activity
20232026
most citedMachine Learning for Improved Current Density Reconstruction from 2D Vector Magnetic Images

11 citations · 11 across the 4 of their papers we have counts for

collaborators

5 papers

physics.comp-ph2026

Principles and Techniques for Agentic Research in Experimental Physics

Niko R. Reed, Declan M. Daly, Andrew J. Beling +4

The use of artificial intelligence (AI) in physics research is increasingly common, yet few guidelines exist for its effective use. Starting with a principles-based approach, we ou…

quant-ph2025

Towards Quantum Limited Spatial Resolution of NV-Diamond Magnetometry

Nico Deshler, Declan Daly, Ayan Majumder +2

Optically addressable ensembles of solid-state defects, such as nitrogen vacancy (NV) centers, are a leading modality for imaging-based magnetometry, thermometry and strain sensing…

quant-ph2025

Prospects for Ultralow-Mass Nuclear Magnetic Resonance using Spin Defects in Hexagonal Boron Nitride

Declan M. Daly, Niko R. Reed, Stephen J. DeVience +5

Optically active quantum defects in solids, such as the nitrogen vacancy (NV) center in diamond, are a leading modality for micron-scale and nanoscale (ultralow-mass) nuclear magne…

physics.comp-ph2024★ 11 cited

Machine Learning for Improved Current Density Reconstruction from 2D Vector Magnetic Images

Niko R. Reed, Danyal Bhutto, Matthew J. Turner +8

The reconstruction of electrical current densities from magnetic field measurements is an important technique with applications in materials science, circuit design, quality contro…

quant-ph2023

Nutation-Based Longitudinal Sensing Protocols for High-Field NMR With Nitrogen-Vacancy Centers in Diamond

Declan Daly, Stephen J. DeVience, Emma Huckestein +3

Nitrogen vacancy (NV) centers in diamond enable nuclear magnetic resonance (NMR) spectroscopy of samples at the nano- and micron scales. However, at typical tesla-scale NMR magneti…