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Optimal control of qubits requires the ability to adapt continuously to their ever-changing environment. We demonstrate a real-time control protocol for a two-electron singlet-triplet qubit with two fluctuating Hamiltonian parameters. Our approach leverages single-shot readout classification and dynamic waveform generation, allowing full Hamiltonian estimation to dynamically stabilize and optimize the qubit performance. Powered by a field-programmable gate array (FPGA), the quantum control electronics estimates the Overhauser field gradient between the two electrons in real time, enabling controlled Overhauser-driven spin rotations and thus bypassing the need for micromagnets or nuclear polarization protocols. It also estimates the exchange interaction between the two electrons and adjusts their detuning, resulting in extended coherence of Hadamard rotations when correcting for fluctuations of both qubit axes. Our study highlights the role of feedback in enhancing the performance and stability of quantum devices affected by quasistatic noise.
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http://dx.doi.org/10.1038/s41467-024-45857-0 | DOI Listing |
Nat Commun
February 2024
Center for Quantum Devices, Niels Bohr Institute, University of Copenhagen, 2100, Copenhagen, Denmark.
Optimal control of qubits requires the ability to adapt continuously to their ever-changing environment. We demonstrate a real-time control protocol for a two-electron singlet-triplet qubit with two fluctuating Hamiltonian parameters. Our approach leverages single-shot readout classification and dynamic waveform generation, allowing full Hamiltonian estimation to dynamically stabilize and optimize the qubit performance.
View Article and Find Full Text PDFBiomed Opt Express
July 2023
Institute of Medical Device and Imaging, College of Medicine, National Taiwan University, No. 1, Sec. 1, Jen Ai Rd., Zhongzheng Dist., Taipei City 100, Taiwan.
Quantitative differential phase-contrast (DPC) imaging is one of the commonly used methods for phase retrieval. However, quantitative DPC imaging requires several pairwise intensity measurements, which makes it difficult to monitor living cells in real-time. In this study, we present a single-shot quantitative DPC imaging method based on the combination of deep learning (DL) and color-encoded illumination.
View Article and Find Full Text PDFCytometry A
November 2021
LMAM, School of Mathematical Sciences, Peking University, Beijing, China.
Caenorhabditis elegans (C. elegans) is an ideal model organism for studying neuronal functions at the system level. This article develops a customized system for whole-body motor neuron calcium imaging of freely moving C.
View Article and Find Full Text PDFSensors (Basel)
December 2020
State Key Lab of Digital Manufacturing Equipment & Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
In a tunneling boring machine (TBM), to obtain the attitude in real time is very important for a driver. However, the current laser targeting system has a large delay before obtaining the attitude. So, an adaptive-neuro-fuzzy-based information fusion method is proposed to predict the attitude of a laser targeting system in real time.
View Article and Find Full Text PDFJ Biophotonics
June 2020
MOE Key Laboratory of Laser Life Science & Institute of Laser Life Science, College of Biophotonics, South China Normal University, Guangzhou, China.
Photoacoustic microscopy (PAM) provides a new method for the imaging of small-animals with high-contrast and deep-penetration. However, the established PAM systems have suffered from a limited field-of-view or imaging speed, which are difficult to both monitor wide-field activity of organ and record real-time change of local tissue. Here, we reported a dual-raster-scanned photoacoustic microscope (DRS-PAM) that integrates a two-dimensional motorized translation stage for large field-of-view imaging and a two-axis fast galvanometer scanner for real-time imaging.
View Article and Find Full Text PDF