Quantum computing for smart grid applications
Computational complexities in modern power systems are reportedly increasing daily, and it
is anticipated that traditional computers might be inadequate to provide the computation …
is anticipated that traditional computers might be inadequate to provide the computation …
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 …
Hybrid quantum-classical algorithms in the noisy intermediate-scale quantum era and beyond
Hybrid quantum-classical algorithms are central to much of the current research in quantum
computing, particularly when considering the noisy intermediate-scale quantum (NISQ) era …
computing, particularly when considering the noisy intermediate-scale quantum (NISQ) era …
Quantum computing of the nucleus via ordered unitary coupled clusters
The variational quantum eigensolver (VQE) is an algorithm to compute ground and excited
state energy of quantum many-body systems. A key component of the algorithm and an …
state energy of quantum many-body systems. A key component of the algorithm and an …
Large-scale quantum approximate optimization on nonplanar graphs with machine learning noise mitigation
Quantum computers are increasing in size and quality but are still very noisy. Error
mitigation extends the size of the quantum circuits that noisy devices can meaningfully …
mitigation extends the size of the quantum circuits that noisy devices can meaningfully …
Provably trainable rotationally equivariant quantum machine learning
Exploiting the power of quantum computation to realize superior machine learning
algorithms has been a major research focus of recent years, but the prospects of quantum …
algorithms has been a major research focus of recent years, but the prospects of quantum …
Learning efficient decoders for quasichaotic quantum scramblers
Scrambling of quantum information is an important feature at the root of randomization and
benchmarking protocols, the onset of quantum chaos, and black-hole physics. Unscrambling …
benchmarking protocols, the onset of quantum chaos, and black-hole physics. Unscrambling …
Variational Gibbs state preparation on noisy intermediate-scale quantum devices
The preparation of an equilibrium thermal state of a quantum many-body system on noisy
intermediate-scale quantum (NISQ) devices is an important task in order to extend the range …
intermediate-scale quantum (NISQ) devices is an important task in order to extend the range …
Challenges of variational quantum optimization with measurement shot noise
Quantum enhanced optimization of classical cost functions is a central theme of quantum
computing due to its high potential value in science and technology. The variational …
computing due to its high potential value in science and technology. The variational …
Universal Kardar-Parisi-Zhang scaling in noisy hybrid quantum circuits
Measurement-induced phase transitions (MIPTs) have attracted increasing attention due to
the rich phenomenology of entanglement structures and their relation with quantum …
the rich phenomenology of entanglement structures and their relation with quantum …