Quantum state tomography (QST) refers to any method that allows one to reconstruct the
accurate representation of a quantum system based on data obtainable from an experiment …

Methods of artificial intelligence (AI) and especially machine learning (ML) have been
growing ever more complex, and at the same time have more and more impact on people's …

We introduce an inductive n-qubit pure-state estimation method based on projective
measurements on mn+ 1 separable bases or m entangled bases plus the computational …

This article introduces a process framework for debugging quantum circuits, focusing on
three distinct types of circuit blocks: amplitude–permutation, phase-modulation, and …

Current noise levels in physical realizations of qubits and quantum operations limit the
applicability of conventional methods to characterize entanglement. In this adverse scenario …

This article proposes an end-to-end framework for the learning-enabled control of closed
quantum systems. The proposed learning technique is the first of its kind to utilize a …

The barren plateau (BP) phenomenon is one of the main obstacles to implementing
variational quantum algorithms in the current generation of quantum processors. Here, we …

Hybrid classical quantum optimization methods have become an important tool for efficiently
solving problems in the current generation of noisy intermediate-scale quantum computers …

We introduce a method to estimate unknown pure d-dimensional quantum states using the
probability distributions associated with only three measurement bases. The measurement …

Quantum state tomography is the procedure for reconstructing unknown quantum states
from a series of measurements of different observables. Depending on the physical system …