects in heterogeneous and dynamic media

Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks

On the Generalization of Stochastic Gradient Descent with Momentum