相关论文: Efficient real-time spin readout of nitrogen-vacan…

In this article, we propose a novel method for sampling potential functions based on noisy observation data of a finite number of observables in quantum canonical ensembles, which leads to the accurate sampling of a wide class of test…

In many instances, the application of approximate Bayesian methods is hampered by two practical features: 1) the requirement to project the data down to low-dimensional summary, including the choice of this projection, which ultimately…

Bayesian methods for low-rank matrix completion with noise have been shown to be very efficient computationally. While the behaviour of penalized minimization methods is well understood both from the theoretical and computational points of…

A crucial task in predictive maintenance is estimating the remaining useful life of physical systems. In the last decade, deep learning has improved considerably upon traditional model-based and statistical approaches in terms of predictive…

Optical detection of spin state has been widely used for the solid state spin qubit in the application of quantum information processing. The signal contrast determines the accuracy of quantum state manipulation, sensitivity of quantum…

We utilize nonlinear absorption to design all-optical protocols that improve both charge state initialization and spin readout for the nitrogen-vacancy (NV) center in diamond. Non-monotonic variations in the equilibrium charge state as a…

Quantum sensors, such as the Nitrogen Vacancy (NV) color center in diamond, are known for their exquisite sensitivity, but their performance over time are subject to degradation by environmental noise. To improve the long-term robustness of…

We present a technique that uses an ensemble of nitrogen-vacancy (NV) centers in diamond to image magnetic fields with high spatio-temporal resolution and sensitivity. A focused laser beam is raster-scanned using an acousto-optic deflector…

Machine learning is a powerful tool in finding hidden data patterns for quantum information processing. Here, we introduce this method into the optical readout of electron-spin states in diamond via single-photon collection and demonstrate…

Randomized experiments are the gold standard for evaluating the effects of changes to real-world systems. Data in these tests may be difficult to collect and outcomes may have high variance, resulting in potentially large measurement error.…

Bayesian inference is an effective approach for solving statistical learning problems especially with uncertainty and incompleteness. However, inference efficiencies are physically limited by the bottlenecks of conventional computing…

Nitrogen-vacancy centers in diamond allow for coherent spin state manipulation at room temperature, which could bring dramatic advances to nanoscale sensing and quantum information technology. We introduce a novel method for the optical…

Bayesian method is capable of capturing real world uncertainties/incompleteness and properly addressing the over-fitting issue faced by deep neural networks. In recent years, Bayesian Neural Networks (BNNs) have drawn tremendous attentions…

Sensing of signals from biological processes, such as action potential propagation in nerves, are essential for clinical diagnosis and basic understanding of physiology. Sensing can be performed electrically by placing sensor probes near or…

We propose a restricted win probability estimand for comparing treatments in a randomized trial with a time-to-event outcome. We also propose Bayesian estimators for this summary measure as well as the unrestricted win probability. Bayesian…

RANSAC-based algorithms are the standard techniques for robust estimation in computer vision. These algorithms are iterative and computationally expensive; they alternate between random sampling of data, computing hypotheses, and running…

We present BAE, a problem-tailored and noise-aware Bayesian algorithm for quantum amplitude estimation. In a fault tolerant scenario, BAE is capable of saturating the Heisenberg limit; if device noise is present, BAE can dynamically…

We propose and theoretically analyze the use of coherent population trapping of a single diamond nitrogen vacancy (NV) center for continuous real-time sensing. The formation of the dark state in coherent population trapping prevents optical…

Efficient readout of nitrogen-vacancy (NV) centers in diamond is crucial for various quantum information technologies. However, achieving high-fidelity, single-shot readout at room temperature remains challenging due to limited photon…

We present Sequential Neural Variational Inference (SNVI), an approach to perform Bayesian inference in models with intractable likelihoods. SNVI combines likelihood-estimation (or likelihood-ratio-estimation) with variational inference to…