Search

In this paper, we detail recent and current work that is being carried out to fabricate and advance novel SiC UV instrumentation that is aimed at enabling more sensitive measurements across numerous disciplines, with a short discussion of the promise such detectors may hold for the Habitable Worlds Observatory. We discuss SiC instrument development progress that is being carried out under multiple NASA grants, including several PICASSO and SBIR grants, as well as an ECI grant. Testing of pixel design, properties and layout as well as maturation of the integration scheme developed through these efforts provide key technology and engineering advancement for potential HWO detectors. Achieving desired noise characteristics, responsivity, and validating operation of SiC detectors using standard read out techniques offers a compelling platform for operation of denser and higher dimensionality SiC photodiode arrays of interest for use in potential HWO Coronagraph, Spectrograph, and High Resolution Imaging Instruments. We incorporate these SiC detector properties into a simulation of potential NUV exoplanet observations by HWO using SiC detectors and also discuss potential application to HWO., Comment: 8 figures, Submitted to JATIS

While optical clock technology has advanced rapidly in recent years, incorporating the technology into operational timescales has progressed more slowly. The highest accuracy frequency standards for groundbreaking measurements do not easily translate to critical timing where continuous, uninterrupted operation over many months and years is required. For example, intermittent steering of a hydrogen maser with an optical standard fails to harness all of the dramatic improvements possible with optical technology. Here we present progress on development and integration of optical-clock technology for operational timescales. An optical oscillator steered to an atomic fountain comprises a hybrid clock with optical-level stability at short times and a reliable long-term reference, and obviates the need for a steered maser. Atomic beam optical clocks are being developed to support 24/7 operations at a level that improves upon the performance of the U.S. Naval Observatory's rubidium fountains. An optical lattice is being developed as a gold-standard frequency reference, complementing the role of the atomic beam clocks., Comment: 9th Symposium on Frequency Standards and Metrology

Quantum networking protocols, including quantum teleportation and entanglement swapping, use linear-optical Bell state measurements for heralding the distribution and transfer of quantum information. However, a linear-optical Bell state measurement requires identical photons and is susceptible to errors caused by multiphoton emission, fundamentally limiting the efficiency and fidelity of quantum networking protocols. Here we show a nonlinear Bell state analyzer for time-bin encoded photons based on a nanophotonic cavity with efficient sum-frequency generation to filter multiphoton emissions, and utilize it for faithful quantum teleportation involving spectrally distinct photons with fidelities $\geq 94\%$ down to the single-photon level. Our result demonstrates that nonlinear-optical entangling operations, empowered by our efficient nanophotonics platform, can realize faithful quantum information protocols without requiring identical photons and without the fundamental limit on the efficiency and fidelity of a Bell state measurement imposed by linear optics, which facilitates the realization of practical quantum networks.

Nonlinear optical materials are essential for the development of both nonlinear and quantum optics and have advanced recently from bulk crystals to integrated material platforms. In this Perspective, we provide an overview of the emerging InGaP $\chi^{(2)}$ nonlinear integrated photonics platform and its experimental achievements. With its exceptional $\chi^{(2)}$ nonlinearity and low optical losses, the epitaxial InGaP platform significantly enhances a wide range of second-order nonlinear optical effects, from second-harmonic generation to entangled photon pair sources, achieving efficiencies several orders of magnitude beyond the current state of the art. Moreover, the InGaP platform enables quantum nonlinear optics at the few- and single-photon levels via passive nonlinearities, which has broad implications for quantum information processing and quantum networking. We also examine the current limitations of the InGaP platform and propose potential solutions to fully unlock its capabilities.

We report on the first deployment of a ytterbium (Yb) transportable optical lattice clock (TOLC), commercially shipping the clock 3,000 km from Boulder, Colorado to Washington DC. The system, composed of a rigidly mounted optical reference cavity, atomic physics package, and an optical frequency comb, fully realizes an independent frequency standard for comparisons in the optical and microwave domains. The shipped Yb TOLC was fully operational within 2 days of arrival, enabling frequency comparisons with rubidium (Rb) fountains at the United States Naval Observatory (USNO). To the best of our knowledge, this represents the first deployment of a fully independent TOLC, including the frequency comb, coherently uniting the optical stability of the Yb TOLC to the microwave output of the Rb fountain., Comment: 5 pages, 4 figures

This paper aims to demonstrate how the prevalent practice in the learned video compression community of averaging rate-distortion (RD) curves across a test video set can lead to misleading conclusions in evaluating codec performance. Through analytical analysis of a simple case and experimental results with two recent learned video codecs, we show how averaged RD curves can mislead comparative evaluation of different codecs, particularly when videos in a dataset have varying characteristics and operating ranges. We illustrate how a single video with distinct RD characteristics from the rest of the test set can disproportionately influence the average RD curve, potentially overshadowing a codec's superior performance across most individual sequences. Using two recent learned video codecs on the UVG dataset as a case study, we demonstrate computing performance metrics, such as the BD rate, from the average RD curve suggests conclusions that contradict those reached from calculating the average of per-sequence metrics. Hence, we argue that the learned video compression community should also report per-sequence RD curves and performance metrics for a test set should be computed from the average of per-sequence metrics, similar to the established practice in traditional video coding, to ensure fair and accurate codec comparisons., Comment: Submitted to IEEE Signal Processing Letters

JWST has enabled detecting and spatially resolving the heavily dust-attenuated stellar populations of sub-millimeter galaxies, revealing detail that was previously inaccessible. In this work we construct a sample of 289 sub-millimeter galaxies with detailed joint ALMA and JWST constraints in the COSMOS field. Sources are originally selected using the SCUBA-2 instrument and have archival ALMA observations from various programs. Their JWST NIRCam imaging is from COSMOS-Web and PRIMER. We extract multi-wavelength photometry in a manner that leverages the unprecedented near-infrared spatial resolution of JWST, and fit the data with spectral energy distribution models to derive photometric redshifts, stellar masses, star-formation rates and optical attenuation. The sample has an average z=2.6, A_V=2.5, SFR=270 and log(M*)=11.1. There are 81 (30%) galaxies that have no previous optical/near-infrared detections, including 75% of the z>4 sub-sample (n=28). The faintest observed near-infrared sources have the highest redshifts and largest A_V=4. In a preliminary morphology analysis we find that ~10% of our sample exhibit spiral arms and 5% host stellar bars, with one candidate bar found at z>3. Finally, we find that the clustering of JWST galaxies within 10 arcseconds of a sub-mm galaxy is a factor of 2 greater than what is expected based on either random clustering or the distribution of sources around any red galaxy irrespective of a sub-mm detection., Comment: 37 pages (15 for RGBs + references), 14 figures, submitted to ApJ

We propose PAV, Personalized Head Avatar for the synthesis of human faces under arbitrary viewpoints and facial expressions. PAV introduces a method that learns a dynamic deformable neural radiance field (NeRF), in particular from a collection of monocular talking face videos of the same character under various appearance and shape changes. Unlike existing head NeRF methods that are limited to modeling such input videos on a per-appearance basis, our method allows for learning multi-appearance NeRFs, introducing appearance embedding for each input video via learnable latent neural features attached to the underlying geometry. Furthermore, the proposed appearance-conditioned density formulation facilitates the shape variation of the character, such as facial hair and soft tissues, in the radiance field prediction. To the best of our knowledge, our approach is the first dynamic deformable NeRF framework to model appearance and shape variations in a single unified network for multi-appearances of the same subject. We demonstrate experimentally that PAV outperforms the baseline method in terms of visual rendering quality in our quantitative and qualitative studies on various subjects., Comment: Accepted to ECCV24. Project page: https://akincaliskan3d.github.io/PAV

Among Universe's most consequential events are large impacts generating rapidly-evolving extreme pressures and temperatures. Crystalline and amorphous forms of (Mg, Fe)2SiO4 are abundant and widespread, within planets and in space. The behavior of these minerals is expected to deviate form thermodynamic equilibrium in many of the processes that are critical to the formation and evolution of planets, particularly shock events. To further the understanding of the behavior of the silicate under extreme conditions, we statically compressed a crystal of forsterite up to 160.5 GPa, far beyond the compound's stability field, and probed its long-range ordering with synchrotron microdiffraction. We found that forsterite retains long-range ordering up to the highest pressure reached. Forsterite III, emerging at about 58 GPa, persists in compression to 160.5 GPa and in decompression down to about 13 GPa, for a rare combined occurrence of a metastable phase of nearly 150 GPa. These observations dispute earlier reports of pressure-induced amorphization and are a unique testimony of the resilience of the crystalline state in quasi hydrostatic compression. We confirm that highly disordered forsterite can be obtained from the decompression of forsterite III as suggested from the substantial loss of long-range ordering observed at 7 GPa after further decompression. Such kinetic pathway may explain how synthetic olivine glass have been obtained in shock experiments and could be a mechanism of generation of amorphous forsterite in cosmic dust. The 120 GPa Hugoniot discontinuity finds no correspondence in our data, marking a departure from the parallelism between static "cold compression" and dynamic compression., Comment: 11 pages, 6 figures

Traffic accidents, causing millions of deaths and billions of dollars in economic losses each year globally, have become a significant issue. One of the main causes of these accidents is drivers being sleepy or fatigued. Recently, various studies have focused on detecting drivers' sleep/wake states using camera-based solutions that do not require physical contact with the driver, thereby enhancing ease of use. In this study, besides the eye blink frequency, a driver adaptive eye blink behavior feature set have been evaluated to detect the fatigue status. It is observed from the results that behavior of eye blink carries useful information on fatigue detection. The developed image-based system provides a solution that can work adaptively to the physical characteristics of the drivers and their positions in the vehicle, Comment: 9 pages, 4 figures 3 tables

The design of Envelope and Pilot-Induced Oscillation (PIO) Protection Features, and Failure Cases detection and prevention using Active Control Sidestick (ACS) is a challenging task. While helping the pilot to respect the envelope limitations also in failure scenarios and, therefore, increasing mission effectiveness, these features may have a significant impact on the aircraft's agility. ACS characteristics are investigated in an integrated environment. A set of effective and flexible control laws based on Incremental Nonlinear Dynamic Inversion have been developed in a state-of-the-art aircraft simulation model and coupled with a two-ways communication with the selected ACS. The model can run in real-time in a fixed-based simulator composed of representative cockpit and out-of-the-window.

This paper introduces a flight envelope protection algorithm on a longitudinal axis that leverages reinforcement learning (RL). By considering limits on variables such as angle of attack, load factor, and pitch rate, the algorithm counteracts excessive pilot or control commands with restoring actions. Unlike traditional methods requiring manual tuning, RL facilitates the approximation of complex functions within the trained model, streamlining the design process. This study demonstrates the promising results of RL in enhancing flight envelope protection, offering a novel and easy-to-scale method for safety-ensured flight.

Nonlinear optics plays an important role in many areas of science and technology. The advance of nonlinear optics is empowered by the discovery and utilization of materials with growing optical nonlinearity. Here we demonstrate an indium gallium phosphide (InGaP) integrated photonics platform for broadband, ultra-efficient second-order nonlinear optics. The InGaP nanophotonic waveguide enables second-harmonic generation with a normalized efficiency of $128,000\%$/W/cm$^2$ at 1.55 $\mu$m pump wavelength, nearly two orders of magnitude higher than the state of the art in the telecommunication C band. Further, we realize an ultra-bright, broadband time-energy entangled photon source with a pair generation rate of 97 GHz/mW and a bandwidth of 115 nm centered at the telecommunication C band. The InGaP entangled photon source shows high coincidence-to-accidental counts ratio CAR $>10^4$ and two-photon interference visibility $>98\%$. The InGaP second-order nonlinear photonics platform will have wide-ranging implications for non-classical light generation, optical signal processing, and quantum networking.

In this study, a distinct reconfigurable fault-tolerant flight control strategy is addressed for mitigating one of the persistent safety-critical issue, i.e. loss of control triggered by actuator faults. The attainable acceleration set notion is taken a step further towards incremental attainable acceleration set through a slight modification that enables instantaneous controllability checks. The inner-loop gains are updated in case of a fault using incremental attainable acceleration set and a tuning function, which is in charge as a compensator of agility and robustness. Additionally, the outer-loop gains are also such reconfigured that holding the bandwidth ratio of the successive loops at a prudent level to ensure the closed-loop stability; for this reason, an analytical outer-loop gain update law is derived based on the inner-loop gains and bandwidth, actuator and command filter time constants. Subsequently, the proposed architecture is assessed under a severe fault scenario with a demanding maneuver mission. Noticeably, the proposed method fulfills the expectations of stability and agility sufficiently, and surpasses the fixed-gain approach.

The prevention of the loss of control in agile aircraft during the extreme maneuvers is of concern due to the nonlinear aerodynamics and flight dynamics nature of the aircraft in this study. Within this context, the primary objective is to present an architectural framework and elucidate the methodology for its determination. This architecture enables agile maneuvering aircraft to execute more extreme maneuvers while avoiding departure from stable flight, surpassing maneuverability capabilities of conventional state limiters. Hence, the notion of an incremental attainable moment set is introduced for an instantaneous controllability investigation using demanded control moment coefficients derived in the high-level controller, which is the incremental nonlinear dynamic inversion. In the event of detecting a violation of controllability boundaries, Lyapunov-based dynamic command saturation is employed to limit pilot commands, preventing the aircraft from initiating departure from stable flight. As a result, abrupt and excessive pilot inputs are dynamically softened in-flight, and presumable departure tendencies are mitigated. Consequently, the superiority of the proposed method over conventional state limiters is proven through the flight simulations of agile and abrupt maneuvers, as well as Monte Carlo simulations that demonstrate the expansion of stable maneuverable volumes up to 55%.

We give a complete invariant for shift equivalence for Boolean matrices (equivalently finite relations), in terms of the period, the induced partial order on recurrent components, and the cohomology class of the relation on those components.

We present the latest generation of MobileNets, known as MobileNetV4 (MNv4), featuring universally efficient architecture designs for mobile devices. At its core, we introduce the Universal Inverted Bottleneck (UIB) search block, a unified and flexible structure that merges Inverted Bottleneck (IB), ConvNext, Feed Forward Network (FFN), and a novel Extra Depthwise (ExtraDW) variant. Alongside UIB, we present Mobile MQA, an attention block tailored for mobile accelerators, delivering a significant 39% speedup. An optimized neural architecture search (NAS) recipe is also introduced which improves MNv4 search effectiveness. The integration of UIB, Mobile MQA and the refined NAS recipe results in a new suite of MNv4 models that are mostly Pareto optimal across mobile CPUs, DSPs, GPUs, as well as specialized accelerators like Apple Neural Engine and Google Pixel EdgeTPU - a characteristic not found in any other models tested. Finally, to further boost accuracy, we introduce a novel distillation technique. Enhanced by this technique, our MNv4-Hybrid-Large model delivers 87% ImageNet-1K accuracy, with a Pixel 8 EdgeTPU runtime of just 3.8ms.

This paper explores the paradoxical nature of computational creativity, focusing on the inherent limitations of closed digital systems in emulating the open-ended, dynamic process of human creativity. Through a comprehensive analysis, we delve into the concept of the State Space Paradox (SSP) in computational research on creativity, which arises from the attempt to model or replicate creative behaviors within the bounded state spaces of digital systems. Utilizing a combination of procedural and representational paradigms, we examine various computational models and their capabilities to assist or emulate the creative process. Our investigation encompasses rule-based systems, genetic algorithms, case-based reasoning, shape grammars, and data mining, among others, to understand how these methods contribute to or fall short of achieving genuine creativity. The discussion extends to the implications of SSP on the future of creativity-related computer systems, emphasizing the cultural and contextual fluidity of creativity itself and the challenges of producing truly creative outcomes within the constraints of pre-defined algorithmic structures. We argue that while digital systems can provoke sudden mental insights (SMIs) in human observers and potentially support the creative process, their capacity to autonomously break out of their pre-programmed state spaces and achieve originality akin to human creativity remains fundamentally constrained. The paper concludes with reflections on the future directions for research in computational creativity, suggesting that recognizing and embracing the limitations and potentials of digital systems could lead to more nuanced and effective tools for creative assistance., Comment: 7 pages, 3 tables

With $P_t$ the price in current dollars of a dollar delivered $t$ time units from now, we assume that $P$ is a decreasing function defined for $t \in \mathbb{R}_+$ with $P_0 = 1$. The negative logarithmic derivative, $- \stackrel{\bullet}{P}_t/P_t$ defines the yield curve function $Y_t$. An $n$ parameter linear yield curve model selects as allowable yield curves $Y_t(r) = \sum_{i=1}^n r_i Y^i_t$ with the functions $Y^i$ fixed and with $r$ varying over an open subset of $\mathbb{R}^n$ on which $Y_t(r) \ge 0$ for all $t \in \mathbb{R}_+$. For example, the flat yield curve model with $P_t(r) = e^{-rt}$ is a one parameter linear model with $Y^1_t(r) = r > 0$. We impose two natural economic requirements on the model: (SPA) static prices allowed, i.e. it is always possible that as time moves forward, relative prices do not change, and (NLA) no local arbitrage, i.e. there does not exist a self-financing bundle of futures such that the zero present value is a local minimum with respect to small changes in the space of admissible yield curves. In that case the model always contains one of four simple models. If we impose the additional requirement (LRE) long rates exist, i.e. for every $r$ $Lim_{t \to \infty} Y_t(r)$ exists as a finite limit, then the number of simple models is reduced to two.

While the performance of recent learned intra and sequential video compression models exceed that of respective traditional codecs, the performance of learned B-frame compression models generally lag behind traditional B-frame coding. The performance gap is bigger for complex scenes with large motions. This is related to the fact that the distance between the past and future references vary in hierarchical B-frame compression depending on the level of hierarchy, which causes motion range to vary. The inability of a single B-frame compression model to adapt to various motion ranges causes loss of performance. As a remedy, we propose controlling the motion range for flow prediction during inference (to approximately match the range of motions in the training data) by downsampling video frames adaptively according to amount of motion and level of hierarchy in order to compress all B-frames using a single flexible-rate model. We present state-of-the-art BD rate results to demonstrate the superiority of our proposed single-model motion-adaptive inference approach to all existing learned B-frame compression models., Comment: 7 pages, submitted to IEEE ICIP 2024