The relationship between Metric(M), noise(N) and resource(R) is non-linear for algorithms such as VQE. We can estimate this relationship to build a detailed model of energy consumption of a VQE algorithm.

Study and simulation of Quantum spin systems (1D) for their application in Quantum information Processing. Successfully tested many such systems having varied interactions (Dzyaloshinskii-Moriya, magnetic field and impurities etc.) for their properties viz. chirality, correlation, magnetization, entropy, and fidelity of spin transfer (one and two qubits). We successfully developed a transfer protocol involving kicking helical spin chains with electric field for better transmission fidelity, including in sharing entanglement.

In the low energy limit, the testability of the interplay between QM and gravity looks promising driven by recent theoretical proposals and technological leaps - especially in the quantum domain. At this energy scale, it is assumed (and proven) that QM and gravity hold correct and their respective intrinsic formalism can be extended to probe their interplay. In this regard, many proposals have been laid out to experimentally test this interplay. Through introducing quantum noise in this scenario, we derive novel gravitational decoherence mechanism. We also study a scenario with noisy quantum clocks, as an extension of the proposal probing gravity using quantum clocks.

Recently, there were efforts to incorporate quantum processes in parameter estimation and channel discrimination tasks leading to the development of a general framework of metrology in the quantum process framework. However, the prospect of simultaneous estimation tasks - that of estimating two or more parameters has often been ignored. If considered with thermalizing quantum channels with distinct bath temperatures, the framework of quantum processes constitutes an interesting scenario with the possibility of multi-parameter estimation, specifically multi-temperature estimation, which we have investigated. We have calculated the bounds on the covariance of temperatures, and their attainability for this simultaneous estimation task, using established methods of multiparameter estimation.