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Playa Girón | See also | See also
Geography of Cuba |
Playa Girón | References | References |
Playa Girón | External links | External links
Category:Populated places in Matanzas Province
Category:Beaches of Cuba |
Playa Girón | Table of Content | Use dmy dates, Geography, History, Bay of Pigs Invasion, Other, Music, Gallery, Bibliography, See also, References, External links |
British Columbia Highway 6 | Short description | Highway 6 is a two-lane highway passing between the Kootenay and Okanagan regions in the province of British Columbia, Canada. It is divided into two parts—the Nelson-Nelway Highway between the Canada–United States border and Nelson, and the Vernon-Slocan Highway between South Slocan and Vernon. Highway 6 is a north–south highway between Nelway and the Needles Ferry and an east–west highway between the Needles Ferry and Vernon; it has a total length of . It first opened in 1941 and, aside from minor realignments along its concurrences with 3 and 3A, its very winding path through the western Kootenays has not changed since. |
British Columbia Highway 6 | Route description | Route description |
British Columbia Highway 6 | Nelson-Nelway Highway | Nelson-Nelway Highway
thumb|Highway 6 looking north towards Nelson in the Selkirk mountains.
Highway 6 begins at the Canada–United States border crossing at Nelway, where it connects with Washington State Route 31. The highway parallels the Salmo River for the rivers entire length from Nelson to the border and many views of the river can be seen from the highway. From the Canada–United States border, it travels north through the Selkirk Mountains for to the Burnt Flat Junction, where the Crowsnest Highway (Highway 3) merges onto it from the east. Highway 3 and Highway 6 share a concurrency north for to the town of Salmo, where Highway 3 diverges west.
From Salmo, Highway 6 goes north for , continuing to follow the Salmo River valley to the town of Ymir. Then it continues north for passing through the communities of Porto Rico and Hall Siding, to the city of Nelson, just south of which (10 km) access to the Whitewater Ski Resort is located. Highway 3A merges onto Highway 6 in Nelson, and the two highways travel west for along the Kootenay River, passing through the communities of Taghum, Bonnington Falls, Beasley and Corra Linn to where Highway 3A diverges southwest just west of South Slocan at Playmour Junction. The highway then proceeds north west up the Slocan Valley. |
British Columbia Highway 6 | Vernon-Slocan Highway | Vernon-Slocan Highway
thumb|left|Highway 6 at the Monashee Summit
From South Slocan, Highway 6 follows the Slocan River north for passing through Winlaw, Slocan City and Silverton to the community of New Denver, where Highway 31A meets Highway 6. northwest of New Denver, Highway 6 reaches its junction with Highway 23 at the resort community of Nakusp. Highway 6 then turns southwest and proceeds to follow the east bank of the Columbia River (Lower Arrow Lake) for to Fauquier, on the east shore of Lower Arrow Lake, where the Needles Ferry is located.
From Needles, Highway 6 takes a winding path northwest through the Monashee Mountain range, passing through the community of Cherryville on its exit from the mountains, until it reaches the community of Lumby, away. Highway 6 then proceeds west on its final through the district of Coldstream, and terminates at a junction with Highway 97 in Vernon. |
British Columbia Highway 6 | History | History
Some maps show Highway 6 originally continuing west from Vernon to Monte Creek, approximately east of Kamloops. This section became part of Highway 97 in 1953. |
British Columbia Highway 6 | Major intersections | Major intersections
From south to north: |
British Columbia Highway 6 | References | References |
British Columbia Highway 6 | External links | External links
06
Category:Arrow Lakes
Category:Slocan Valley
Category:West Kootenay
006
Category:Highways in the Okanagan |
British Columbia Highway 6 | Table of Content | Short description, Route description, Nelson-Nelway Highway, Vernon-Slocan Highway, History, Major intersections, References, External links |
Saturnus | '''Saturnus''' | Saturnus may refer to:
Saturn (mythology), a Roman god whose Latin name was Saturnus
Saturnus (band), a band from Denmark
Saturnus (butterfly), a genus of butterflies in the grass skipper family
Saturn, a planet in the Solar System |
Saturnus | Table of Content | '''Saturnus''' |
Taha Māori | Short description | Taha Māori is a New Zealand phrase, used in both Māori and New Zealand English. It means "the Māori side (of a question)" or "the Māori perspective" as opposed to the Pākehā or European side or perspective.
In many New Zealand families, particularly those established for two or three generations or more, there has been intermarriage between Māori and Pākehā. This means that a large proportion of people born in New Zealand are of mixed descent, both Māori and Pākehā. The Taha Māori refers not to their ancestry so much as to the customs of their Māori ancestors and appropriateness of both acknowledging and following these customs.
For many years Pākehā custom and usage has been dominant in New Zealand. However, since about the 1980s the place of Māori custom in New Zealand society has been increasingly recognized, albeit reluctantly, by many sections of the populace.
A person who accepts their Taha Māori will often try to live according to Tikanga Māori. |
Taha Māori | See also | See also
Māori culture |
Taha Māori | References | References
Category:Māori culture
Category:Māori words and phrases
Category:Māori society |
Taha Māori | Table of Content | Short description, See also, References |
First Growth | Short description | First Growth () status is a classification of wines primarily from the Bordeaux region of France.
The wines considered “best of the best” are assigned the rank of Premier Cru, with only five wines, Château Lafite Rothschild, Château Margaux, Château Haut-Brion, Château Latour, and Château Mouton Rothschild rated “First Growth”. |
First Growth | History | History |
First Growth | Bordeaux reds | Bordeaux reds
The need for a classification of the best Bordeaux wines arose from the 1855 Exposition Universelle de Paris. The result was the Bordeaux Wine Official Classification of 1855, a list of the top ranked wines, named the Grand Crus Classés (Great Classified Growths). With several thousand Chateaux producing their wines in Bordeaux, to be classified was to carry a mark of high prestige.
Within the Grand Cru Classé list, wines were further ranked and placed in one of five divisions. The best of the best wines were assigned the highest rank of Premier Cru; only four wines, Château Latour, Château Lafite Rothschild, Château Margaux and Château Haut-Brion were deemed worthy. Of all the 61 great classified wines, all but one came from the Médoc region. The exception was the premier cru Château Haut-Brion, produced in Graves.
The 1855 list remained unchanged for over a hundred years until finally Mouton Rothschild was promoted to Premier Cru status in 1973, after decades of relentless lobbying by its powerful owner, Baron Philippe de Rothschild. Of lesser importance, in 1988 the premier cru Château Haut-Brion was changed in appellation from Graves to Pessac-Leognan to represent apparent changes in soil structure caused by the urbanisation of areas surrounding Bordeaux. |
First Growth | Bordeaux sweet wines | Bordeaux sweet wines
Also in 1855, 21 of the best sweet wines from Bordeaux were classified as Grand Crus Classés in a separate list. In the original classification, nine wines (primarily from the Sauternes and Barsac regions) were classed as Premier Cru, while 11 were assigned the lower (though still prestigious) rank of Deuxième Cru (Second Growth). One wine (Château d'Yquem) was considered so great it was granted a special Premier Cru Supérieur classification. |
First Growth | Other classification schemes in Bordeaux | Other classification schemes in Bordeaux
With the exception of Château Haut-Brion from Graves, the 1855 Classification did not include producers in the regions of Graves, Saint-Émilion and Pomerol. For details on their own classification schemes, see their sections below. |
First Growth | Other classification schemes in France | Other classification schemes in France
Burgundy maintains its own classification scheme based on specific appellations. Although the terminology used is similar, the classification hierarchy is different and also attaches to the vineyards themselves. The most-highly rated vineyards are graded as Grand Cru, while those at the next level are classified as Premier Cru. |
First Growth | First Growth wines today | First Growth wines today |
First Growth | Bordeaux reds | Bordeaux reds |
First Growth | ''Premier Grand Cru'' | Premier Grand Cru
Château Lafite Rothschild Médoc (Pauillac)
Château Margaux Médoc (Margaux)
Château Latour Médoc (Pauillac)
Château Haut-Brion Graves (Pessac-Leognan)
Château Mouton-Rothschild Médoc (Pauillac) |
First Growth | Bordeaux sweet wines | Bordeaux sweet wines |
First Growth | ''Premier Cru Supérieur'' | Premier Cru Supérieur
Château d'Yquem (Sauternes) |
First Growth | ''Premier Cru'' | Premier Cru
Château La Tour Blanche, Bommes (Sauternes)
Château Lafaurie-Peyraguey, Bommes (Sauternes)
Château Clos Haut-Peyraguey, Bommes (Sauternes)
Château de Rayne-Vigneau, Bommes (Sauternes)
Château Suduiraut, Preignac (Sauternes)
Château Coutet, Barsac
Château Climens, Barsac
Château Guiraud, Sauternes
Château Rieussec, Fargues (Sauternes)
Château Rabaud-Promis, Bommes (Sauternes)
Château Sigalas-Rabaud, Bommes (Sauternes)
The communes of Bommes, Fargues and Preignac were once separate communes but now fall into the single commune of Sauternes. |
First Growth | The Graves classification | The Graves classification
After the Second World War the omission of wines of Graves from the official classification was having a negative effect on the price and desirability of wines from the region. To improve marketing the region announced in 1953 its own classification of red wines and one white wine, with more white wines added in 1959. Sixteen wines were given special classification.
Château Bouscaut (red & white)
Château Carbonnieux (red & white)
Château Couhins (white)
Château Couhins-Lurton (white)
Domaine de Chevalier (red & white)
Château de Fieuzal (red)
Château Haut-Bailly (red)
Château Haut-Brion (red)
Château La Mission Haut-Brion (red)
Château La Tour Haut-Brion (red)
Château Latour-Martillac (red & white)
Château Laville Haut-Brion (white)
Château Malartic-Lagravière (red & white)
Château Olivier (red & white)
Château Pape Clément (red)
Château Smith Haut Lafitte (red) |
First Growth | The Saint-Émilion classification | The Saint-Émilion classification
Missing from the 1855 list, the Bordeaux region of Saint-Émilion offered its own classification in 1955 to improve market demand and prices. The Classification of Saint-Émilion wine differs from the 1855 list in that it is updated approximately every ten years based on new assessments of quality. For each new release of the classification, wines may be promoted or demoted within the list. A wine may even be removed entirely, while other unclassified wines may be added. In 2006, for example, eleven wines were removed from the list, six new wines added, and two existing wines promoted to a higher division.
The Saint-Émilion Classification currently labels 15 wines as First Growths. These Premiers Grands Crus Classés, subdivided into two further classes : A (2 wines) and B (13 wines). A further 64 wines are currently classified as Grands Crus Classés. |
First Growth | Premiers Grands Crus Classés A | Premiers Grands Crus Classés A
Château Figeac
Château Pavie |
First Growth | Premiers Grands Crus Classés B | Premiers Grands Crus Classés B
Château Beauséjour (Duffau-Lagarrosse)
Château Beau-Séjour Bécot
Château Bélair-Monange
Château Canon
Château Canon-la-Gaffelière
Château Figeac
Clos Fourtet
Château Larcis Ducasse
Château La Gaffelière
Château Magdelaine
Château Pavie-Macquin
Château Troplong Mondot
Château Trottevieille |
First Growth | Former Premier Crus Classés | Former Premier Crus Classés
Château Angélus
Château Ausone
Château Cheval Blanc |
First Growth | Pomerol | Pomerol
Pomerol has refused to create any sort of classification scheme but it has produced red wines that are among the most expensive in the world, such as Petrus. |
First Growth | See also | See also
French wine
Bordeaux wine
Wine labels
Second wine |
First Growth | References | References
Category:Bordeaux wine
Category:Wine classification
Category:Wine terminology |
First Growth | Table of Content | Short description, History, Bordeaux reds, Bordeaux sweet wines, Other classification schemes in Bordeaux, Other classification schemes in France, First Growth wines today, Bordeaux reds, ''Premier Grand Cru'', Bordeaux sweet wines, ''Premier Cru Supérieur'', ''Premier Cru'', The Graves classification, The Saint-Émilion classification, Premiers Grands Crus Classés A, Premiers Grands Crus Classés B, Former Premier Crus Classés, Pomerol, See also, References |
Sloan Digital Sky Survey | short description | The Sloan Digital Sky Survey or SDSS is a major multi-spectral imaging and spectroscopic redshift survey using a dedicated 2.5-m wide-angle optical telescope at Apache Point Observatory in New Mexico, United States. The project began in 2000 and was named after the Alfred P. Sloan Foundation, which contributed significant funding.
A consortium of the University of Washington and Princeton University was established to conduct a redshift survey. The Astrophysical Research Consortium (ARC) was established in 1984 with the additional participation of New Mexico State University and Washington State University to manage activities at Apache Point. In 1991, the Sloan Foundation granted the ARC funding for survey efforts and the construction of equipment to carry out the work. |
Sloan Digital Sky Survey | Background | Background
At the time of its design, the SDSS was a pioneering combination of novel instrumentation as well as data reduction and storage techniques that drove major advances in astronomical observations, discoveries, and theory.
The SDSS project was centered around two instruments and data processing pipelines that were groundbreaking for the scale at which they were implemented:
A multi-filter/multi-array scanning CCD camera to take an imaging survey of the sky at high efficiency, followed by
A multi-object/multi-fiber spectrograph that could take spectra in bulk (several hundred objects at a time) of targets identified from the survey
A major new challenge was how to deal with the exceptional data volume generated by the telescope and instruments. At the time, hundreds of gigabytes of raw data per night was unprecedented, and a collaborating team as complex as the original hardware and engineering team was needed to design a software and storage system for processing the data. From each imaging run, object catalogs, reduced images, and associated files were produced in a highly automated pipeline, yielding the largest astronomical object catalogs (billions of objects) available in digital queryable form at the time. For each spectral run, thousands of two-dimensional spectral images had to be processed to automatically extract calibrated spectra (flux versus wavelength).
In the approximate decade it took to achieve these goals, SDSS contributed to notable advances in massive database storage and accessing technology, such as SQL, and was one of the first major astronomical projects to make data available in this form. The model of giving the scientific community and public broad and internet-accessible access to the survey data products was also relatively new at the time.
The collaboration model around the project was also complex but successful, given the large numbers of institutions and individuals needed to bring expertise to the system. Universities and foundations were participants along with the managing partner ARC. Other participants included Fermi National Accelerator Laboratory (Fermilab), which supplied computer processing and storage capabilities, and colleagues from the computing industry. |
Sloan Digital Sky Survey | Operation | Operation
thumb|SDSS map shown as a rainbow of colors, located within the observable Universe (the outer sphere, showing fluctuations in the Cosmic Microwave Background). As we look out in distance, we look back in time. So, the location of these signals reveals the expansion rate of the Universe at different times in cosmic history. (2020)
Data collection began in 2000; the final imaging data release (DR9) covers over 35% of the sky, with photometric observations of around nearly 1 billion objects, while the survey continues to acquire spectra, having so far taken spectra of over 4 million objects. The main galaxy sample has a median redshift of z = 0.1; there are redshifts for luminous red galaxies as far as z = 0.7, and for quasars as far as z = 5; and the imaging survey has been involved in the detection of quasars beyond a redshift z = 6.
Data release 8 (DR8), released in January 2011, includes all photometric observations taken with the SDSS imaging camera, covering 14,555 square degrees on the sky (just over 35% of the full sky). Data release 9 (DR9), released to the public on 31 July 2012, includes the first results from the Baryon Oscillation Spectroscopic Survey (BOSS), including over 800,000 new spectra. Over 500,000 of the new spectra are of objects in the Universe 7 billion years ago (roughly half the age of the universe). Data release 10 (DR10), released to the public on 31 July 2013, includes all data from previous releases, plus the first results from the APO Galactic Evolution Experiment (APOGEE), including over 57,000 high-resolution infrared spectra of stars in the Milky Way. DR10 also includes over 670,000 new BOSS spectra of galaxies and quasars in the distant universe. The publicly available images from the survey were made between 1998 and 2009.
In July 2020, after a 20-year-long survey, astrophysicists of the Sloan Digital Sky Survey published the largest, most detailed 3D map of the universe so far, filled a gap of 11 billion years in its expansion history, and provided data which supports the theory of a flat geometry of the universe and confirms that different regions seem to be expanding at different speeds. |
Sloan Digital Sky Survey | Observations | Observations
SDSS uses a dedicated 2.5 m wide-angle optical telescope; from 1998 to 2009 it observed in both imaging and spectroscopic modes. The imaging camera was retired in late 2009, since then the telescope has observed entirely in spectroscopic mode.
Images were taken using a photometric system of five filters (named u, g, r, i and z). These images are processed to produce lists of objects observed and various parameters, such as whether they seem pointlike or extended (as a galaxy might) and how the brightness on the CCDs relates to various kinds of astronomical magnitude.
For imaging observations, the SDSS telescope used the drift scanning technique, but with a choreographed variation of right ascension, declination, tracking rate, and image rotation which allows the telescope to track along great circles and continuously record small strips of the sky. The image of the stars in the focal plane drifts along the CCD chip, and the charge is electronically shifted along the detectors at the same rate, instead of staying fixed as in tracked telescopes. (Simply parking the telescope as the sky moves is only workable on the celestial equator, since stars at different declination move at different apparent speeds). This method allows consistent astrometry over the widest possible field and minimises overheads from reading out the detectors. The disadvantage is minor distortion effects.
The telescope's imaging camera is made up of 30 CCD chips, each with a resolution of pixels, totaling approximately 120 megapixels. The chips are arranged in 5 rows of 6 chips. Each row has a different optical filter with average wavelengths of 355.1 (u), 468.6 (g), 616.5 (r), 748.1 (i), and 893.1 (z)nm, with 95% completeness in typical seeing to magnitudes of 22.0, 22.2, 22.2, 21.3, and 20.5, for u, g, r, i, z respectively. The filters are placed on the camera in the order r, i, u, z, g. To reduce noise, the camera is cooled to 190 kelvins (about −80°C) by liquid nitrogen.
+SDSS photometric system filtersugrizMean wavelength (nm)355.1 468.6616.5748.1893.1Magnitude limit22.022.222.221.320.5
Note: colors are only approximate and based on wavelength to sRGB representation.
Using these photometric data, stars, galaxies, and quasars are also selected for spectroscopy. The spectrograph operates by feeding an individual optical fibre for each target through a hole drilled in an aluminum plate. Each hole is positioned specifically for a selected target, so every field in which spectra are to be acquired requires a unique plate. The original spectrograph attached to the telescope was capable of recording 640 spectra simultaneously, while the updated spectrograph for SDSSIII can record 1000 spectra at once. Throughout each night, between six and nine plates are typically used for recording spectra. In spectroscopic mode, the telescope tracks the sky in the standard way, keeping the objects focused on their corresponding fiber tips.
Every night the telescope produces about 200GB of data. |
Sloan Digital Sky Survey | Phases | Phases
thumb|Quasars acting as gravitational lenses. To find these cases of galaxy–quasar combinations acting as lenses, astronomers selected 23,000 quasar spectra from the SDSS. |
Sloan Digital Sky Survey | SDSS-I: 2000–2005 | SDSS-I: 2000–2005
During its first phase of operations, 2000–2005, the SDSS imaged more than 8,000 square degrees of the sky in five optical bandpasses, and it obtained spectra of galaxies and quasars selected from 5,700 square degrees of that imaging. It also obtained repeated imaging (roughly 30 scans) of a 300 square-degree stripe in the southern Galactic cap. |
Sloan Digital Sky Survey | SDSS-II: 2005–2008 | SDSS-II: 2005–2008
In 2005 the survey entered a new phase, the SDSS-II, by extending the observations to explore the structure and stellar makeup of the Milky Way, the SEGUE and the Sloan Supernova Survey, which watches after supernova Ia events to measure the distances to far objects. |
Sloan Digital Sky Survey | Sloan Legacy Survey | Sloan Legacy Survey
The Sloan Legacy Survey covers over 7,500 square degrees of the Northern Galactic Cap with data from nearly 2 million objects and spectra from over 800,000 galaxies and 100,000 quasars. The information on the position and distance of the objects has allowed the large-scale structure of the Universe, with its voids and filaments, to be investigated for the first time. Almost all of these data were obtained in SDSS-I, but a small part of the footprint was finished in SDSS-II. |
Sloan Digital Sky Survey | Sloan Extension for Galactic Understanding and Exploration (SEGUE) | Sloan Extension for Galactic Understanding and Exploration (SEGUE)
The Sloan Extension for Galactic Understanding and Exploration obtained spectra of 240,000 stars (with a typical radial velocity of 10 km/s) to create a detailed three-dimensional map of the Milky Way. SEGUE data provide evidence for the age, composition and phase space distribution of stars within the various Galactic components, providing crucial clues for understanding the structure, formation and evolution of our galaxy.
The stellar spectra, imaging data, and derived parameter catalogs for this survey are publicly available as part of SDSS Data Release 7 (DR7). |
Sloan Digital Sky Survey | Sloan Supernova Survey | Sloan Supernova Survey
The SDSS Supernova Survey, which ran from 2005 to 2008, performed repeat imaging of one stripe of sky 2.5° wide centered on the celestial equator, going from 20 hours right ascension to 4 hours RA so that it was in the southern galactic cap (see Draft:Galactic cap) and did not suffer from galactic extinction. The project discovered more than 500 type Ia supernovae, Running until the end of the year 2007, the Supernova Survey searched for Type Ia supernovae. The survey rapidly scanned a 300 square degree area to detect variable objects and supernovae. It detected 130 confirmed supernovae Ia events in 2005 and a further 197 in 2006. In 2014 an even larger catalogue was released containing 10,258 variable and transient sources. Of these, 4,607 sources are either confirmed or likely supernovae, which makes this the largest set of supernovae so far compiled. |
Sloan Digital Sky Survey | SDSS III: 2008–2014 | SDSS III: 2008–2014
In mid-2008, SDSS-III was started. It comprised four separate surveys: |
Sloan Digital Sky Survey | APO Galactic Evolution Experiment (APOGEE) | APO Galactic Evolution Experiment (APOGEE)
The APO Galactic Evolution Experiment (APOGEE) used high-resolution, high signal-to-noise infrared spectroscopy to penetrate the dust that obscures the inner Galaxy. APOGEE surveyed 100,000 red giant stars across the full range of the galactic bulge, bar, disk, and halo. It increased the number of stars observed at high spectroscopic resolution (R ≈ 20,000 at λ ≈ 1.6μm) and high signal-to-noise ratio () by more than a factor of 100. The high-resolution spectra revealed the abundances of about 15 elements, giving information on the composition of the gas clouds the red giants formed from. APOGEE planned to collect data from 2011 to 2014, with the first data released as part of SDSS DR10 in late 2013. |
Sloan Digital Sky Survey | Baryon Oscillation Spectroscopic Survey (BOSS) | Baryon Oscillation Spectroscopic Survey (BOSS)
The SDSS-III's Baryon Oscillation Spectroscopic Survey (BOSS) was designed to measure the expansion rate of the Universe. It mapped the spatial distribution of luminous red galaxies (LRGs) and quasars to determine their spatial distribution and detect the characteristic scale imprinted by baryon acoustic oscillations in the early universe. Sound waves that propagate in the early universe, like spreading ripples in a pond, imprint a characteristic scale on the positions of galaxies relative to each other. It was announced that BOSS had measured the scale of the universe to an accuracy of one percent, and was completed in Spring 2014. |
Sloan Digital Sky Survey | Multi-object APO Radial Velocity Exoplanet Large-area Survey (MARVELS) | Multi-object APO Radial Velocity Exoplanet Large-area Survey (MARVELS)
The Multi-object APO Radial Velocity Exoplanet Large-area Survey (MARVELS) monitored the radial velocities of 11,000 bright stars, with the precision and cadence needed to detect gas giant planets that have orbital periods ranging from several hours to two years. This ground-based Doppler survey used the SDSS telescope and new multi-object Doppler instruments to monitor radial velocities.
The main goal of the project was to generate a large-scale, statistically well-defined sample of giant planets. It searched for gaseous planets having orbital periods ranging from hours to 2 years and masses between 0.5 and 10 times that of Jupiter. A total of 11,000 stars were analyzed with 25–35 observations per star over 18 months. It was expected to detect between 150 and 200 new exoplanets, and was able to study rare systems, such as planets with extreme eccentricity, and objects in the "brown dwarf desert".
The collected data was used as a statistical sample for the theoretical comparison and discovery of rare systems. The project started in the fall of 2008, and continued until spring 2014. |
Sloan Digital Sky Survey | SEGUE-2 | SEGUE-2
The original Sloan Extension for Galactic Understanding and Exploration (SEGUE-1) obtained spectra of nearly 240,000 stars of a range of spectral types. Building on this success, SEGUE-2 spectroscopically observed around 120,000 stars, focusing on the in situ stellar halo of the Milky Way, from distances of 10 to 60kpc. SEGUE-2 doubled the sample size of SEGUE-1.
Combining SEGUE-1 and 2 revealed the complex kinematic and chemical substructure of the galactic halo and disks, providing essential clues to the assembly and enrichment history of the galaxy. In particular, the outer halo was expected to be dominated by late-time accretion events. SEGUE data can help constrain existing models for the formation of the stellar halo and inform the next generation of high-resolution simulations of galaxy formation. In addition, SEGUE-1 and SEGUE-2 may help uncover rare, chemically primitive stars that are fossils of the earliest generations of cosmic star formation. |
Sloan Digital Sky Survey | SDSS IV: 2014–2020 | SDSS IV: 2014–2020
thumb|Light from distant galaxies has been smeared and twisted into odd shapes, arcs, and streaks.
The fourth generation of the SDSS (SDSS-IV, 2014–2020) is extending precision cosmological measurements to a critical early phase of cosmic history (eBOSS), expanding its infrared spectroscopic survey of the Galaxy in the northern and southern hemispheres (APOGEE-2), and for the first time using the Sloan spectrographs to make spatially resolved maps of individual galaxies (MaNGA). |
Sloan Digital Sky Survey | APO Galactic Evolution Experiment (APOGEE-2) | APO Galactic Evolution Experiment (APOGEE-2)
A stellar survey of the Milky Way, with two major components: a northern survey using the bright time at APO, and a southern survey using the 2.5m Du Pont Telescope at Las Campanas. |
Sloan Digital Sky Survey | Extended Baryon Oscillation Spectroscopic Survey (eBOSS) | Extended Baryon Oscillation Spectroscopic Survey (eBOSS)
A cosmological survey of quasars and galaxies, also encompassing subprograms to survey variable objects (TDSS) and X-ray sources (SPIDERS). |
Sloan Digital Sky Survey | Mapping Nearby Galaxies at APO (MaNGA) | Mapping Nearby Galaxies at APO (MaNGA)
thumb|A simplified graphical representation of a 7-fibre bundle. MaNGA measures 17 galaxies at a time, using bundles of 19, 37, 61, 91, and 127 fibers.
MaNGA (Mapping Nearby Galaxies at Apache Point Observatory), explored the detailed internal structure of nearly 10,000 nearby galaxies
from 2014 to the spring of 2020. Earlier SDSS surveys only allowed spectra to be observed from the center of galaxies. By using two-dimensional arrays of optical fibers bundled together into a hexagonal shape, MaNGA was able to use spatially resolved spectroscopy to construct maps of the areas within galaxies, allowing deeper analysis of their structure, such as radial velocities and star formation regions. |
Sloan Digital Sky Survey | SDSS-V: 2020–current | SDSS-V: 2020–current
Apache Point Observatory in New Mexico began to gather data for SDSS-V in October 2020. Apache Point is scheduled to be converted by mid-2021 from plug plates (aluminum plates with manually-placed holes for starlight to shine through) to small automated robot arms, with Las Campanas Observatory in Chile following later in the year. The Milky Way Mapper survey will target the spectra of six million stars. The Black Hole Mapper survey will target galaxies to indirectly analyze their supermassive black holes. The Local Volume Mapper will target nearby galaxies to analyze their clouds of interstellar gas. |
Sloan Digital Sky Survey | Data access | Data access
thumb|LRG-4-606 is a luminous red galaxy. LRG is the acronym given to a catalog of bright red galaxies found in the SDSS.
The survey makes the data releases available over the Internet. The SkyServer provides a range of interfaces to an underlying Microsoft SQL Server. Both spectra and images are available in this way, and interfaces are made very easy to use so that, for example, a full-color image of any region of the sky covered by an SDSS data release can be obtained just by providing the coordinates. The data are available for non-commercial use only, without written permission. The SkyServer also provides a range of tutorials aimed at everyone from schoolchildren up to professional astronomers. The tenth major data release, DR10, released in July 2013, provides images, imaging catalogs, spectra, and redshifts via a variety of search interfaces.
The raw data (from before being processed into databases of objects) are also available through another Internet server and first experienced as a 'fly-through' via the NASA World Wind program.
Sky in Google Earth includes data from the SDSS, for those regions where such data are available. There are also KML plugins for SDSS photometry and spectroscopy layers, allowing direct access to SkyServer data from within Google Sky.
The data is also available on Hayden Planetarium with a 3D visualizer.
There is also the ever-growing list of data for the Stripe 82 region of the SDSS.
Following Technical Fellow Jim Gray's contribution on behalf of Microsoft Research with the SkyServer project, Microsoft's WorldWide Telescope makes use of SDSS and other data sources.
MilkyWay@home also used SDSS's data to create a highly accurate three-dimensional model of the Milky Way galaxy. |
Sloan Digital Sky Survey | Results | Results
Along with publications describing the survey itself, SDSS data have been used in publications over a huge range of astronomical topics. The SDSS website has a full list of these publications covering distant quasars at the limits of the observable universe, the distribution of galaxies, the properties of stars in our galaxy and also subjects such as dark matter and dark energy in the universe. |
Sloan Digital Sky Survey | Maps | Maps
Based on the release of Data Release 9 a new 3D map of massive galaxies and distant black holes was published on August 8, 2012. |
Sloan Digital Sky Survey | See also | See also
Alex Szalay
Alfred P. Sloan Foundation
Apache Point Observatory
Dark Energy Spectroscopic Instrument
Galaxy color-magnitude diagram
Galaxy Zoo
James E. Gunn
Sloan Great Wall |
Sloan Digital Sky Survey | References | References |
Sloan Digital Sky Survey | Further reading | Further reading
Ann K. Finkbeiner. A Grand and Bold Thing: An Extraordinary New Map of the Universe Ushering In A New Era of Discovery (2010), a journalistic history of the project |
Sloan Digital Sky Survey | External links | External links
Category:Alfred P. Sloan Foundation
Category:Astronomical surveys
*
Category:Exoplanet search projects
Category:Observational astronomy
Category:Photometric systems
* |
Sloan Digital Sky Survey | Table of Content | short description, Background, Operation, Observations, Phases, SDSS-I: 2000–2005, SDSS-II: 2005–2008, Sloan Legacy Survey, Sloan Extension for Galactic Understanding and Exploration (SEGUE), Sloan Supernova Survey, SDSS III: 2008–2014, APO Galactic Evolution Experiment (APOGEE), Baryon Oscillation Spectroscopic Survey (BOSS), Multi-object APO Radial Velocity Exoplanet Large-area Survey (MARVELS), SEGUE-2, SDSS IV: 2014–2020, APO Galactic Evolution Experiment (APOGEE-2), Extended Baryon Oscillation Spectroscopic Survey (eBOSS), Mapping Nearby Galaxies at APO (MaNGA), SDSS-V: 2020–current, Data access, Results, Maps, See also, References, Further reading, External links |
SDSS | '''SDSS''' | SDSS may refer to:
Sloan Digital Sky Survey, a major multi-filter imaging and spectroscopic redshift survey
Social Democratic Party of Slovakia
Spatial Decision Support System, a GIS based decision aiding system
Independent Democratic Serb Party, a political party of Croatian Serbs (Samostalna demokratska srpska stranka in Serbo-Croatian)
South Delta Secondary School, a school in Delta, British Columbia, Canada |
SDSS | Table of Content | '''SDSS''' |
Victor Recording Orchestra | More citations needed | The Victor Recording Orchestra was a jazz band led by Jean Goldkette. It was known for its innovative arrangements and strong rhythm.
Among its members were:
Bix Beiderbecke
Steve Brown
Hoagy Carmichael
Jimmy Dorsey
Tommy Dorsey
Eddie Lang
Don Murray
Howdy Quicksell
Pee Wee Russell
Frankie Trumbauer
Joe Venuti
Bill Rank
Among the band's own arrangers was Russ Morgan; the band also traded arrangements with Fletcher Henderson. The band's most popular records included "After I Say I'm Sorry," "Dinah," "Gimme a Little Kiss, Will Ya, Huh?" and "Lonesome and Sorry." According to Rex Stewart, the primitive recording techniques of the day (for example, bass and snare drums could not be recorded) failed to provide a true record of the band. |
Victor Recording Orchestra | References | References
Category:American jazz ensembles
Category:Musical groups established in 1924
Category:Musical groups with year of disestablishment missing
Category:Musical groups from the United States with local place of origin missing
Category:1924 establishments in the United States |
Victor Recording Orchestra | Table of Content | More citations needed, References |
Stoned | wiktionary | Stoned may refer to:
Substance intoxication, particularly cannabis intoxication
Petrification, process of organic matter turning into stone
Stoning, a form of punishment where a group throws stones at the victim
Stoning (metalworking), a method to sharpen the edges of steel tools
Stoned (computer virus), a boot-sector virus created in 1987 |
Stoned | Arts and entertainment | Arts and entertainment |
Stoned | Film and television | Film and television
Stoned (TV special), a 1981 ABC Afterschool Special episode starring Scott Baio
Stoned (film), a 2005 film about Brian Jones, one of the founders of The Rolling Stones |
Stoned | Autobiography | Autobiography
Stoned, a 1998 autobiography by Andrew Loog Oldham
Stoned: Photographs & treasures from life with the Rolling Stones, a 2019 autobiography by Jo Wood |
Stoned | Music | Music |
Stoned | Albums | Albums
Stoned, Part I, a 2003 album by Lewis Taylor
Stoned, Part II, a 2004 album by Lewis Taylor
Stoned (Acid Witch album), 2010
Lapidation (album), a 2007 album by composer and keyboardist Anthony Coleman |
Stoned | Songs | Songs
"Stoned" (Rolling Stones song), a 1963 recording
"Stoned", a song from the 1999 album Astro Lounge by Smash Mouth
"Stoned" (Dido song), a 2003 single
"Stoned" (Puddle of Mudd song), a 2010 reocording
"Stoned", a song from the deluxe edition of the 2023 album Subtract by Ed Sheeran |
Stoned | See also | See also
Stone (disambiguation) |
Stoned | Table of Content | wiktionary, Arts and entertainment, Film and television, Autobiography, Music, Albums, Songs, See also |
Marxist Forward Bloc | Refimprove | The Marxist Forward Bloc is a political party in India, a splinter group of the All India Forward Bloc. The MFB was formed in 1953 as Satyapriya Banerjee, a member of the AIFB Central Secretariat, Amar Bose, Suhurit Chaudhury and Ram Chatterji were expelled from AIFB. At its foundation, Satyapriya Banerjee was the party's general secretary and Amar Bose its chairman.
The MFB is part of the Left Front and has been associated with the combined left movement since its inception. Its leader Ram Chatterjee was a minister in the West Bengal Left Front government for several years. Later the MFB was led by Pratim Chatterjee, who served in the West Bengal government as Minister of Fire Services in the Left Front cabinet. Chatterjee represented the Tarakeswar seat from 1996 in the West Bengal Legislative Assembly till 2011, when he lost to Rachhpal Singh of the TMC.
In West Bengal Assembly elections till 2011, the MFB contested the seats for Tarakeswar in Hooghly district and Jamalpur in East Burdwan district as a Left Front partner. In the 2006 West Bengal Legislative Assembly election, the party retained both seats as Pratim Chatterjee and Samar Hazra won with good margins. Later in the 2011 election the party lost its representation in the Legislative Assembly when both of the sitting MLAs lost from their respective constituencies.
In the Kolkata municipal polls in 2005, the MFB contested two wards as a Left Front partner. Biren Chakroborty, the secretary of the MFB, was elected from ward number 57.
In the 2008 Panchayet polls, the MFB won seats in Panchayet, Panchayet Samity and ZP levels in Hoogly and Burdwan districts.
In the 2010 municipal polls, the MFB lost its seat in Kolkata corporation. It won a seat each at Rampurhat in Birbhum and Arambagh in Hooghly.
From 2014 Jaihind Singh is the party chairperson. |
Marxist Forward Bloc | References | References
Category:1953 establishments in West Bengal
Category:Socialist parties in India
Category:Marxist parties in India
Category:Political parties established in 1953
Category:Political parties in West Bengal
Category:All India Forward Bloc |
Marxist Forward Bloc | Table of Content | Refimprove, References |
Bhattacharyya distance | Short description | In statistics, the Bhattacharyya distance is a quantity which represents a notion of similarity between two probability distributions. It is closely related to the Bhattacharyya coefficient, which is a measure of the amount of overlap between two statistical samples or populations.
It is not a metric, despite being named a "distance", since it does not obey the triangle inequality. |
Bhattacharyya distance | History | History
Both the Bhattacharyya distance and the Bhattacharyya coefficient are named after Anil Kumar Bhattacharyya, a statistician who worked in the 1930s at the Indian Statistical Institute. He has developed this through a series of papers. He developed the method to measure the distance between two non-normal distributions and illustrated this with the classical multinomial populations, this work despite being submitted for publication in 1941, appeared almost five years later in Sankhya. Consequently, Professor Bhattacharyya started working toward developing a distance metric for probability distributions that are absolutely continuous with respect to the Lebesgue measure and published his progress in 1942, at Proceedings of the Indian Science Congress and the final work has appeared in 1943 in the Bulletin of the Calcutta Mathematical Society. |
Bhattacharyya distance | Definition | Definition
For probability distributions and on the same domain , the Bhattacharyya distance is defined as
where
is the Bhattacharyya coefficient for discrete probability distributions.
For continuous probability distributions, with and where and are the probability density functions, the Bhattacharyya coefficient is defined as
.
More generally, given two probability measures on a measurable space , let be a (sigma finite) measure such that and are absolutely continuous with respect to i.e. such that , and for probability density functions with respect to defined -almost everywhere. Such a measure, even such a probability measure, always exists, e.g. . Then define the Bhattacharyya measure on by
It does not depend on the measure , for if we choose a measure such that and an other measure choice are absolutely continuous i.e. and , then
,
and similarly for . We then have
.
We finally define the Bhattacharyya coefficient
.
By the above, the quantity does not depend on , and by the Cauchy inequality . Using , and , |
Bhattacharyya distance | Gaussian case | Gaussian case
Let , , where is the normal distribution with mean and variance ; then
.
And in general, given two multivariate normal distributions ,
,
where Note that the first term is a squared Mahalanobis distance. |
Bhattacharyya distance | Properties | Properties
and .
does not obey the triangle inequality, though the Hellinger distance does. |
Bhattacharyya distance | Bounds on Bayes error | Bounds on Bayes error
The Bhattacharyya distance can be used to upper and lower bound the Bayes error rate:
where and is the posterior probability.Devroye, L., Gyorfi, L. & Lugosi, G. A Probabilistic Theory of Pattern Recognition. Discrete Appl Math 73, 192–194 (1997). |
Bhattacharyya distance | Applications | Applications
The Bhattacharyya coefficient quantifies the "closeness" of two random statistical samples.
Given two sequences from distributions , bin them into buckets, and let the frequency of samples from in bucket be , and similarly for , then the sample Bhattacharyya coefficient is
which is an estimator of . The quality of estimation depends on the choice of buckets; too few buckets would overestimate , while too many would underestimate.
A common task in classification is estimating the separability of classes. Up to a multiplicative factor, the squared Mahalanobis distance is a special case of the Bhattacharyya distance when the two classes are normally distributed with the same variances. When two classes have similar means but significantly different variances, the Mahalanobis distance would be close to zero, while the Bhattacharyya distance would not be.
The Bhattacharyya coefficient is used in the construction of polar codes.
The Bhattacharyya distance is used in feature extraction and selection,Euisun Choi, Chulhee Lee, "Feature extraction based on the Bhattacharyya distance", Pattern Recognition, Volume 36, Issue 8, August 2003, Pages 1703–1709 image processing,François Goudail, Philippe Réfrégier, Guillaume Delyon, "Bhattacharyya distance as a contrast parameter for statistical processing of noisy optical images", JOSA A, Vol. 21, Issue 7, pp. 1231−1240 (2004) speaker recognition,Chang Huai You, "An SVM Kernel With GMM-Supervector Based on the Bhattacharyya Distance for Speaker Recognition", Signal Processing Letters, IEEE, Vol 16, Is 1, pp. 49-52 phone clustering,Mak, B., "Phone clustering using the Bhattacharyya distance", Spoken Language, 1996. ICSLP 96. Proceedings., Fourth International Conference on, Vol 4, pp. 2005–2008 vol.4, 3−6 Oct 1996 and in genetics. |
Bhattacharyya distance | See also | See also
Bhattacharyya angle
Kullback–Leibler divergence
Hellinger distance
Mahalanobis distance
Chernoff bound
Rényi entropy
F-divergence
Fidelity of quantum states |
Bhattacharyya distance | References | References |
Bhattacharyya distance | External links | External links
Statistical Intuition of Bhattacharyya's distance
Some of the properties of Bhattacharyya Distance
Nielsen, F.; Boltz, S. (2010). "The Burbea–Rao and Bhattacharyya centroids". IEEE Transactions on Information Theory. 57 (8): 5455–5466.
Kailath, T. (1967). "The Divergence and Bhattacharyya Distance Measures in Signal Selection". IEEE Transactions on Communication Technology. 15 (1): 52–60.
Djouadi, A.; Snorrason, O.; Garber, F. (1990). "The quality of Training-Sample estimates of the Bhattacharyya coefficient". IEEE Transactions on Pattern Analysis and Machine Intelligence. 12 (1): 92–97.
Category:Statistical distance
Category:Statistical deviation and dispersion
Category:Anil Kumar Bhattacharya |
Bhattacharyya distance | Table of Content | Short description, History, Definition, Gaussian case, Properties, Bounds on Bayes error, Applications, See also, References, External links |
Catherine's Palace | # | Redirect Catherine Palace |
Catherine's Palace | Table of Content | # |
William Sarjeant | Use dmy dates | William Antony Swithin Sarjeant (15 July 1935 – 8 July 2002), also known by the pen name Antony Swithin, was a professor of geology at University of Saskatchewan. He was also interested in mystery writing, fantasy writing, folk singing, and heritage preservation. He received the Sue Tyler Friedman Medal in 1990 for his work in the history of geology.
Born in Sheffield, England, he wrote The Perilous Quest for Lyonesse series of novels (1990-1993) in the vein of The Lord of the Rings. They were set in a fictional land of Rockall based upon the small real island of the same name northwest of Scotland and Ireland.
Sarjeant died of cancer at age 66 in July 2002. Following his death, William Sarjeant Park in the city of Saskatoon's Willowgrove neighborhood was named in his honor. |
William Sarjeant | Writings | Writings
thumb|William Sarjeant Park in Willowgrove neighborhood
Princes of Sandastre
The Lords of the Stoney Mountains
The Winds of the Wastelands
The Nine Gods of Saffadne
|
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