Experimental demonstration of optimized quantum process tomography on the IBM quantum experience

Abstract

We experimentally performed complete and optimized quantum process tomography of quantum gates implemented on superconducting qubit-based IBM QX2 quantum processor via two constrained convex optimization (CCO) techniques: least squares optimization and compressed sensing optimization. We studied the performance of these methods by comparing the experimental complexity involved and the experimental fidelities obtained. We experimentally characterized several two-qubit quantum gates: identity gate, a controlled-NOT gate, and a SWAP gate. The general quantum circuit is efficient in the sense that the data needed to perform CCO-based process tomography can be directly acquired by measuring only a single qubit. The quantum circuit can be extended to higher dimensions and is also valid for other experimental platforms.

Classification and measurement of multipartite entanglement by reconstruction of correlation tensors on an NMR quantum processor

“…The angles α, β and γ were set to α = π 3 , β = arcsin ( 1 The standard methods for quantum state reconstruction for NMR quantum information processing typically involve performing full state tomography [42,43] which is computationally expensive, although some alternatives involving maximum likelihood estimation have been pro- posed and used in our group [44]. For this work, we have used a least squares constrained convex optimization method to reconstruct the density matrix of the desired state [45]. Fidelities of the experimentally reconstructed states (as compared to the theoretically expected state) were computed using the Uhlmann-Jozsa measure [46,47]:…”

Implementing efficient selective quantum process tomography of superconducting quantum gates on IBM quantum experience

“…Resource requirements for standard QST and QPT methods grow exponentially with increasing system size, and hence several novel methods have been designed that focus on simplifying and reducing experimental complexity such as maximum likelihood estimation 3 , adaptive quantum tomography 4 , self-guided tomography 5 , ancilla-assisted tomography 6 , compressed sensing tomography 7 , 8 , and least square optimization based tomography 9 , 10 . These novel tomography protocols have been experimentally demonstrated on various physical configurations such as NMR 11 , 12 , linear-optics 13 , NV-centers 14 , ion-trap based quantum processors 15 , photonic qubits 16 , and superconducting qubits 17 – 20 .…”

Simulating open quantum dynamics on an NMR quantum processor using the Sz.-Nagy dilation algorithm

“…To demonstrate the efficacy of the Sz.-Nagy algorithm, we experimentally simulated two non-unitary quantum processes acting on a two-qubit system: a phase damping channel acting independently on the two qubits where the Kraus operators are already known, and a magnetic field gradient pulse (MFGP), where the Kraus operators are not directly available and need to be computed. Further, to validate the quality of the experimentally simulated quantum channel, we perform convex optimization-based full quantum process tomography [25,26].…”