In this article, we investigate the stability of probabilistic error cancellation (PEC) outcomes in the presence of nonstationary noise, which is an obstacle to achieving accurate observable estimates. Leveraging Bayesian methods, we design a strategy to enhance PEC stability and accuracy. Our experiments using a five-qubit implementation of the Bernstein–Vazirani algorithm and conducted on the […]
Quantum information cannot be perfectly cloned, but approximate copies of quantum information can be generated. Quantum telecloning combines approximate quantum cloning, more typically referred to as quantum cloning, and quantum teleportation. Quantum telecloning allows approximate copies of quantum information to be constructed by separate parties, using the classical results of a Bell measurement made on […]
In this article, we propose a postprocessing variationally scheduled quantum algorithm (pVSQA) for solving constrained combinatorial optimization problems (COPs). COPs are typically transformed into ground-state search problems of the Ising model on a quantum annealer or gate-based quantum device. Variational methods are used to find an optimal schedule function that leads to high-quality solutions in […]
Quanvolutional Neural Networks (QNNs) have been successful in image classification, exploiting inherent quantum capabilities to improve performance of the traditional convolution. Unfortunately, the qubit’s reliability can be a significant issue for QNNs inference, since its logical state can be altered by both intrinsic noise and by the interaction with natural radiation. In this paper we […]
Recent advancements have highlighted the limitations of current quantum systems, particularly the restricted number of qubits available on near-term quantum devices. This constraint greatly inhibits the range of applications that can leverage quantum computers. Moreover, as the available qubits increase, the computational complexity grows exponentially, posing additional challenges. Consequently, there is an urgent need to […]
The light’s image is the primary source of information carrier in nature. Indeed, a single photon’s image possesses a vast information capacity that can be harnessed for quantum information processing. Our scheme for implementing quantum information processing on a discretized photon wavefront via universal multiport processors employs a class of quantum Fourier optical systems composed […]
Quantum computers present a compelling platform for the study of open quantum systems, namely, the nonunitary dynamics of a system. Here, we investigate and report digital simulations of Markovian nonunitary dynamics that converge to a unique steady state. The steady state is programmed as a desired target state, yielding semblance to a quantum state preparation […]
The widespread use of machine learning has raised the question of quantum supremacy for supervised learning as compared to quantum computational advantage. In fact, a recent work shows that computational and learning advantages are, in general, not equivalent, i.e., the additional information provided by a training set can reduce the hardness of some problems. This […]
The widespread use of machine learning has raised the question of quantum supremacy for supervised learning as compared to quantum computational advantage. In fact, a recent work shows that computational and learning advantages are, in general, not equivalent, i.e., the additional information provided by a training set can reduce the hardness of some problems. This […]
While quantum computers provide exciting opportunities for information processing, they currently suffer from noise during computation that is not fully understood. Incomplete noise models have led to discrepancies between quantum program success rate (SR) estimates and actual machine outcomes. For example, the estimated probability of success (ESP) is the state-of-the-art metric used to gauge quantum […]