Who Let the Diamonds Out?
- URL: http://arxiv.org/abs/2509.19179v2
- Date: Fri, 10 Oct 2025 19:13:33 GMT
- Title: Who Let the Diamonds Out?
- Authors: Vincent Halde, Olivier Bernard, Mathieu Brochu, Laurier Dufresne, Nicolas Fleury, Kayla Johnson, Benjamin Moffett, David Roy-Guay,
- Abstract summary: Nitrogen-Vacancy (NV) center magnetometry is a highly promising quantum sensing technology.<n>We introduce a fully portable, hand-held NV-based magnetometer that delivers a vector sensitivity of approximately 400 pT/sqrt(Hz)
- Score: 0.5387033080274478
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Nitrogen-Vacancy (NV) center magnetometry is a highly promising quantum sensing technology, with early prototypes demonstrating impressive sensitivity in compact sensing heads. Yet, most existing implementations remain tied to laboratory setups, lacking the portability and environmental robustness needed to unlock their full potential in real-world applications. In this work, we introduce a fully portable, hand-held NV-based magnetometer that delivers a vector sensitivity of approximately 400 pT/sqrt(Hz), heading errors below 5 nT in Earth's field, and a wide signal bandwidth that supports on-field recalibration and operation on moving platforms. We further demonstrate the system's technological maturity through environmental qualification such as thermal, vibration, radiation and other operational stresses related to deployment in low Earth orbit, and through successful deployments in demanding scenarios, including northern Canadian weather conditions, drone-mounted surveys and high-altitude balloon flights. Together, these achievements establish this NV-based magnetometer as a robust, versatile tool ready to bring quantum sensing performance to a broad range of field and autonomous applications.
Related papers
- A Fully-integrated Diamond Nitrogen-Vacancy Magnetometer with Nanotesla Sensitivity [6.235588868921862]
This study introduces a fully integrated DNV magnetometer that encompasses all the essential components typically found in traditional platforms.<n>In contrast to previous efforts, we successfully address these challenges by integrating a high-power laser, a lock-in amplifier, and a digitally-modulated microwave source.<n>These home-made components show comparable performance with commercial devices under our circumstance, resulting in an optimal sensitivity of 2.14 nT/sqrtHz.
arXiv Detail & Related papers (2025-08-05T09:06:45Z) - Training on the Fly: On-device Self-supervised Learning aboard Nano-drones within 20 mW [52.280742520586756]
Miniaturized cyber-physical systems (CPSes) powered by tiny machine learning (TinyML), such as nano-drones, are becoming an increasingly attractive technology.
Simple electronics make these CPSes inexpensive, but strongly limit the computational, memory, and sensing resources available on board.
We present a novel on-device fine-tuning approach that relies only on the limited ultra-low power resources available aboard nano-drones.
arXiv Detail & Related papers (2024-08-06T13:11:36Z) - Automatic Detection of Nuclear Spins at Arbitrary Magnetic Fields via Signal-to-Image AI Model [0.0]
We present a signal-to-image deep learning model capable of automatically inferring the number of nuclear spins surrounding a NV sensor.
Our model is trained to operate effectively across various magnetic field scenarios, requires no prior knowledge of the involved nuclei, and is designed to handle noisy signals.
arXiv Detail & Related papers (2023-11-25T14:18:38Z) - Robotic vectorial field alignment for spin-based quantum sensors [2.8770761243361593]
We show that a robotic arm equipped with a magnet can sensitise an NV centre quantum magnetometer in challenging conditions unachievable with standard techniques.
Our work opens up the prospect of integrating across many quantum degrees of freedom in constrained settings.
arXiv Detail & Related papers (2023-05-26T15:36:24Z) - Ultra-low Power Deep Learning-based Monocular Relative Localization
Onboard Nano-quadrotors [64.68349896377629]
This work presents a novel autonomous end-to-end system that addresses the monocular relative localization, through deep neural networks (DNNs), of two peer nano-drones.
To cope with the ultra-constrained nano-drone platform, we propose a vertically-integrated framework, including dataset augmentation, quantization, and system optimizations.
Experimental results show that our DNN can precisely localize a 10cm-size target nano-drone by employing only low-resolution monochrome images, up to 2m distance.
arXiv Detail & Related papers (2023-03-03T14:14:08Z) - All-Optical Nuclear Quantum Sensing using Nitrogen-Vacancy Centers in
Diamond [52.77024349608834]
Microwave or radio-frequency driving poses a significant limitation for miniaturization, energy-efficiency and non-invasiveness of quantum sensors.
We overcome this limitation by demonstrating a purely optical approach to coherent quantum sensing.
Our results pave the way for highly compact quantum sensors to be employed for magnetometry or gyroscopy applications.
arXiv Detail & Related papers (2022-12-14T08:34:11Z) - Environmental Sensor Placement with Convolutional Gaussian Neural
Processes [65.13973319334625]
It is challenging to place sensors in a way that maximises the informativeness of their measurements, particularly in remote regions like Antarctica.
Probabilistic machine learning models can suggest informative sensor placements by finding sites that maximally reduce prediction uncertainty.
This paper proposes using a convolutional Gaussian neural process (ConvGNP) to address these issues.
arXiv Detail & Related papers (2022-11-18T17:25:14Z) - Autonomous Aerial Robot for High-Speed Search and Intercept Applications [86.72321289033562]
A fully-autonomous aerial robot for high-speed object grasping has been proposed.
As an additional sub-task, our system is able to autonomously pierce balloons located in poles close to the surface.
Our approach has been validated in a challenging international competition and has shown outstanding results.
arXiv Detail & Related papers (2021-12-10T11:49:51Z) - Zero- and Low-Field Sensing with Nitrogen Vacancy Centers [0.0]
nitrogen vacancy (NV) centers in diamond are easily accessible and precise magnetic field sensors.
We exploit the full spin $S=1$ nature of the NV center, allowing us to detect nuclear spin signals at zero- and low-field.
Our work allows for much broader and simpler applications of NV centers as magnetic field sensors in the zero- and low-field regime.
arXiv Detail & Related papers (2021-07-22T09:29:18Z) - Optimal control of a nitrogen-vacancy spin ensemble in diamond for
sensing in the pulsed domain [52.77024349608834]
Defects in solid state materials provide an ideal platform for quantum sensing.
Control of such an ensemble is challenging due to the spatial variation in both the defect energy levels and in any control field across a macroscopic sample.
We experimentally demonstrate that we can overcome these challenges using Floquet theory and optimal control optimization methods.
arXiv Detail & Related papers (2021-01-25T13:01:05Z) - Integrated and portable magnetometer based on nitrogen-vacancy ensembles
in diamond [0.0]
Negatively charged nitrogen-vacancy centers in diamond have emerged as a promising high sensitivity platform for measuring magnetic fields at room temperature.
Here, we demonstrate a fiber-based NV magnetometer featuring a complete integration of all functional components without using any bulky laboratory equipment.
arXiv Detail & Related papers (2020-12-02T09:49:23Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.