arXiv subjects

Matthew J. Turner

Publications and source records attributed to Matthew J. Turner.

At least 19 recordsLinked to original sources

arXiv2025

All-Optical Photoluminescence Response of Nitrogen-Vacancy Ensembles in Diamond at Low Magnetic Fields

All-optical (AO), microwave-free magnetometry using nitrogen-vacancy (NV) centers in diamond is attractive due to its broad sample compatibility and reduced experimental complexity. In this work, we investigate room-temperature AO photoluminescence (PL) at low magnetic fields (<2 mT) using diamonds with NV ensembles at ppm concentrations. Measured AO-PL contrast features as a function of applied magnetic field magnitude and direction are correlated with near-degenerate NV electronic spin and hyperfine transitions from different NV orientations within the diamond host. Reasonable agreement is found between low-field AO-PL measurements and model-based simulations of the effects of resonant dipolar interactions between NV centers. Maximum observed AO-PL contrast depends on both NV concentration and laser illumination intensity at 532 nm. These results imply different optimal conditions for low-field AO NV sensing compared to conventional optically detected magnetic resonance (ODMR) techniques, suggesting new research and application opportunities using AO measurements with lower system complexity, size, weight, and power.

quant-ph↗

arXiv2025

Technique Inference Engine: A Recommender Model to Support Cyber Threat Hunting

Cyber threat hunting is the practice of proactively searching for latent threats in a network. Engaging in threat hunting can be difficult due to the volume of network traffic, variety of adversary techniques, and constantly evolving vulnerabilities. To aid analysts in identifying techniques which may be co-occurring as part of a campaign, we present the Technique Inference Engine, a tool to infer tactics, techniques, and procedures (TTPs) which may be related to existing observations of adversarial behavior. We compile the largest (to our knowledge) available dataset of cyber threat intelligence (CTI) reports labeled with relevant TTPs. With the knowledge that techniques are chronically under-reported in CTI, we apply several implicit feedback recommender models to the data in order to predict additional techniques which may be part of a given campaign. We evaluate the results in the context of the cyber analyst's use case and apply t-SNE to visualize the model embeddings. We provide our code and a web interface.

cs.CR↗

arXiv2025

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

The reconstruction of electrical current densities from magnetic field measurements is an important technique with applications in materials science, circuit design, quality control, plasma physics, and biology. Analytic reconstruction methods exist for planar currents, but break down in the presence of high spatial frequency noise or large standoff distance, restricting the types of systems that can be studied. Here, we demonstrate the use of a deep convolutional neural network for current density reconstruction from two-dimensional (2D) images of vector magnetic fields acquired by a quantum diamond microscope (QDM) utilizing a surface layer of Nitrogen Vacancy (NV) centers in diamond. Trained network performance significantly exceeds analytic reconstruction for data with high noise or large standoff distances. This machine learning technique can perform quality inversions on lower SNR data, reducing the data collection time by a factor of about 400 and permitting reconstructions of weaker and three-dimensional current sources.

physics.comp-ph↗

arXiv2023

Quantum Diamond Microscope for Dynamic Imaging of Magnetic Fields

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 diverse samples from across the physical and life sciences. Recently, wide-field NV magnetic imaging based on the Ramsey protocol has achieved uniform and enhanced sensitivity compared to conventional measurements. Here, we integrate the Ramsey-based protocol with spin-bath driving to extend the NV spin dephasing time and improve magnetic sensitivity. We also employ a high-speed camera to enable dynamic wide-field magnetic imaging. We benchmark the utility of this quantum diamond microscope (QDM) by imaging magnetic fields produced from a fabricated wire phantom. Over a $270\times270 \hspace{0.08333em} μ\mathrm{m}$$^2$ field of view, a median per-pixel magnetic sensitivity of $4.1(1)\hspace{0.08333em}\mathrm{nT}$$/\sqrt{\mathrm{Hz}}$ is realized with a spatial resolution $\lesssim\hspace{0.08333em}10\hspace{0.08333em}μ\mathrm{m}$ and sub-millisecond temporal resolution. Importantly, the spatial magnetic noise floor can be reduced to the picotesla scale by time-averaging and signal modulation, which enables imaging of a magnetic-field pattern with a peak-to-peak amplitude difference of about $300\hspace{0.08333em}\mathrm{pT}$. Finally, we discuss potential new applications of this dynamic QDM in studying biomineralization and electrically-active cells.

quant-ph↗

arXiv2022

Scanning X-ray Diffraction Microscopy for Diamond Quantum Sensing

Understanding nano- and micro-scale crystal strain in CVD diamond is crucial to the advancement of diamond quantum technologies. In particular, the presence of such strain and its characterization present a challenge to diamond-based quantum sensing and information applications -- as well as for future dark matter detectors where directional information of incoming particles is encoded in crystal strain. Here, we exploit nanofocused scanning X-ray diffraction microscopy to quantitatively measure crystal deformation from defects in diamond with high spatial and strain resolution. Combining information from multiple Bragg angles allows stereoscopic three-dimensional modeling of strain feature geometry; the diffraction results are validated via comparison to optical measurements of the strain tensor based on spin-state-dependent spectroscopy of ensembles of nitrogen vacancy (NV) centers in the diamond. Our results demonstrate both strain and spatial resolution sufficient for directional detection of dark matter via X-ray measurement of crystal strain, and provide a promising tool for diamond growth analysis and improvement of defect-based sensing.

physics.app-ph↗

arXiv2022

High-precision mapping of diamond crystal strain using quantum interferometry

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. Here, we report diamond strain measurements with a unique set of capabilities, including micron-scale spatial resolution, millimeter-scale field-of-view, and a two order-of-magnitude improvement in volume-normalized sensitivity over previous work [1], reaching $5(2) \times 10^{-8}/\sqrt{\rm{Hz}\cdot\rm{μm}^3}$ (with spin-strain coupling coefficients representing the dominant systematic uncertainty). We use strain-sensitive spin-state interferometry on ensembles of nitrogen vacancy (NV) color centers in single-crystal CVD bulk diamond with low strain gradients. This quantum interferometry technique provides insensitivity to magnetic-field inhomogeneity from the electronic and nuclear spin bath, thereby enabling long NV ensemble electronic spin dephasing times and enhanced strain sensitivity. We demonstrate the strain-sensitive measurement protocol first on a scanning confocal laser microscope, providing quantitative measurement of sensitivity as well as three-dimensional strain mapping; and second on a wide-field imaging quantum diamond microscope (QDM). Our strain microscopy technique enables fast, sensitive characterization for diamond material engineering and nanofabrication; as well as diamond-based sensing of strains applied externally, as in diamond anvil cells or embedded diamond stress sensors, or internally, as by crystal damage due to particle-induced nuclear recoils.

quant-ph↗

arXiv2022

Ramsey Envelope Modulation in NV Diamond Magnetometry

Nitrogen-vacancy (NV) spin ensembles in diamond provide an advanced magnetic sensing platform, with applications in both the physical and life sciences. The development of isotopically engineered $^{15}$NV diamond offers advantages over naturally occurring $^{14}$NV for magnetometry, due to its simpler hyperfine structure. However, for sensing modalities requiring a bias magnetic field not aligned with the sensing NV axis, the absence of a quadrupole moment in the $^{15}$N nuclear spin leads to pronounced envelope modulation effects in time-dependent measurements of $^{15}$NV spin evolution. While such behavior in spin echo experiments are well studied, analogous effects in Ramsey measurements and the implications for magnetometry remain under-explored. Here, we derive the modulated $^{15}$NV Ramsey response to a misaligned bias field, using a simple vector description of the effective magnetic field on the nuclear spin. The predicted modulation properties are then compared to experimental results, revealing significant magnetic sensitivity loss if unaddressed. We demonstrate that double-quantum coherences of the NV $S=1$ electronic spin states dramatically suppress these envelope modulations, while additionally proving resilient to other parasitic effects such as strain heterogeneity and temperature shifts.

quant-ph↗

arXiv2022

Hardware Trojan Detection Using Unsupervised Deep Learning on Quantum Diamond Microscope Magnetic Field Images

This paper presents a method for hardware trojan detection in integrated circuits. Unsupervised deep learning is used to classify wide field-of-view (4x4 mm$^2$), high spatial resolution magnetic field images taken using a Quantum Diamond Microscope (QDM). QDM magnetic imaging is enhanced using quantum control techniques and improved diamond material to increase magnetic field sensitivity by a factor of 4 and measurement speed by a factor of 16 over previous demonstrations. These upgrades facilitate the first demonstration of QDM magnetic field measurement for hardware trojan detection. Unsupervised convolutional neural networks and clustering are used to infer trojan presence from unlabeled data sets of 600x600 pixel magnetic field images without human bias. This analysis is shown to be more accurate than principal component analysis for distinguishing between field programmable gate arrays configured with trojan free and trojan inserted logic. This framework is tested on a set of scalable trojans that we developed and measured with the QDM. Scalable and TrustHub trojans are detectable down to a minimum trojan trigger size of 0.5% of the total logic. The trojan detection framework can be used for golden-chip free detection, since knowledge of the chips' identities is only used to evaluate detection accuracy

cs.CV↗

arXiv2022

Vector Magnetic Current Imaging of an 8 nm Process Node Chip and 3D Current Distributions Using the Quantum Diamond Microscope

The adoption of 3D packaging technology necessitates the development of new approaches to failure electronic device analysis. To that end, our team is developing a tool called the quantum diamond microscope (QDM) that leverages an ensemble of nitrogen vacancy (NV) centers in diamond, achieving vector magnetic imaging with a wide field-of-view and high spatial resolution under ambient conditions. Here, we present the QDM measurement of 2D current distributions in an 8-nm flip chip IC and 3D current distributions in a multi-layer PCB. Magnetic field emanations from the C4 bumps in the flip chip dominate the QDM measurements, but these prove to be useful for image registration and can be subtracted to resolve adjacent current traces in the die at the micron scale. Vias in 3D ICs display only Bx and By magnetic fields due to their vertical orientation and are difficult to detect with magnetometers that only measure the Bz component (orthogonal to the IC surface). Using the multi-layer PCB, we show that the QDM's ability to simultaneously measure Bx, By, and Bz is advantageous for resolving magnetic fields from vias as current passes between layers. We also show how spacing between conducting layers is determined by magnetic field images and how it agrees with the design specifications of the PCB. In our initial efforts to provide further z-depth information for current sources in complex 3D circuits, we show how magnetic field images of individual layers can be subtracted from the magnetic field image of the total structure. This allows for isolation of signal layers and can be used to map embedded current paths via solution of the 2D magnetic inverse. In addition, the paper also discusses the use of neural networks to identify 2D current distributions and its potential for analyzing 3D structures.

physics.app-ph↗

arXiv2021

Multiplexed sensing of magnetic field and temperature in real time using a nitrogen vacancy spin ensemble in diamond

Nitrogen-Vacancy (NV) spin in diamond is a versatile quantum sensor, being able to measure physical quantities such as magnetic field, electric field, temperature, and pressure. In the present work, we demonstrate a multiplexed sensing of magnetic field and temperature. The dual frequency driving technique we employ here is based on frequency-division multiplexing, which enables sensing both measurables in real time. The pair of NV resonance frequencies for dual frequency driving must be selected to avoid coherent population trapping of NV spin states. With an enhanced optical collection efficiency higher than 50 $\%$ and a type 1b diamond crystal with natural abundance $^{13}$C spins, we achieve sensitivities of about 70 pT/$\sqrt{\mathrm{Hz}}$ and 25 $μ$K/$\sqrt{\mathrm{Hz}}$ simultaneously. A high isolation factor of 34 dB in NV thermometry signal against magnetic field was obtained, and we provide a theoretical description for the isolation factor. This work paves the way for extending the application of NV quantum diamond sensors into more demanding conditions.

quant-ph↗

arXiv2021

NV-Diamond Magnetic Microscopy using a Double Quantum 4-Ramsey Protocol

We introduce a double quantum (DQ) 4-Ramsey measurement protocol that enables wide-field magnetic imaging using nitrogen vacancy (NV) centers in diamond, with enhanced homogeneity of the magnetic sensitivity relative to conventional single quantum (SQ) techniques. The DQ 4-Ramsey protocol employs microwave-phase alternation across four consecutive Ramsey (4-Ramsey) measurements to isolate the desired DQ magnetic signal from any residual SQ signal induced by microwave pulse errors. In a demonstration experiment employing a 1-$μ$m-thick NV layer in a macroscopic diamond chip, the DQ 4-Ramsey protocol provides volume-normalized DC magnetic sensitivity of $η^\text{V}=34\,$nTHz$^{-1/2} μ$m$^{3/2}$ across a $125\,μ$m$ \,\times\,125\,μ$m field of view, with about 5$\times$ less spatial variation in sensitivity across the field of view compared to a SQ measurement. The improved robustness and magnetic sensitivity homogeneity of the DQ 4-Ramsey protocol enable imaging of dynamic, broadband magnetic sources such as integrated circuits and electrically-active cells.

quant-ph↗

arXiv2021

Directional detection of dark matter with diamond

Searches for WIMP dark matter will in the near future be sensitive to solar neutrinos. Directional detection offers a method to reject solar neutrinos and improve WIMP searches, but reaching that sensitivity with existing directional detectors poses challenges. We propose a combined atomic/particle physics approach using a large-volume diamond detector. WIMP candidate events trigger a particle detector, after which spectroscopy of nitrogen vacancy centers reads out the direction of the incoming particle. We discuss the current state of technologies required to realize directional detection in diamond and present a path towards a detector with sensitivity below the neutrino floor.

physics.ins-det↗

arXiv2020

Micron-scale SABRE-enhanced NV-NMR Spectroscopy

Optically-probed nitrogen-vacancy (NV) quantum defects in diamond can detect nuclear magnetic resonance (NMR) signals with high-spectral resolution from micron-scale sample volumes of about 10 picoliters. However, a key challenge for NV-NMR is detecting samples at millimolar concentrations. Here, we demonstrate an improvement in NV-NMR proton concentration sensitivity of about $10^5$ over thermal polarization by hyperpolarizing sample proton spins through signal amplification by reversible exchange (SABRE), enabling micron-scale NMR of small molecule sample concentrations as low as 1 millimolar in picoliter volumes. The SABRE-enhanced NV-NMR technique may enable detection and chemical analysis of low concentration molecules and their dynamics in complex micron-scale systems such as single-cells.

physics.app-ph↗

arXiv2020

Sensitivity Optimization for NV-Diamond Magnetometry

Solid-state spin systems including nitrogen-vacancy (NV) centers in diamond constitute an increasingly favored quantum sensing platform. However, present NV ensemble devices exhibit sensitivities orders of magnitude away from theoretical limits. The sensitivity shortfall both handicaps existing implementations and curtails the envisioned application space. This review analyzes present and proposed approaches to enhance the sensitivity of broadband ensemble-NV-diamond magnetometers. Improvements to the spin dephasing time, the readout fidelity, and the host diamond material properties are identified as the most promising avenues and are investigated extensively. Our analysis of sensitivity optimization establishes a foundation to stimulate development of new techniques for enhancing solid-state sensor performance.

quant-ph↗

arXiv2020

Magnetic Field Fingerprinting of Integrated Circuit Activity with a Quantum Diamond Microscope

Current density distributions in active integrated circuits (ICs) result in patterns of magnetic fields that contain structural and functional information about the IC. Magnetic fields pass through standard materials used by the semiconductor industry and provide a powerful means to fingerprint IC activity for security and failure analysis applications. Here, we demonstrate high spatial resolution, wide field-of-view, vector magnetic field imaging of static (DC) magnetic field emanations from an IC in different active states using a Quantum Diamond Microscope (QDM). The QDM employs a dense layer of fluorescent nitrogen-vacancy (NV) quantum defects near the surface of a transparent diamond substrate placed on the IC to image magnetic fields. We show that QDM imaging achieves simultaneous $\sim10$ $μ$m resolution of all three vector magnetic field components over the 3.7 mm $\times$ 3.7 mm field-of-view of the diamond. We study activity arising from spatially-dependent current flow in both intact and decapsulated field-programmable gate arrays (FPGAs); and find that QDM images can determine pre-programmed IC active states with high fidelity using machine-learning classification methods.

quant-ph↗

arXiv2020

Generation of nitrogen-vacancy ensembles in diamond for quantum sensors: Optimization and scalability of CVD processes

Ensembles of nitrogen-vacancy (NV) centers in diamond are a leading platform for practical quantum sensors. Reproducible and scalable fabrication of NV-ensembles with desired properties is crucial. This work addresses these challenges by developing a chemical vapor deposition (CVD) synthesis process to produce diamond material at scale with improved NV-ensemble properties for a target NV density. The material reported in this work enables immediate sensitivity improvements for current devices. In addition, techniques established in this work for material and sensor characterization at different stages of the CVD synthesis process provide metrics for future efforts targeting other NV densities or sample geometries.

cond-mat.mtrl-sci↗

arXiv2019

Principles and Techniques of the Quantum Diamond Microscope

We provide an overview of the experimental techniques, measurement modalities, and diverse applications of the Quantum Diamond Microscope (QDM). The QDM employs a dense layer of fluorescent nitrogen-vacancy (NV) color centers near the surface of a transparent diamond chip on which a sample of interest is placed. NV electronic spins are coherently probed with microwaves and optically initialized and read out to provide spatially resolved maps of local magnetic fields. NV fluorescence is measured simultaneously across the diamond surface, resulting in a wide-field, two-dimensional magnetic field image with adjustable spatial pixel size set by the parameters of the imaging system. NV measurement protocols are tailored for imaging of broadband and narrowband fields, from DC to GHz frequencies. Here we summarize the physical principles common to diverse implementations of the QDM and review example applications of the technology in geoscience, biology, and materials science.

physics.ins-det↗

arXiv2019

Quantum diamond spectrometer for nanoscale NMR and ESR spectroscopy

Nitrogen-vacancy (NV) quantum defects in diamond are sensitive detectors of magnetic fields. Due to their atomic size and optical readout capability, they have been used for magnetic resonance spectroscopy of nanoscale samples on diamond surfaces. Here we present a protocol for fabricating NV-diamond chips and for constructing and operating a simple, low-cost quantum diamond spectrometer for performing nuclear magnetic resonance (NMR) and electron spin resonance (ESR) spectroscopy in nanoscale volumes. The instrument is based on a commercially-available diamond chip, with an ion-implanted NV-ensemble at a depth of ~ 10 nm below the diamond surface. The spectrometer operates at low magnetic fields (~ 300 G) and requires standard optical and microwave components for NV spin preparation, manipulation and readout. We demonstrate the utility of this device for nanoscale proton and fluorine NMR spectroscopy, as well as for the detection of transition metals via ESR noise spectroscopy. We estimate that the full protocol requires 2-3 months to implement, depending on the availability of equipment, diamond substrates, and user experience.

physics.app-ph↗