How close are quantum computers to being useful?

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1. 1

   Evidence of scaling advantage on an NP-complete problem with enhanced quantum solvers.

   Nature computational science (Lu et al.)Published Jun 19, 2026Checked Oct 4, 2026

   “Without complexity proofs, scaling advantage-where quantum resource requirements grow more slowly than their classical counterparts-is the primary indicator. However, direct applications of quantum optimization algorithms to classically intractable problems have yet to demonstrate this advantage. Here we develop enhanced quantum solvers for the NP-complete one-in-three Boolean satisfiability problem. We propose a restricting space reduction algorithm that achieves optimal search-space dimensionality under mod-2 arithmetic, thereby reducing qubit requirements and time complexity. Numerical studies on instances with up to 70 variables demonstrate that our enhanced quantum approximate optimization algorithm- and quantum adiabatic algorithm-based solvers outperform state-of-the-art classical solvers; the quantum adiabatic algorithm-based solver serves as a lower-bound reference while retaining scaling advantage. Furthermore, experiments on a 13-qubit superconducting processor confirm the predicted improvements. Collectively, our results provide empirical evidence of quantum speedup for an NP-complete problem.”

2. 2

   Quantum Computing and Quantum Technologies in Drug Discovery and Therapeutics: Evidence, Benchmarking, and Translational Integration.

   Drug design, development and therapy (Niazi)Published Apr 30, 2026Checked Oct 4, 2026

   “We summarize demonstrated capabilities and constraints of NISQ-era computing, outline algorithmic classes for quantum chemistry and hybrid variational methods, evaluate quantum error-mitigation strategies and their limits, and contrast claimed performance with classical baselines in computational chemistry and machine learning. We conclude that near-term translational value is most substantial for quantum sensing and for device/physical platforms with established clinical evidence. In contrast, quantum computing remains principally hypothesis-generating until fault tolerance and reproducible advantage are established. Device-based modalities-including transcranial photobiomodulation for neuropsychiatric indications, focused ultrasound enabling CNS drug delivery, and home-supervised neuromodulation-are already reshaping therapeutic landscapes and clinical trial design. For drug discovery, the central requirement is not quantum novelty but validated decision impact, demonstrated under controlled benchmarks aligned with reproducibility expectations comparable to those evolving for AI/ML-driven methods in regulated contexts.”

3. 3

   Quantum-enhanced generative artificial intelligence: a critical review of classical limitations, complexity barriers, and hybrid quantum-classical architectures.

   Frontiers in artificial intelligence (Singh et al.)Published Jul 21, 2026Checked Oct 4, 2026

   “In this study, both architectures are compared in a contrastive manner in terms of mathematics. The data reveals that identical dynamics that help classical systems learn natural language distributions constrain its ability to use efficient sampling of quantum-mechanical spaces. Performing complexity-theoretic separations (i.e., the widely believed but unproven conjecture that BPP ⊆ BQP) and a 2025 preprint reporting experimental demonstrations of quantum advantage for generative tasks we conclude that quantum utility is unlikely to lie in tasks involving natural language processing under current architectures, but rather in certain computational subroutines. We then suggest a hybrid quantum-classical architecture as the best direction to take in the future, as it has the advantages of both paradigms. This is done by studying a case study that optimizes retrieval-augmented generation (RAG) pipelines with Grover's search algorithm.”

4. 4

   Quantum computing (Wikipedia)

   WikipediaPublished Oct 3, 2026Checked Oct 4, 2026

   “A quantum computer is a computer that represents and processes information using quantum states. Quantum computations exploit phenomena such as superposition, interference, and entanglement. Quantum computers have the potential to complete some calculations exponentially faster than classical computers. For example, a large-scale quantum computer could break widely used encryption schemes and aid physicists in performing physical simulations. However, current hardware implementations of quantum computation are largely experimental and suitable for only certain specialized tasks. The basic unit of information in quantum computing, the qubit (quantum bit), serves a similar function as the bit in ordinary or "classical" computing. Unlike a classical bit, which can be in one of two states (a binary), a qubit can exist in a linear combination of states known as a quantum superposition. The result of measuring a qubit is one of the two states, given by a probabilistic rule. If a quantum computer manipulates the qubit in a particular way, wave interference effects amplify the probability of the desired measurement result.”

5. 5

   Distributed quantum information processing: a review of recent progress.

   Reports on progress in physics. Physical Society (Great Britain) (Knörzer et al.)Published Jul 2, 2026Checked Oct 4, 2026

   “Distributed quantum information processing seeks to overcome the scalability limitations of monolithic quantum devices by interconnecting multiple quantum processing nodes via classical and quantum communication. This approach extends the capabilities of individual devices, enabling access to larger problem instances and novel algorithmic techniques. Beyond increasing qubit counts, it also enables qualitatively new capabilities, such as joint measurements on multiple copies of high-dimensional quantum states. The distinction between single-copy and multi-copy access reveals important differences in task complexity and helps identify which computational problems stand to benefit from distributed quantum resources. At the same time, it highlights trade-offs between classical and quantum communication models and the practical challenges involved in realizing them experimentally. In this review, we contextualize recent developments by surveying the theoretical foundations of distributed quantum protocols and examining the experimental platforms and algorithmic applications that realize them in practice.”