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The color memory effect is the non-abelian gauge theory analog of the gravitational memory effect, in which the passage of color radiation induces a net relative SU(3) color rotation of a pair of nearby quarks. It is proposed that this effect can be measured in the Regge limit of deeply inelastic scattering at electron–ion colliders.
The optical color distributions of globular clusters (GCs) in most large elliptical galaxies are bimodal. Based on the assumed linear relationship between GC colors and their metallicities, the bimodality has been taken as evidence of two GC subsystems with different metallicities in each galaxy and has led to a number of theories in the context of galaxy formation. More recent observations and modeling of GCs, however, suggests that the color-metallicity relations (CMRs) are inflected, and thus colors likely trace metallicities in a nonlinear manner. The nonlinearity could produce bimodal color distributions from a broad underlying metallicity spread, even if it is unimodal. Despite the far-reaching implications, whether CMRs are nonlinear and whether the nonlinearity indeed causes the color bimodality are still open questions. Given that the spectroscopic refinement of CMRs is still very challenging, we here propose a new photometric technique to probe the possible nonlinear nature of CMRs. In essence, a color distribution of GCs is a 'projected' distribution of their metallicities. Since the form of CMRs hinges on which color is used, the shape of color distributions varies depending significantly on the colors. Among other optical colors, the u-band related colors (e.g., u - g and u - z) are theoretically predicted to exhibit significantly less inflected CMRs than other preferred CMRs (e.g., for g - z). As a case study, we performed the Hubble Space Telescope (HST)/WFPC2 archival u-band photometry for the M87 (NGC 4486) GC system with confirmed color bimodality. We show that the u-band color distributions are significantly different from that of g - z and consistent with our model predictions. With more u-band measurements, this method will support or rule out the nonlinear CMR scenario for the origin of GC color bimodality with high confidence. The HST/WFC3 observations in F336W for nearby large elliptical galaxies are highly anticipated in this regard.
We identified a general course of classical nova outbursts in the B – V versus U – B color-color diagram. It is reported that novae show spectra similar to those of A-F supergiants near optical light maximum. However, they do not follow the supergiant sequence in the color-color diagram, neither the blackbody nor the main-sequence sequence. Instead, we found that novae evolve along a new sequence in the pre-maximum and near-maximum phases, which we call 'the nova-giant sequence'. This sequence is parallel to but Δ(U – B) ≈ –0.2 mag bluer than the supergiant sequence. This is because the mass of a nova envelope is much (∼10{sup –4} times) less than that of a normal supergiant. After optical maximum, its color quickly evolves back blueward along the same nova-giant sequence and reaches the point of free-free emission (B – V = –0.03, U – B = –0.97), which coincides with the intersection of the blackbody sequence and the nova-giant sequence, and remains there for a while. Then the color evolves leftward (blueward in B – V but almost constant in U – B), owing mainly to the development of strong emission lines. This is the general course of nova outbursts in the color-color diagram, which was deduced from eight well-observed novae in various speed classes. For a nova with unknown extinction, we can determine a reliable value of the color excess by matching the observed track of the target nova with this general course. This is a new and convenient method for obtaining the color excesses of classical novae. Using this method, we redetermined the color excesses of 20 well-observed novae. The obtained color excesses are in reasonable agreement with the previous results, which in turn support the idea of our general track of nova outbursts. Additionally, we estimated the absolute V magnitudes of about 30 novae using a method for time-stretching nova light curves to analyze the distance-reddening relations of the novae.
Solid-state lighting is currently based on light-emitting diodes (LEDs) and phosphors. Solid-state lighting based on lasers would offer significant advantages including high potential efficiencies at high current densities. Light emitted from lasers, however, has a much narrower spectral line-width than light emitted from LEDs or phosphors. Therefore it is a common belief that white light produced by a set of lasers of different colors would not be of high enough quality for general illumination. We tested this belief experimentally, and found the opposite to be true. This result paves the way for the use of lasers in solid-state lighting.
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Though sometimes referred to as a two-measure system for evaluating color rendition, IES TM-30-15 includes other key components that go beyond the high-level average values IES Rf and IES Rg. This article focuses on the Color Vector Graphic and Local Chroma Shift (IES Rcs,hj), discussing the calculation methods for these evaluation tools and providing context for the interpretation of the values. It also presents alternatives for quantifying the same characteristics, which can inform the development of future measures. The Color Vector Graphic (CVG) is a visual representation of hue and chroma shifts across different hues. It quickly communicates complex information about how object colors will be rendered by a light source, although it is difficult or impossible to use for writing a specification. CVGs demonstrate that increases in chroma for certain hues sometimes means a decrease in chroma for other hues, and illustrates hue shifts for intermediate colors. The combination of shifts over different hues can be referred to as gamut shape. Complementing this information are the IES Rcs,hj values, which quantify the average relative chroma shift for samples in each of the 16 hue-angle bins (j) specified in IES TM-30-15. Unlike measures of average color fidelity and gamut area, gamut shape and hue-specific chroma shift are new concepts with no directly-comparable historical references. It will be critical to incorporate the Color Vector Graphic and Local Chroma Shift values into practice because they capture information about color rendition that is impossible to describe with average measures (such as CIE Ra, IES Rf, or IES Rg), but that is critical to understanding human evaluations of color quality in architectural environments.
Purpose: The aim of this study is to propose a method for the quantitative evaluation of image quality of both monochrome and color liquid-crystal displays (LCDs) using a commercially available color digital camera. Methods: The intensities of the unprocessed red (R), green (G), and blue (B) signals of a camera vary depending on the spectral sensitivity of the image sensor used in the camera. For consistent evaluation of image quality for both monochrome and color LCDs, the unprocessed RGB signals of the camera were converted into gray scale signals that corresponded to the luminance of the LCD. Gray scale signals for the monochrome LCD were evaluated by using only the green channel signals of the camera. For the color LCD, the RGB signals of the camera were converted into gray scale signals by employing weighting factors (WFs) for each RGB channel. A line image displayed on the color LCD was simulated on the monochrome LCD by using a software application for subpixel driving in order to verify the WF-based conversion method. Furthermore, the results obtained by different types of commercially available color cameras and a photometric camera were compared to examine the consistency of the authors’ method. Finally, image quality for both the monochrome and color LCDs was assessed by measuring modulation transfer functions (MTFs) and Wiener spectra (WS). Results: The authors’ results demonstrated that the proposed method for calibrating the spectral sensitivity of the camera resulted in a consistent and reliable evaluation of the luminance of monochrome and color LCDs. The MTFs and WS showed different characteristics for the two LCD types owing to difference in the subpixel structure. The MTF in the vertical direction of the color LCD was superior to that of the monochrome LCD, although the WS in the vertical direction of the color LCD was inferior to that of the monochrome LCD as a result of luminance fluctuations in RGB subpixels. Conclusions: The authors’ method based on the use of a commercially available color camera is useful to evaluate and understand the display performances of both monochrome and color LCDs in radiology departments.
We report a structural color printing platform based on aluminum plasmonic metamaterials supporting near perfect light absorption and narrow-band spectral response tunable across the visible spectrum to realize high-resolution, angle-insensitive color printing with high color purity and saturation. Additionally, the fabricated metamaterials can be protected by a transparent polymer thin layer for ambient use with further improved color performance. The demonstrated structural color printing with aluminum plasmonic metamaterials offers great potential for relevant applications such as security marking and information storage.
We conduct a pilot investigation to determine the optimal combination of color and variability information to identify quasars in current and future multi-epoch optical surveys. We use a Bayesian quasar selection algorithm to identify 35,820 type 1 quasar candidates in a 239 deg{sup 2} field of the Sloan Digital Sky Survey (SDSS) Stripe 82, using a combination of optical photometry and variability. Color analysis is performed on 5-band single- and multi-epoch SDSS optical photometry to a depth of r∼22.4. From these data, variability parameters are calculated by fitting the structure function of each object in each band with a power-law model using 10 to >100 observations over timescales from ∼1 day to ∼8 years. Selection was based on a training sample of 13,221 spectroscopically confirmed type-1 quasars, largely from the SDSS. Using variability alone, colors alone, and combining variability and colors we achieve 91%, 93%, and 97% quasar completeness and 98%, 98%, and 97% efficiency, respectively, with particular improvement in the selection of quasars at 2.7<z<3.5 where quasars and stars have similar optical colors. The 22,867 quasar candidates that are not spectroscopically confirmed reach a depth of i∼22.0; 21,876 (95.7%) are dimmer than coadded i-band magnitude of 19.9, the cutoff for spectroscopic follow-up for SDSS on Stripe 82. Brighter than 19.9, we find 5.7% more quasar candidates without confirming spectra in sky regions otherwise considered complete. The resulting quasar sample has sufficient purity (and statistically correctable incompleteness) to produce a luminosity function comparable to those determined by spectroscopic investigations. We discuss improvements that can be made to the process in preparation for performing similar photometric selection and science on data from post-SDSS sky surveys.
Color distributions of globular clusters (GCs) in most massive galaxies are bimodal. Assuming linear color-to-metallicity conversions, bimodality is viewed as the presence of merely two GC subsystems with distinct metallicities, which serves as a critical backbone of various galaxy formation theories. Recent studies, however, revealed that the color-metallicity relations (CMRs) often used to derive GC metallicities (e.g., CMRs of g - z, V - I, and C - T{sub 1}) are in fact inflected. Such inflection can create bimodal color distributions if the underlying GC metallicity spread is simply broad as expected from the hierarchical merging paradigm of galaxy formation. In order to test the nonlinear-CMR scenario for GC color bimodality, the u-band photometry is proposed because the u-related CMRs (e.g., CMRs of u - g and u - z) are theoretically predicted to be least inflected and most distinctive among commonly used optical CMRs. Here, we present Hubble Space Telescope (HST)/WFC3 F336W (u-band) photometry of the GC system in M84, a giant elliptical in the Virgo galaxy cluster. Combining the u data with the existing HST ACS/WFC g and z data, we find that the u - z and u - g color distributions are different from the g - z distribution in a very systematic manner and remarkably consistent with our model predictions based on the nonlinear-CMR hypothesis. The results lend further confidence to the validity of the nonlinear-CMR scenario as an explanation for GC color bimodality. There are some GC systems showing bimodal spectroscopic metallicity, and in such systems the inflected CMRs often create stronger bimodality in the color domain.
Abstract Coral snakes in the genus Micrurus are venomous, aposematic organisms that signal danger to predators through vivid coloration. Previous studies found that they serve as models to several harmless species of Batesian mimics. However, the extent to which Micrurus species engage in Müllerian mimicry remains poorly understood. We integrate detailed morphological and geographical distribution data to investigate if coral snakes are Müllerian mimics. We found that coloration is spatially structured and that Micrurus species tend to be more similar where they co-occur. Though long supposed, we demonstrate for the first time that coral snakes might indeed be Müllerian mimics as they show some convergence in coloration patterns. Additionally, we found that the length of red-coloured rings in Micrurus is conserved, even at large geographic scales. This finding suggests that bright red rings may be under more substantial stabilizing selection than other aspects of coloration and probably function as a generalized signal for deterring predators.
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In this paper we propose a spectroscopy-based stellar color regression (SCR) method to perform accurate color calibration for modern imaging surveys, taking advantage of millions of stellar spectra now available. The method is straightforward, insensitive to systematic errors in the spectroscopically determined stellar atmospheric parameters, applicable to regions that are effectively covered by spectroscopic surveys, and capable of delivering an accuracy of a few millimagnitudes for color calibration. As an illustration, we have applied the method to the Sloan Digital Sky Survey (SDSS) Stripe 82 data. With a total number of 23,759 spectroscopically targeted stars, we have mapped out the small but strongly correlated color zero-point errors present in the photometric catalog of Stripe 82, and we improve the color calibration by a factor of two to three. Our study also reveals some small but significant magnitude dependence errors in the z band for some charge-coupled devices (CCDs). Such errors are likely to be present in all the SDSS photometric data. Our results are compared with those from a completely independent test based on the intrinsic colors of red galaxies presented by Ivezić et al. The comparison, as well as other tests, shows that the SCR method has achieved a color calibration internally consistent at a level of about 5 mmag in u – g, 3 mmag in g – r, and 2 mmag in r – i and i – z. Given the power of the SCR method, we discuss briefly the potential benefits by applying the method to existing, ongoing, and upcoming imaging surveys.
Color rendition and energy efficiency have long been considered characteristics of light sources that cannot be maximized simultaneously. The tradeoff has been studied extensively, but usually considering only average color fidelity. This work examines the color rendition versus energy efficiency tradeoff in the context of ANSI/IES TM-30-18, Method for Evaluating Light Source Color Rendition, which provides numerous measures beyond average color fidelity. The analysis demonstrates that color rendition criteria based on combinations of ANSI/IES TM-30-18 values can be used to improve color quality with less of an effect on spectral efficiency (luminous efficacy of radiation) than increasing CIE Ra alone. No change in the direction of LED emitter or downconverter development is needed.
The Spitzer Space Telescope routinely detects asteroids in astrophysical observations near the ecliptic plane. For the galactic or extragalactic astronomer, these solar system bodies can introduce appreciable uncertainty into the source identification process. We discuss an infrared color discrimination tool that may be used to distinguish between solar system objects and extrasolar sources. We employ four Spitzer Legacy data sets, the First Look Survey-Ecliptic Plane Component (FLS-EPC), SCOSMOS, SWIRE, and GOODS. We use the Standard Thermal Model to derive FLS-EPC main belt asteroid (MBA) diameters of 1-4 km for the numbered asteroids in our sample and note that several of our solar system sources may have fainter absolute magnitude values than previously thought. A number of the MBAs are detected at flux densities as low as a few tens of {mu}Jy at 3.6 {mu}m. As the FLS-EPC provides the only 3.6-24.0 {mu}m observations of individual asteroids to date, we are able to use this data set to carry out a detailed study of asteroid color in comparison to astrophysical sources observed by SCOSMOS, SWIRE, and GOODS. Both SCOSMOS and SWIRE have identified a significant number of asteroids in their data, and we investigate the effectiveness of using relative color to distinguish between asteroids and background objects. We find a notable difference in color in the IRAC 3.6-8.0 mm and MIPS 24 {mu}m bands between the majority of MBAs, stars, galaxies, and active galactic nuclei, though this variation is less significant when comparing fluxes in individual bands. We find median colors for the FLS-EPC asteroids to be [F(5.8/3.6), F(8.0/4.5), F(24/8)] = (4.9 {+-} 1.8, 8.9 {+-} 7.4, 6.4 {+-} 2.3). Finally, we consider the utility of this technique for other mid-infrared observations that are sensitive to near-Earth objects, MBAs, and trans-Neptunian objects. We consider the potential of using color to differentiate between solar system and background sources for several space-based observatories, including Warm Spitzer, Herschel, and WISE.
Using new, highly accurate photometric redshifts from the MUSYC medium-band survey in the Extended Chandra Deep Field-South (ECDF-S), we fit synthetic stellar population models to compare active galactic nucleus (AGN) host galaxies to inactive galaxies at 0.8 {<=} z {<=} 1.2. We find that AGN host galaxies are predominantly massive galaxies on the red sequence and in the green valley of the color-mass diagram. Because both passive and dusty galaxies can appear red in optical colors, we use rest-frame near-infrared colors to separate passively evolving stellar populations from galaxies that are reddened by dust. As with the overall galaxy population, {approx}25% of the 'red' AGN host galaxies and {approx}75% of the 'green' AGN host galaxies have colors consistent with young stellar populations reddened by dust. The dust-corrected rest-frame optical colors are the blue colors of star-forming galaxies, which imply that these AGN hosts are not passively aging to the red sequence. At z {approx} 1, AGN activity is roughly evenly split between two modes of black hole growth: the first in passively evolving host galaxies, which may be heating up the galaxy's gas and preventing future episodes of star formation, and the second in dust-reddened young galaxies, which may be ionizing the galaxy's interstellar medium and shutting down star formation.
In this study, we analyze both linear and nonlinear color mappings by training on versions of a curated dataset collected in a controlled campus environment. We experiment with color space and color resolution to assess model performance in vehicle recognition tasks. Color encodings can be designed in principle to highlight certain vehicle characteristics or compensate for lighting differences when assessing potential matches to previously encountered objects. The dataset used in this work includes imagery gathered under diverse environmental conditions, including daytime and nighttime lighting. Experimental results inform expectations for possible improvements with automatic color space selection through feature learning. Moreover, we find there is only a gradual decrease in model performance with degraded color resolution, which suggests the need for simplified data collection and processing. By focusing on the most critical features, we could see improved model generalization and robustness, as the model becomes less prone to overfitting to noise or irrelevant details in the data. Such a reduction in resolution will lower computational complexity, leading to quicker training and inference times.