Noise in quantum hardware presents a significant hurdle

The gap

Evidence profile

Sourced from the stated research gap and future-work section and abstract and stated challenges of the source papers, classified as general, spanning 6 journals.

Supporting evidence — 7 representative gaps

• SCALABLE QUANTUM INSPIRED DATA PROCESSING ARCHITECTURE FOR REAL TIME CYBER PHYSICAL SYSTEMS AND AUTONOMOUS DECISION INTELLIGENCE IN COMPUTER SCIENCE AND ENGINEERING APPLICATIONS (2026) · INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING & TECHNOLOGY · doi

  Existing quantum inspired models are designed for batch processing or offline optimization, lacking real-time scalability. The paper identifies the need for a scalable quantum inspired architecture for real-time CPS and autonomous decision intelligence.

  generalstated research gap
  Keywords: existing quantum inspired models designed batch processing offline
• CMOS compatible probabilistic computing hardware with cointegrated reconfigurable p-bits and synapse arrays (2026) · Nature Communications · doi

  The need for a probabilistic computing hardware that can efficiently solve complex combinatorial optimization problems. The limitation of conventional deterministic computing in finding the optimal solution within a feasible time. The requirement for a cryogenic environment in quantum computing.

  generalstated research gap
  Keywords: need probabilistic computing hardware efficiently solve complex combinatorial
• Reconstruction of phylogenetic trees via graph-splitting using quantum computing (2026) · The Journal of Supercomputing · doi

  To improve the scalability of the QNMcut algorithm to large datasets. To apply the QNMcut algorithm to other optimization problems in bioinformatics. To explore the potential of quantum computing for other applications in bioinformatics.

  generalfuture-work section
  Keywords: improve scalability qnmcut algorithm large datasets apply other
• QUBO Modeling of Module Learning With Errors: Stability and Scaling in Post-Quantum Cryptography (2026) · arXiv

  Although current quantum annealing hardware remains insufficient for cryptographically relevant parameters, the proposed methodology offers a structured basis for studying lattice-based problems in quantum optimization settings without implying a practical threat to standardized post-quantum schemes.

  generalabstractevidence 5/5
  Keywords: quantum current annealing hardware remains insufficient cryptographically relevant parameters proposed methodology offers structured basis studying
• The Quantum Optimization Benchmarking Library (2026) · Nature Computational Science · doi

  There is a need for a systematic, fair and comparable benchmarking framework for quantum optimization methods. There is a need for a library of problem instances and solutions that can be used to develop and test new quantum optimization algorithms. There is a need to track progress towards quantum advantage in combinatorial optimization.

  generalstated research gapevidence 5/5
  Keywords: there need systematic fair comparable benchmarking framework quantum
• The Quantum Optimization Benchmarking Library (2026) · Nature Computational Science · doi

  Future research should focus on developing new quantum optimization algorithms that can solve the problem instances in the library. Future research should focus on improving the performance of existing quantum optimization algorithms. Future research should focus on exploring new application domains for quantum optimization.

  generalfuture-work sectionevidence 5/5
  Keywords: future research focus developing new quantum optimization algorithms
• Promise of Graph Sparsification and Decomposition for Noise Reduction in QAOA: Analysis for Trapped-Ion Compilations (2026) · Quantum · doi

  Noise in quantum hardware presents a significant hurdle to achieving scalable quantum computing. Quantum noise remains a major challenge. Classical methods continue to outperform quantum algorithms for combinatorial optimization.

  generalstated challengesevidence 5/5
  Keywords: noise quantum hardware presents significant hurdle achieving scalable

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