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Nitrogen vacancy (NV) centers in diamond have emerged as a leading quantum sensor platform, combining exceptional sensitivity with nanoscale spatial resolution by optically detected magnetic resonance (ODMR). Because fluorescence-based ODMR…
Diamond colour centres are promising optically-addressable solid state spins that can be matter-qubits, mediate deterministic interaction between photons and act as single photon emitters. Useful quantum computers will comprise millions of…
Quantum sensing exploits the strong sensitivity of quantum systems to measure small external signals. The nitrogen-vacancy (NV) center in diamond is one of the most promising platforms for real-world quantum sensing applications,…
The negatively charged nitrogen-vacancy (NV) center spin in diamond can be used to realize quantum computation and to sense magnetic fields. Its spin triplet consists of three levels labeled with its spin z-components of +1, 0, and -1.…
We investigate native nitrogen (NV) and silicon vacancy (SiV) color centers in commercially available, heteroepitaxial, wafer-sized, mm thick, single-crystal diamond. We observe single, native NV centers with a density of roughly 1 NV per…
Quantum computing leverages quantum effects to build algorithms that are faster then their classical variants. In machine learning, for a given model architecture, the speed of training the model is typically determined by the size of the…
Nitrogen vacancy (NV) centers in diamond have distinct promise as solid-state qubits. This is because of their large dipole moment, convenient level structure and very long room-temperature coherence times. In general, a combination of ion…
A central aim of quantum information processing is the efficient entanglement of multiple stationary quantum memories via photons. Among solid-state systems, the nitrogen-vacancy (NV) centre in diamond has emerged as an excellent optically…
Crystal strain variation imposes significant limitations on many quantum sensing and information applications for solid-state defect qubits in diamond. Thus, precision measurement and control of diamond crystal strain is a key challenge.…
Quantum simulators offer the potential to utilize the quantum nature of a physical system to study another physical system. In contrast to conventional simulation, which experiences an exponential increase in computational complexity,…
The nitrogen-vacancy (NV) center in diamond is a promising quantum system for magnetometry applications exhibiting optical readout of minute energy shifts in its spin sub-levels. Key material requirements for NV ensembles are a high NV$^-$…
Quantum machine learning is a rapidly growing field at the intersection of quantum computing and machine learning. In this work, we examine our quantum machine learning models, which are based on quantum support vector classification (QSVC)…
Diamond photonics is an ever growing field of research driven by the prospects of harnessing diamond and its colour centres as suitable hardware for solid-state quantum applications. The last two decades have seen the field been shaped by…
Optically active color centers in nanodiamonds offer unique opportunities for generating and manipulating quantum states of light. These mechanically, chemically, and optically robust emitters can be produced in mass quantities,…
Machine learning and quantum computing are two technologies each with the potential for altering how computation is performed to address previously untenable problems. Kernel methods for machine learning are ubiquitous for pattern…
We show that nitrogen-vacancy (NV) centers in diamond can produce a novel quantum hyperbolic metamaterial. We demonstrate that a hyperbolic dispersion relation in diamond with NV centers can be engineered and dynamically tuned by applying a…
As a potential candidate for quantum computation and metrology, the nitrogen vacancy (NV)center in diamond presented both challenges and opportunities resulted from charge state conversion. By utilizing different lasers for the…
The last two decades have seen an explosive growth in the theory and practice of both quantum computing and machine learning. Modern machine learning systems process huge volumes of data and demand massive computational power. As silicon…
Hybrid quantum devices, in which disparate quantum elements are combined in order to achieve enhanced functionality, have received much attention in recent years due to their exciting potential to address key problems in quantum information…
Magnetometers based on quantum mechanical processes enable high sensitivity and long-term stability without the need for re-calibration, but their integration into fieldable devices remains challenging. This paper presents a CMOS quantum…