William McGahey

Phone: 412-624-9697
Email:wem@pitt.edu

This laboratory in the Department of Electrical and Computer Engineering, directed by Alex Jones, PhD, provides the hardware and software necessary for students to design and build digital circuits. It is used in two undergraduate laboratory courses where students are provided with an understanding of the three-way relationship between the mathematical abstraction of logic as expressed in Boolean algebra, schematics and simulations using CAD tools, and the physical realization of these circuits in hardware. The facility contains 24 networked high-performance workstations, complete with logic analyzers, oscilloscopes, and related equipment used to design, breadboard, and test digital circuits. In addition, the laboratory contains complete support for both Altera and Xilinx Field Programmable Gate Array system development. Finally, a full complement of software, including the Mentor Graphics Design Tools and the Microsoft Visual Studio, is available which allows students to simulate their designs and develop new hardware and software systems. This laboratory was created through a generous gift from John A. Jurenko, a Pitt alumnus and friend of the University.

https://engineering.pitt.edu/jjma

Our research is devoted to the computational study of correlated systems, mostly relying on exact simulations and tensor network algorithms. We address two main scenarios: many-body quantum systems, and turbulent flows.

Quantum Systems of Many Interacting Particles

Correlations in many-body quantum systems lead to spectacular states of matter such as insulating phases, magnetic order, and superconductivity. We rely on simple yet rich models, and on powerful tensor network algorithms, to analyze these states in and out of equilibrium. 

Quantum Mechanics for Fluid Dynamics

We develop tensor network and quantum computing algorithms to simulate partial differential equations, with focus on fluid dynamics. Advantages over standard numerical methods are assessed. This work opens the door for performing computational fluid dynamics on quantum hardware.