To improve the efficiency of the algorithm
Research gap analysis derived from 8 physics papers in our local library.
The gap
To improve the efficiency of the algorithm. - To improve the accuracy of the algorithm. - To apply the results to other areas of quantum computing and quantum information theory.
Evidence profile
Stated in the inline gaps and abstract and cells research gap and cells future research sections of the source papers, classified as general, spanning 5 journals. Those papers have been cited 1 times in total.
Research trend
Established — well-defined area with open sub-problems.
Supporting evidence — 8 representative gaps
- Efficient Quantum Hermite Transform (2026) · doi
poly( 1 ε k) quantum queries and poly(n 1 ε 6 Open problems and outlook The most pressing question regarding our work is to find additional practical problems for which the QHT gives quantum advantage.
generalstated in inline gapsevidence 5/5Keywords: poly quantum problems queries open outlook pressing question regarding find additional practical gives advantage - 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.
generalstated in abstractevidence 5/5Keywords: quantum current annealing hardware remains insufficient cryptographically relevant parameters proposed methodology offers structured basis studying - Deterministic quantum search for arbitrary initial success probabilities (2026) · Quantum Information Processing · doi
Prior quantum search algorithms are probabilistic and do not guarantee success. - There is a need for a deterministic quantum search algorithm that operates effectively for arbitrary initial success probabilities.
generalstated in cells research gapevidence 5/5Keywords: prior quantum search algorithms probabilistic guarantee success there - Learning Stabilizer Structure of Quantum States (2026) · cited 1× · doi
To improve the efficiency of the algorithm. - To improve the accuracy of the algorithm. - To apply the results to other areas of quantum computing and quantum information theory.
generalstated in cells future researchevidence 5/5Keywords: improve efficiency algorithm accuracy apply results other areas - PennyLane–Qiskit Plugin: A Protocol for Integrating Noisy, Fake, and Real Quantum Backends (2026) · EAI Endorsed Transactions on Tourism, Technology and Intelligence · doi
Optimizing predictive performance and conducting a rigorous benchmarking of the backends. - Exploring the use of the PennyLane-Qiskit plugin with other quantum computing frameworks.
generalstated in cells future researchevidence 5/5Keywords: optimizing predictive performance conducting rigorous benchmarking backends exploring - Comparison of hyperplane rounding for max-cut and quantum approximate optimization algorithm over certain regular graph families (2026) · Operations Research Letters · doi
There is a need to identify challenging instances of NP-hard problems to demonstrate quantum advantage. - There is a need to explore the performance of quantum algorithms on specific graph families.
generalstated in cells research gapevidence 5/5Keywords: there need identify challenging instances np-hard problems demonstrate - Comparison of hyperplane rounding for max-cut and quantum approximate optimization algorithm over certain regular graph families (2026) · Operations Research Letters · doi
Future research can explore the performance of QAOA on other graph families. - Future research can explore the development of new quantum algorithms for solving combinatorial optimization problems.
generalstated in cells future researchevidence 5/5Keywords: future research explore performance qaoa other graph families - 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 in cells research gapevidence 5/5Keywords: there need systematic fair comparable benchmarking framework quantum
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