Very high modulation efficiency two-sections tapered laser diode at 1060nm for free space optical communications

High-power (more than 500 mW) and high-speed (more than 1 Gbps) tapered lasers at 1060 nm are required in free-space optical communications and (at lower frequencies of around 100 MHz) display applications for frequency doubling to the green. On a 3 mm long tapered laser, we have obtained an open eye diagram at 1 Gbps, together with a high extinction ratio of 11 dB, an optical modulation amplitude of 530 mW, and a high modulation efficiency of 13 W/A. On a 4 mm-long tapered laser, we have obtained an open eye diagram at 700 Mbps, together with a high extinction ratio of 19 dB, a high optical modulation amplitude of 1.6 W, and a very high modulation efficiency of 19 W/A. On a 6 mm-long tapered laser, we have obtained a very high power of 5W CW and a very high static modulation efficiency of 59.8 W/A. © 2011 SPIE.

Effects of high-order laser distortion products in radio over free-space optical links

RoFSO links are found to be susceptible to high-order laser distortion making conventional SFDR ineffective as a performance indicator. For the first time, peak input power is demonstrated as a service-independent bound on dynamic range. © 2011 OSA.

Near optimal combination of sensory and motor uncertainty in time during a naturalistic perception-action task.

Most behavioral tasks have time constraints for successful completion, such as catching a ball in flight. Many of these tasks require trading off the time allocated to perception and action, especially when only one of the two is possible at any time. In general, the longer we perceive, the smaller the uncertainty in perceptual estimates. However, a longer perception phase leaves less time for action, which results in less precise movements. Here we examine subjects catching a virtual ball. Critically, as soon as subjects began to move, the ball became invisible. We study how subjects trade-off sensory and movement uncertainty by deciding when to initiate their actions. We formulate this task in a probabilistic framework and show that subjects' decisions when to start moving are statistically near optimal given their individual sensory and motor uncertainties. Moreover, we accurately predict individual subject's task performance. Thus we show that subjects in a natural task are quantitatively aware of how sensory and motor variability depend on time and act so as to minimize overall task variability.