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We present a scheme for linear optical quantum computation (LOQC) which is highly robust to imperfect single photon sources and inefficient detectors. In particular we show that if the product of the detector efficiency with the source…
Qubits used in quantum computing tend to suffer from errors, either from the qubit interacting with the environment, or from imperfect control when quantum logic gates are applied. Fault-tolerant construction based on quantum error…
Quantum metrology is a promising application of quantum technologies, enabling the precise measurement of weak external fields at a local scale. In typical quantum sensing protocols, a qubit interacts with an external field, and the…
In this study, we investigate a simple quantum pre-processing filter kernel designed with only two CNOT gates for image feature extraction. We examine the impact of these filters when combined with a classical neural network for image…
Many applications of quantum optics demand delicate quantum properties of light carefully tailored to accomplish a specific task. To this end, numerical simulations of quantum light sources are vital for designing, characterizing, and…
Most of the correlation filter based tracking algorithms can achieve good performance and maintain fast computational speed. However, in some complicated tracking scenes, there is a fatal defect that causes the object to be located…
Nonlinear spectroscopy with quantum entangled photons is an emerging field of research that holds the promise to achieve a superior signal-to-noise ratio and effectively isolate many-body interactions. Photon sources used for this purpose…
We propose a novel method to significantly enhance the signal rate in qubit-based dark matter detection experiments with the help of quantum interference. Various quantum sensors possess ideal properties for detecting wave-like dark matter,…
Chip-integrated photon-pair sources based on spontaneous parametric down-conversion (SPDC) have emerged as a promising solution for scalable quantum light generation. Thin-film lithium tantalate (TFLT) is a compelling $\chi^{(2)}$ platform,…
We discuss the conditional measurement of field amplitudes by a nonclassical photon sequence in the Jaynes-Cummings (JC) model under multiphoton operation. We do so by employing a correlator of immediate experimental relevance to reveal a…
Quantum computing has made remarkable strides in recent years, as demonstrated by quantum supremacy experiments and the realization of high-fidelity, fault-tolerant gates. However, a major obstacle persists: practical real-world…
Network motif identification problem aims to find topological patterns in biological networks. Identifying non-overlapping motifs is a computationally challenging problem using classical computers. Quantum computers enable solving high…
Imaging with quantum states of light promises advantages over classical approaches in terms of resolution, signal-to-noise ratio and sensitivity. However, quantum detectors are particularly sensitive sources of classical noise that can…
We present a scheme for tuning two quantum point contacts as a quantum-limited charge detector. Based on the scattering matrix approach, we analyze a general condition of quantum-limited detection with a single-channel quantum detector…
Estimating the quality of a single-photon source is crucial for its use in quantum technologies. The standard test for semiconductor sources is a value of the second-order correlation function of the emitted field below $1/2$ at zero…
Searches for signals of new physics in particle physics are usually done by training a supervised classifier to separate a signal model from the known Standard Model physics (also called the background model). However, even when the signal…
Detecting object with low reflectivity embedded within a noisy background is a challenging task. Quantum correlations between pairs of quantum states of light, though are highly sensitive to background noise and losses, offer advantages…
Sensors for mapping the trajectory of an incoming particle find important utility in experimental high energy physics and searches for dark matter. For a quantum sensing protocol that uses projective measurements on a multi-qubit sensor…
Feature selection plays an essential role in improving the predictive performance and interpretability of trained models in classical machine learning. On the other hand, the usability of conventional feature selection could be limited for…
Multi-photon interference is at the heart of photonic quantum technologies. Arrays of integrated cavities can support bright sources of single-photons with high purity and small footprint, but the inevitable spectral distinguishability…