Bias-dependent recovery time of all-optical resonant nonlinearity in InGaAsP/InGaAsP MQW waveguide

We have investigated a resonant refractive nonlinearity in a semiconductor waveguide by measuring intensity dependent phase shifts and bias-dependent recovery times. The measurements were performed on an optimized 750-μm-long AR coated buried heterostructure MQW p-i-n waveguide with a bandedge at 1.48 μm. Figure 1 shows the experimental arrangement. The mode-locked color center laser was tuned to 50 meV beyond the bandedge and 8 ps pulses with peak incident power up to 57 W were coupled into the waveguide. Some residual bandtail absorption remains at this wavelength and this is sufficient to cause carriers to be photogenerated and these give rise to a refractive nonlinearity, predominantly by plasma and bandfilling effects. A Fabry-Perot interferometer is used to measure the spectrum of the light which exits the waveguide. The nonlinearity within the guide causes self phase modulation (SPM) of the light and a study of the spectrum allows information to be recovered on the magnitude and recovery time of the nonlinear phase shift with a reasonable degree of accuracy. SPM spectra were recorded for a variety of pulse energies coupled into he unbiased waveguide. Figure 2 shows the resultant phase shift measured from the SPM spectra as a function of pulse energy. The relationship is a linear one, indicating that no saturation of the nonlinearity occurs for coupled pulse energies up to 230 pJ. A π phase shift, the minimum necessary for an all-optical switch, is obtained for a coupled pulse energy of 57 pJ while the maximum phase shift, 4 π, was measured for 230 pJ. The SPM spectra were highly asymmetric with pulse energy shifted to higher frequencies. Such spectra are characteristic of a slow, negative nonlinearity. This relatively slow speed is expected for the unbiased guide as the recovery time will be of the order of the recombination time of the photogenerated electrons, about 1 ns for InGaAsP material. In order to reduce the recovery time of the nonlinearity, it is necessary to remove the photogenerated carriers from the waveguide by a process other than recombination. One such technique is to apply a reverse bias to the waveguide in order to sweep the carriers out. Figure 3 shows the effect on the recovery time of the nonlinearity of applying reverse bias to the waveguide for 230 pJ coupled power. The recovery time was reduced from one much longer than the length of the pulse, estimated to be about 1 ns, at zero bias to 18 ± 3 ps for a bias voltage greater than -4 V. This compares with a value of 24 ps obtained in a bulk waveguide.

Perceptual learning, roving and the unsupervised bias

Perceptual learning improves perception through training. Perceptual learning improves with most stimulus types but fails when . certain stimulus types are mixed during training (roving). This result is surprising because classical supervised and unsupervised neural network models can cope easily with roving conditions. What makes humans so inferior compared to these models? As experimental and conceptual work has shown, human perceptual learning is neither supervised nor unsupervised but reward-based learning. Reward-based learning suffers from the so-called unsupervised bias, i.e., to prevent synaptic " drift" , the . average reward has to be exactly estimated. However, this is impossible when two or more stimulus types with different rewards are presented during training (and the reward is estimated by a running average). For this reason, we propose no learning occurs in roving conditions. However, roving hinders perceptual learning only for combinations of similar stimulus types but not for dissimilar ones. In this latter case, we propose that a critic can estimate the reward for each stimulus type separately. One implication of our analysis is that the critic cannot be located in the visual system. © 2011 Elsevier Ltd.

Bias-free identification of a linear model-predictive steering controller from measured driver steering behavior

Recent developments in modeling driver steering control with preview are reviewed. While some validation with experimental data has been presented, the rigorous application of formal system identification methods has not yet been attempted. This paper describes a steering controller based on linear model-predictive control. An indirect identification method that minimizes steering angle prediction error is developed. Special attention is given to filtering the prediction error so as to avoid identification bias that arises from the closed-loop operation of the driver-vehicle system. The identification procedure is applied to data collected from 14 test drivers performing double lane change maneuvers in an instrumented vehicle. It is found that the identification procedure successfully finds parameter values for the model that give small prediction errors. The procedure is also able to distinguish between the different steering strategies adopted by the test drivers. © 2006 IEEE.

Light-bias induced instability and persistent photoconductivity in In-Zn-O/Ga-In-Zn-O thin film transistors

Stress/recovery measurements demonstrate that even high-performance passivated In-Zn-O/ Ga-In-Zn-O thin film transistors with excellent in-dark stability suffer from light-bias induced threshold voltage shift (ΔV T) and defect density changes. Visible light stress leads to ionisation of oxygen vacancy sites, causing persistent photoconductivity. This makes the material act as though it was n-doped, always causing a negative threshold voltage shift under strong illumination, regardless of the magnitude and polarity of the gate bias.

P-16: Light-bias induced instability and persistent photoconductivity in in-zn-o/ga-in-zn-o thin film transistors

Stress/recovery measurements demonstrate that even highperformance passivated In-Zn-O/ Ga-In-Zn-O thin film transistors with excellent in-dark stability suffer from light-bias induced threshold voltage shift (ΔV T) and defect density changes. Visible light stress leads to ionisation of oxygen vacancy sites, causing persistent photoconductivity. This makes the material act as though it was n-doped, always causing a negative threshold voltage shift under strong illumination, regardless of the magnitude and polarity of the gate bias. © 2011 SID.

Insula and striatum mediate the default bias.

Humans are creatures of routine and habit. When faced with situations in which a default option is available, people show a consistent tendency to stick with the default. Why this occurs is unclear. To elucidate its neural basis, we used a novel gambling task in conjunction with functional magnetic resonance imaging. Behavioral results revealed that participants were more likely to choose the default card and felt enhanced emotional responses to outcomes after making the decision to switch. We show that increased tendency to switch away from the default during the decision phase was associated with decreased activity in the anterior insula; activation in this same area in reaction to "switching away from the default and losing" was positively related with experienced frustration. In contrast, decisions to choose the default engaged the ventral striatum, the same reward area as seen in winning. Our findings highlight aversive processes in the insula as underlying the default bias and suggest that choosing the default may be rewarding in itself.

Beyond dataset bias: Multi-task unaligned shared knowledge transfer

Many visual datasets are traditionally used to analyze the performance of different learning techniques. The evaluation is usually done within each dataset, therefore it is questionable if such results are a reliable indicator of true generalization ability. We propose here an algorithm to exploit the existing data resources when learning on a new multiclass problem. Our main idea is to identify an image representation that decomposes orthogonally into two subspaces: a part specific to each dataset, and a part generic to, and therefore shared between, all the considered source sets. This allows us to use the generic representation as un-biased reference knowledge for a novel classification task. By casting the method in the multi-view setting, we also make it possible to use different features for different databases. We call the algorithm MUST, Multitask Unaligned Shared knowledge Transfer. Through extensive experiments on five public datasets, we show that MUST consistently improves the cross-datasets generalization performance. © 2013 Springer-Verlag.

A genetically mediated bias in decision making driven by failure of amygdala control.

Genetic variation at the serotonin transporter-linked polymorphic region (5-HTTLPR) is associated with altered amygdala reactivity and lack of prefrontal regulatory control. Similar regions mediate decision-making biases driven by contextual cues and ambiguity, for example the "framing effect." We hypothesized that individuals hemozygous for the short (s) allele at the 5-HTTLPR would be more susceptible to framing. Participants, selected as homozygous for either the long (la) or s allele, performed a decision-making task where they made choices between receiving an amount of money for certain and taking a gamble. A strong bias was evident toward choosing the certain option when the option was phrased in terms of gains and toward gambling when the decision was phrased in terms of losses (the frame effect). Critically, this bias was significantly greater in the ss group compared with the lala group. In simultaneously acquired functional magnetic resonance imaging data, the ss group showed greater amygdala during choices made in accord, compared with those made counter to the frame, an effect not seen in the lala group. These differences were also mirrored by differences in anterior cingulate-amygdala coupling between the genotype groups during decision making. Specifically, lala participants showed increased coupling during choices made counter to, relative to those made in accord with, the frame, with no such effect evident in ss participants. These data suggest that genetically mediated differences in prefrontal-amygdala interactions underpin interindividual differences in economic decision making.

Low-bias terahertz amplitude modulator based on split-ring resonators and graphene.

Split-ring resonators represent the ideal route to achieve optical control of the incident light at THz frequencies. These subwavelength metamaterial elements exhibit broad resonances that can be easily tuned lithographically. We have realized a design based on the interplay between the resonances of metallic split rings and the electronic properties of monolayer graphene integrated in a single device. By varying the major carrier concentration of graphene, an active modulation of the optical intensity was achieved in the frequency range between 2.2 and 3.1 THz, achieving a maximum modulation depth of 18%, with a bias as low as 0.5 V.