Nicola Lanata Headshot

Nicola Lanata

Assistant Professor

School of Physics and Astronomy
College of Science

Office Location

Nicola Lanata

Assistant Professor

School of Physics and Astronomy
College of Science

Bio

I am a physicist with a PhD in “Theory and Numerical Simulation in Condensed Matter Systems” from the International School for Advanced Studies (SISSA-ISAS) in Italy. I have held several research positions, including a “Dirac Fellowship” at the National High Magnetic Field Laboratory and assistant professor positions at Aarhus University in Denmark and NORDITA in Sweden. Currently, I am a tenure-track assistant professor at the RIT Department of Physics and Astronomy and a Visiting Scholar at the Center for Computational Quantum Physics (CCQ) in New York.

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Areas of Expertise

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Journal Paper
Lee, Tsung-Han, Nicola Lanatà, and Gabriel Kotliar. "Accuracy of ghost rotationally invariant slave-boson and dynamical mean field theory as a function of the impurity-model bath size." Phys. Rev. B (Letter) 107. (2023): L121104. Print.
Lanatà, Nicola. "Derivation of the ghost Gutzwiller approximation from quantum embedding principles: Ghost density matrix embedding theory." Phys. Rev. B 108. (2023): 235112. Print.
Lanatà, Nicola, et al. "Efficient implementation of the Gutzwiller variational method." Phys. Rev. B 85. (2012): 35133. Print.
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Currently Teaching

PHYS-377
3 Credits
This course introduces students to advanced methods for using computers to model the behavior of physical systems. Topics will include numerical solutions to differential equations such as heat transfer, planetary motion, and shock waves, the Monte Carlo approach to problems with large domains, tradeoffs between efficiency and precision, minimization and maximization of functions, and the statistical modeling of data.
PHYS-610
3 Credits
This graduate-level course in mathematical physics covers partial differential equations, Bessel, Legendre and related functions, Fourier series and transforms.
PHYS-790
1 - 4 Credits
Graduate-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.