Near-term quantum computing techniques: Variational quantum algorithms, error mitigation, circuit compilation, benchmarking and classical simulation
Quantum computing is a game-changing technology for global academia, research centers
and industries including computational science, mathematics, finance, pharmaceutical …
and industries including computational science, mathematics, finance, pharmaceutical …
t| ket⟩: a retargetable compiler for NISQ devices
We present t| ket⟩, a quantum software development platform produced by Cambridge
Quantum Computing Ltd. The heart of t| ket⟩ is a language-agnostic optimising compiler …
Quantum Computing Ltd. The heart of t| ket⟩ is a language-agnostic optimising compiler …
A hardware-aware heuristic for the qubit mapping problem in the nisq era
Due to several physical limitations in the realization of quantum hardware, today's quantum
computers are qualified as noisy intermediate-scale quantum (NISQ) hardware. NISQ …
computers are qualified as noisy intermediate-scale quantum (NISQ) hardware. NISQ …
Timing and resource-aware mapping of quantum circuits to superconducting processors
Quantum algorithms need to be compiled to respect the constraints imposed by quantum
processors, which is known as the mapping problem. The mapping procedure will result in …
processors, which is known as the mapping problem. The mapping procedure will result in …
Hybrid discrete-continuous compilation of trapped-ion quantum circuits with deep reinforcement learning
Shortening quantum circuits is crucial to reducing the destructive effect of environmental
decoherence and enabling useful algorithms. Here, we demonstrate an improvement in …
decoherence and enabling useful algorithms. Here, we demonstrate an improvement in …
Survey on quantum circuit compilation for noisy intermediate-scale quantum computers: Artificial intelligence to heuristics
Computationally expensive applications, including machine learning, chemical simulations,
and financial modeling, are promising candidates for noisy intermediate scale quantum …
and financial modeling, are promising candidates for noisy intermediate scale quantum …
Quantum neural network compression
Model compression, such as pruning and quantization, has been widely applied to optimize
neural networks on resource-limited classical devices. Recently, there are growing interest …
neural networks on resource-limited classical devices. Recently, there are growing interest …
Quantum circuit transformation based on simulated annealing and heuristic search
Quantum algorithm design usually assumes access to a perfect quantum computer with
ideal properties like full connectivity, noise-freedom, and arbitrarily long coherence time. In …
ideal properties like full connectivity, noise-freedom, and arbitrarily long coherence time. In …
[HTML][HTML] New coding scheme to compile circuits for quantum approximate optimization algorithm by genetic evolution
Compiling quantum circuits on target quantum hardware architectures is one of the key
issues in the development of quantum algorithms, and the related problem is known as the …
issues in the development of quantum algorithms, and the related problem is known as the …
[HTML][HTML] Quantum circuit compilation by genetic algorithm for quantum approximate optimization algorithm applied to maxcut problem
Abstract The Quantum Circuit Compilation Problem (QCCP) is challenging to the Artificial
Intelligence community. It was already tackled with temporal planning, constraint …
Intelligence community. It was already tackled with temporal planning, constraint …