Research Projects

This project aims to develop practical protocols and algorithms for quantum systems in the noisy intermediate-scale quantum (NISQ) era. Quantum systems offer computational and informational advantages over classical counterparts due to uniquely quantum resources—such as entanglement, which powers device-independent quantum cryptography, and nonstabilizer properties, essential for universal quantum computation. But unlike their classical counterparts, quantum information can be destroyed when probed and is very susceptible to noise. Therefore, as parts of large-scale quantum information processing and computing architectures, it is important to efficiently characterize, verify, and estimate the operationally critical quantum properties that work as the key ingredients. In this project, we model quantum data and processes as sequences of quantum states and channels and investigate problems such as discrimination, verification, and the learning unknown system properties. This will help us understand the resource requirement of many tasks of practical importance like quantum data analysis and probing many-body systems. We will seek to develop optimal protocols in terms of resource consumption or benchmark proposed protocols against already existing ones. Starting from general quantum systems, we will progressively focus on many-body systems that are promising candidates for quantum computing and information-processing platforms. We aim to design efficient algorithms for probing the properties of such systems using correlations extracted from local randomized measurements—techniques that are feasible with existing experimental capabilities.