Electrical isolation of GaN by MeV ion irradiation

The evolution of sheet resistance of n-type GaN epilayers exposed to irradiation with MeV H, Li, C, and O ions is studied in situ. Results show that the threshold dose necessary for complete isolation linearly depends on the original free electron concentration and reciprocally depends on the number of atomic displacements produced by ion irradiation. Furthermore, such isolation is stable to rapid thermal annealing at temperatures up to 900 °C. In addition to providing a better understanding of the physical mechanisms responsible for electrical isolation, these results can be used for choosing implant conditions necessary for an effective electrical isolation of GaN-based devices.This work was partly supported by Conselho Nacional de Pesquisas (CNPq, Brazil) under Contract No. 200541/ 99-4

Incoherent excitation and switching of spin states in exciton-polariton condensates

We investigate, theoretically and numerically, the spin dynamics of a two-component exciton-polariton condensate created and sustained by non-resonant spin-polarized optical pumping of a semiconductor microcavity. Using the open-dissipative mean-field model, we show that the existence of well defined phase-locked steady states of the condensate may lead to efficient switching and control of spin (polarization) states with a non-resonant excitation. Spatially inhomogeneous pulsed excitations can cause symmetry breaking in the pseudo-spin structure of the condensate and lead to formation of non-trivial spin textures. Our model is universally applicable to two weakly coupled polariton condensates, and therefore can also describe the behaviour of condensate populations and phases in 'double-well' type potentials

Adversarial Convolutional Networks with Weak Domain-Transfer for Multi-sequence Cardiac MR Images Segmentation

Analysis and modeling of the ventricles and myocardium are important in the diagnostic and treatment of heart diseases. Manual delineation of those tissues in cardiac MR (CMR) scans is laborious and time-consuming. The ambiguity of the boundaries makes the segmentation task rather challenging. Furthermore, the annotations on some modalities such as Late Gadolinium Enhancement (LGE) MRI, are often not available. We propose an end-to-end segmentation framework based on convolutional neural network (CNN) and adversarial learning. A dilated residual U-shape network is used as a segmentor to generate the prediction mask; meanwhile, a CNN is utilized as a discriminator model to judge the segmentation quality. To leverage the available annotations across modalities per patient, a new loss function named weak domain-transfer loss is introduced to the pipeline. The proposed model is evaluated on the public dataset released by the challenge organizer in MICCAI 2019, which consists of 45 sets of multi-sequence CMR images. We demonstrate that the proposed adversarial pipeline outperforms baseline deep-learning methods.Comment: 9 pages, 4 figures, conferenc

Frustrated Heisenberg antiferromagnet on the honeycomb lattice: Spin gap and low-energy parameters

We use the coupled cluster method implemented to high orders of approximation to investigate the frustrated spin-$\frac{1}{2}$ $J_{1}$--$J_{2}$--$J_{3}$ antiferromagnet on the honeycomb lattice with isotropic Heisenberg interactions of strength $J_{1} > 0$ between nearest-neighbor pairs, $J_{2}>0$ between next-nearest-neighbor pairs, and $J_{3}>0$ between next-next-neareast-neighbor pairs of spins. In particular, we study both the ground-state (GS) and lowest-lying triplet excited-state properties in the case $J_{3}=J_{2} \equiv \kappa J_{1}$, in the window $0 \leq \kappa \leq 1$ of the frustration parameter, which includes the (tricritical) point of maximum classical frustration at $\kappa_{{\rm cl}} = \frac{1}{2}$. We present GS results for the spin stiffness, $\rho_{s}$, and the zero-field uniform magnetic susceptibility, $\chi$, which complement our earlier results for the GS energy per spin, $E/N$, and staggered magnetization, $M$, to yield a complete set of accurate low-energy parameters for the model. Our results all point towards a phase diagram containing two quasiclassical antiferromagnetic phases, one with N\'eel order for $\kappa < \kappa_{c_{1}}$, and the other with collinear striped order for $\kappa > \kappa_{c_{2}}$. The results for both $\chi$ and the spin gap $\Delta$ provide compelling evidence for a quantum paramagnetic phase that is gapped over a considerable portion of the intermediate region $\kappa_{c_{1}} < \kappa < \kappa_{c_{2}}$, especially close to the two quantum critical points at $\kappa_{c_{1}}$ and $\kappa_{c_{2}}$. Each of our fully independent sets of results for the low-energy parameters is consistent with the values $\kappa_{c_{1}} = 0.45 \pm 0.02$ and $\kappa_{c_{2}} = 0.60 \pm 0.02$, and with the transition at $\kappa_{c_{1}}$ being of continuous (and probably of the deconfined) type and that at $\kappa_{c_{2}}$ being of first-order type

Topology design and performance analysis of an integrated communication network

A research study on the topology design and performance analysis for the Space Station Information System (SSIS) network is conducted. It is begun with a survey of existing research efforts in network topology design. Then a new approach for topology design is presented. It uses an efficient algorithm to generate candidate network designs (consisting of subsets of the set of all network components) in increasing order of their total costs, and checks each design to see if it forms an acceptable network. This technique gives the true cost-optimal network, and is particularly useful when the network has many constraints and not too many components. The algorithm for generating subsets is described in detail, and various aspects of the overall design procedure are discussed. Two more efficient versions of this algorithm (applicable in specific situations) are also given. Next, two important aspects of network performance analysis: network reliability and message delays are discussed. A new model is introduced to study the reliability of a network with dependent failures. For message delays, a collection of formulas from existing research results is given to compute or estimate the delays of messages in a communication network without making the independence assumption. The design algorithm coded in PASCAL is included as an appendix

Origin of Native Driving Force in Protein Folding

We derive an expression with four adjustable parameters that reproduces well the 20x20 Miyazawa-Jernigan potential matrix extracted from known protein structures. The numerical values of the parameters can be approximately computed from the surface tension of water, water-screened dipole interactions between residues and water and among residues, and average exposures of residues in folded proteins.Comment: LaTeX file, Postscript file; 4 pages, 1 figure (mij.eps), 2 table