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 full costs of state preparation, measurement, error handling, and coupling to classical simulation are included.
Abstract
The predictive simulation of molecules and materials has had a broad and significant impact. It nevertheless remains constrained by the cost of accurately treating electronic correlation, excited states, and complex energy landscapes. Quantum computing offers a fundamentally different computational paradigm in which quantum states are encoded and manipulated directly rather than approximated on classical hardware. Here we discuss where this approach may provide a genuine scientific advantage in chemistry, materials science, and biochemistry. Promising directions include the high-accuracy treatment of correlated active spaces, improved excited-state simulations, and accelerated exploration of combinatorial structure spaces. The central challenge is therefore not qubit scaling alone, but demonstrably chemically meaningful gains in predictive reliability. We argue that near-term value is most likely to come from disciplined workflow integration rather than wholesale replacement of classical methods. Noisy physical devices, error-mitigated utility experiments, early fault-tolerant devices, and fully fault-tolerant quantum computers offer different scientific prospects, and claims of usefulness must be tied to the specific regime being discussed. Quantum computing will become scientifically valuable when it demonstrably reduces uncertainty in computed energies, rates, spectra, or materials stability after the full costs of state preparation, measurement, error handling, and coupling to classical simulation are included.
This work presents a hybrid DFT-Quantum Embedding (QDFT) framework integrating classical HPC-based DFT with a quantum electronic-structure solver, demonstrating quantum embedding's potential to improve selected electronic-structure properties while retaining classical HPC's scalability.
N. Manglani, S. Maity, Shashank Sharma et al.· 0 citations
: Quantum computing has progressed greatly, yet no current hardware platform achieves coherence preservation, precise control, and scalability at the same time. In this commentary, we consider molecular qubits as a conceptually distinct approach to quantum hardware, in which part of the required functionality can be encoded directly through chemically programmable structure rather than imposed entirely by external engineering. Owing to their atomic precision, synthetic reproducibility, tunable interactions, and diverse internal energy levels, molecular systems provide attractive opportunities for quantum information science. We review advances in molecular qubits, emphasizing their potential for uniformity, scalability, programmability, and coherence at elevated temperatures. At the same time, major challenges remain, including single-molecule readout, addressability, device integration, and the realization of high-fidelity entangling gates. We argue that the near-term impact of molecular qubits may not directly replace established platforms but instead enable hybrid architectures and promote a new paradigm of quantum hardware: the systematic chemical design of quantum function. In the long term, we may be able to address the challenges outlined in the DiVincenzo criteria and thereby enable universal quantum computation.
This Perspective analyses how historical narratives and structural separations of expertise slowed the formation of this coupling and outlines what it takes to build: explicit interfaces between technical teams and domain context and intermediate layers that translate quantum outputs into decision-relevant observables without suffocating foundational innovation.
The pursuit of a universal, fault-tolerant quantum computer has transformed quantum computing from a predominantly theoretical discipline into a rapidly diversifying hardware ecosystem. This review presents a comprehensive and technically grounded analysis of the principal physical qubit modalities: superconducting circuits, trapped ions, photonic platforms, neutral atoms, semiconductor spin qubits, and topological approaches, focusing on their underlying operating principles, performance characteristics, and system-level constraints. We examine how these qubit technologies are embedded within scalable quantum processor architectures, including control and readout infrastructures, connectivity topologies, and quantum error correction strategies. The review provides a comparative study of key performance metrics, such as coherence times, gate fidelities, error rates, and scalability, reveals fundamental trade-offs between speed, robustness, and operational complexity that shape distinct technological roadmaps and target applications. We further highlight the ongoing transition from noisy intermediate-scale quantum (NISQ) devices toward architectures centred on logical qubits, driven by advances in materials engineering, precision control, and quantum information theory. Together, these developments sketch the emerging routes toward fault-tolerant quantum computing and practical quantum advantage, while offering readers a coherent entry point and reference guide to the current quantum hardware landscape.
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.
Claude Cockfield, M. Garuba· Open Access Research Journal...· 0 citations
This review elucidates how recent advances at the intersection of artificial neural networks and quantum computing have evolved, and details the architectural evolution from Restricted Boltzmann Machines to autoregressive models like RNNs and Transformers, which enable exact, uncorrelated sampling and bypass critical bottlenecks.
Chengze Yang· International Journal of Qua...· 0 citations
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