Design and performance of GaSb-based quantum cascade detectors.

InAs/AlSb quantum cascade detectors (QCDs) grown strain-balanced on GaSb substrates are presented. This material system offers intrinsic performance-improving properties, like a low effective electron mass of the well material of 0.026 m 0, enhancing the optical transition strength, and a high conduction band offset of 2.28 eV, reducing the noise and allowing for high optical transition energies. InAs and AlSb strain balance each other on GaSb with an InAs:AlSb ratio of 0.96:1. To regain the freedom of a lattice-matched material system regarding the optimization of a QCD design, submonolayer InSb layers are introduced. With strain engineering, four different active regions between 3.65 and 5.5 µm were designed with InAs:AlSb thickness ratios of up to 2.8:1, and subsequently grown and characterized. This includes an optimized QCD design at 4.3 µm, with a room-temperature peak responsivity of 26.12 mA/W and a detectivity of 1.41 × 108 Jones. Additionally, all QCD designs exhibit higher-energy interband signals in the mid- to near-infrared, stemming from the InAs/AlSb type-II alignment and the narrow InAs band gap.

Anomalous Temperature Effect in Weakly Coupled Superlattices: Carrier Transport in a THz Quantum Cascade Laser.

We present an investigation into the vertical transport through 13 different superlattice structures, where the well and barrier widths, doping concentration, dopant position, and contact layers were varied. Although superlattices have been extensively studied since 1970, there is a lack of publications on transport through superlattices similarly low doped as THz quantum cascade lasers (QCLs), for which the doping is in the 3-5×10^{10} cm^{-2} range. The superlattices presented are doped in the same range as THz QCLs, with contact layers and fabrication comparable to high-temperature THz QCLs. The temperature-dependent current-voltage characteristics were measured starting from 5 K and an anomalous temperature effect was observed at the first plateau. The measured current through the superlattice first decreases before increasing again with increasing temperature, resulting in the lowest current occurring at 75-110 K. This behavior is also observed in some THz QCLs. The effect disappears for thinner barriers, higher quantum well doping, or modified contact layers, indicating a strong dependency on band bending, due to the large difference in the doping of the contact layers and the superlattice, which is confirmed with multiscattering Büttiker simulations.

Ultrabroadband Heterogeneous THz Quantum Cascade Laser.

Broadband emission in the terahertz spectral region is a prerequisite for applications such as spectroscopy or white light sources. Appropriate signal powers and a compact design are advantageous for this use. A technology which meets these requirements are terahertz quantum cascade lasers. These electrically pumped, on-chip semiconductor lasers provide high output powers and the freedom of tailoring their emission wavelength by bandstructure engineering. By combining multiple active region designs emitting at different wavelengths in a single structure, one can obtain broadband emission from a single device. Here, we present a heterogeneous terahertz quantum cascade laser consisting of five individual active regions based on a three-well, LO-phonon depopulation design. The devices lase in pulsed and continuous-wave operation and emit in a spectral range from 1.9 to 4.5 THz, covering a bandwidth of 1.37 octaves. The use of the three-well design, which was optimized for high temperature operation, leads to a maximum operating temperature in the pulsed operation of 143 K.

A photosensor employing data-driven binning for ultrafast image recognition.

Pixel binning is a technique, widely used in optical image acquisition and spectroscopy, in which adjacent detector elements of an image sensor are combined into larger pixels. This reduces the amount of data to be processed as well as the impact of noise, but comes at the cost of a loss of information. Here, we push the concept of binning to its limit by combining a large fraction of the sensor elements into a single "superpixel" that extends over the whole face of the chip. For a given pattern recognition task, its optimal shape is determined from training data using a machine learning algorithm. We demonstrate the classification of optically projected images from the MNIST dataset on a nanosecond timescale, with enhanced dynamic range and without loss of classification accuracy. Our concept is not limited to imaging alone but can also be applied in optical spectroscopy or other sensing applications.