Quantum annealing for industry applications: Introduction and review
Quantum annealing (QA) is a heuristic quantum optimization algorithm that can be used to
solve combinatorial optimization problems. In recent years, advances in quantum …
solve combinatorial optimization problems. In recent years, advances in quantum …
The neurobench framework for benchmarking neuromorphic computing algorithms and systems
Neuromorphic computing shows promise for advancing computing efficiency and
capabilities of AI applications using brain-inspired principles. However, the neuromorphic …
capabilities of AI applications using brain-inspired principles. However, the neuromorphic …
Quantum optimization of maximum independent set using Rydberg atom arrays
Realizing quantum speedup for practically relevant, computationally hard problems is a
central challenge in quantum information science. Using Rydberg atom arrays with up to …
central challenge in quantum information science. Using Rydberg atom arrays with up to …
Quantum optimization with arbitrary connectivity using Rydberg atom arrays
Programmable quantum systems based on Rydberg atom arrays have recently been used
for hardware-efficient tests of quantum optimization algorithms [Ebadi et al., Science, 376 …
for hardware-efficient tests of quantum optimization algorithms [Ebadi et al., Science, 376 …
Quantum feature maps for graph machine learning on a neutral atom quantum processor
Using a quantum processor to embed and process classical data enables the generation of
correlations between variables that are inefficient to represent through classical …
correlations between variables that are inefficient to represent through classical …
Hardness of the maximum-independent-set problem on unit-disk graphs and prospects for quantum speedups
Rydberg atom arrays are among the leading contenders for the demonstration of quantum
speedups. Motivated by recent experiments with up to 289 qubits [Ebadi, Science 376, 1209 …
speedups. Motivated by recent experiments with up to 289 qubits [Ebadi, Science 376, 1209 …
Quantum-informed recursive optimization algorithms
We propose and implement a family of quantum-informed recursive optimization (QIRO)
algorithms for combinatorial optimization problems. Our approach leverages quantum …
algorithms for combinatorial optimization problems. Our approach leverages quantum …
Quantum machine learning on near-term quantum devices: Current state of supervised and unsupervised techniques for real-world applications
The past decade has witnessed significant advancements in quantum hardware,
encompassing improvements in speed, qubit quantity, and quantum volume—a metric …
encompassing improvements in speed, qubit quantity, and quantum volume—a metric …
Designing quantum annealing schedules using Bayesian optimization
We propose and analyze the use of Bayesian optimization techniques to design quantum
annealing schedules with minimal user and resource requirements. We showcase our …
annealing schedules with minimal user and resource requirements. We showcase our …
Quantum computing in telecommunication—a survey
F Phillipson - Mathematics, 2023 - mdpi.com
Quantum computing, an emerging paradigm based on the principles of quantum mechanics,
has the potential to revolutionise various industries, including Telecommunications. This …
has the potential to revolutionise various industries, including Telecommunications. This …