Perturbative quantum simulation
Approximation based on perturbation theory is the foundation for most of the quantitative
predictions of quantum mechanics, whether in quantum many-body physics, chemistry …
predictions of quantum mechanics, whether in quantum many-body physics, chemistry …
Noise propagation in hybrid tensor networks
The hybrid tensor network (HTN) method is a general framework allowing for constructing an
effective wavefunction with the combination of classical tensors and quantum tensors, ie …
effective wavefunction with the combination of classical tensors and quantum tensors, ie …
Quantum computing quantum Monte Carlo with hybrid tensor network for electronic structure calculations
S Kanno, H Nakamura, T Kobayashi, S Gocho… - npj Quantum …, 2024 - nature.com
Quantum computers have a potential for solving quantum chemistry problems with higher
accuracy than classical computers. Quantum computing quantum Monte Carlo (QC-QMC) is …
accuracy than classical computers. Quantum computing quantum Monte Carlo (QC-QMC) is …
Quantum Machine Learning and TensorNetworks as an Aid in the Clinical Diagnosis ofCoronary Artery Disease
S Bopardikar, M Montoya, P Decoodt… - 2024 - researchsquare.com
Current applications of quantum machine learning are emerging, dueto the potential
benefits that quantum technologies could bring in thenear future. One of the most recent …
benefits that quantum technologies could bring in thenear future. One of the most recent …
Development of Hybrid Quantum Algorithm for Investment Portfolio Optimization
F Malik, K Iqbal, Z Ali - Journal of Tecnologia Quantica, 2024 - journal.ypidathu.or.id
The background of this research focuses on the challenges of investment portfolio
optimization, which often requires long computing time and high complexity, especially with …
optimization, which often requires long computing time and high complexity, especially with …