Search of variable stars with multiple periodicity by materials received from SibSU observatory

В работе представлены 18 переменных пульсирующих звезд с двойной и более периодичностью.This article presents 18 variable pulsating stars with a double and more periodicity

Comparative performance of selected variability detection techniques in photometric time series

Photometric measurements are prone to systematic errors presenting a challenge to low-amplitude variability detection. In search for a general-purpose variability detection technique able to recover a broad range of variability types including currently unknown ones, we test 18 statistical characteristics quantifying scatter and/or correlation between brightness measurements. We compare their performance in identifying variable objects in seven time series data sets obtained with telescopes ranging in size from a telephoto lens to 1m-class and probing variability on time-scales from minutes to decades. The test data sets together include lightcurves of 127539 objects, among them 1251 variable stars of various types and represent a range of observing conditions often found in ground-based variability surveys. The real data are complemented by simulations. We propose a combination of two indices that together recover a broad range of variability types from photometric data characterized by a wide variety of sampling patterns, photometric accuracies, and percentages of outlier measurements. The first index is the interquartile range (IQR) of magnitude measurements, sensitive to variability irrespective of a time-scale and resistant to outliers. It can be complemented by the ratio of the lightcurve variance to the mean square successive difference, 1/h, which is efficient in detecting variability on time-scales longer than the typical time interval between observations. Variable objects have larger 1/h and/or IQR values than non-variable objects of similar brightness. Another approach to variability detection is to combine many variability indices using principal component analysis. We present 124 previously unknown variable stars found in the test data.Comment: 29 pages, 8 figures, 7 tables; accepted to MNRAS; for additional plots, see http://scan.sai.msu.ru/~kirx/var_idx_paper

СОДЕРЖАНИЕ И КАЧЕСТВЕННЫЙ СОСТАВ ГУМУСА КАШТАНОВОЙ ПОЧВЫ В ДИНАМИКЕ МНОГОЛЕТНИХ РЯДОВ СИСТЕМАТИЧЕСКОГО ПРИМЕНЕНИЯ УДОБРЕНИЙ

The results of long-term agrochemical experiments highlight quantitative and qualitative changes in the humus status of chestnut soil when applying organic and mineral fertilizers. When fertilizers were not applied, the initial humus concentration in the soil was reduced and on average reached its minimum level of 0.94 ± 0.03% in the 48th year of research. During the whole period in the unfertilized variant, the soil lost 28.3% of the initial amount of humus, or 11.0 t/ha, with an average annual loss of 228 kg. Kinetic parameters of humus reducing in the soil of the control variant reached k = 0.008 year -1 in rapid manifestation. When mineral fertilizers were applied, the humus concentration was higher than in the control variant and reached 1.17 ± 0.05% by the last date of determination. The reduction rate in the variant of applying mineral fertilizer was k = 0.003 year -1. The average annual inflow of root and stubble residues when applying mineral fertilizes compensated humus losses and stabilized its concentration after 30 years of research. Reducing of humus reserves in the soil revealed in a corresponding reduction of annual losses, which reached 131 kg/ha in the first 16 years, with further decrease of 107 kg/ha in 14 years, followed by their absence and slight decrease in the last 7 years - 41 kg/ha. Deficient and positive balance of humus was provided by the variant with manure application. The humus concnetration in the soil for 48 years of applying fertilizers reached 1.50 ± 0.04% and significantly exceeded the initial concentration. On average, during the research period the soil multiplied its reserves on 5.6 t/ha with an average annual growth rate of 117 kg/ha. Kinetics of humus concentration increase in soil in the variant with manure application had a growth rate constant k = 0.002 per year. Ranking of positive quantitative (S gen, %) and qualitative (HC: FC) changes of humus in soil according to estimation variants in dynamics of perennial series occurs in a row: no fertilizers (0.56 % and 0.75) → complete fertilization NPK (0.69 % and 0.79) → manure (0.86 % and 0.92).По результатам длительного агрохимического опыта установлены количественные и качественные изменения гумусного состояния каштановой почвы при систематическом применении органических и минеральных удобрений. В отсутствие удобрений исходное содержание гумуса в почве в контроле снижалось и в среднем на 48-й год исследований достигло своего минимального уровня– 0,94 ± 0,03%. За весь период внеудобренном варианте почва утратила 28,3% исходного количества гумуса, или 11,0 т/га, со среднегодовой величиной потерь 228 кг. В скоростном проявлении кинетические параметры снижения гумуса в почве контрольного варианта достигали k = 0,008 год –1. Содержание гумуса почвы при систематическом внесении полного минерального удобрения оказалось достоверно выше, чем в контрольном варианте, и достигло 1,17 ± 0,05% к последнему сроку определения. Константа скорости снижения вварианте минерального удобрения составила k = 0,003 год –1. Среднегодовое поступление корневых и пожнивных остатков в варианте с полным минеральным удобрением после 30 лет исследований компенсировало потери гумуса и стабилизировало его содержание. Снижение запасов гумуса в почве проявилось в соответствующем уменьшении ежегодных потерь, которые в первые 16 лет достигали 131 кг/га, с дальнейшей за 14 лет величиной убыли 107 кг/га, при последующем 12-летнем их отсутствии и незначительном снижении в последние 7 лет – 41 кг/га. Бездефицитный и положительный баланс гумуса обеспечивал только вариант с внесением навоза. Содержание гумуса в почве за 48 лет внесения достигло 1,50 ± 0,04% и значительно превышало исходное содержание. В среднем за период исследований почва при внесении навоза пополнила свои запасы на 5,6 т/га со среднегодовым ежегодным приростом по 117 кг/га. Кинетика увеличения содержания гумуса в почве в варианте с навозом имела константу скорости роста k = 0,002 в год. Ранжирование положительных количественных (Собщ,%) и качественных (ГК : ФК) изменений гумуса в почве по вариантам оценки в динамике многолетних рядов происходит в ряду: без удобрений (0,56% и 0,75) → полное удобрение NPK (0,69% и 0,79) → навоз (0,86% и 0,92)

Comparative performance of selected variability detection techniques in photometric time series data

Photometric measurements are prone to systematic errors presenting a challenge to lowamplitude variability detection. In search for a general-purpose variability detection technique able to recover a broad range of variability types including currently unknown ones, we test 18 statistical characteristics quantifying scatter and/or correlation between brightness measurements. We compare their performance in identifying variable objects in seven time series data sets obtained with telescopes ranging in size from a telephoto lens to 1 m-class and probing variability on time-scales from minutes to decades. The test data sets together include light curves of 127 539 objects, among them 1251 variable stars of various types and represent a range of observing conditions often found in ground-based variability surveys. The real data are complemented by simulations. We propose a combination of two indices that together recover a broad range of variability types from photometric data characterized by a wide variety of sampling patterns, photometric accuracies and percentages of outlier measurements. The first index is the interquartile range (IQR) of magnitude measurements, sensitive to variability irrespective of a time-scale and resistant to outliers. It can be complemented by the ratio of the light-curve variance to the mean square successive difference, 1/η, which is efficient in detecting variability on time-scales longer than the typical time interval between observations. Variable objects have larger 1/η and/or IQR values than non-variable objects of similar brightness. Another approach to variability detection is to combine many variability indices using principal component analysis.We present 124 previously unknown variable stars found in the test data. © 2016 The Authors. Published by Oxford University Press on behalf of the Royal Astronomical Society