Broadly tunable CW green-to-red laser source based on frequency doubling of a quantum-dot external cavity diode laser in a PPKTP waveguide

Here we present a compact tunable all-room-temperature frequency-doubling scheme, using a periodically poled potassium titanyl phosphate (PPKTP) waveguide and a QD-ECDL. A broad wavelength tunability of the second harmonic generated light (SHG) in the spectral region between 567.7 and 629.1 nm was achieved, with maximum conversion efficiencies in range of 0.34%-7.9%. The maximum output power for the SHG light was 4.11 mW at 591.5 nm, achieved for 52 mW of launched pump power at 1183 nm, resulting in a conversion efficiency of 7.9%.

Efficient yellow-green light generation at 561 nm by frequency-doubling of a QD-FBG laser diode in a PPLN waveguide

A compact high-power yellow-green continuous wave (CW) laser source based on second-harmonic generation (SHG) in a 5% MgO doped periodically poled congruent lithium niobate (PPLN) waveguide crystal pumped by a quantum-dot fiber Bragg grating (QD-FBG) laser diode is demonstrated. A frequency-doubled power of 90.11 mW at the wavelength of 560.68 nm with a conversion efficiency of 52.4% is reported. To the best of our knowledge, this represents the highest output power and conversion efficiency achieved to date in this spectral region from a diode-pumped PPLN waveguide crystal, which could prove extremely valuable for the deployment of such a source in a wide range of biomedical applications.

Message passing for distributed optimisation of power allocation with renewable resources

The increase in renewable energy generators introduced into the electricity grid is putting pressure on its stability and management as predictions of renewable energy sources cannot be accurate or fully controlled. This, with the additional pressure of fluctuations in demand, presents a problem more complex than the current methods of controlling electricity distribution were designed for. A global approximate and distributed optimisation method for power allocation that accommodates uncertainties and volatility is suggested and analysed. It is based on a probabilistic method known as message passing [1], which has deep links to statistical physics methodology. This principled method of optimisation is based on local calculations and inherently accommodates uncertainties; it is of modest computational complexity and provides good approximate solutions.We consider uncertainty and fluctuations drawn from a Gaussian distribution and incorporate them into the message-passing algorithm. We see the effect that increasing uncertainty has on the transmission cost and how the placement of volatile nodes within a grid, such as renewable generators or consumers, effects it.