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Visualizing nanoscale heterogeneity in perylene thin films via tip-enhanced photoluminescence with unsupervised machine learning
We investigate the properties of ultrathin 3, 4, 9, 10-perylenetetracarboxylic diimide (PTCDI)
films using a combination of tip-enhanced photoluminescence and unsupervised machine …
films using a combination of tip-enhanced photoluminescence and unsupervised machine …
Optimized Quantum Autoencoder
Y Huang, M Yang, DL Zhou - arxiv preprint arxiv:2404.08429, 2024 - arxiv.org
Quantum autoencoder (QAE) compresses a bipartite quantum state into its subsystem by a
self-checking mechanism. How to characterize the lost information in this process is …
self-checking mechanism. How to characterize the lost information in this process is …
Autoencoder-based analytic continuation method for strongly correlated quantum systems
Solving ill-posed problems is central to a variety of scientific investigations. We focus here
on the analytic continuation of imaginary-time data obtained from quantum Monte Carlo …
on the analytic continuation of imaginary-time data obtained from quantum Monte Carlo …
Detecting quantum critical points of correlated systems by quantum convolutional neural network using data from variational quantum eigensolver
Machine learning has been applied to a wide variety of models, from classical statistical
mechanics to quantum strongly correlated systems, for classifying phase transitions. The …
mechanics to quantum strongly correlated systems, for classifying phase transitions. The …
Quantum Classical Algorithm for the Study of Phase Transitions in the Hubbard Model via Dynamical Mean-Field Theory
A Baul, HF Fotso, H Terletska, J Moreno… - arxiv preprint arxiv …, 2023 - arxiv.org
Simulating quantum many-body systems is believed to be one of the most promising
applications of near-term noisy quantum computers. However, in the near term, system size …
applications of near-term noisy quantum computers. However, in the near term, system size …
Explaining the Machine Learning Solution of the Ising Model
RC Alamino - arxiv preprint arxiv:2402.11701, 2024 - arxiv.org
As powerful as machine learning (ML) techniques are in solving problems involving data
with large dimensionality, explaining the results from the fitted parameters remains a …
with large dimensionality, explaining the results from the fitted parameters remains a …
Quantum Classical Algorithm for Solving the Hubbard Model Via Dynamical Mean-field Theory
A Baul - 2024 - search.proquest.com
Modeling many-body quantum systems is widely regarded as one of the most promising
applications for near-term noisy quantum computers. However, in the near term, system size …
applications for near-term noisy quantum computers. However, in the near term, system size …