Related papers: Machine Learning Enables Optimization of Diamond f…
A novel numerical methodology has been developed, which makes possible to optimize arbitrary emitting dipole and plasmonic nano-resonator configuration with an arbitrary objective function. By selecting quantum efficiency as the objective…
In recent years, nitrogen-vacancy (NV) color centers in diamond have become excellent solid-state quantum sensors due to their electronic spin properties. Especially for their easy optical initialization and detection, together with their…
The rapid growth of computer vision and increasingly complex image recognition tasks has exposed fundamental computational limitations of classical machine learning models, motivating the exploration of quantum computing as an emerging new…
Quantum networks can enable long-range quantum communication and modular quantum computation. A powerful approach is to use multi-qubit network nodes which provide the quantum memory and computational power to perform entanglement…
We employ so-called quantum kernel estimation to exploit complex quantum dynamics of solid-state nuclear magnetic resonance for machine learning. We propose to map an input to a feature space by input-dependent Hamiltonian evolution, and…
The engineering of defects in diamond, particularly nitrogen-vacancy (NV) centers, is important for many applications in quantum science. A materials science approach based on chemical vapor deposition (CVD) growth of diamond and in-situ…
Process refinement to consistently produce high-quality material over a large area of the grown crystal, enabling various applications from optics crystals to quantum detectors, has long been a goal for diamond growth. Machine learning…
This study utilises linear-scaling density functional theory (DFT) and develops a new machine-learning potential for carbon and nitrogen (GAP-CN), based on the carbon potential (GAP20), to investigate the interaction between carbon…
Quantum sensing with solid-state spin defects has transformed nanoscale metrology, offering sub-wavelength spatial resolution with exceptional sensitivity to multiple signal types. Maximizing these advantages requires minimizing both the…
We introduce scalable machine learning models to accurately predict two key quantum transport properties, the transmission coefficient T(E) and average local density of states (Average-LDOS) in two-dimensional (2D) hexagonal materials with…
Spin squeezed states provide a seminal example of how the structure of quantum mechanical correlations can be controlled to produce metrologically useful entanglement. Such squeezed states have been demonstrated in a wide variety of…
Wide-field imaging of magnetic signals using ensembles of nitrogen-vacancy (NV) centers in diamond has garnered increasing interest due to its combination of micron-scale resolution, millimeter-scale field of view, and compatibility with…
We introduce an algorithm that is able to find the facets of Coulomb diamonds in quantum dot arrays. We simulate these arrays using the constant-interaction model, and rely only on one-dimensional raster scans (rays) to learn a model of the…
We explore the utility of quantum spin squeezing in quantum magnetometry, focusing on three-level (qutrit) Nitrogen-Vacancy (NV) centers within diamond, utilizing a standard Ramsey interferometry pulse protocol. Our investigation…
Solid-state electron spin qubits, like the nitrogen-vacancy center in diamond, rely on control sequences of population inversion to enhance sensitivity and improve device coherence. But even for this paradigmatic system, the fundamental…
In recent years, the field of quantum sensing has garnered increasing attention due to its potential to revolutionize various scientific and technological domains. Among the different quantum sensors, the nitrogen-vacancy (NV) color center…
Nitrogen vacancy centers in diamond are among the leading solid state quantum platforms, offering exceptional spatial resolution and sensitivity for applications such as magnetic field sensing, thermometry, and bioimaging. However, in high…
The nitrogen-vacancy (NV) center in diamond has become a widely used platform for quantum sensing. The four NV axes in mono-crystalline diamond specifically allow for vector magnetometry, with magnetic-field sensitivities reaching down to…
Nitrogen-Vacancy (NV) color centers in diamond have emerged as promising quantum solid-state systems, with applications ranging from quantum information processing to magnetic sensing. One of the most useful properties of NVs is the ability…
For a practical quantum key distribution (QKD) system, parameter optimization - the choice of intensities and probabilities of sending them - is a crucial step in gaining optimal performance, especially when one realistically considers…