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We report on widefield microwave vector field imaging with sub-\\(100\\;\\mu {\\rm{m}}\\) resolution using a microfabricated alkali vapor cell. The setup can additionally image dc magnetic fields, and can be configured to image microwave electric fields. Our camera-based widefield imaging system records 2D images with a 6 × 6 mm2 field of view at a rate of 10 Hz. It provides up to \\(50\\;\\mu {\\rm{m}}\\) spatial resolution, and allows imaging of fields as close as \\(150\\;\\mu {\\rm{m}}\\) above structures, through the use of thin external cell walls. This is crucial in allowing us to take practical advantage of the high spatial resolution, as feature sizes in near-fields are on the order of the distance from their source, and represent an order of magnitude improvement in surface-feature resolution compared to previous vapor cell experiments. We present microwave and dc magnetic field images above a selection of devices, demonstrating a microwave sensitivity of \\(1.4\\;\\mu {\\rm{T}}\\;{\\mathrm{Hz}}^{-1/2}\\) per \\(50\\times 50\\times 140\\;\\mu {{\\rm{m}}}^{3}\\) voxel, at present limited by the speed of our camera system. Since we image 120 × 120 voxels in parallel, a single scanned sensor would require a sensitivity of at least \\(12\\;\\mathrm{nT}\\;{\\mathrm{Hz}}^{-1/2}\\) to produce images with the same sensitivity. Our technique could prove transformative in the design, characterization, and debugging of microwave devices, as there are currently no satisfactory established microwave imaging techniques. Moreover, it could find applications in medical imaging.

Diamond quantum processors consisting of a nitrogen-vacancy centre and surrounding nuclear spins have been the key to significant advancements in room-temperature quantum computing, quantum sensing and microscopy. The optimisation of these processors is crucial for the development of large-scale diamond quantum computers and the next generation of enhanced quantum sensors and microscopes. Here, we present a full model of multi-qubit diamond quantum processors and develop a semi-analytical method for designing gate pulses. This method optimises gate speed and fidelity in the presence of random control errors and is readily compatible with feedback optimisation routines. We theoretically demonstrate infidelities approaching ∼10−5 for single-qubit gates and established evidence that this can also be achieved for a two-qubit CZ gate. Consequently, our method reduces the effects of control errors below the errors introduced by hyperfine field misalignment and the unavoidable decoherence that is intrinsic to the processors. Having developed this optimal control, we simulated the performance of a diamond quantum processor by computing quantum Fourier transforms. We find that the simulated diamond quantum processor is able to achieve fast operations with low error probability.

Background Excess water in all its forms (moisture, dampness, hidden water) in buildings negatively impacts occupant health but is hard to reliably detect and quantify. Recent advances in through-wall imaging recommend microwaves as a tool with a high potential to noninvasively detect and quantify water throughout buildings. Methods Microwaves in both transmission and reflection (radar) modes were used to perform a simple demonstration of the detection of water both on and hidden within building materials. Results We used both transmission and reflection modes to detect as little as 1 mL of water between two 7 cm thicknesses of concrete. The reflection mode was also used to detect 1 mL of water on a metal surface. We observed oscillations in transmitted and reflected microwave amplitude as a function of microwave wavelength and water layer thickness, which we attribute to thin-film interference effects. Conclusions Improving the detection of water in buildings could help design, maintenance, and remediation become more efficient and effective and perhaps increase the value of microbiome sequence data. Microwave characterization of all forms of water throughout buildings is possible; its practical development would require new collaborations among microwave physicists or engineers, architects, building engineers, remediation practitioners, epidemiologists, and microbiologists.

Antimicrobial resistance continues to outpace the development of new chemotherapeutics. Novel pathogens continue to evolve and emerge. Public health innovation has the potential to open a new front in the war of “our wits against their genes” (Joshua Lederberg). Dense sampling coupled to next generation sequencing can increase the spatial and temporal resolution of microbial characterization while sensor technologies precisely map physical parameters relevant to microbial survival and spread. Microbial, physical, and epidemiological big data could be combined to improve prospective risk identification. However, applied in the wrong way, these approaches may not realize their maximum potential benefits and could even do harm. Minimizing microbial-human interactions would be a mistake. There is evidence that microbes previously thought of at best “benign” may actually enhance human health. Benign and health-promoting microbiomes may, or may not, spread via mechanisms similar to pathogens. Infectious vaccines are approaching readiness to make enhanced contributions to herd immunity. The rigorously defined nature of infectious vaccines contrasts with indigenous “benign or health-promoting microbiomes” but they may converge. A “microbial Neolithic revolution” is a possible future in which human microbial-associations are understood and managed analogously to the macro-agriculture of plants and animals. Tradeoffs need to be framed in order to understand health-promoting potentials of benign, and/or health-promoting microbiomes and infectious vaccines while also discouraging pathogens. Super-spreaders are currently defined as individuals who play an outsized role in the contagion of infectious disease. A key unanswered question is whether the super-spreader concept may apply similarly to health-promoting microbes. The complex interactions of individual rights, community health, pathogen contagion, the spread of benign, and of health-promoting microbiomes including infectious vaccines require study. Advancing the detailed understanding of heterogeneity in microbial spread is very likely to yield important insights relevant to public health.

Events have structure. At the token level, this structure is characterized to a large extent by the relations that individual events bear to their participants and to their subevents. At the type level, kinds of events and semantic roles are often organized into hierarchical ontologies. This thesis studies type- and token-level event structure in the context of full documents, where an account of a single event may span multiple sentences and may involve diverse kinds of subevents and participants. We explore ways of making event structure at both levels more transparent and more extensible through two broad approaches: decompositions of events into simpler events and event properties, and natural language descriptions of events and event ontologies.

We report on widefield microwave vector field imaging with sub- resolution using a microfabricated alkali vapor cell. The setup can additionally image dc magnetic fields, and can be configured to image microwave electric fields. Our camera-based widefield imaging system records 2D images with a 6 × 6 mm2 field of view at a rate of 10 Hz. It provides up to spatial resolution, and allows imaging of fields as close as above structures, through the use of thin external cell walls. This is crucial in allowing us to take practical advantage of the high spatial resolution, as feature sizes in near-fields are on the order of the distance from their source, and represent an order of magnitude improvement in surface-feature resolution compared to previous vapor cell experiments. We present microwave and dc magnetic field images above a selection of devices, demonstrating a microwave sensitivity of per voxel, at present limited by the speed of our camera system. Since we image 120 × 120 voxels in parallel, a single scanned sensor would require a sensitivity of at least to produce images with the same sensitivity. Our technique could prove transformative in the design, characterization, and debugging of microwave devices, as there are currently no satisfactory established microwave imaging techniques. Moreover, it could find applications in medical imaging.

Direct Analysis in Real Time (DART) ionization/mass spectrometry allows for the high throughput analysis of a wide range of materials including but not limited to: solids, liquids, powders, tablets, and plant materials. The ability to detect cocaine was established in a reproducible manner with the use of a DART ionization source (IonSense Inc., Saugus, MA) interfaced to a modified single quadrupole mass spectrometer. Development of a methodology for the detection of cocaine within contrived street quality drug mixtures involved the optimization of the ionization source, sample introduction mechanism, ion guide, and mass analysis parameters. An analytical method was created that utilized ionized helium carrier gas heated to 300°C and an automated sample introduction apparatus consisting of a Linear Rail Enclosure that holds consumable QuickStrip™ sample cards. Ionized molecules were then fragmented by manipulation of voltage levels within the ion guide to gain more structural information prior to detection by a single quadrupole mass spectrometer. Cocaine was detected by the modified DART/MS analytical platform and gave two peaks within the mass spectrum at m/z 304 and 182. Optimization of insource fragmentation by manual adjustment of the skimmer focus voltage allowed for the reproducible fragmentation of cocaine and the ability to increase or decrease the amount of fragmentation seen between the two peaks detected for cocaine. With the use of fragmentation, this analytical platform can be classified as a Category A technique as defined by the Scientific Working Group for the Analysis of Seized Drugs. The robust detection of cocaine was demonstrated for reference samples at concentrations as low as 10 ng/μL (50 ng) with high signal abundance greater than ten times the signal to noise ratio. Furthermore, the detection of cocaine at 10 ng/μL was demonstrated for multi component mixtures of up to 14 additional components containing common adulterants and diluents found within street quality samples. In total, 25 common excipients were tested using the same method parameters as optimized for cocaine analysis. Of these 25 excipients tested, five were not detected in positive ion mode (one could be detected in negative ion mode). Of the twenty excipients that could be detected by mass spectrometry, two pairs of excipients (levamisole/tetramisole and creatine/creatinine) could not be differentiated from each other. There were no excipients tested that had equivalent m/z values as those of cocaine. Experimentation into the effects of various excipients at multiple concentrations on the abundance of the two cocaine peaks was performed. Regardless of excipient amount (up to 10 times more concentrated than cocaine) and the number of components (up to 15 total components) the ratio of abundance between the m/z 304 to 182 peaks did not vary greater than 22% relative standard deviation. A match criteria protocol was developed for the ability of an analyst to confirm the presence of cocaine within unknown forensic case samples that have previously tested positive for the presumptive identification of cocaine. The identification of cocaine was based on various factors such as the signal to noise ratio at m/z 304 and 182, the ratio of abundance between those two peaks as well as positive and negative controls. This match criteria protocol was utilized for 25 double blind mock forensic casework samples was performed. Determination for the presence of cocaine within these unknown samples gave an analyst error rate of 0%, with no false positives or false negatives predicted. To further aid human interpretation and identification of compounds within mixtures, the advanced chemometric software, Analyze IQ, was utilized. Development of predictive classification models using a combination of preprocessing steps, principle component analysis and machine learning techniques was achieved. Using the DART/MS analytical platform, 25 mock forensic casework samples along with positive and negative controls were analyzed and identified for the presence of cocaine within 30 minutes. On the order of 15 to 30 times faster than modern GC/MS and LC/MS methods, the ability to analyze and identify samples faster would allow for an increase in samples being processed on a daily basis and allow for the reduction of case backlogs that currently plague controlled substances sections of forensic science laboratories throughout the United States. (Abstract shortened by UMI.)

We use an atomic vapor cell as a frequency tunable microwave field detector operating at frequencies from GHz to tens of GHz. We detect microwave magnetic fields from 2.3 GHz to 26.4 GHz, and measure the amplitude of the sigma+ component of an 18 GHz microwave field. Our proof-of-principle demonstration represents a four orders of magnitude extension of the frequency tunable range of atomic magnetometers from their previous dc to several MHz range. When integrated with a high resolution microwave imaging system, this will allow for the complete reconstruction of the vector components of a microwave magnetic field and the relative phase between them. Potential applications include near-field characterisation of microwave circuitry and devices, and medical microwave sensing and imaging.

Diamond quantum processors consisting of a nitrogen-vacancy (NV) centre and surrounding nuclear spins have been the key to significant advancements in room-temperature quantum computing, quantum sensing and microscopy. The optimisation of these processors is crucial for the development of large-scale diamond quantum computers and the next generation of enhanced quantum sensors and microscopes. Here, we present a full model of multi-qubit diamond quantum processors and develop a semi-analytical method for designing gate pulses. This method optimises gate speed and fidelity in the presence of random control errors and is readily compatible with feedback optimisation routines. We theoretically demonstrate infidelities approaching \\(\\sim 10^{-5}\\) for single-qubit gates and established evidence that this can also be achieved for a two-qubit CZ gate. Consequently, our method reduces the effects of control errors below the errors introduced by hyperfine field misalignment and the unavoidable decoherence that is intrinsic to the processors. Having developed this optimal control, we simulated the performance of a diamond quantum processor by computing quantum Fourier transforms. We find that the simulated diamond quantum processor is able to achieve fast operations with low error probability.

Almost 50% of national energy consumption can be attributed to the operation of buildings. This places an immense burden on natural systems, as a function of increasing extraction and transportation of fossil fuels, and the associated impacts of their combustion. Measures are available to vastly improve energy efficiency in both new and existing buildings, but these opportunities are not being seized. Instead of becoming more efficient, buildings are actually placing an increasing burden on the environment through their profligate use of energy, further compounded by an increase in total floor area. Developed with Carillion Plc on major public sector projects, but applicable to wider construction markets, this thesis presents a design tool, which predicts the energy and cost performance of buildings. Providing a powerful source of information at influential stages of building design, the so called Energy Toolkit opens up new avenues of communication with clients, promoting a more integrated, cross-disciplinary design led approach to energy issues. Clients have testified the strengths this tool has brought to Carillion’s proposals. Energy efficiency in buildings is generally perceived to be expensive, and consequently, a cost that will not be borne by today’s clients and property developers. The thesis demonstrates that best available techniques could reduce energy consumption of buildings in the order of 50%, without requiring significant capital expenditure. Empirical testing on a representative sample of public buildings shows that this could deliver considerable environmental and economic benefits. Barriers to energy efficiency are well documented, and this thesis demonstrates how such barriers can be broken down using actual case studies. Notwithstanding a number of concerning characteristics, new avenues of procurement such as the UK Government’s Private Finance Initiative, represent a good platform from which to expose these barriers, and their effect upon environmental and economic performance.