Related papers: Machine Learning Enables Optimization of Diamond f…
Here we will give a perspective on new possible interplays between Machine Learning and Quantum Physics, including also practical cases and applications. We will explore the ways in which machine learning could benefit from new quantum…
Single nitrogen vacancy (NV) centers in diamond have been used extensively for high-sensitivity nanoscale sensing, but conventional approaches use confocal microscopy to measure individual centers sequentially, limiting throughput and…
Quantum machine learning aims to release the prowess of quantum computing to improve machine learning methods. By combining quantum computing methods with classical neural network techniques we aim to foster an increase of performance in…
There has been rapidly growing interest in hybrid quantum devices involving a solid-state spin and a macroscopic mechanical oscillator. Such hybrid devices create exciting opportunities to mediate interactions between disparate qubits and…
The interplay between ion beam modification techniques in the MeV range and the controlled generation of negatively charged nitrogen-vacancy (NV-) centers in nitrogen-doped synthetic diamond crystals is explored. An experimental approach…
Quantum technologies promise secure communication networks and powerful new forms of information processing, but building these systems at scale remains a major challenge. Diamond is an especially attractive material for quantum devices…
Quantum machine learning with quantum kernels for classification problems is a growing area of research. Recently, quantum kernel alignment techniques that parameterise the kernel have been developed, allowing the kernel to be trained and…
The negatively-charged nitrogen-vacancy (NV-) center in diamond is the focus of widespread attention for applications ranging from quantum information processing to nanoscale metrology. Although most work so far has focused on the NV-…
Engineering coherent systems is a central goal of quantum science. Color centers in diamond are a promising approach, with the potential to combine the coherence of atoms with the scalability of a solid state platform. However, the solid…
Atomic level qubits in silicon are attractive candidates for large-scale quantum computing, however, their quantum properties and controllability are sensitive to details such as the number of donor atoms comprising a qubit and their…
Quantum machine learning (QML) leverages the potential from machine learning to explore the subtle patterns in huge datasets of complex nature with quantum advantages. This exponentially reduces the time and resources necessary for…
Current quantum systems have significant limitations affecting the processing of large datasets with high dimensionality, typical of high energy physics. In the present paper, feature and data prototype selection techniques were studied to…
The Nitrogen-Vacancy (NV) defect in diamond is a unique quantum system that offers precision sensing of nanoscale physical quantities beyond the current state-of-the-art. Here we present a method to controllably encode the interactions in…
Nitrogen-vacancy (NV) and silicon-vacancy (SiV) color defects in diamond are promising systems for applications in quantum technology. The NV and SiV centers have multiple charge states, and their charge states have different electronic,…
Nitrogen-vacancy (NV) centers in diamond have attracted significant interest because of their excellent spin and optical characteristics for quantum information and metrology. To take advantage of the characteristics, the precise control of…
Solid state spin qubits are promising candidates for quantum information processing, but controlled interactions and entanglement in large, multi-qubit systems are currently difficult to achieve. We describe a method for programmable…
Sensing based on Nitrogen-Vacancy (NV) centers in nanodiamonds (NDs) offers significant potential across various applications. However, optimizing their quantum-optical properties remains challenging. This study focuses on enhancing and…
Sensitive nanoscale magnetic resonance imaging (MRI) of target spins using nitrogen-vacancy (NV) centers in diamond will require a quantitative understanding of dominant noise at the surface. We probe this noise by applying dynamical…
Quantum matter, the research field studying phases of matter whose properties are intrinsically quantum mechanical, draws from areas as diverse as hard condensed matter physics, materials science, statistical mechanics, quantum information,…
Precise coherent control of the individual electronic spins associated with atom-like impurities in the solid state is essential for applications in quantum information processing and quantum metrology. We demonstrate all-optical…