Quick Navigation

Topics

Quantum Machine Learning

A brief overview of programmed instructions for quantum software education

arXiv
Authors: Richard A. Wolf, Sho Araiba

Year

2023

Paper ID

52545

Status

Preprint

Abstract Read

~2 min

Abstract Words

120

Citations

N/A

Abstract

In this paper we provide an overview of the programmed instructions approach for the purpose of quantum software education. The article presents the programmed instructions method and recent successes in STEM fields before describing its operating mode. Elements tackled include the core components of programmed instructions, its behavioural roots and early use as well as adaptation to complex STEM material. In addition, we offer recommendations for its use in the specific context of quantum software education and provide one example of PI-based instruction for the notion of entanglement. The aim of this work is to provide high-level guidelines for incorporating programmed instructions in quantum education with the goal of disseminating quantum skills and notions more efficiently to a wider audience.

Why This Paper Matters

  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
  • It adds a 2023 reference point for readers tracking recent quantum research.
  • In this paper we provide an overview of the programmed instructions approach for the purpose of quantum software education.

Paper Tools

Become a member to use research tools

Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.

Show Paper arXiv Publisher Share Cite This Paper Copy URL Compare Copy DOI Add to Reading List Category Correction Request

References & Citation Signals

Local Citation Graph (Related-Paper Links)

Current Paper #52545 #69596 Comprehensive pKa Data Augmenta... #69584 OQMD: Single-Qubit Rotation Con... #69549 REGRID-QAOA: A Resource-Efficie... #69539 Learning ground state observabl...

External citation index: OpenAlex citation signal

Community Reactions

Quick sentiment from readers on this paper.

Score: 0
Likes: 0 Dislikes: 0

Sign in to react to this paper.

Discussion & Reviews (Moderated)

Average Rating: 0.0 / 5 (0 ratings)

No written reviews yet.