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Mohsen Asad

Publications and source records attributed to Mohsen Asad.

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Role of polarity in the growth of cubic GaN within silicon inverted pyramids

A lack of spontaneous internal polarization makes cubic GaN (c-GaN) a well-suited material for emerging micro-LED-based short-range communication, where c-GaN promises increased speed over conventional hexagonal GaN (h-GaN). Although c-GaN is metastable, there are well-established methods for growing it in Si V- or U-grooves; the logical step is to truncate these grooves to wedges or inverted pyramids for small devices. There are limited reports of GaN grown in inverted pyramid templates, and the results are contradictory. To study this process, we perform selective area growth of GaN using organometallic vapor phase epitaxy (OMVPE) on Si inverted pyramidal templates and analyze our samples by cross-sectional TEM. We find that polarity is critical to understanding the growth of c-GaN in this four-fold geometry, in contrast to the growth in long grooves. This effect fits within the broader set of challenges of polar-on-nonpolar heteroepitaxy; the c-GaN inside the four-fold symmetric template has its symmetry reduced by polarity to be two-fold. In typical growth conditions -- where the underlying h-GaN polarity is uniform -- we find this implies that two h-GaN to c-GaN grain boundaries will have a polarity inversion. We observe two different structures at these inverting boundaries, including a previously unreported inversion domain boundary along the basal plane of the undoped h-GaN. These findings show that for small devices -- such as micro-LEDs -- the polarity-inverting interfaces must be prevented, for example by suppressing the growth of h-GaN on two facets of the template or by locally controlling the h-GaN polarity.

cond-mat.mtrl-sci

Beyond-classical computation in quantum simulation

Quantum computers hold the promise of solving certain problems that lie beyond the reach of conventional computers. However, establishing this capability, especially for impactful and meaningful problems, remains a central challenge. Here, we show that superconducting quantum annealing processors can rapidly generate samples in close agreement with solutions of the Schrödinger equation. We demonstrate area-law scaling of entanglement in the model quench dynamics of two-, three-, and infinite-dimensional spin glasses, supporting the observed stretched-exponential scaling of effort for matrix-product-state approaches. We show that several leading approximate methods based on tensor networks and neural networks cannot achieve the same accuracy as the quantum annealer within a reasonable time frame. Thus, quantum annealers can answer questions of practical importance that may remain out of reach for classical computation.

quant-ph