Low-loss phase-change material based programmable mode converter for photonic computing
Xueyang Shen, Ruixuan Chu, Ding Xu, Yuan Gao, Wen Zhou, Wei Zhang

TL;DR
This paper introduces a low-loss phase-change material, Sb2Se3, for programmable photonic mode converters, enabling multilevel optical encoding with reduced loss, suitable for scalable neuromorphic photonic computing.
Contribution
The study demonstrates the design and simulation of a low-loss, multilevel programmable mode converter using Sb2Se3, advancing scalable photonic computing technologies.
Findings
Achieved 5-bit (32 levels) programming precision in simulations.
Designed a scalable photonic tensor core potentially supporting 128x128 arrays.
Provided a detailed comparison showing advantages over conventional PCM materials.
Abstract
Phase-change materials (PCMs)-based integrated photonic memory offers a viable pathway for the development of neuromorphic computing chip. The sizable optical contrast in the telecom band between amorphous and crystalline phases of PCM, in particular, Ge2Sb2Te5 (GST), is used for multilevel programming. However, the high extinction coefficient k of crystalline GST leads to high optical loss, posing a serious challenge for scaling up the device array for practical use. In this work, we focus on the atomic understanding and application of the so-called low-loss PCM, Sb2Se3, through multiscale simulations. First, we elucidate the bonding origin of the wavelength dependent optical properties of amorphous and crystalline Sb2Se3 via ab initio calculations. Given the suppressed k in the telecom band, we design a programable mode converter (PMC) waveguide device that utilizes only the contrast…
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Taxonomy
TopicsPhase-change materials and chalcogenides · Neural Networks and Reservoir Computing · Advanced Memory and Neural Computing
