Astronomy

Has J been used by itself as a spectral type?

Has J been used by itself as a spectral type?

While answering the question "Why have brown dwarf classes been dubbed L, T and Y?" I noticed that in the paper Kirkpatrick et al. (1999) "Dwarfs Cooler than 'M': The Definition of Spectral Type 'L' Using Discoveries from the 2 Micron All-Sky Survey (2MASS)", the letter "J" was ruled out as being in use as a standard carbon star type.

So far I have not seen a source that uses "J" as a carbon star type by itself, I've only seen it in combination with "C", e.g. "C3,3J" or "C-J4 C2 5" (both from XHIP). This contrasts with the other carbon star types "R" and "N" which have definitely been used as separate identifiers.

Has "J" ever been used as a stand-alone spectral type, e.g. "J3"?


As far as I can tell, the J-type was introduced by Bouigue (1954), and have subsequently often called "J-type stars" or "J-stars", e.g. Abia & Isern (2000). This likely led to the J-type designation being put as "in use", though the spectral types themselves appear to always have been used in combination with "C".


Spectral Signatures

While the spectral signature of the NV center has long been known, the structure of the corresponding defect was established in the 1960s and 1970s through irradiation and annealing experiments combined with optical spectroscopy [144] . As shown in Fig. 13.24 a, the NV center consists of a substitutional nitrogen atom next to a missing carbon atom (vacancy) in the diamond lattice. The axis connecting the nitrogen atom to the adjacent vacancy can lie along any of the four (1 1 1) crystallographic directions of the diamond lattice. Since either the nitrogen or vacancy can rest at a particular site, a total of eight configurations are allowed. The NV center has trigonal symmetry (point group C 3 v ) with a threefold rotational symmetry about the N-V axis. As discussed below, the NV center has two optical transitions with dipole moments orthogonal to the N-V axis. As a result, the polarization of light emitted by an NV center depends both on the orientation of the N-V axis, and on the direction of the light emission, and hence on the crystal orientation of the polished surface. Figure 13.24 b–d illustrates this geometry for diamond samples polished along (1 0 0), (1 1 0), and (1 1 1). For a (1 0 0) surface, the magnitude of the angle between the N-V axis and the surface normal is the same for all orientations, but when collecting light normal to this surface, one will observe preferential polarization along either of two possible directions. For a (1 1 0) surface there are two orientations with the N-V axis parallel to the surface, providing poor optical access, while the other orientations, which are predominantly out-of-plane, have a more favorable collection geometry. For a (1 1 1) surface, there are three N-V orientations with poor optical access, but the fourth orientation has the N-V axis exactly normal to the surface, so that both dipole transitions can be optimally excited, and the emission most efficiently collected.

Figure 13.24 . Structure of the nitrogen-vacancy center in diamond, as seen from (a) a low-symmetry direction, (b) along [1 0 0], (c) along [1 1 0], and (d) along [1 1 1]. The yellow spheres, blue spheres, and dashed circles represent carbon atoms, nitrogen atoms, and vacancies, respectively.

NV centers can be created in several ways. For diamond of a given purity, NV centers created during diamond growth appear to have the best low-temperature optical linewidths and spin coherence properties. Figure 13.25 a shows an optical confocal microscopy image of single NV centers in a natural diamond sample. Since the surface of this sample is polished along (1 1 1), the four orientations of NV centers can be uniquely determined through the excitation polarization dependence alone [145] . It has recently been found [146] that in synthetic diamond grown by chemical vapor deposition (CVD) on a (1 1 0) surface, NV centers can be grown preferentially in the two out-of-plane orientations, [ 1 1 ¯ 1 ¯ ] and [ 1 ¯ 1 1 ¯ ] , as shown in Fig. 13.25 b. As mentioned above, if the NV center is excited non-resonantly, or at room temperature, the resulting mixture of light emitted from the two dipole transitions can be collected more efficiently for this geometry than for NV centers below a (1 0 0)-polished surface. It has also been shown that NV centers with good properties can be obtained in thin films grown by CVD [147–149] .

Figure 13.25 . Confocal microscopy images of NV centers. In (a, b), the dependence of the emission intensity on laser polarization has been encoded into color. (a) NV centers in natural diamond, imaged through a (1 1 1) surface. The four orientations are clearly distinguished through their polarization dependence. Scan size: 12 μ m . See Alegre et al., Ref. [145] . (b) NV centers in synthetic diamond grown on a (1 1 0) surface, showing preferential out-of-plane orientation. Scan size: 77 μ m . See Edmonds et al., Ref. [146] . (c) NV centers made by nitrogen ion implantation through lithographically defined nano-apertures.

Image courtesy of David Toyli. See also Ref. [154] .

To obtain a higher density of NV centers, or to obtain a useful density in ultra-pure diamond with nitrogen concentrations in the part-per-billion range, various implantation and irradiation techniques have been developed. For example, nitrogen ions may be implanted with depths ranging from a few nanometers to a few microns, depending on the chosen accelerating voltage. The sample is then annealed in an oxygen-free environment at temperatures ranging typically from 600 to 1000 °C, where vacancies become mobile and can combine with nitrogen impurities to form NV centers [150–152] . The efficiency of converting an implanted nitrogen atom into an NV center is typically only in the ≈ 5 % range, but may be increased using co-implantation with carbon to increase the number of vacancies [153] . The ion implantation may be performed through a lithographically defined mask [154] , as shown in Fig. 13.25 c, or through a scanned aperture [155,156] , to control the positions where NV centers will form to within a few tens of nanometers. The optical and spin properties of NV centers formed by nitrogen ion implantation and annealing are typically degraded, compared with as-grown NV centers in the same material. This is thought to result from interactions between the NV center and other defects in its vicinity resulting from implantation damage. Additional high-temperature annealing steps have been developed to recover better properties [157] .

One can also convert existing nitrogen into NV centers using MeV electron irradiation to create vacancies, followed by annealing [144,158,159] . While this method, by itself, does not provide control over the position of the NV centers (the electrons can travel for millimeters through the crystal at the energies required to create vacancies), NV centers created by this method can have properties as good as those of NV centers created during crystal growth [160] . Implantation with other particles such as protons, neutrons, helium ions, and gallium ions may also be used [161–164] .

None of the methods demonstrated to date can deterministically create a single NV center at a precise location and with a controlled orientation. Even deterministic ion implantation [165,166] would not be sufficient, since the conversion efficiency from an implanted ion to an NV center is low using existing techniques.


NANOSTRUCTURE PHYSICS, DEPTH VS. FASHION

Publisher Summary

This chapter provides an overview of nanostructure physics. It discusses mesoscopic systems and spectral correlations in the physics of nanostructures. Mesoscopic systems may be the ideal arena to study the interface between quantum mechanics and statistical and macroscopic physics. The first lessons that the research on mesoscopics has taught those that have not appreciated it before is the fundamental distinction between the two different kinds of scattering that an electron may undergo in a solid. The next issue that the mesoscopic experiments have clarified is the fact that such samples are not large enough to be self-averaging at low temperature. Some outstanding theoretical issues that remain are a fuller understanding of the effects of electron–electron interactions on dephasing and relaxation, equilibrium properties and transport. Even the validity of the single parameter scaling theory of noninteracting electron localization is still under debate. Finally, mesoscopic research should throw some fresh light on quantum measurement theory. Experiments should help to shed light on all of these issues.


Occurrence of planetary systems in the universe as a problem in stellar astronomy

In many problems involving binaries, rotating stars, and planetary systems, the angular momentum serves as an important parameter in addition to the mass, and merits some special considerations. In this paper the orientations in space of stellar angular-momentum vectors are first discussed in the light of empirical data, and their origin is then explained in terms of simple models.

The mutual relations between these three kinds of cosmic objects are then examined. It is found that the formation of planetary systems is closely related to the braking of stellar rotation and must be genetically different from that of binaries. For this reason the frequency occurrence and perhaps even the nature of planetary systems around the main-sequence stars later than F 5 may be estimated from the rotational behavior of the main-sequence stars of early spectral types. According to this estimate the size of our own planetary system lies within the estimated range.


Solar Thermal Energy, Industrial Heat Applications

Sanjay Vijayaraghavan , D.Y. Goswami , in Encyclopedia of Energy , 2004

4.1 The Utilizability Method

Utilizability, ϕ, has been used to describe the fraction of solar flux absorbed by a collector that is delivered to the working fluid. On a monthly time scale,

Here, the overbar is used to indicate monthly average values, Qu is the monthly averaged daily total useful energy delivery, F is a heat exchanger transfer factor, η ¯ o is the daily averaged optical efficiency of the collector, and Ic is the monthly averaged daily solar radiation incident on the collectors. φ ¯ is the fraction of the absorbed solar flux that is delivered to the fluid in a collector operating at a fixed temperature Tc. The φ ¯ concept does not apply to a system composed of collectors, storage, and other components where the value of Tc varies continuously. However, with most concentrators for concentration ratios greater than 10, the collector is relatively insensitive to a small range of operating temperatures. To check this assumption for a particular process, values of φ ¯ at the extremes of the expected temperature excursion can be compared.

The value of φ ¯ depends on many system and climatic parameters. Collares-Pereira and Rabl showed that only three are of the first order: the clearness index K ¯ T the critical intensity ratio X ¯ and the ratio r d / r T . The first is related to insolation statistics, the second to collector parameters and operating conditions, and the third to collector tracking and solar geometry.

Empirical expressions for φ ¯ have been developed for several collector types.

For example, for nontracking collectors,

Here, X ¯ is the monthly average daily critical intensity ratio, defined as the ratio of collector heat loss to absorbed solar flux at the “no net energy delivery” condition. The monthly averaged clearness index K ¯ T is defined as the ratio of the monthly averaged daily total radiation on a horizontal surface to that on a corresponding surface outside the earth's atmosphere. The ratio r d / r T is a factor that depends on solar geometry and collector tracking. Expressions are available and tabulated for various collector types.

Similar equations are available for other collector types and other clearness index values. In some cases, the collection time Δtc might need to be determined for nontracking, low-concentration collectors.

A well-known method to calculate the long-term performance of collector systems with storage is using the “f-Chart” method developed by Klein and Beckman. The f-Chart method can be used for estimating the fraction of the load that will be met by the solar thermal system. The method uses the utilizability (defined differently from the method given previously) and a few other nondimensional parameters to predict the monthly solar load fraction fs. Predictions are based on the results of simulations for various climatic conditions by an hourly time scale computer model.


Has J been used by itself as a spectral type? - Astronomy

Tue, 09 Mar 2021 15:32:45 +0000

5000 over an instantaneous wavelength range of 366-959 nm or at a resolution of R

20000 over two more-limited wavelength ranges. WEAVE has been delivered to the WHT and will be on sky in the summer of 2021 to provide complete phase-space coordinates of roughly 3 million stars in the northern sky selected with ESO’s Gaia satellite, chemical analysis of more than 1 million stars from Gaia, half a million massive stars in the Galactic Plane, distances and properties of galaxies selected from the low-frequency radio-wave surveys being conducted with LOFAR, “three-dimensional" spectroscopy of galaxies selected from surveys using the new Apertif focal plane array at WSRT, and deep surveys of galaxy clusters and moderate-redshift galaxies. I will discuss the design of WEAVE, its current status, and the eight surveys that comprise the 5- to 7-year WEAVE Survey.</div> <div> </div> <div> Zoom Recording: <a>https://uky.zoom.us/rec/share/rrYRpPaaPnBTWbBaaGwiVI_M_wgYn8wtBnZc9WOTQU5QTsqs_d72eMamjSkCk9mF.spTKWwXs6MhsQKlX</a></div></div></div></div><div field-name-field-tags field-type-taxonomy-term-reference field-label-inline clearfix"><div </div><ul inline"><li href="/tag/astronomy" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">astronomy</a></li><li href="/tag/physics-astronomy" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">physics &amp astronomy</a></li></ul></div><div field-name-field-event-type field-type-taxonomy-term-reference field-label-inline clearfix"><div of Event (for grouping events): </div><ul inline"><li href="/event-type/astro-seminar" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Astro Seminar</a></li><li href="/event-type/physics-and-astronomy-astro-seminar" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Physics and Astronomy Astro Seminar</a></li></ul></div><ul inline"><li first last"><a href="/calendar-asdate/month" title="View the calendar.">Calendar</a></li> </ul>

Thu, 04 Mar 2021 01:40:28 +0000

Wed, 03 Mar 2021 14:22:32 +0000

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Tue, 23 Feb 2021 15:16:32 +0000

20 streams with over 50 nights on AAT. In this talk, I will give a brief overview of the current status of the program, highlighting the latest science results from the survey, and end the talk with the public data release plan.</p> <p>Zoom Recording: <a>https://uky.zoom.us/rec/share/paz-EUSX-RPTLxR_bh9fOpUkrdfRrijEg3vPg7cdyqpX6EQREvS9LPJ8_O_SjsI.Z-EES8dDkrCZJ0-6</a></p></div></div></div><div field-name-field-tags field-type-taxonomy-term-reference field-label-inline clearfix"><div </div><ul inline"><li href="/tag/astronomy" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">astronomy</a></li><li href="/tag/physics-astronomy" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">physics &amp astronomy</a></li></ul></div><div field-name-field-event-type field-type-taxonomy-term-reference field-label-inline clearfix"><div of Event (for grouping events): </div><ul inline"><li href="/event-type/astro-seminar" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Astro Seminar</a></li><li href="/event-type/physics-and-astronomy-astro-seminar" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Physics and Astronomy Astro Seminar</a></li></ul></div><ul inline"><li first last"><a href="/calendar-asdate/month" title="View the calendar.">Calendar</a></li> </ul>

Sun, 31 Jan 2021 17:58:40 +0000

Sun, 31 Jan 2021 12:18:10 +0000

3.3, spanning the past 12 Gyr of cosmic history. I will discuss the implications for outflow rates and mass loading factors of galactic winds. I will also examine future observational prospects to improve the connection between gas flows and the metal and gas content of galaxies, and to extend gas-phase abundance studies into the epoch of reionization with JWST.<br /><div> <br /><a>Zoom Recording available: https://uky.zoom.us/rec/share/MCnGRgZDUm9N46Kb_k5_fvd75YC-VtwPz0yXM93r_M2zvW31UB7L-cxpli1EPvZi.bdpaiGguZO-M53HI</a></div></div></div></div><div field-name-field-tags field-type-taxonomy-term-reference field-label-inline clearfix"><div </div><ul inline"><li href="/tag/astronomy" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">astronomy</a></li><li href="/tag/physics-astronomy" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">physics &amp astronomy</a></li></ul></div><div field-name-field-event-type field-type-taxonomy-term-reference field-label-inline clearfix"><div of Event (for grouping events): </div><ul inline"><li href="/event-type/astro-seminar" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Astro Seminar</a></li><li href="/event-type/physics-and-astronomy-astro-seminar" typeof="skos:Concept" property="rdfs:label skos:prefLabel" datatype="">Physics and Astronomy Astro Seminar</a></li></ul></div><ul inline"><li first last"><a href="/calendar-asdate/month" title="View the calendar.">Calendar</a></li> </ul>

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0.003(1+z) photo-z for up to 9E7 LRG and ELG galaxies plus several million QSOs, sampling an effective volume of

1.3 reaching Stage IV radial BAO experiment. J-PAS is expected to detect

7E5 galaxy clusters and groups, setting constraints on Dark Energy which rival those obtained from its BAO measurements. </span></span></p> <p dir="ltr"><span to the superb characteristics of the site (seeing


Star type

Alkaid is a young star of the spectral type B3 V, indicating a star bluish in colour and still on the main sequence, burning hydrogen into helium in its core. It has 6.1 times the Sun’s mass and 3.4 times its radius. With an estimated temperature of 15,540 K, Alkaid is about 594 times more luminous than the Sun. It has an absolute magnitude of -0.67.

Alkaid (Eta Ursae Majoris), image: Wikisky

Alkaid is a fast spinner, with a projected rotational velocity of 150 km/s. Its estimated age is only 10 million years.

The star’s high surface temperature is likely due to “gravity darkening,” a phenomenon common among fast spinners. The stars that rotate so rapidly have an oblate spheroid shape and their equatorial radius is larger than their radius at the poles. Because the poles are closer to the centre of mass, they have a higher surface gravity, as well as higher temperature. As a result, their poles are brighter than the equator. Vega in the constellation Lyra and Achernar in Eridanus, the 5th and 9th brightest stars in the sky, are two other well-known examples of this.

B-type stars have pretty short lives. Alkaid is expected to burn through its supply of fuel in less than 100 million years and start evolving into a giant. It will eventually shed its outer layers to become a white dwarf with a mass of about 0.85 solar masses.


1 This is sometimes called the ‘Wolfer sunspot number’ in time-series textbooks. See Izenman [1].

2 Data files for all the examples in Feigelson’s review are available from http://xweb.nrl.navy.mil/timeseries/timeseries.html.

3 For example, events that fall within particular energy channels and within a particular part of the detector image. Not all events recorded by the detector will be caused by X-rays from the target source. Some event selection is required to reduce or remove background events, non-X-ray events and other contaminants.

4 Astronomers typically define QPOs in terms of the width of the peak, δf, relative to its centroid frequency, f0: Q=f0/δf the quality factor (also called coherence) of the oscillation. Periodic, quasi-periodic and noise processes are loosely defined in terms of their Q values: unresolved peaks with very high Q are strictly periodic, peaks with finite Q down to Q=2 are defined as QPOs (quasi-periodic) and even broader features (Q<2) are usually called noise (aperiodic).

5 Strictly, we should consider non-stationary and nonlinearity to be properties of models or processes, not data, which are but realizations of the process. In the present case, the model may be described as either nonlinear or non-stationary.

6 This algorithm seems to have been discovered several times. Very similar methods are discussed by Ripley [58], § 4.5, Davies & Harte [59] and Davis et al. [60].

7 In some astronomy contexts, this is also called as the transfer function.

8 The cross-spectrum and cross-covariance are Fourier counterparts, just as the power spectrum and auto-covariance are Fourier counterparts.

One contribution of 17 to a Discussion Meeting Issue ‘Signal processing and inference for the physical sciences’.


1.5. Stellar atmospheric parameters estimation

The stellar parameters estimation is to obtain the atmospheric parameters from the stellar spectra. These parameters, such as Teff (the effective temperature), log g (the surface gravity) and [Fe/H] (the metallicity) reflect the intrinsic physical properties of stars, such as ages, masses, and elemental abundances. From the view of machine learning, this task can be regarded as a regression, in which the representative spectra along with known parameters are used to train a nonlinear regression model. This model is then used to predict the unknown stellar atmospheric parameters. Since ANN is a commonly used model for regression, it also can be used in stellar parameters estimation. Gulati et al. [53] train an ANN with synthetic spectra to assign the effective temperatures for G-K dwarfs. Bailer-Jones et al. [54] employ ANNs to produce physical parameters for observed stellar spectra. They generate a grid of synthetic spectra for a range of different atmospheric parameters. These synthetic optical stellar spectra are used to train a network. The trained network is then used to determine the effective temperature for over 5,000 real observed dwarfs and giants. Subsequently, Bailer-Jones [55] investigates the performance of ANN in the stellar parameter estimation with spectra at low resolution and SNR. It is found that neural networks can yield good determination of stellar parameters even at low resolution. Manteiga et al. [56] take coefficients of Fast Fourier Transform (FFT) and Discrete Wavelet Transform (DWT) as input features to an ANN which is trained to estimate the parameters Teff, log g, [Fe/H] and [α/Fe]. With the advancement of observation instruments, the increasing amount spectral data make the training of more sophisticated networks feasible. Yang and Li [57] use the auto-encoder to learn a set of local representations from stellar spectra. Then they use a back-propagation (BP) network to estimate stellar parameters.


Mass inventory of the giant-planet formation zone in a solar nebula analogue

The initial mass distribution in the solar nebula is a critical input to planet formation models that seek to reproduce today’s Solar System 1 . Traditionally, constraints on the gas mass distribution are derived from observations of the dust emission from disks 2,3 , but this approach suffers from large uncertainties in dust opacity and gas-to-dust ratio 2 . On the other hand, previous observations of gas tracers only probe surface layers above the bulk mass reservoir 4 . Here we present the first partially spatially resolved observations of the 13 C 18 O J = 3–2 line emission in the closest protoplanetary disk, TW Hydrae, a gas tracer that probes the bulk mass distribution. Combining it with the C 18 O J = 3–2 emission and the previously detected HD J = 1–0 flux, we directly constrain the mid-plane temperature and optical depths of gas and dust emission. We report a gas mass distribution with radius, R, of 13 − 5 + 8 × ( R / 20 .5 au ) − 0.9 − 0.3 + 0.4 g cm −2 in the expected formation zone of gas and ice giants (5–21 au). We find that the mass ratio of total gas to millimetre-sized dust is 140 in this region, suggesting that at least 2.4M of dust aggregates have grown to centimetre sizes (and perhaps much larger). The radial distribution of gas mass is consistent with a self-similar viscous disk profile but much flatter than the posterior extrapolation of mass distribution in our own and extrasolar planetary systems.

The primary theory for the formation of giant planets is the ‘core accretion’ scenario, in which a rock-and-ice core forms through the coagulation of planetesimals until it becomes sufficiently massive to accrete a gaseous envelope 1 . In this theory, the spatial distribution of gas in the primitive nebula is not only critical to the later accretion of the atmosphere of giant planets, but also plays an important role in the early planetesimal formation processes, as the transport and mixing of grain aggregates depend on the gas turbulence and density 5,6 .