Presents corrections to the article “The Present and Future of Discrete Logarithm Problems on Noisy Quantum Computers”. For more about this article see link below. https://ieeexplore.ieee.org/document/10185464 For the open access PDF link of this article please click.
We apply quantum error mitigation (QEM) techniques to a variety of benchmark problems and quantum computers to evaluate the performance of QEM in practice. To do so, we define an empirically motivated, resource-normalized metric of the improvement of error mitigation, which we call the improvement factor, and calculate this metric for each experiment we perform. […]
Noisy intermediate-scale quantum computers are widely used for quantum computing (QC) from quantum cloud providers. Among them, superconducting quantum computers, with their high scalability and mature processing technology based on traditional silicon-based chips, have become the preferred solution for most commercial companies and research institutions to develop QC. However, superconducting quantum computers suffer from fluctuation […]
The noise and complexity inherent to quantum communication networks leads to technical challenges in designing quantum network protocols using classical methods. We address this issue with a hybrid variational quantum optimization (VQO) framework that simulates quantum networks on quantum hardware and optimizes the simulation using differential programming. We maximize nonlocality in noisy quantum networks to […]
Noisy intermediate-scale quantum algorithms, which run on noisy quantum computers, should be carefully designed to boost the output state fidelity. While several compilation approaches have been proposed to minimize circuit errors, they often omit the detailed circuit structure information that does not affect the circuit depth or the gate count. In the presence of spatial […]
Combinatorial optimization on near-term quantum devices is a promising path to demonstrating quantum advantage. However, the capabilities of these devices are constrained by high noise or error rates. In this article, inspired by the variational quantum eigensolver (VQE), we propose an iterative layer VQE (L-VQE) approach. We present a large-scale numerical study, simulating circuits with […]
We determine the resource scaling of machine learning-based quantum state reconstruction methods, in terms of inference and training, for systems of up to four qubits when constrained to pure states. Further, we examine system performance in the low-count regime, likely to be encountered in the tomography of high-dimensional systems. Finally, we implement our quantum state […]
In developing the global quantum Internet, quantum communication with low-earth-orbit satellites will play a pivotal role. Such communication will need to be two way: effective not only in the satellite-to-ground (downlink) channel but also in the ground-to-satellite channel (uplink). Given that losses on this latter channel are significantly larger relative to the former, techniques that […]
Exact requirement of controlled NOT (CNOT) and single-qubit gates to implement a quantum algorithm in a given architecture is one of the central problems in this computational paradigm. In this article, we take a tutorial approach in explaining the preparation of Dicke states (|D k n 〉) using concise realizations of partially defined unitary transformations. We show how […]
Solving combinatorial optimization problems on current noisy quantum devices is currently being advocated for (and restricted to) binary polynomial optimization with equality constraints via quantum heuristic approaches. This is achieved using, for example, the variational quantum eigensolver (VQE) and the quantum approximate optimization algorithm (QAOA). In this article, we present a decomposition-based approach to extend […]