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The field of infrared upconversion for astronomy is reviewed. The basic theory of upconversion is presented, along with a brief historical summary of upconversion techniques. Several investigators have employed upconverters in astronomical studies, but have met with only modest success. Upconversion will become a useful detection method for astronomy only if substantial but perhaps foreseeable improvements can be realized.
A method of mounting a cryogenically cooled, lightweight, double arch, glass mirror was developed for infrared, astronomical telescopes such as the Space Infrared Telescope Facility (SIRTF). A 50 cm, fused silica mirror which was previously fabricated was modified for use with a new mount configuration. This mount concept was developed. The modification of the mirror, the fabrication of the mirror mount, and the room temperature testing of the mounted mirror are reported. A design for a SIRTF class primary mirror is suggested.
The association of Halley particle results with data from existing meteoritic materials that can be analyzed in the laboratory is discussed. Comet samples must exist in present collections of meteoritic materials and the Halley results provide clues for identifying them. Although it is not presently possible to positively identify cometary meteorites or cometary interplanetary dust (IDP) samples, it is possible to determine which materials are similar to Halley dust and which ones are distinctly unlike Halley. The properties of these existing Halley-compatible samples provide insight into the possible properties of cometary material. Positive identification of meteoritic comet samples or direct samples returned from a comet nucleus would of course revolutionize our ability to study carbonaceous matter in comets. Modern analytical techniques are very powerful and it is possible to perform elemental, chemical, mineralogical and even limited isotopic analysis on micron-size particles. There is an important synergism between the laboratory studies of collected samples and astronomical data from comets and interstellar grains. To fully interpret results there must be convincing methods for associating a particular class or classes of meteoritic material with comets. Ultimately this will be done by direct comet sample return such as the Rosetta mission under development by ESA. At the present time the only links that can be made involve comparison with sample properties and measurable properties of comets. Unfortunately there is at present no known unique property of cometary dust that allows its absolute identification in the laboratory. The results from Halley encounters and observation do provide much new information on cometary grains. The Halley grain compositions, density, size distribution and scattering properties all provide a basis for future investigations. Other Halley properties such as the presence of polyoxymethylene and the 3.4um emission feature could play key roles for making convincing links in the future.
We demonstrate a key step along a technical route to achieving cm/s scale accuracy for astronomical spectrographs over long (multi-year) time scales, which is critical for the Doppler characterization of Earth sized exoplanets, and measurement of small cosmic redshift drift over many years. This same technique also enables searching exoplanet atmospheres for biosignificant molecules in direct planet imaging using, otherwise, insufficiently low resolution and drift prone dispersive (grating or prism) spectrographs. Using a method called crossfading for externally dispersed interferometers (EDIs) to get highly robust spectra, we recently demonstrated a factor of 1000 x reduction in the net shift of an EDI measured ThAr line to a deliberate simulated wavelength translation of the detector. This 1000 x gain in disperser stability can be combined with conventional stability gains afforded by fiber scramblers, vacuum tanks, and thermal control, to provide an additional 1 to 3 orders of magnitude reduction in the net point spread function shift drift. Crossfading combines high- and low-delay fringing signals that react oppositely in phase to cancel their net reaction to a detector wavelength drift. This can be implemented by an interferometer addition to a facility spectrograph.
It is pointed out that the simple and traditional method of measuring resistance using an electrometer is ineffective since it is limited to a narrow and nonrepresentative range of terminal voltages. The present investigation is concerned with a resistor measurement technique which was developed to select and calibrate the Transimpedance Mode Amplifier (TIA) load resistors on the Infrared Astronomical Satellite (IRAS) for the wide variety of time and voltage varying signals which will be processed during the flight. The developed method has great versatility and power, and makes it possible to measure the varied and complex responses of nonideal feedback resistors to IR photo-detector currents. When employed with a stable input coupling capacitor, and a narrow band RMS voltmeter, the five input waveforms thouroughly test and calibrate all the features of interest in a load resistor and its associated TIA circuitry.
Laser beam projector for continuous, precise alignment between target, laser generator, and astronomical telescope during tracking
This paper contains a collection of computational algorithms for determining geocentric ephemerides of Earth satellites, useful for both mission planning and data reduction applications. Special emphasis is placed on the computation of sidereal time, and on the determination of the geocentric coordinate of the center of the Sun, all to the accuracy found in the Astronomical Almanac. The report is completely self-contained in that no requirement is placed on any external source of information, and hence, these methods are ideal for computer application.
As soon as reliable methods for observationally determining the heliocentric orbits of meteoroids and hence the mean orbit of a meteoroid stream in the 1950s and 60s, astronomers strived to investigate the evolution of the orbit under the effects of gravitational perturbations from the planets. At first, the limitations in the capabilities of computers, both in terms of speed and memory, placed severe restrictions on what was possible to do. As a consequence, secular perturbation methods, where the perturbations are averaged over one orbit became the norm. The most popular of these is the Halphen- Goryachev method which was used extensively until the early 1980s. The main disadvantage of these methods lies in the fact that close encounter can be missed, however they remain useful for performing very long-term integrations. Direct integration methods determine the effects of the perturbing forces at many points on an orbit. This give a better picture of the orbital evolution of an individual meteoroid, but many meteoroids have to be integrated in order to obtain a realistic picture of the evolution of a meteoroid stream. The notion of generating a family of hypothetical meteoroids to represent a stream and directly integrate the motion of each was probably first used by Williams Murray & Hughes (1979), to investigate the Quadrantids. Because of computing limitations, only 10 test meteoroids were used. Only two years later, Hughes et. al. (1981) had increased the number of particles 20-fold to 200 while after a further year, Fox Williams and Hughes used 500 000 test meteoroids to model the Geminid stream. With such a number of meteoroids it was possible for the first time to produce a realistic cross-section of the stream on the ecliptic. From that point on there has been a continued increase in the number of meteoroids, the length of time over which integration is carried out and the frequency with which results can be plotted so that it is now possible to produce moving images of the stream. As a consequence, over recent years, emphasis has moved to considering stream formation and the role fragmentation plays in this.
The Chromospheric Lyman-Alpha Spectro-Polarimeter (CLASP) is a sounding-rocket instrument developed at the National Astronomical Observatory of Japan (NAOJ) as a part of an international collaboration. The in- strument main scientific goal is to achieve polarization measurement of the Lyman-alpha line at 121.56 nm emitted from the solar upper-chromosphere and transition region with an unprecedented 0.1% accuracy. For this purpose, the optics are composed of a Cassegrain telescope coated with a "cold mirror" coating optimized for UV reflection and a dual-channel spectrograph allowing for simultaneous observation of the two orthogonal states of polarization. Although the polarization sensitivity is the most important aspect of the instrument, the spatial and spectral resolutions of the instrument are also crucial to observe the chromospheric features and resolve the Ly- pro les. A precise alignment of the optics is required to ensure the resolutions, but experiments under vacuum conditions are needed since Ly-alpha is absorbed by air, making the alignment experiments difficult. To bypass this issue, we developed methods to align the telescope and the spectrograph separately in visible light. We will explain these methods and present the results for the optical alignment of the CLASP telescope and spectrograph. We will then discuss the combined performances of both parts to derive the expected resolutions of the instrument, and compare them with the flight observations performed on September 3rd 2015.
Modern neural networks (NNs) often do not generalize well in the presence of a ‘covariate shift’; that is, in situations where the training and test data distributions differ, but the conditional distribution of classification labels given the data remains unchanged. In such cases, NN generalization can be reduced to a problem of learning more robust, domain-invariant features. Domain adaptation (DA) methods include a broad range of techniques aimed at achieving this; however, these methods have struggled with the need for extensive hyperparameter tuning, which then incurs significant computational costs. In this work, we introduce SInkhorn Dynamic Domain Adaptation (SIDDA), an out-of-the-box DA training algorithm built upon the Sinkhorn divergence, that can achieve effective domain alignment with minimal hyperparameter tuning and computational overhead. We demonstrate the efficacy of our method on multiple simulated and real datasets of varying complexity, including simple shapes, handwritten digits, real astronomical observations, and remote sensing data. These datasets exhibit covariate shifts due to noise, blurring, differences between telescopes, and variations in imaging wavelengths. SIDDA is compatible with a variety of NN architectures, and it works particularly well in improving classification accuracy and model calibration when paired with symmetry-aware equivariant NNs (ENNs). We find that SIDDA consistently enhances the generalization capabilities of NNs, achieving up to a ${\approx}40\%$ improvement in classification accuracy on unlabeled target data, while also providing a more modest performance gain of $\lesssim 1\%$ on labeled source data. We also study the efficacy of DA on ENNs with respect to the varying group orders of the dihedral group DN, and find that the model performance improves as the degree of equivariance increases. Finally, if SIDDA achieves proper domain alignment, it also enhances model calibration on both source and target data, with the most significant gains in the unlabeled target domain—achieving over an order of magnitude improvement in the expected calibration error and Brier score. SIDDA’s versatility across various NN models and datasets, combined with its automated approach to domain alignment, has the potential to significantly advance multi-dataset studies by enabling the development of highly generalizable models.
We introduce Mahakala, a Python-based, modular, radiative ray-tracing code for curved spacetimes. We employ Google's JAX framework for accelerated automatic differentiation, which can efficiently compute Christoffel symbols directly from the metric, allowing the user to easily and quickly simulate photon trajectories through non-Kerr spacetimes. JAX also enables Mahakala to run in parallel on both CPUs and GPUs. Mahakala natively uses the Cartesian Kerr–Schild coordinate system, which avoids numerical issues caused by the pole in spherical coordinate systems. We demonstrate Mahakala's capabilities by simulating 1.3 mm wavelength images (the wavelength of Event Horizon Telescope observations) of general relativistic magnetohydrodynamic simulations of low-accretion rate supermassive black holes. The modular nature of Mahakala allows us to quantitatively explore how different regions of the flow influence different image features. We show that most of the emission seen in 1.3 mm images originates close to the black hole and peaks near the photon orbit. We also quantify the relative contribution of the disk, forward jet, and counterjet to 1.3 mm images.
Observations about the relationship between seismic activity and astronomical phenomena are discussed. First, after investigating the seismic data (magnitude 7.0 and over) with the method of superposed epochs it is found that world seismicity evidently increased after the occurring of novae with apparent magnitude brighter than 2.2. Second, a great many earthquakes of magnitude 7.0 and over occurred in the 13th month after two of the largest ground level solar cosmic ray events (GLEs). The causes of three high level phenomena of global seismic activity in 1918-1965 can be related to these, and it is suggested that according to the information of large GLE or bright nova predictions of the times of global intense seismic activity can be made.
Consideration is given to a definition of a distribution format for X-ray data, the Einstein on-line system, the NASA/IPAC extragalactic database, COBE astronomical databases, Cosmic Background Explorer astronomical databases, the ADAM software environment, the Groningen Image Processing System, search for a common data model for astronomical data analysis systems, deconvolution for real and synthetic apertures, pitfalls in image reconstruction, a direct method for spectral and image restoration, and a discription of a Poisson imagery super resolution algorithm. Also discussed are multivariate statistics on HI and IRAS images, a faint object classification using neural networks, a matched filter for improving SNR of radio maps, automated aperture photometry of CCD images, interactive graphics interpreter, the ROSAT extreme ultra-violet sky survey, a quantitative study of optimal extraction, an automated analysis of spectra, applications of synthetic photometry, an algorithm for extra-solar planet system detection and data reduction facilities for the William Herschel telescope.
Remote sensing and astronomical image formation is often complicated by deficiencies in measurement quality, density, or diversity. Penalized likelihood methods can incorporate additional first-principles physical prior knowledge and improve the image reconstructions, but a systematic bias is unavoidable as a consequence. This work derives theory to understand the bias and develops a computational tool to probe its effect on the reconstructed image and bound resolution limits. Though the focus is on image formation, the contributions of this paper apply to any inference problem that can be expressed under the linear state-space signal model.
For free-space optical communication systems, numerical wave optics simulations provide a useful technique for modeling turbulence-induced beam degradation when the analytical theory is insufficient for characterizing the atmospheric channel. Motivated by such applications we use a split-step method modeling the turbulence as a series of random phase screens using the Hufnagel-Valley turbulence profile. We employ a space-to-ground case study to examine the irradiance and phase statistics for uniformly and non-uniformly located screens and find better agreement with theory using a non-uniform discretization minimizing the contribution of each screen to the total scintillation. In this poster, we summarize the method and the results of the case study including a comparison to layered models used in astronomical imaging applications.
The paper examines some of the theoretical and practical aspects of (1) the relationship between the natural (astronomic) and the geometric sets of geodetic coordinates, expressed through the parameters of the geodetic datum, and (2) the reduction of the geometric and natural observations to their appropriate reference surfaces, that is, a rotational ellipsoid and the geoid, respectively. The distinction between absolute and astrogeodetic (relative) geodetic datums is made and the chief considerations for the reduction of observations are examined. Datum transformation and network distortions are discussed on the example of North American Datum 1927.
Modern neural networks (NNs) often do not generalize well in the presence of a "covariate shift"; that is, in situations where the training and test data distributions differ, but the conditional distribution of classification labels remains unchanged. In such cases, NN generalization can be reduced to a problem of learning more domain-invariant features. Domain adaptation (DA) methods include a range of techniques aimed at achieving this; however, these methods have struggled with the need for extensive hyperparameter tuning, which then incurs significant computational costs. In this work, we introduce SIDDA, an out-of-the-box DA training algorithm built upon the Sinkhorn divergence, that can achieve effective domain alignment with minimal hyperparameter tuning and computational overhead. We demonstrate the efficacy of our method on multiple simulated and real datasets of varying complexity, including simple shapes, handwritten digits, and real astronomical observations. SIDDA is compatible with a variety of NN architectures, and it works particularly well in improving classification accuracy and model calibration when paired with equivariant neural networks (ENNs). We find that SIDDA enhances the generalization capabilities of NNs, achieving up to a ≈40% improvement in classification accuracy on unlabeled target data. We also study the efficacy of DA on ENNs with respect to the varying group orders of the dihedral group DN, and find that the model performance improves as the degree of equivariance increases. Finally, we find that SIDDA enhances model calibration on both source and target data--achieving over an order of magnitude improvement in the ECE and Brier score. SIDDA's versatility, combined with its automated approach to domain alignment, has the potential to advance multi-dataset studies by enabling the development of highly generalizable models.
The effect of radiative reaction on the motion of particles is evaluated for pulsars with electromagnetic fields as strong as 10 to the twelfth power G, assuming that the pulsars are sources of high-energy particles. The analysis is limited to the specific motion of the particles. A simple method of solution, suitable for solving other similar problems, is proposed. The significance of particle motion to astronomical problems is examined.