Quantum many body computation of strongly-correlated electron systems

Quantum many body computation of strongly-correlated electron systems

We conduct quantum many-body calculations using the combination of machine learning and Monte Carlo methods.

The flexible representability of artificial neural networks enables us to extract nontrivial quantum correlations and to achieve highly accurate variational calculations.

The relationship between high-temperature superconductivity associated with fractionalization and quantum critical phenomena will be studied.