P. B. Dixon

Bio: P. B. Dixon is an academic researcher from University of Rochester. The author has contributed to research in topics: Physics & Computer science. The author has an hindex of 1, co-authored 1 publications receiving 132 citations.

Photon-counting compressive sensing laser radar for 3D imaging

Abstract: We experimentally demonstrate a photon-counting, single-pixel, laser radar camera for 3D imaging where transverse spatial resolution is obtained through compressive sensing without scanning. We use this technique to image through partially obscuring objects, such as camouflage netting. Our implementation improves upon pixel-array based designs with a compact, resource-efficient design and highly scalable resolution.

An integrated photonic engine for programmable atomic control

Abstract: Solutions for scalable, high-performance optical control are important for the development of scaled atom-based quantum technologies. Modulation of many individual optical beams is central to the application of arbitrary gate and control sequences on arrays of atoms or atom-like systems. At telecom wavelengths, miniaturization of optical components via photonic integration has pushed the scale and performance of classical and quantum optics far beyond the limitations of bulk devices [1– 3]. However, these material platforms for high-speed telecom integrated photonics [4, 5] are not transparent at the short wavelengths required by leading atomic systems [6–8]. Here, we propose and implement a scalable and reconfigurable photonic architecture for multi-channel quantum control using integrated, visible-light modulators based on thin-film lithium niobate [9, 10]. Our approach combines techniques in free-space optics, holography, and control theory together with a sixteen-channel integrated photonic device to stabilize temporal and cross-channel power deviations and enable precise and uniform control. Applying this device to a homogeneous constellation of silicon-vacancy artificial atoms in diamond, we present techniques to spatially and spectrally address a dynamically-selectable set of these stochastically-positioned point emitters. We anticipate that this scalable and reconfigurable optical architecture will lead to systems that could enable parallel individual programmability of large many-body atomic systems, which is a critical step towards universal quantum computation on such hardware. on insulator, thin-film lithium niobate, large-scale, multi-channel, visible modulator, silicon-vacancy, quantum control

Large-scale optical characterization of solid-state quantum emitters

Abstract: Solid-state quantum emitters have emerged as a leading quantum memory for quantum network-ing applications. However, standard optical characterization techniques are neither efficient nor repeatable at scale. In this work, we introduce and demonstrate spectroscopic techniques that enable large-scale, automated characterization of color centers. We first demonstrate the ability to track color centers by registering them to a fabricated machine-readable global coordinate system, enabling systematic comparison of the same color center sites over many experiments. We then implement resonant photoluminescence excitation in a widefield cryogenic microscope to parallelize resonant spectroscopy, achieving two orders of magnitude speed-up over confocal microscopy. Fi-nally, we demonstrate automated chip-scale characterization of color centers and devices at room temperature, imaging thousands of microscope fields of view. These tools will enable accelerated identification of useful quantum emitters at chip-scale, enabling advances in scaling up color center platforms for quantum information applications, materials science, and device design and characterization. After tri-acid cleaning, two populations of ¯ ω/ 2 π are observed, attributable to polarization due to the presence of an electric field caused by a change in surface termination. e, Visualization of the shift in the splitting ∆ δ = δ i − δ j between the two m s = 0 transitions between experiments j = 1 & i = 2, which served as a control, and between experiments j = 1 & i = 3, before and after tri-acid cleaning.

Free-space Forwarded-pump Entanglement Source Synchronization

Abstract: We investigate entanglement source synchronization using a forwarded-pump signal sent over a 3.2-km free-space retro-reflected link. Results show sub-picosecond alignment between the sources. The paper considers several fundamental and practical aspects of this approach.

A fully packaged multi-channel cryogenic module for optical quantum memories

Abstract: Realizing a quantum network will require long-lived quantum memories with optical interfaces incorporated into a scalable architecture. Color centers quantum emitters in diamond have emerged as a promising memory modality due to their optical properties and compatibility with scalable integration. However, developing a scalable color center emitter module requires significant advances in the areas of heterogeneous integration and cryogenically compatible packaging. Here we report on a cryogenically stable and network compatible quantum-emitter module for memory use. This quantum-emitter module is a significant development towards advanced quantum networking applications such as distributed sensing and processing.

Principles and prospects for single-pixel imaging

Abstract: Modern digital cameras employ silicon focal plane array (FPA) image sensors featuring millions of pixels. However, it is possible to make a camera that only needs one pixel. In these cameras a spatial light modulator, placed before or after the object to be imaged, applies a time-varying pattern and synchronized intensity measurements are made with a single-pixel detector. The principle of compressed sensing then allows an image to be generated. As the approach suits a wide a variety of detector technologies, images can be collected at wavelengths outside the reach of FPA technology or at high frame rates or in three dimensions. Promising applications include the visualization of hazardous gas leaks and 3D situation awareness for autonomous vehicles. Rather than requiring millions of pixels, it is possible to make a camera that only needs one pixel. This Review details the working principle, advantages, technical considerations and future potential of single-pixel imaging.

Single-pixel three-dimensional imaging with time-based depth resolution

Abstract: A three-dimensional imaging system which distributes the optical illumination over the full field-of-view is sought after. Here, the authors demonstrate the capability of reconstructing 128 × 128 pixel resolution three-dimensional scenes to an accuracy of 3 mm as well as real-time video with a frame-rate up to 12 Hz.

Single-pixel imaging 12 years on: a review

Abstract: Modern cameras typically use an array of millions of detector pixels to capture images. By contrast, single-pixel cameras use a sequence of mask patterns to filter the scene along with the corresponding measurements of the transmitted intensity which is recorded using a single-pixel detector. This review considers the development of single-pixel cameras from the seminal work of Duarte et al. up to the present state of the art. We cover the variety of hardware configurations, design of mask patterns and the associated reconstruction algorithms, many of which relate to the field of compressed sensing and, more recently, machine learning. Overall, single-pixel cameras lend themselves to imaging at non-visible wavelengths and with precise timing or depth resolution. We discuss the suitability of single-pixel cameras for different application areas, including infrared imaging and 3D situation awareness for autonomous vehicles.

A Russian Dolls ordering of the Hadamard basis for compressive single-pixel imaging.

Abstract: Single-pixel imaging is an alternate imaging technique particularly well-suited to imaging modalities such as hyper-spectral imaging, depth mapping, 3D profiling. However, the single-pixel technique requires sequential measurements resulting in a trade-off between spatial resolution and acquisition time, limiting real-time video applications to relatively low resolutions. Compressed sensing techniques can be used to improve this trade-off. However, in this low resolution regime, conventional compressed sensing techniques have limited impact due to lack of sparsity in the datasets. Here we present an alternative compressed sensing method in which we optimize the measurement order of the Hadamard basis, such that at discretized increments we obtain complete sampling for different spatial resolutions. In addition, this method uses deterministic acquisition, rather than the randomized sampling used in conventional compressed sensing. This so-called ‘Russian Dolls’ ordering also benefits from minimal computational overhead for image reconstruction. We find that this compressive approach performs as well as other compressive sensing techniques with greatly simplified post processing, resulting in significantly faster image reconstruction. Therefore, the proposed method may be useful for single-pixel imaging in the low resolution, high-frame rate regime, or video-rate acquisition.

Adaptive foveated single-pixel imaging with dynamic supersampling

Abstract: In contrast to conventional multipixel cameras, single-pixel cameras capture images using a single detector that measures the correlations between the scene and a set of patterns. However, these systems typically exhibit low frame rates, because to fully sample a scene in this way requires at least the same number of correlation measurements as the number of pixels in the reconstructed image. To mitigate this, a range of compressive sensing techniques have been developed which use a priori knowledge to reconstruct images from an undersampled measurement set. Here, we take a different approach and adopt a strategy inspired by the foveated vision found in the animal kingdom—a framework that exploits the spatiotemporal redundancy of many dynamic scenes. In our system, a high-resolution foveal region tracks motion within the scene, yet unlike a simple zoom, every frame delivers new spatial information from across the entire field of view. This strategy rapidly records the detail of quickly changing features in the scene while simultaneously accumulating detail of more slowly evolving regions over several consecutive frames. This architecture provides video streams in which both the resolution and exposure time spatially vary and adapt dynamically in response to the evolution of the scene. The degree of local frame rate enhancement is scene-dependent, but here, we demonstrate a factor of 4, thereby helping to mitigate one of the main drawbacks of single-pixel imaging techniques. The methods described here complement existing compressive sensing approaches and may be applied to enhance computational imagers that rely on sequential correlation measurements.