Generation of Anisotropic Massless Dirac Fermions and Asymmetric Klein Tunneling in Few-Layer Black Phosphorus Superlattices

Artificial lattices have been employed in many two-dimensional systems, including those of electrons, atoms and photons, in a quest for massless Dirac particles with flexibility and controllability. Periodically patterned molecule assembly and electrostatic gating as well as moir\'e pattern induced by substrate, have produced electronic states with linear dispersions from isotropic two-dimensional electron gas (2DEG). Here we demonstrate that massless Dirac fermions with tunable anisotropic characteristics can, in general, be generated in highly anisotropic 2DEG under slowly varying external periodic potentials. For patterned few-layer black phosphorus superlattices, the new chiral quasiparticles exist exclusively in an isolated energy window and inherit the strong anisotropic properties of pristine black phosphorus. These states exhibit asymmetric Klein tunneling with the direction of incidence for wave packet with perfect transmission deviating from normal incidence by more than 50{\deg} under an appropriate barrier orientation

Quantum Circuit Design for Solving Linear Systems of Equations

Recently, it is shown that quantum computers can be used for obtaining certain information about the solution of a linear system Ax=b exponentially faster than what is possible with classical computation. Here we first review some key aspects of the algorithm from the standpoint of finding its efficient quantum circuit implementation using only elementary quantum operations, which is important for determining the potential usefulness of the algorithm in practical settings. Then we present a small-scale quantum circuit that solves a 2x2 linear system. The quantum circuit uses only 4 qubits, implying a tempting possibility for experimental realization. Furthermore, the circuit is numerically simulated and its performance under different circuit parameter settings is demonstrated.Comment: 7 pages, 3 figures. The errors are corrected. For the general case, discussions are added to account for recent results. The 4x4 example is replaced by a 2x2 one due to recent experimental efforts. The 2x2 example was devised at the time of writing v1 but not included in v1 for brevit

Impartial comparative analysis of measurement of leukocyte telomere length/DNA content by Southern blots and qPCR.

Telomere length/DNA content has been measured in epidemiological/clinical settings with the goal of testing a host of hypotheses related to the biology of human aging, but often the conclusions of these studies have been inconsistent. These inconsistencies may stem from various reasons, including the use of different telomere length measurement techniques. Here, we report the first impartial evaluation of measurements of leukocyte telomere length by Southern blot of the terminal restriction fragments and quantitative PCR (qPCR) of telomere DNA content, expressed as the ratio of telomeric product (T)/single copy gene (S) product. Blind measurements on the same samples from 50 donors were performed in two independent laboratories on two different occasions. Both the qPCR and Southern blots displayed highly reproducible results as shown by r values > 0.9 for the correlations between results obtained by either method on two occasions. The inter-assay CV measurement for the qPCR was 6.45%, while that of the Southern blots was 1.74%. The relation between the results generated by Southern blots versus those generated by qPCR deviated from linearity. We discuss the ramifications of these findings with regard to measurements of telomere length/DNA content in epidemiological/clinical circumstances

Chromatic assimilation: spread light or neural mechanism?

AbstractChromatic assimilation is the shift in color appearance of a test field toward the appearance of nearby light. Possible explanations of chromatic assimilation include wavelength independent spread light, wavelength-dependent chromatic aberration and neural summation. This study evaluated these explanations by measuring chromatic assimilation from a concentric-ring pattern into an equal-energy-white background, as a function of the inducing rings’ width, separation, chromaticity and luminance. The measurements showed, in the s direction, that assimilation was observed with different inducing-ring widths and separations when the inducing luminance was lower or higher than the test luminance. In general, the thinner the inducing rings and the smaller their separation, the stronger the assimilation in s. In the l direction, either assimilation or contrast was observed, depending on the ring width, separation and luminance. Overall, the measured assimilation could not be accounted for by the joint contributions from wavelength-independent spread light and wavelength-dependent chromatic aberration. Spatial averaging of neural signals explained the assimilation in s reasonably well, but there were clear deviations from neural spatial averaging for the l direction

Learning-based Single-step Quantitative Susceptibility Mapping Reconstruction Without Brain Extraction

Quantitative susceptibility mapping (QSM) estimates the underlying tissue magnetic susceptibility from MRI gradient-echo phase signal and typically requires several processing steps. These steps involve phase unwrapping, brain volume extraction, background phase removal and solving an ill-posed inverse problem. The resulting susceptibility map is known to suffer from inaccuracy near the edges of the brain tissues, in part due to imperfect brain extraction, edge erosion of the brain tissue and the lack of phase measurement outside the brain. This inaccuracy has thus hindered the application of QSM for measuring the susceptibility of tissues near the brain edges, e.g., quantifying cortical layers and generating superficial venography. To address these challenges, we propose a learning-based QSM reconstruction method that directly estimates the magnetic susceptibility from total phase images without the need for brain extraction and background phase removal, referred to as autoQSM. The neural network has a modified U-net structure and is trained using QSM maps computed by a two-step QSM method. 209 healthy subjects with ages ranging from 11 to 82 years were employed for patch-wise network training. The network was validated on data dissimilar to the training data, e.g. in vivo mouse brain data and brains with lesions, which suggests that the network has generalized and learned the underlying mathematical relationship between magnetic field perturbation and magnetic susceptibility. AutoQSM was able to recover magnetic susceptibility of anatomical structures near the edges of the brain including the veins covering the cortical surface, spinal cord and nerve tracts near the mouse brain boundaries. The advantages of high-quality maps, no need for brain volume extraction and high reconstruction speed demonstrate its potential for future applications.Comment: 26 page