Experimental characterization of the transition to coherence collapse in a semiconductor laser with optical feedback

Abstract

Semiconductor lasers with time-delayed optical feedback display a wide range of dynamical regimes, which have found various practical applications. They also provide excellent testbeds for data analysis tools for characterizing complex signals. Recently, several of us have analyzed experimental intensity time-traces and quantitatively identified the onset of different dynamical regimes, as the laser current increases. Specifically, we identified the onset of low-frequency fluctuations (LFFs), where the laser intensity displays abrupt dropouts, and the onset of coherence collapse (CC), where the intensity fluctuations are highly irregular. Here we map these regimes when both, the laser current and the feedback strength vary. We show that the shape of the distribution of intensity fluctuations (characterized by the standard deviation, the skewness, and the kurtosis) allows to distinguish among noise, LFFs and CC, and to quantitatively determine (in spite of the gradual nature of the transitions) the boundaries of the three regimes. Ordinal analysis of the inter-dropout time intervals consistently identifies the three regimes occurring in the same parameter regions as the analysis of the intensity distribution. Simulations of the well-known time-delayed Lang-Kobayashi model are in good qualitative agreement with the observations.

Comparing the dynamics of periodically forced lasers and neurons

“…For D=3, we have 3!=6 possible OPs: 012 (ΔT 3 >ΔT 2 >ΔT 1 ), 021 (ΔT 2 >ΔT 3 >ΔT 1 ), 102 (ΔT 3 >ΔT 1 >ΔT 2 ), 120 (ΔT 2 >ΔT 1 > ΔT 3 ), 201 (ΔT 1 >ΔT 3 >ΔT 2 ) and 210 (ΔT 1 >ΔT 2 >ΔT 3 ). As in previous works [38,55,56,62,63] we use D=3, which allows identifying temporal relations among four consecutive spikes. As the number of possible patterns increases as D!, a larger D significantly increases the data requirements, because very long sequences of spikes are needed for a robust estimation of the probabilities of the D!…”

“…We also compare the laser spikes with the neuronal spikes using OP analysis [38,40]. This is a popular technique to investigate complex signals, which has been extensively used to characterize the dynamical regimes of semiconductor lasers with optical feedback [41,[48][49][50][51][52][53][54][55][56][57]. A main advantage of this methodology is that, in its simplest implementation, it has only one parameter that is the size, D of the pattern, which determines the length of the temporal correlations studied: the D!…”

Experimental study of modulation waveforms for entraining the spikes emitted by a semiconductor laser with optical feedback

“…The dc value of the pump current was varied from 25 mA to 29 mA in steps of 0.5 mA. As discussed in [40,41], for the lowest and for the highest pump current values the spikes are not well defined as the intensity dynamics is noisy and irregular. In contrast, well-defined spikes occur for pump currents in the range 25.5-27.5 mA, where the natural spike frequency (without modulation) varies in the range 3-30 MHz (see in [42] a video showing how the intensity dynamics gradually changes as the pump current increases).…”

“…We analyze the time series of the laser intensity (see Fig. 1) and detect the spike times with the same method as in [40,41]. First, the intensity time series, which has mean value equal to zero due to the amplifier, is normalized to unit variance.…”

Semiconductor Laser in Distributed Optical Feedback Regime

“…Along with examining the effects of optical feedback on a laser device, intense research work has been carried out to control the deleterious effects induced by feedback, such as to stabilize the laser diode, and to make positive use of feedback in sophisticate applications such as chaotic communications [5]. The recent works considers only a single-concentrated external reflector which provides optical feedback [6][7][8].…”