Passive optical time-of-flight for Non line-of-sight localization

Optical imaging through diffusive, visually-opaque barriers, and around corners is an important challenge in many fields, ranging from defense to medical applications. Recently, novel techniques that combine time-of-flight (TOF) measurements with computational reconstruction, have allowed breakthrough imaging and tracking of objects hidden from view. These light detection and ranging (LiDAR)-based approaches, however, require active short-pulsed illumination and ultrafast time-resolved detection. Here, bringing notions from passive RADAR and passive geophysical mapping approaches, we present an optical TOF technique that allows to passively localize light sources and reflective objects through diffusive barriers and around corners. Our approach retrieves TOF information from temporal cross-correlations of scattered light, providing temporal resolution that surpasses the state-of-the-art ultrafast detectors by three orders of magnitude. We demonstrate passive localization of multiple white-light sources and reflective objects hidden from view, using a simple setup, with interesting potential for covert imaging.Comment: Article: 20 pages, 5 figures. Supplementary materials: 14 pages, 8 figure

A trillion frames per second: the techniques and applications of light-in-flight photography

Cameras capable of capturing videos at a trillion frames per second allow to freeze light in motion, a very counterintuitive capability when related to our everyday experience in which light appears to travel instantaneously. By combining this capability with computational imaging techniques, new imaging opportunities emerge such as three dimensional imaging of scenes that are hidden behind a corner, the study of relativistic distortion effects, imaging through diffusive media and imaging of ultrafast optical processes such as laser ablation, supercontinuum and plasma generation. We provide an overview of the main techniques that have been developed for ultra-high speed photography with a particular focus on `light-in-flight' imaging, i.e. applications where the key element is the imaging of light itself at frame rates that allow to freeze it's motion and therefore extract information that would otherwise be blurred out and lost.Comment: Published in Reports on progress in Physic

Root Causes of Cycle-to-Cycle Combustion Variations in Spark Ignited Engines.

Stricter governmental emission regulations, climate change concerns, and consumer demands for high fuel efficiency push the development of advanced cleaner and more efficient combustion strategies. Many strategies that rely on spark ignition are limited in their peak efficiencies by excessive cycle-to-cycle combustion variations (CCV). In this study, various laser-based and passive optical techniques are used to measure flow fields, spark discharge and other factors that impact early flame growth from which CCV originate. Bulk flow motion, as one contributing factor to CCV, is characterized in an optical engine under motored and fired conditions. In the fired cases, the flow velocities are higher during the gas exchange period but lower at the time of ignition, due to higher charge viscosities, caused by higher gas temperatures. Ten different fuel-air mixtures are strategically chosen to isolate the effects of laminar flame speed, thermo-diffusive mixture properties and change of stoichiometrically deficient species on the mechanisms that are responsible for cycle-to-cycle variability. Single value decomposition methods are found to be inefficient in identifying flow structures that are related to combustion variability. Physical flow parameters such as velocity magnitude and shear strength around time of ignition are identified to affect combustion variability. The relative impact of these parameters on energy output and combustion phasing are quantified for all mixtures and show some weak dependence on Markstein number and laminar flame speed. In a more fundamental fan-stirred combustion vessel experiments, variability effects of flame-flow interactions on CCV are isolated and thermo-diffusive effects are shown to impact combustion variability. Unstable negative Markstein number mixtures tend to exhibit higher combustion variability when interacting with gradients in the flow field around the time of ignition. High shear strength at the point of ignition causes an increased flame wrinkling, increasing the surface area, leading to faster combustion. This is an important finding because the common Lewis number equals 1 assumption in CFD simulations might lead to an under-prediction of CCV in low turbulence cases for negative Markstein number mixtures.PhDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/133396/1/pschiffm_1.pd

Quantum-inspired computational imaging

Computational imaging combines measurement and computational methods with the aim of forming images even when the measurement conditions are weak, few in number, or highly indirect. The recent surge in quantum-inspired imaging sensors, together with a new wave of algorithms allowing on-chip, scalable and robust data processing, has induced an increase of activity with notable results in the domain of low-light flux imaging and sensing. We provide an overview of the major challenges encountered in low-illumination (e.g., ultrafast) imaging and how these problems have recently been addressed for imaging applications in extreme conditions. These methods provide examples of the future imaging solutions to be developed, for which the best results are expected to arise from an efficient codesign of the sensors and data analysis tools.Y.A. acknowledges support from the UK Royal Academy of Engineering under the Research Fellowship Scheme (RF201617/16/31). S.McL. acknowledges financial support from the UK Engineering and Physical Sciences Research Council (grant EP/J015180/1). V.G. acknowledges support from the U.S. Defense Advanced Research Projects Agency (DARPA) InPho program through U.S. Army Research Office award W911NF-10-1-0404, the U.S. DARPA REVEAL program through contract HR0011-16-C-0030, and U.S. National Science Foundation through grants 1161413 and 1422034. A.H. acknowledges support from U.S. Army Research Office award W911NF-15-1-0479, U.S. Department of the Air Force grant FA8650-15-D-1845, and U.S. Department of Energy National Nuclear Security Administration grant DE-NA0002534. D.F. acknowledges financial support from the UK Engineering and Physical Sciences Research Council (grants EP/M006514/1 and EP/M01326X/1). (RF201617/16/31 - UK Royal Academy of Engineering; EP/J015180/1 - UK Engineering and Physical Sciences Research Council; EP/M006514/1 - UK Engineering and Physical Sciences Research Council; EP/M01326X/1 - UK Engineering and Physical Sciences Research Council; W911NF-10-1-0404 - U.S. Defense Advanced Research Projects Agency (DARPA) InPho program through U.S. Army Research Office; HR0011-16-C-0030 - U.S. DARPA REVEAL program; 1161413 - U.S. National Science Foundation; 1422034 - U.S. National Science Foundation; W911NF-15-1-0479 - U.S. Army Research Office; FA8650-15-D-1845 - U.S. Department of the Air Force; DE-NA0002534 - U.S. Department of Energy National Nuclear Security Administration)Accepted manuscrip

Diffuse Optical Imaging with Ultrasound Priors and Deep Learning

Diffuse Optical Imaging (DOI) techniques are an ever growing field of research as they are noninvasive, compact, cost-effective and can furnish functional information about human tissues. Among others, they include techniques such as Tomography, which solves an inverse reconstruction problem in a tissue volume, and Mapping which only seeks to find values on a tissue surface. Limitations in reliability and resolution, due to the ill-posedness of the underlying inverse problems, have hindered the clinical uptake of this medical imaging modality. Multimodal imaging and Deep Learning present themselves as two promising solutions to further research in DOI. In relation to the first idea, we implement and assess here a set of methods for SOLUS, a combined Ultrasound (US) and Diffuse Optical Tomography (DOT) probe for breast cancer diagnosis. An ad hoc morphological prior is extracted from US B-mode images and utilised for the regularisation of the inverse problem in DOT. Combination of the latter in reconstruction with a linearised forward model for DOT is assessed on specifically designed dual phantoms. The same reconstruction approach with the incorporation of a spectral model has been assessed on meat phantoms for reconstruction of functional properties. A simulation study with realistic digital phantoms is presented for an assessment of a non-linear model in reconstruction for the quantification of optical properties of breast lesions. A set of machine learning tools is presented for diagnosis breast lesions based on the reconstructed optical properties. A preliminary clinical study with the SOLUS probe is presented. Finally, a specifically designed deep learning architecture for diffusion is applied to mapping on the brain cortex or Diffuse Optical Cortical Mapping (DOCM). An assessment of its performances is presented on simulated and experimental data

Making GHG Emissions Trading Work - Crucial Issues in Designing National and International Emissions Trading Systems

Art. 17 of the Kyoto Protocol defines International Emissions Trading exclusively on country level, sub-national entities like industrial installations or households are not included initially. However, there are some arguments for such an expansion, of which the most important ones are a significant increase of the overall efficiency of the trading system as well as an increase of market liquidity. In the first part of this paper, the options for an inclusion of sub-national entities are analysed, concluding that AAUs should not be allocated to participants directly. Instead, there are several options how those entities can be included in International Emissions Trading as defined in the Kyoto-Protocol in an indirect way. The second part of the paper elaborates on the design options of national trading systems. All governments planning to introduce a domestic emissions trading scheme covering entities need to consider several design parameters, e.g. the characteristics of emission targets, participants of the trading scheme, participation mode, covered gases, non-compliance provisions, etc. We analyse and evaluate the options for each of those aspects, having in mind that the design of a trading system must assure its environmental integrity and keep transaction costs low at the same time. Der "Internationale Emissionshandel (IET)" wird nach Artikel 17 des Kyoto-Protokolls zunächst ausschließlich auf Staatenebene definiert. Es sprechen jedoch einige Gründe dafür, den Emissionshandel auch auf nicht staatliche Einheiten, wie z.B. industrielle und/oder private Emittenten auszudehnen. Die wesentlichen Vorteile sind die zu erwartende deutliche Erhöhung der Effizienz des Handelssystems sowie der Marktliquidität. Wir analysieren die verschiedenen Möglichkeiten einer derartigen Ausweitung des Emissionshandels. Eine direkte Einbeziehung subnationaler Einheiten durch die Zuteilung von Emissionsrechten nach dem Kyoto-Protokoll (AAUs) in den IET erscheint nicht empfehlenswert. Statt dessen bestehen verschiedene Möglichkeiten der indirekten Einbeziehung, bei der nationale "Währungen" für Emissionsrechte ausgegeben werden. Zudem werden die verschiedenen Ausgestaltungsparameter analysiert, die bei der Einrichtung eines (inter-)nationalen Emissionshandelssystems berücksichtigt werden müssen. Dies sind u.a. die Definition von Teilnehmerkreis, Teilnahmemodus, Art der Emissionsziele, Einbeziehung von Gasen, Einbeziehung der projektbasierten Mechanismen sowie Strafregelungen. Die einzelnen Ausgestaltungsoptionen werden evaluiert, insbesondere hinsichtlich der grundlegenden Ziele des Emissionshandels: Sicherung der ökologischen Integrität bei Minimierung der entstehenden Kosten.Environmental Economics and Policy,

On Real-Time AER 2-D Convolutions Hardware for Neuromorphic Spike-Based Cortical Processing

In this paper, a chip that performs real-time image convolutions with programmable kernels of arbitrary shape is presented. The chip is a first experimental prototype of reduced size to validate the implemented circuits and system level techniques. The convolution processing is based on the address–event-representation (AER) technique, which is a spike-based biologically inspired image and video representation technique that favors communication bandwidth for pixels with more information. As a first test prototype, a pixel array of 16x16 has been implemented with programmable kernel size of up to 16x16. The chip has been fabricated in a standard 0.35- m complimentary metal–oxide–semiconductor (CMOS) process. The technique also allows to process larger size images by assembling 2-D arrays of such chips. Pixel operation exploits low-power mixed analog–digital circuit techniques. Because of the low currents involved (down to nanoamperes or even picoamperes), an important amount of pixel area is devoted to mismatch calibration. The rest of the chip uses digital circuit techniques, both synchronous and asynchronous. The fabricated chip has been thoroughly tested, both at the pixel level and at the system level. Specific computer interfaces have been developed for generating AER streams from conventional computers and feeding them as inputs to the convolution chip, and for grabbing AER streams coming out of the convolution chip and storing and analyzing them on computers. Extensive experimental results are provided. At the end of this paper, we provide discussions and results on scaling up the approach for larger pixel arrays and multilayer cortical AER systems.Commission of the European Communities IST-2001-34124 (CAVIAR)Commission of the European Communities 216777 (NABAB)Ministerio de Educación y Ciencia TIC-2000-0406-P4Ministerio de Educación y Ciencia TIC-2003-08164-C03-01Ministerio de Educación y Ciencia TEC2006-11730-C03-01Junta de Andalucía TIC-141

Adaptive microfluidic gradient generator for quantitative chemotaxis experiments

Chemotactic motion in a chemical gradient is an essential cellular function that controls many processes in the living world. For a better understanding and more detailed modelling of the underlying mechanisms of chemotaxis, quantitative investigations in controlled environments are needed. We developed a setup that allows us to separately address the dependencies of the chemotactic motion on the average background concentration and on the gradient steepness of the chemoattractant. In particular, both the background concentration and the gradient steepness can be kept constant at the position of the cell while it moves along in the gradient direction. This is achieved by generating a well-defined chemoattractant gradient using flow photolysis. In this approach, the chemoattractant is released by a light-induced reaction from a caged precursor in a microfluidic flow chamber upstream of the cell. The flow photolysis approach is combined with an automated real-time cell tracker that determines changes in the cell position and triggers movement of the microscope stage such that the cell motion is compensated and the cell remains at the same position in the gradient profile. The gradient profile can be either determined experimentally using a caged fluorescent dye or may be alternatively determined by numerical solutions of the corresponding physical model. To demonstrate the function of this adaptive microfluidic gradient generator, we compare the chemotactic motion of Dictyostelium discoideum cells in a static gradient and in a gradient that adapts to the position of the moving cell