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For short-wavelength infrared (SWIR) avalanche photodiodes, a separate absorption, charge, and multiplication design is widely used. AlInAsSb on an InP substrate is a potential multiplication layer with a lattice match to absorber candidates across the SWIR. Our new measurements demonstrate that AlInAsSb on InP is a promising multiplier candidate with a relatively low dark current density of 10−4 A/cm2 at a gain of 30; a high gain, measured up to 245 in this study; and a large differentiation of electron and hole ionization leading to a low excess noise, measured to be 2.5 at a gain of 30. These characteristics are all improvements over commercially available SWIR detectors incorporating InAlAs or InP as the multiplier. We measured and analyzed gain for multiple wavelengths to extract the ionization coefficients as a function of an electric field over the range 0.33–0.6 MV/cm.

 

This article presents a new method to solve a dynamic sensor fusion problem. We consider a large number of remote sensors which measure a common Gauss–Markov process. Each sensor encodes and transmits its measurement to a data fusion center through a resource restricted communication network. The communication cost incurred by a given sensor is quantified as the expected bitrate from the sensor to the fusion center. We propose an approach that attempts to minimize a weighted sum of these communication costs subject to a constraint on the state estimation error at the fusion center. We formulate the problem as a difference-of-convex program and apply the convex-concave procedure (CCP) to obtain a heuristic solution. We consider a 1D heat transfer model and a model for 2D target tracking by a drone swarm for numerical studies. Through these simulations, we observe that our proposed approach has a tendency to assign zero data rate to unnecessary sensors indicating that our approach is sparsity-promoting, and an effective sensor selection heuristic. 

We consider a dynamic sensor fusion problem where a large number of remote sensors observe a common Gauss-Markov process and the observations are transmitted to a fusion center over a resource constrained communication network. The design objective is to allocate an appropriate data rate to each sensor in such a way that the total data traffic to the fusion center is minimized, subject to a constraint on the fusion center's state estimation error covariance. We show that the problem can be formulated as a difference-of-convex program, to which we apply the convex-concave procedure (CCP) and the alternating direction method of multiplier (ADMM). Through a numerical study on a truss bridge sensing system, we observe that our algorithm tends to allocate zero data rate to unneeded sensors, implying that the proposed method is an effective heuristic for sensor selection. 

Functional MRI contrast has generally been associated with changes in transverse relaxivity caused by blood oxygen concentration, the so‐called blood oxygen level dependent contrast. However, this interpretation of fMRI contrast has been called into question by several recent experiments at high spatial resolution. Experiments were conducted to examine contrast dependencies that cannot be explained only by differences in relaxivity in a single‐spin population.

Measurements of functional signal and contrast were obtained in human early visual cortex during a high‐contrast visual stimulation over a large range of TEs and for several flip angles. Small voxels (1.5 mm) were used to restrict the measurements to cortical gray matter in early visual areas identified using retinotopic mapping procedures.

Measurements were consistent with models that include 2 spin populations. The dominant population has a relatively short transverse lifetime that is strongly modulated by activation. However, functional contrast is also affected by volume changes between this short‐lived population and the longer‐lived population.

Some of the previously observed “nonclassical” behaviors of functional contrast can be explained by these interacting dual‐spin populations.

 

Protons consist of three valence quarks, two up-quarks and one down-quark, held together by gluons and a sea of quark-antiquark pairs. Collectively, quarks and gluons are referred to as partons. In a proton-proton collision, typically only one parton of each proton undergoes a hard scattering – referred to as single-parton scattering – leaving the remainder of each proton only slightly disturbed. Here, we report the study of double- and triple-parton scatterings through the simultaneous production of three J/ψmesons, which consist of a charm quark-antiquark pair, in proton-proton collisions recorded with the CMS experiment at the Large Hadron Collider. We observed this process – reconstructed through the decays of J/ψmesons into pairs of oppositely charged muons – with a statistical significance above five standard deviations. We measured the inclusive fiducial cross-section to be$$27{2}_{-104}^{+141}\,{{{\rm{(stat)}}}}\,\pm 17\,{{{\rm{(syst)}}}}\,{{{\rm{fb}}}}\,$$$272_{-104}^{+141}\mathrm{(stat)}\pm 17\mathrm{(syst)}\mathrm{fb}$, and compared it to theoretical expectations for triple-J/ψmeson production in single-, double- and triple-parton scattering scenarios. Assuming factorization of multiple hard-scattering probabilities in terms of single-parton scattering cross-sections, double- and triple-parton scattering are the dominant contributions for the measured process.