Quantum Computing

Quantum computers are expected to accelerate scientific discovery spanning many different areas such as medicine, AI, material science, and financial predictions. Quantum hardware manipulates data with much more complex information than the binary information represented in classical computers. In recent years, quantum devices with up to tens of qubits on universal quantum computers and a few thousand qubits on quantum annealer devices have become available. These advances have enabled researchers to use real quantum hardware to solve small problems for the first time. In the near term, quantum computers are expected to stay very limited, in both the number and quality of qubits, which will make it difficult to use them for practical applications that often require hundreds or even thousands of qubits. Challenges such as qubit connectivity limitations, high noise levels, and full error-correction overhead, plus concerns about scalability raise a variety of extremely interesting problems related to quantum algorithms, their applicability on practical problems, and hybridization with classical devices.

Current Faculty

• Ilya Safro, Associate Professor. Quantum computing; Quantum algorithms; Hybrid quantum-classical methods;

Quantum Computing Laboratories