Identifying Hamiltonian of a quantum system is of vital importance for quantum information processing. In this Letter, we realized and benchmarked a quantum Hamiltonian identification algorithm recently proposed [Phys. Rev. Lett. 113, 080401 (2014)]. we realized the algorithm on liquid nuclear magnetic resonance quantum information processor using two different working media with different forms of Hamiltonian. Our experiment realized the quantum identification algorithm based on free induction decay signals. We also showed how to process data obtained in practical experiment. We studied the influence of decoherence by numerical simulations. Our experiments and simulations demonstrate that the algorithm is effective and robust. Introduction.-One critical task is to characterize a quantum system so that it can be used for quantum information processing tasks, such as quantum teleportation [1], quantum cryptography [2,3], quantum computation [4,5] and quantum metrology [6]. One way of fully characterizing a quantum system is doing quantum processing tomography (QPT). The QPT approach requires an exponential number of experiments, which makes it difficult to be realized for even a small sized quantum system [7][8][9][10].
SpinQ Gemini is a commercial desktop quantum computing platform designed and manufactured by SpinQ Technology. It is an integrated hardware-software system. The first generation product with two qubits was launched in January 2020. The hardware is based on NMR spectrometer, with permanent magnets providing ∼1 T magnetic field. SpinQ Gemini operates under room temperature (0–30°C), highlighting its lightweight (55 kg with a volume of $70\times 40 \times 80\text{ cm}^{3}$ 70 × 40 × 80 cm 3 ), cost-effective (under 50k USD), and maintenance-free. SpinQ Gemini aims to provide real-device experience for quantum computing education for K-12 and at the college level. It also features quantum control design capabilities that benefit the researchers studying quantum control and quantum noise. Since its first launch, SpinQ Gemini has been shipped to institutions in Canada, Taiwan and Mainland China. This paper introduces the system of design of SpinQ Gemini, from hardware to software. We also demonstrate examples for performing quantum computing tasks on SpinQ Gemini, including one task for a variational quantum eigensolver of a two-qubit Heisenberg model. The next generations of SpinQ quantum computing devices will adopt models of more qubits, advanced control functions for researchers with comparable cost, as well as simplified models for much lower cost (under 5k USD) for K-12 education. We believe that low-cost portable quantum computing products will facilitate hands-on experience for teaching quantum computing at all levels, well-prepare younger generations of students and researchers for the future of quantum technologies.
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