Distributed Quantum Computation
Research overview
One approach to scaling up quantum computing is distributed quantum computation, in which several quantum computers or modules are connected and work together. This requires methods for exchanging quantum information between separated quantum systems and ways to combine devices with limited capabilities.
The Distributed Quantum Computation (DQC) team studies the technologies needed for distributed quantum computation, primarily through theory and numerical simulations. We investigate optical connections between quantum computers, quantum optimal control, continuous-variable photonic quantum information processing, and noise and quantum error correction in real devices. Our work spans physical devices and information processing.
Connecting different quantum computers with light
Distributed quantum computation requires entanglement between quantum computers so that they can work together. We study the properties and control of photons emitted by qubits, and ways to create high-quality quantum connections between nodes with different characteristics.
Examples of our research: performance analysis of remote entanglement generation, and photon waveform optimization between different cavity-QED systems
Error-resilient quantum information processing with continuous variables of light
Quantum information can be encoded in qubits based on 0 and 1, and also in continuous degrees of freedom such as the amplitude and phase of light. We study how bosonic codes, including cat codes, and optical measurements can improve the efficiency and error resilience of photonic quantum information processing.
Examples of our research: optical Bell measurements using cat codes, and continuous-variable photonic quantum information processing
Studying error correction through noise in real quantum devices
The physical properties of quantum devices give rise to different types of errors. We study noise through physical models, including models of trapped-ion quantum gates, and use these results to develop quantum error correction and simulations that account for real devices.
Examples of our research: analyzing physical noise in quantum gates, and building error models for quantum error correction
How we conduct research
The DQC team works mainly through theory and numerical simulations. We identify research questions from previous work and describe the quantum systems or information-processing tasks with mathematical models. We use tools such as Python for simulations and numerical optimization, analyzing the results and discussing them with faculty and team members.