Quantum Computing and Optimization Lab (QCOL) to join I-DISC as a new Research Group.
Quantum Computing has the potential to solve problems faster than classical supercomputers. This capability can change our world by enabling new methods to decrypt data, faster molecular analysis to design better drug treatments and to solve complex optimization problems rapidly.
The Quantum Computing Research Group is formed by the Quantum Computing and Optimization Lab (QCOL), established in 2019 by the Industrial and System Engineering Department of Lehigh University. Its aim was to accelerate the development of quantum computing optimization methodology. Mathematical optimization has critical applications in many disciplines, including physics, biology, engineering, economics, business, and finance. Quantum speed-up has the potential to lead to transformative, revolutionary advances and fundamentally impact society.
- Quantum Interior Point Methods for solving Linear Programming, Semi-definite Programming, and Second-order Cone Optimization problems
- Quantum methods to solve Combinatorial optimization problem such as Stable Set Problem in Graph theory
- Quantum Errors and Their Models
The QCOL’s research focus is on developing novel QC methodologies to solve complex optimization problems.
Current research topics include:
Quantum Interior Point Methods
Making use of Quantum Linear Solvers and Block Encodings to achieve a quantum speedup over classical runtimes by solving the Newton system more efficiently.
Noise in NISQ Devices
Building up a description of physical errors in quantum computers from both individual gate and integrated quantum circuit aspects.
Solving Combinatorial Problems in NISQ devices
Development and study of implementable QUBO formulations of combinatorial problems using QAOA algorithms.
Quantum Computing and Optimization Lab (QCOL) is supported by a recently awarded $2,128,658 research grant from the Defense Advanced Research Projects Agency (DARPA).
Read the article about this award.
Research Group Members
Tamás Terlaky, Industrial & Systems Engineering
Luis Zuluaga, Industrial & Systems Engineering
Xiu Yang, Industrial & Systems Engineering
- Ramin Fakhimi
- Brandon Augustino
- Yu Xie
- Muqing Zheng
- Mohammadhossein Mohammadisiahroudi
- Rodolfo Alexander Quintero Ospina
- Zeguan Wu
- David E. Bernal
- Giacomo Nannicini, IBM T.J. Research Center, Yorktown Height, CT
- Stefan Wild, NAISE, Evaston, IL
- Alain Sarlette, INRIA Paris, France
- Monique Laurent, CWI, Amsterdam, The Netherlands