Skip to content
Review Open access

From qubits to general-purpose computing: quantum advantage and its limits

Jul 2026 · Open Access Research Journal of Engineering and Technology · Vol 11, pp. 023-033 · 0 citations

TL;DR

It is concluded that quantum computing is best positioned, in the near term, as a specialized co-processor rather than a general-purpose replacement for classical computing.

Abstract

Quantum computing has been championed as a ground-breaking technology due to its significant computational advantage over classical computing systems. At present, fault-tolerant, large-scale universal quantum computing remains elusive, and these issues remain central challenges in engineering, physics, and computer science. In theory, quantum advantage offers the potential to make many currently intractable computational problems practically solvable, with profound implications across science, industry, and computing. This paper examines the contemporary case for general-purpose quantum computing and the prevailing challenges that presently prevent its widespread adoption. It surveys the theoretical foundations of computation and quantum mechanics that underpin quantum computers, describes the quantum computational model and a working implementation on IBM's Qiskit platform, and evaluates the persistent barriers of noise, decoherence, and scalability that constrain quantum systems today. We conclude that quantum computing is best positioned, in the near term, as a specialized co-processor rather than a general-purpose replacement for classical computing.

Read PDF

Similar papers

Preprint Sep 2026

Benchmarking the computational power of quantum computers

This work demonstrates direct, cross-platform measurement of quantum computational capability using a new benchmark that quantifies the size of the largest computationally relevant quantum circuits that a machine can execute successfully and the speed at which it can execute them, and project the growth of capability a...

Timothy Proctor, Oliver Hart, Oliver Widzowski Maupin et al. · 1 citation
Review Sep 2026

From Bits to Qubits: The Theory and Practice of Quantum Data Encoding

Encoding classical data into quantum systems is a foundational step in the execution of nearly all quantum algorithms, and a critical bottleneck in realizing practical quantum advantage. This review provides a comprehensive account of the concepts, algorithms, and practical considerations associated with quantum data e...

Xiao-Ming Zhang, Arthur G. Rattew, Bu-Jiao Wu et al. · 2 citations
Preprint Sep 2026

Quantum computers will not be that different: A blueprint for quantum computer architecture at scale

It is argued that utility-scale quantum architecture is primarily a cost-performance problem across a coupled quantum-classical system, leading to a blueprint for scalable quantum processing unit (QPU) design, which closely resembles the architecture of high-performance network stacks.

T. Hoefler, M. Troyer · 0 citations
Preprint Aug 2026

Demonstrating advantages of dynamic quantum circuits on a hybrid superconducting qubit-cavity processor

Dynamic quantum circuits (DQCs) provide a hardware-efficient route to quantum computing by reducing physical-qubit overhead and compressing circuit topology through mid-circuit measurements, qubit reset and reuse, and classical feed-forward control. Here, we demonstrate the advantages of DQCs on a single hybrid superco...

Hongbo Wu, Ling Hu, Jiasheng Mai et al. · 0 citations
Preprint Aug 2026

Scientific applications of quantum computing: challenges and opportunities

It is argued that near-term value is most likely to come from disciplined workflow integration rather than wholesale replacement of classical methods, and quantum computing will become scientifically valuable when it demonstrably reduces uncertainty in computed energies, rates, spectra, or materials stability after the...

Bruno Camino, C. R. Catlow, J. Buckeridge et al. · 0 citations
Open access Sep 2026

Quantum Artificial Intelligence opportunities, challenges, threats, use case and future trends

QAI research focuses on using quantum computing to solve computationally challenging AI problems and, conversely, using AI to address the difficulties associated with developing and running quantum computing systems.

Mahmood Ali Mirza, Narasimha Rao Thota, Faheem Ali Mirza · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.