Indexing current-voltage characteristics using a hash function

TL;DR

This paper introduces a novel indexing method using locality-sensitive hashing to efficiently identify and differentiate similar current-voltage characteristics in nanoscale devices, improving device management and reliability.

Contribution

The paper applies locality-sensitive hashing to current-voltage data, enabling rapid device identification and differentiation based on subtle characteristic differences.

Findings

Hashing effectively distinguishes devices with similar characteristics.

Streamlines management of large device datasets.

Applicable to Coulomb blockade phenomena in nanoscale transistors.

Abstract

Differentiating between devices of the same size is essential for ensuring their reliability. However, identifying subtle differences can be challenging, particularly when the devices share similar characteristics, such as transistors on a wafer. To address this issue, we propose an indexing method for current-voltage characteristics that assigns proximity numbers to similar devices. Specifically, we demonstrate the application of the locality-sensitive hashing (LSH) algorithm to Coulomb blockade phenomena observed in PMOSFETs and nanowire transistors. In this approach, lengthy data on current characteristics are replaced with hashed IDs, facilitating identification of individual devices, and streamlining the management of a large number of devices.