At Luddy, we investigate the advantages of quantum information in computation and communication. Topics under investigation include development of algorithms, programming languages, and hardware architecture offering scalable advantages over classical computers. Research in this area promises new computational frameworks with significant applications.
A multidisciplinary field comprising aspects of computer science, physics, and mathematics
Subareas
Quantum complexity theory
We mathematically analyze the inherent difficulty of quantum computations, in particular as distinct from classical computing. We further investigate limitations of and barriers to efficient quantum computing.
Quantum information
We study the theory of quantum computing, communication, and sensing in the presence of noise. Related topics include quantum error correction, theory of noisy quantum channels, and measurement of quantum systems.
Computing systems
We study how quantum software interacts with hardware, including quantum compilation, distributed quantum computing, and computational implications of different physical media.
Programming languages
The majority of programming models for quantum computers place a special emphasis on qubits and gates, which are low-level constructs that require specialist knowledge. Our aim is to design and implement high-level quantum abstractions that enable quantum programmers to express algorithms in terms of the natural domain-specific data representations and operations.
Machine learning
We study the foundations of learning in quantum settings to design and analyze quantum algorithms for inference from classical and quantum data. Relevant topics include quantum learning theory, variational quantum algorithms, and quantum neural networks.