Since people became aware of the power of quantum phenomena in the domain of traditional computation, a great number of complex problems that were once considered intractable in the classical world have been tackled. The downsides of quantum supremacy are its high cost and unpredictability. Numerous researchers are relying on quantum simulators running on classical […]
The escalating threat and impact of network-based attacks necessitate innovative intrusion detection systems. Machine learning has shown promise, with recent strides in quantum machine learning offering new avenues. However, the potential of quantum computing is tempered by challenges in current noisy intermediate-scale quantum era machines. In this article, we explore quantum neural networks (QNNs) for […]
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 […]
A limited number of qubits, high error rates, and limited qubit connectivity are major challenges for effective near-term quantum computations. Quantum circuit partitioning divides a quantum computation into classical postprocessing steps and a set of smaller scale quantum computations that individually require fewer qubits, lower qubit connectivity, and typically incur less error. However, as partitioning […]
A limited number of qubits, high error rates, and limited qubit connectivity are major challenges for effective near-term quantum computations. Quantum circuit partitioning divides a quantum computation into classical postprocessing steps and a set of smaller scale quantum computations that individually require fewer qubits, lower qubit connectivity, and typically incur less error. However, as partitioning […]
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 […]
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 […]
This article examines the current status of quantum computing (QC) in Earth observation and satellite imagery. We analyze the potential limitations and applications of quantum learning models when dealing with satellite data, considering the persistent challenges of profiting from quantum advantage and finding the optimal sharing between high-performance computing (HPC) and QC. We then assess […]
This article examines the current status of quantum computing (QC) in Earth observation and satellite imagery. We analyze the potential limitations and applications of quantum learning models when dealing with satellite data, considering the persistent challenges of profiting from quantum advantage and finding the optimal sharing between high-performance computing (HPC) and QC. We then assess […]
In portfolio theory, the investment portfolio optimization problem is one of those problems whose complexity grows exponentially with the number of assets. By backtesting classical and quantum computing algorithms, we can get a sense of how these algorithms might perform in the real world. This work establishes a methodology for backtesting classical and quantum algorithms […]