The Case for Quantum Software.

Leonie Mueck

Iaakov Exman

It is widely understood that quantum computing — quantum gates upon qubits — is the general case, encompassing computing by classical means, viz. Boolean logic upon classical bits. It also seems reasonable that Quantum Software should encompass Classical Software. However, to accept such a statement regarding software, the feeling that it seems reasonable is not enough. One needs clear-cut definitions and formal conclusions. This is exactly the purpose of this paper. Previously, we have represented Classical Software by the Laplacian Matrix. More recently, we have shown that Quantum Software is faithfully represented by Density Matrices. It turns out that a Laplacian Matrix normalized by the Laplacian Trace easily obtains a Density Matrix. This opens the horizons for Quantum Software operations — such as unitary and reversible evolution — not naturally available with the classical Laplacian. This paper provides the necessary definitions and conclusions, illustrating the more general Quantum operations with a relevant case study, playing the double role of both classical and quantum software.

Cecilia Carbonelli, Michael Felderer, Matthias Jung +7 more

Abstract Quantum software is becoming a key enabler for applying quantum computing to industrial use cases. This poses challenges to quantum software engineering in providing efficient and effective means to develop such software. Eventually, this must be reliably achieved in time, on budget, and in quality, using sound and well-principled engineering approaches. Given that quantum computers are based on fundamentally different principles than classical machines, this raises the question if, how, and to what extent established techniques for systematically engineering software need to be adapted. In this chapter, we analyze three paradigmatic application scenarios for quantum software engineering from an industrial perspective. The respective use cases center around (1) optimization and quantum cloud services, (2) quantum simulation, and (3) embedded quantum computing. Our aim is to provide a concise overview of the current and future applications of quantum computing in diverse industrial settings. We derive presumed challenges for quantum software engineering and thus provide research directions for this emerging field.

Ricardo Pérez‐Castillo, Mario G. Piattini

John P. Preskill

Deepak Mishra, Kavitha Selvaraj

This paper explores the potential of integrating quantum computing into the software development lifecycle (SDLC) to enhance efficiency, speed, and problem-solving capabilities. As traditional SDLC models face increasing challenges in managing large-scale systems and complex problem-solving, quantum computing presents an innovative approach to optimize key aspects of software engineering. We discuss the basics of quantum computing and its relevant algorithms, followed by an examination of how quantum technologies can be integrated with existing SDLC models. The paper also highlights case studies and real-world use cases demonstrating the benefits of quantum-enhanced development processes. Despite the promising advantages, challenges such as quantum hardware limitations and the learning curve for developers remain. This paper concludes by proposing future directions for quantum computing in software development and its potential to revolutionize the field.