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