Understand the computational power of quantum mechanics. Discover applications where quantum computers can outperform the best classical algorithms even in the presence of noise.
Researchers:
Scott Aaronson
Professor, Department of Computer Science
Research Interests
- The capabilities and limits of quantum computers
- Computational complexity theory
Jonathan Baker
Assistant Professor, Chandra Department of Electrical & Computer Engineering
Research Interests
- Quantum computing architecture.
- Practical execution of quantum error correction.
- Quantum compilation, synthesis, multi-radix architectures, and error mitigation.
Poulami Das
Assistant Professor, Chandra Department of Electrical & Computer Engineering
Research Interests
- Quantum Programming: Application and device specific compilation, Software error mitigation.
- Quantum Error Correction: Software scheduling, Architecture for error detection, System-level architectures.
- Quantum Cloud Services: Efficient quantum resource management, Quantum job (user program) scheduling.
Nick Hunter-Jones
Professor, Department of Physics & Computer Science
Research Interests
- Random quantum circuits.
- Unitary designs. Quantum complexity.
- Quantum simulation.
- Demonstrations of quantum advantage.
Matteo Ippoliti
Assistant Professor, Department of Physics
Research Interests
- Dynamics of quantum information: Understanding thermal equilibrium and its exceptions, protecting quantum information from noise, efficiently learning quantum states
- Many-body physics experiments on quantum computers
- Classical simulation of quantum computers and quantum matter: Tensor networks, physics-informed algorithm development
David Soloveichik
Associate Professor, Chandra Department of Electrical and Computer Engineering
Research Interests
Natural computing: computation inspired by nature
Molecular programming: engineering smart molecules
Distributed computing
