Reseach Areas

Quantum information (QI) theory explores the ways in which information can been coded, processed, and transmitted using different quantum systems, thereby providing new algorithms, architectures and protocols for computation, communication, sensing and other quantum-enhanced capabilities. The CoE-QuICST features research groups working on various facets of QI theory, ranging from dynamics and control of open and hybrid quantum systems to protocols for entanglement distribution in a quantum network and adiabatic quantum computation.

In quantum simulations, we study a quantum system of interest by mapping its state space and dynamics to that of an artificial quantum system such as a quantum computer. The latter acts as a simulator of the potentially complex system of interest, allowing a study of its properties under controlled evolution and measurement. Several theory groups in CoE-QuICST are developing algorithms for simulating complex condensed matter systems and quantum chemical models that can be mapped to superconducting qubits, trapped ions and other quantum computational hardware. These algorithms will be of crucial importance for applications in the design of drug molecules, designer quantum materials and testing fundamental theories of nature.

Quantum computing aims to use the laws of quantum mechanics to develop solutions for a large class of computational problems, using exponentially fewer resources like time and memory, compared to the best-known classical algorithms. Research groups from the CoE-QuICST are involved in the development of quantum computing hardware, across different promising platforms. In parallel, CoE-QuICST teams are also involved in development of quantum algorithms, for applications in areas of drug discovery, management of supply chains and data analysis.

Quantum sensing and metrology deals with precision detection and quantification, respectively. Quantum systems in superposed or entangled states can be used to build sensors with efficiencies considerably better than the best classical  sensing devices. The CoE-QuICST features both experimental and theoretical teams that work in this exciting area. Our experimental expertise includes the development of precision NV center magnetometry and our theoretical groups include those working at the forefront of quantum information science for developing innovative paradigms for quantum sensing.

Quantum communication is a field of quantum technology that deals with the information processing and transfer of quantum states between nodes of a communication network. One can make the peculiar properties of quantum information work to our advantage in making such communication secure against attacks by adversaries equipped even with quantum computers. These technologies will therefore be critical to the next generation of data protection and transmission. The CoE-QuICST features theoretical groups working in the area of post quantum cryptography, quantum repeater designs for efficient entanglement distribution and large-scale quantum networks. In parallel, experimental research groups are engaged in R&D of single photon emitters and detectors.

The area of quantum materials and devices has become an integral part and an enabling platform for quantum technologies. Quantum materials feature unconventional quantum states that are “protected” and hence “disciplined” despite the presence of the agents such as defects and impurities that normally result in power dissipation in logic and memory devices and qubit decoherence in quantum computing. The CoE-QuICST features research teams working at the cutting edge of quantum materials and devices which includes superconducting hybrid systems, silicon qubits, light matter interactions in quantum materials and correlated quantum matter.

Quantum enabled technologies contribute to the performance of target applications by exploiting quantum correlations. At CoE-QuICST research groups specialize in technologies such as quantum engines, quantum batteries, quantum sensors, quantum machine learning. Quantum machine learning is envisioned to have path-breaking impact on drug-discovery and finance. .