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We have detected the T Tauri star, DO Tauri, in a 0.6'-resolution VLA map of 43.3 GHz (l = 7 mm) continuum emission. Upper limits to the flux densities at 8.4 and 22.5 GHz limit the contribution of free-free emission due to a compact ionized wind to less than 49%.
The moon offers particular advantages for interferometry, including a vacuum environment, a large stable base on which to assemble multi-kilometer baselines, and a cold nighttime temperature to allow for passive cooling of optics for high IR sensitivity. A baseline design for a Lunar Optical Interferometer (LOI) which exploits these features is presented. The instrument operates in the visible to mid-IL region, and is designed for both astrometry and synthesis imaging. The design uses a Y-shaped array of 12 siderostats, with maximum arm lengths of about 1 km. The inner siderostats are monitored in three dimensions from a central laser metrology structure to allow for high precision astrometry. The outer siderostats, used primarily for synthesis imaging, exploit the availability of bright reference stars in order to determine the instrument geometry. The path delay function is partitioned into coarse and fine components, the former accomplished with switched banks of range mirrors monitored with an absolute laser metrology system, and the latter with a short cat's eye delay line. The back end of the instrument is modular, allowing for beam combiners for astrometry, visible and IR synthesis imaging, and direct planet detection. With 1 m apertures, the instrument will have a point-source imaging sensitivity of about 29 mag; with the laser metrology system, astrometry at the microarcsecond level will be possible.
The two worlds of interactive graphics and realistic graphics have remained separate. Fast graphics hardware runs simple algorithms and generates simple looking images. Photorealistic image synthesis software runs slowly on large expensive computers. The time has come for these two branches of computer graphics to merge. The speed and expense of graphics hardware is no longer the barrier to the wide acceptance of photorealism. There is every reason to believe that high quality image synthesis will become a standard capability of every graphics machine, from superworkstation to personal computer. The significant barrier has been the lack of a common language, an agreed-upon set of terms and conditions, for 3-D modeling systems to talk to 3-D rendering systems for computing an accurate rendition of that scene. Pixar has introduced RenderMan to serve as that common language. RenderMan, specifically the extensibility it offers in shading calculations, is discussed.
The Space Interferometry Mission (SIM) is the next major space mission in NASA's Origins program after SIRTF. The SIM architecture uses three Michelson interferometers in low-earth orbit to provide 4 microarcsecond precision absolute astrometric measurements on approx. 40,000 stars. SIM will also provide synthesis imaging in the visible waveband to a resolution of 10 milliarcsecond, and interferometric nulling to a depth of 10(exp -4). A near-IR (1-2 micron) capability is being considered. Many key technologies will be demonstrated by SIM that will be carried over directly or can be readily scaled to future Origins missions such as TPF. The SIM spacecraft will carry a triple Michelson interferometer with baselines in the 10 meter range. Two interferometers act as high precision trackers, providing attitude information at all time, while the third one conducts the science observations. Ultra-accurate laser metrology and active systems monitor the systematic errors and to control the instrument vibrations in order to reach the 4 microarcsecond level on wide-angle measurements. SIM will produce a wealth of new astronomical data. With an absolute positional precision of 4 microarcsecond, SIM will improve on the best currently available measures (the Hipparcos catalog) by 2 or 3 orders of magnitude, providing parallaxes accurate to 10% and transverse velocities to 0.2 km/s anywhere in the Galaxy, to stars as faint as 20th magnitude. With the addition of radial velocities, knowledge of the 6-dimension phase space for objects of interest will allow us to attack a wide array of previously inaccessible problems such as: search for planets down to few earth masses; calibration of stellar luminosities and by means of standard candles, calibration of the cosmic distance scale; detecting perturbations due to spiral arms, disk warps and central bar in our galaxy; probe of the gravitational potential of the Galaxy, several kiloparsecs out of the galactic plane; synthesis imaging of circumstellar disks around young stellar objects; imaging the narrow-line regions of AGNs in the optical; direct distance determination of a half dozen nearby spiral galaxies using rotational kinematics, thereby sidestepping reddening and metallicity issues in the calibration of distance estimators like Tully-Fisher; imaging exozodiacal dust disks (when operating in its nulling mode, SIM will be sensitive, at a distance of (beta) Pic (20 pc), to scales ranging from 0.2 to 5 AU).
This paper describes the Multimission VICAR (Video Image Communication and Retrieval) Planner (MVP) (Chien 1994) system, which uses artificial intelligence planning techniques (Iwasaki & Friedland, 1985, Pemberthy & Weld, 1992, Stefik, 1981) to automatically construct executable complex image processing procedures (using models of the smaller constituent image processing subprograms) in response to image processing requests made to the JPL Multimission Image Processing Laboratory (MIPL). The MVP system allows the user to specify the image processing requirements in terms of the various types of correction required. Given this information, MVP derives unspecified required processing steps and determines appropriate image processing programs and parameters to achieve the specified image processing goals. This information is output as an executable image processing program which can then be executed to fill the processing request.
This paper describes the Multimission VICAR Planner [Chien 1994] (MVP) system, which use Artificial Intelligence (AI) Planning techniques [Iwasaki & Friedland, 1985, Pemberthy & Weld, 1992, Stefik, 1981] to automatically construct executable complex image processing procedures.
A description of the results of the Venus northern hemisphere radar survey in 1983-1984 from the Venera 15 and 16 spacecrafts is presented. In addition, we discuss some peculiarities in the function of the radar equipment that defined the technology of SAR data processing. Among these peculiarities are insufficient calibration of SAR and radar altimeter and erroneous automatic gain control data transmission from the spacecrafts. As a result, the procedure of image synthesis and mosaicking contained multistage image brightness corrections. This led to the fact that the average image brightness in a spot 100 km in diameter was constant everywhere in the mosaics. Twenty-seven radar mosaics in the Lambert-Hauss conic projection with 1-2 km spatial resolution covering 25 percent of the surface of Venus have been produced. A Venus surface roughness map was constructed by joint processing of SAR and altimeter data. The mutual calibration of the SAR and altimeter was made in the special radar session when the SAR and altimeter were declined from the local vertical at the same angle. The possibility of estimating relative variations in surface reflection properties over a tens-of-kilometers interval from Venera images is still being considered. Joint analysis of the coordinates of small features of the Venera and Magellan images is one more approach being used to refine the period of rotation for Venus.
MATISSE is the second-generation mid-infrared spectrograph and imager for the Very Large Telescope Interferometer (VLTI) at Paranal. This new interferometric instrument will allow significant advances by opening new avenues in various fundamental research fields: studying the planet-forming region of disks around young stellar objects, understanding the surface structures and mass loss phenomena affecting evolved stars, and probing the environments of black holes in active galactic nuclei. As a first breakthrough, MATISSE will enlarge the spectral domain of current optical interferometers by offering the L and M bands in addition to the N band. This will open a wide wavelength domain, ranging from 2.8 to 13 microns, exploring angular scales as small as 3 mas (L band) 10 mas (N band). As a second breakthrough, MATISSE will allow mid-infrared imaging - closure-phase aperture-synthesis imaging - with up to four Unit Telescopes (UT) or Auxiliary Telescopes (AT) of the VLTI. Moreover, MATISSE will offer a spectral resolution range from R approx. 30 to R approx. 5000. Here, we present one of the main science objectives, the study of protoplanetary disks, that has driven the instrument design and motivated several VLTI upgrades (GRA4MAT and NAOMI). We introduce the physical concept of MATISSE including a description of the signal on the detectors and an evaluation of the expected performances. We also discuss the current status of the MATISSE instrument, which is entering its testing phase, and the foreseen schedule for the next two years that will lead to the first light at Paranal.
Experimental science is enabled by the combination of synthesis, imaging, and functional characterization organized into evolving discovery loop. Synthesis of new material is typically followed by a set of characterization steps aiming to provide feedback for optimization or discover fundamental mechanisms. However, the sequence of synthesis and characterization methods and their interpretation, or research workflow, has traditionally been driven by human intuition and is highly domain specific. Here, we explore concepts of scientific workflows that emerge at the interface between theory, characterization, and imaging. In this study, we discuss the criteria by which these workflows can be constructed for special cases of multiresolution structural imaging and functional characterization, as a part of more general material synthesis workflows. Some considerations for theory–experiment workflows are provided. We further pose that the emergence of user facilities and cloud labs disrupts the classical progression from ideation, orchestration, and execution stages of workflow development. To accelerate this transition, we propose the framework for workflow design, including universal hyperlanguages describing laboratory operation, ontological domain matching, reward functions and their integration between domains, and policy development for workflow optimization. These tools will enable knowledge-based workflow optimization; enable lateral instrumental networks, sequential and parallel orchestration of characterization between dissimilar facilities; and empower distributed research.
We present a formal comparison of the performance of algorithms used for synthesis imaging with optical/infrared long-baseline interferometers. Six different algorithms are evaluated based on their performance with simulated test data. Each set of test data is formated in the interferometry Data Exchange Standard and is designed to simulate a specific problem relevant to long-baseline imaging. The data are calibrated power spectra and bispectra measured with a ctitious array, intended to be typical of existing imaging interferometers. The strengths and limitations of each algorithm are discussed.
We present a formal comparison of the performance of algorithms used for synthesis imaging with optical/infrared long-baseline interferometers. Five different algorithms are evaluated based on their performance with simulated test data. Each set of test data is formatted in the OI-FITS format. The data are calibrated power spectra and bispectra measured with an array intended to be typical of existing imaging interferometers. The strengths and limitations of each algorithm are discussed.
Abstract Background The findings of the 2023 AAPM Grand Challenge on Deep Generative Modeling for Learning Medical Image Statistics are reported in this Special Report. Purpose The goal of this challenge was to promote the development of deep generative models for medical imaging and to emphasize the need for their domain‐relevant assessments via the analysis of relevant image statistics. Methods As part of this Grand Challenge, a common training dataset and an evaluation procedure was developed for benchmarking deep generative models for medical image synthesis. To create the training dataset, an established 3D virtual breast phantom was adapted. The resulting dataset comprised about 108 000 images of size 512 512. For the evaluation of submissions to the Challenge, an ensemble of 10 000 DGM‐generated images from each submission was employed. The evaluation procedure consisted of two stages. In the first stage, a preliminary check for memorization and image quality (via the Fréchet Inception Distance [FID]) was performed. Submissions that passed the first stage were then evaluated for the reproducibility of image statistics corresponding to several feature families including texture, morphology, image moments, fractal statistics, and skeleton statistics. A summary measure in this feature space was employed to rank the submissions. Additional analyses of submissions was performed to assess DGM performance specific to individual feature families, the four classes in the training data, and also to identify various artifacts. Results Fifty‐eight submissions from 12 unique users were received for this Challenge. Out of these 12 submissions, 9 submissions passed the first stage of evaluation and were eligible for ranking. The top‐ranked submission employed a conditional latent diffusion model, whereas the joint runners‐up employed a generative adversarial network, followed by another network for image superresolution. In general, we observed that the overall ranking of the top 9 submissions according to our evaluation method (i) did not match the FID‐based ranking, and (ii) differed with respect to individual feature families. Another important finding from our additional analyses was that different DGMs demonstrated similar kinds of artifacts. Conclusions This Grand Challenge highlighted the need for domain‐specific evaluation to further DGM design as well as deployment. It also demonstrated that the specification of a DGM may differ depending on its intended use.
High-frequency long-baseline experiments with the Atacama Large Millimeter/submillimeter Array were organized to test the high angular resolution imaging capabilities in the submillimeter wave regime using baselines up to 16 km. Four experiments were conducted, two Band 7 (289 GHz) and two Band 8 (405 GHz) observations. Phase correction using band-to-band (B2B) phase referencing was used with a phase calibrator only [[Formula]] away observed in Band 3 (96 GHz) and Band 4 (135 GHz), respectively. In Band 8, we achieved the highest resolution of 14 × 11 mas. We compared the synthesis images of the target quasar using 20 and 60 s switching cycle times in the phase referencing. In Band 7, the atmosphere had good stability in phase rms (<0.5 rad over 2 minutes), and there was little difference in image coherence between the 20 and 60 s switching cycle times. One Band 8 experiment was conducted under a worse phase rms condition (>1 rad over 2 minutes), which led to a significantly reduced coherence when using the 60 s switching cycle time. One of our four experiments indicates that the residual phase rms error after phase referencing can be reduced to 0.16 rad at 289 GHz in using the 20 s switching cycle time. Such conditions would meet the phase correction requirement of image coherence of >70% in Band 10, assuming a similar phase calibrator separation angle, emphasizing the need for such B2B phase referencing observing at high frequencies.
A structural-stochastic image model is developed for the analysis and synthesis of cloud images. The ability of the model to characterize the visual appearance of cloud fields observed by satellite with a limited number of parameters is demonstrated. The model merges structural and stochastic information, the stochastic model acting as a local statistical operator applied to the output of the structural model. The structural or large-scale organization of the scene is retrieved from the two-dimensional Fourier representation of the digital image. The pattern generated by the major Fourier components provides a first guess of the scene. The stochastic aspect is described by a Markov model of texture that assumes a binomial probability distribution for the local grey-level variability. This Markov model provides four parameters that represent the clustering strength in the horizontal, vertical and diagonal directions. These parameters are estimated by a standard maximum-likelihood technique. The image can be reproduced with a fair degree of verisimilitude from these parameters. The data compression factor is of the order of one hundred to several hundreds.
By arguing that the limiting noise is the photoelectron shot noise, we show that the sensitivity of image synthesis by an ideal optical interferometer is independent of the details of beam-splitting and recombination. The signal-to-noise ratio of the synthesized image is proportional to the square root of the total number of photoelectrons detected by the entire array. For non-ideal interferometers, which are forced to employ a closure-phase method of indirect inference of the visibility data, essentially the same result holds for strong sources, but at weak light levels beam-splitting degrades sensitivity.
Among current deep learning approaches for synthetic image generation, diffusion-based models stand out in terms of algorithmic stability and ability to retain high-fidelity image features with detailed resolution. Here, in this work, we employ Dreambooth, a method for fine-tuning Stable Diffusion, on X-ray CT images of microstructure of the polymer-bonded form (PBX) of a commonly used high explosive, Pentaerythritol tetranitrate (PETN), which yields generative models for creating synthetic PBX images. The models developed here represent five classes (or ‘lots’) of microstructures and demonstrate successful generation of images of each class with high fidelity, as verified by computed classification accuracy of ∼ 94% or higher. Data augmentation afforded by such image synthesis can be used to more reliably decipher underlying statistics, build processing-structure correlations, recognize off-normal structural anomalies, and identify age-related changes. Ideas related to converting image data into appropriate density mapping and performing mesoscale simulation or surrogate modeling of detonation are also discussed.
The National Radio Astronomy Observatory's proposed Millimeter Array (MMA) will bring unprecedented sensitivity, angular resolution, and image dynamic range to the millimeter wavelength region of the spectrum. An obvious question is whether such an instrument could be used to detect planets orbiting nearby stars. The techniques of aperture synthesis imaging developed for centimeter wavelength radio arrays are capable of producing images whose dynamic ranges greatly exceed the brightness ratio of a solar-type star and a Jupiter-like planet at sub-millimeter or millimeter wavelengths. The angular resolution required to separate a star and planet at a few pc distance can be obtained with baselines of several km. The greatest challenge is sensitivity. At the highest possible observing frequencies (approximately 300 GHz for typical high, dry sites, and approximately 900 GHz from the Antarctic plateau), the proposed MMA will be unable to detect the thermal emission from a Jupiter-like planet a few pc away. An upgraded MMA operating near 300 GHz with twice the currently proposed number of antennas, a 20% fractional bandwidth, and improved receivers could detect Jupiter at 4 pc in a few months. Building such an array on the Antarctic plateau and operating at approximately 900 GHz would allow Jupiter at 4 pc to be detected in approximately one day of observing time.
The Fizeau Interferometer Testbed (FIT) is a collaborative effort between NASA's Goddard Space Flight Center, the Naval Research Laboratory, Sigma Space Corporation, and the University of Maryland. The testbed will be used to explore the principles of and the requirements for the full, as well as the pathfinder, Stellar Imager mission concept. It has a long term goal of demonstrating closed-loop control of a sparse array of numerous articulated mirrors to keep optical beams in phase and optimize interferometric synthesis imaging. In this paper we present the optical and data acquisition system design of the testbed, and discuss the wavefront sensing and control algorithms to be used. Currently we have completed the initial design and hardware procurement for the FIT. The assembly and testing of the Testbed will be underway at Goddard's Instrument Development Lab in the coming months.