scholarly journals Retrieving the True Masses of Gravitational Wave Sources

Proceedings ◽  
2019 ◽  
Vol 17 (1) ◽  
pp. 4 ◽  
Author(s):  
Xian Chen ◽  
Zhefeng Shen
Keyword(s):  
Hydrodynamic Drag ◽  
Chirp Signal ◽  
Binary Black Holes ◽  
Best Fitting ◽  
Real Mass ◽  
The Masses ◽  
The Impact ◽  
Best Fit ◽  
Gas Effect ◽  
Fitting Parameters

Gravitational waves (GWs) encode important information about the mass of the source. For binary black holes (BBHs), the templates that are used to retrieve the masses normally are developed under the assumption of a vacuum environment. However, theories suggest that some BBHs form in gas-rich environments. Here, we study the effect of hydrodynamic drag on the chirp signal of a stellar-mass BBH and the impact on the measurement of the mass. Based on theoretical arguments, we show that the waveform of a BBH in gas resembles that of a more massive BBH residing in vacuum. The effect is important for those GW sources in the band of space-borne detectors but negligible for those in ground-based ones. Furthermore, we carry out a matched-filtering search of the best fitting parameters. We find that the best-fit chirp mass could be significantly greater than the real mass when the gas effect is ignored. Our results have important implications for the future joint observation of BBHs using both ground- and space-based detectors.

scholarly journals Separating the intrinsic alignment signal and the lensing signal using self-calibration in photo-z surveys with KiDS450 and KV450 Data

2020 ◽  
Vol 495 (4) ◽  
pp. 3900-3919 ◽  
Author(s):  
Ji Yao ◽  
Eske M Pedersen ◽  
Mustapha Ishak ◽  
Pengjie Zhang ◽  
Anish Agashe ◽  
...  
Keyword(s):  
Full Potential ◽  
Photometric Redshift ◽  
Self Calibration ◽  
Intrinsic Shape ◽  
Best Fitting ◽  
Systematic Biases ◽  
Cosmic Shear ◽  
Validation Tests ◽  
The Impact ◽  
Best Fit

ABSTRACT To reach the full potential for the next generation of weak lensing surveys, it is necessary to mitigate the contamination of intrinsic alignments (IAs) of galaxies in the observed cosmic shear signal. The self-calibration (SC) of IAs provides an independent method to measure the IA signal from the survey data and the photometric redshift information. It operates differently from the marginalization method based on the IA modelling. In this work, we present the first application of SC to the KiDS450 data and the KV450 data, to split directly the intrinsic shape–galaxy density (Ig) correlation signal and the gravitational shear–galaxy density (Gg) correlation signal, using the information from photometric redshift (photo-z). We achieved a clear separation of the two signals and performed several validation tests. Our measured signals are found to be in general agreement with the KiDS450 cosmic shear best-fitting cosmology, for both lensing and IA measurements. For KV450, we use partial (high-z) data, and our lensing measurements are also in good agreement with KV450 cosmic shear best fit, while our IA signal suggests a larger IA amplitude for the high-z sample. We discussed the impact of photo-z quality on IA detection and several other potential systematic biases. Finally, we discuss the potential application of the information extracted for both the lensing signal and the IA signal in future surveys.

scholarly journals Binary black holes in young star clusters: the impact of metallicity

2020 ◽  
Vol 498 (1) ◽  
pp. 495-506 ◽  
Author(s):  
Ugo N Di Carlo ◽  
Michela Mapelli ◽  
Nicola Giacobbo ◽  
Mario Spera ◽  
Yann Bouffanais ◽  
...  
Keyword(s):  
Black Holes ◽  
Initial Density ◽  
Star Clusters ◽  
Young Star ◽  
Binary Black Holes ◽  
Binary Evolution ◽  
Merger Rate ◽  
The Masses ◽  
The Impact ◽  
Young Star Clusters

ABSTRACT Young star clusters are the most common birthplace of massive stars and are dynamically active environments. Here, we study the formation of black holes (BHs) and binary black holes (BBHs) in young star clusters, by means of 6000 N-body simulations coupled with binary population synthesis. We probe three different stellar metallicities (Z = 0.02, 0.002, and 0.0002) and two initial-density regimes (density at the half-mass radius ρh ≥ 3.4 × 104 and ≥1.5 × 102 M⊙ pc−3 in dense and loose star clusters, respectively). Metal-poor clusters tend to form more massive BHs than metal-rich ones. We find ∼6, ∼2, and <1 per cent of BHs with mass mBH > 60 M⊙ at Z = 0.0002, 0.002, and 0.02, respectively. In metal-poor clusters, we form intermediate-mass BHs with mass up to ∼320 M⊙. BBH mergers born via dynamical exchanges (exchanged BBHs) can be more massive than BBH mergers formed from binary evolution: the former (latter) reach total mass up to ∼140 M⊙ (∼80 M⊙). The most massive BBH merger in our simulations has primary mass ∼88 M⊙, inside the pair-instability mass gap, and a mass ratio of ∼0.5. Only BBHs born in young star clusters from metal-poor progenitors can match the masses of GW 170729, the most massive event in first and second observing run (O1 and O2), and those of GW 190412, the first unequal-mass merger. We estimate a local BBH merger rate density ∼110 and ∼55 Gpc−3 yr−1, if we assume that all stars form in loose and dense star clusters, respectively.

scholarly journals Global Optimization Of A Numerical Two-Layer Model Using Observed Data: A Case Study Of The 2018 Sunda Strait Tsunami

2020 ◽  
Author(s):  
Kwanchai Pakoksung ◽  
Anawat Suppasri ◽  
Muhari Abdul ◽  
Syamsidik Syamsidik ◽  
Fumihiko Imamura
Keyword(s):  
Global Optimization ◽  
Grid Cell ◽  
Optimization Procedure ◽  
Observation Data ◽  
Layer Model ◽  
Landslide Volume ◽  
Best Fitting ◽  
Two Layer Model ◽  
The Impact ◽  
Fitting Parameters

Abstract Following the eruption of Mount Anak Krakatau, a considerable landslide occurred on the southwestern part of the volcano and, upon entering the sea, generated a large tsunami within the Sunda Strait, Indonesia, on 22 December 2018. This tsunami traveled ~5 km across the strait basin and inundated the shorelines of Sumatra and Java with a vertical runup reaching 13 m. Following the event, observed field data, GPS measurements of the inundation, and multibeam echo soundings of the bathymetry within the strait were collected and publicly provided. Using this dataset, numerical modeling of the tsunami was conducted using the two-layer (soil and water) TUNAMI-N2 model based on a combination of landslide sources and bathymetry data. The two-layer model was implemented to nest the grid system using a finest grid size of 20 m. To constrain the unknown landslide parameters, the differential evolution (DE) global optimization algorithm was applied, which resulted in a parameter set that minimized the deviation from the measured bathymetry after the event. The DE global optimization procedure was effective at determining the landslide parameters for the model with the minimum deviation from the measured seafloor. The lowest deviation from the measured bathymetry was obtained for the best-fitting parameters: a maximum landslide thickness of 301.2 m and a landslide time of 10.8 minutes. The landslide volume of 0.182 km3 estimated by the best-fitting parameters shows that the tsunami flow depth could have reached 3-10 m along the shore with a K value of 0.89, although the simulated flow depths were underestimated in comparison with the observation data. According to the waveforms, the general wave pattern was well reproduced at tide gauges during the event. A large number of objective function evaluations were necessary to locate the minimum with the DE procedure to fix the grid cell size to 20 m; this limited the accuracy of the obtained parameter values for the two-layer model. Moreover, considering the generalizations in the modeling of landslide movements, the impact landslide time and thickness must be carefully calculated to obtain a suitable accuracy.

scholarly journals Global optimization of a numerical two-layer model using observed data: a case study of the 2018 Sunda Strait tsunami

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
K. Pakoksung ◽  
A. Suppasri ◽  
A. Muhari ◽  
Syamsidik ◽  
F. Imamura
Keyword(s):  
Global Optimization ◽  
Grid Cell ◽  
Optimization Procedure ◽  
Observation Data ◽  
Layer Model ◽  
Landslide Volume ◽  
Best Fitting ◽  
Two Layer Model ◽  
The Impact ◽  
Fitting Parameters

Abstract Following the eruption of Mount Anak Krakatau, a considerable landslide occurred on the southwestern part of the volcano and, upon entering the sea, generated a large tsunami within the Sunda Strait, Indonesia, on December 22, 2018. This tsunami traveled ~ 5 km across the strait basin and inundated the shorelines of Sumatra and Java with a vertical runup reaching 13 m. Following the event, observed field data, GPS measurements of the inundation, and multibeam echo soundings of the bathymetry within the strait were collected and publicly provided. Using this dataset, numerical modeling of the tsunami was conducted using the two-layer (soil and water) TUNAMI-N2 model based on a combination of landslide sources and bathymetry data. The two-layer model was implemented to nest the grid system using the finest grid size of 20 m. To constrain the unknown landslide parameters, the differential evolution (DE) global optimization algorithm was applied, which resulted in a parameter set that minimized the deviation from the measured bathymetry after the event. The DE global optimization procedure was effective at determining the landslide parameters for the model with the minimum deviation from the measured seafloor. The lowest deviation from the measured bathymetry was obtained for the best-fitting parameters: a maximum landslide thickness of 301.2 m and a landslide time of 10.8 min. The landslide volume of 0.182 km3 estimated by the best-fitting parameters shows that the tsunami flow depth could have reached 3–10 m along the shore with a K value of 0.89, although the simulated flow depths were underestimated in comparison with the observation data. According to the waveforms, the general wave pattern was well reproduced at tide gauges during the event. A large number of objective function evaluations were necessary to locate the minimum with the DE procedure to fix the grid cell size to 20 m; this limited the accuracy of the obtained parameter values for the two-layer model. Moreover, considering the generalizations in the modeling of landslide movements, the impact landslide time and thickness must be carefully calculated to obtain a suitable accuracy.

scholarly journals SU(5) GUTs with A4 modular symmetry

2021 ◽  
Vol 2021 (4) ◽  
Author(s):  
Peng Chen ◽  
Gui-Jun Ding ◽  
Stephen F. King
Keyword(s):  
Double Beta Decay ◽  
Mixing Parameters ◽  
Wide Range ◽  
Mass Matrices ◽  
Different Types ◽  
Best Fitting ◽  
Neutrino Experiments ◽  
The Masses ◽  
Best Fit ◽  
Matter Fields

Abstract We combine SU(5) Grand Unified Theories (GUTs) with A4 modular symmetry and present a comprehensive analysis of the resulting quark and lepton mass matrices for all the simplest cases. Classifying the models according to the representation assignments of the matter fields under A4, we find that there are seven types of SU(5) models with A4 modular symmetry. We present 53 benchmark models with the fewest free parameters. The parameter space of each model is scanned to optimize the agreement between predictions and experimental data, and predictions for the masses and mixing parameters of quarks and leptons are given at the best fitting points. The best fit predictions for the leptonic CP violating Dirac phase, the lightest neutrino mass and the neutrinoless double beta decay parameter when displayed graphically are observed to cover a wide range of possible values, but are clustered around particular regions, allowing future neutrino experiments to discriminate between the different types of models.

Preliminary Evaluation of a Weibull Function for Fitting Slow-Component Eye Velocity over the Time Course of Caloric-Induced Nystagmus

1989 ◽  
Vol 32 (3) ◽  
pp. 681-687 ◽  
Author(s):  
C. Formby ◽  
B. Albritton ◽  
I. M. Rivera
Keyword(s):  
Time Course ◽  
Slow Component ◽  
Weibull Function ◽  
Preliminary Evaluation ◽  
Mathematical Function ◽  
Before And After ◽  
Best Fitting ◽  
Eye Velocity ◽  
Fitting Parameters ◽  
Weibull Equation

We describe preliminary attempts to fit a mathematical function to the slow-component eye velocity (SCV) over the time course of caloric-induced nystagmus. Initially, we consider a Weibull equation with three parameters. These parameters are estimated by a least-squares procedure to fit digitized SCV data. We present examples of SCV data and fitted curves to show how adjustments in the parameters of the model affect the fitted curve. The best fitting parameters are presented for curves fit to 120 warm caloric responses. The fitting parameters and the efficacy of the fitted curves are compared before and after the SCV data were smoothed to reduce response variability. We also consider a more flexible four-parameter Weibull equation that, for 98% of the smoothed caloric responses, yields fits that describe the data more precisely than a line through the mean. Finally, we consider advantages and problems in fitting the Weibull function to caloric data.

Data Field for Hierarchical Clustering

2011 ◽  
Vol 7 (4) ◽  
pp. 43-63 ◽  
Author(s):  
Shuliang Wang ◽  
Wenyan Gan ◽  
Deyi Li ◽  
Deren Li
Keyword(s):  
Hierarchical Clustering ◽  
Physical Space ◽  
Core Data ◽  
Data Object ◽  
Group Data ◽  
Data Field ◽  
Data Objects ◽  
The Masses ◽  
Space Data ◽  
The Impact

In this paper, data field is proposed to group data objects via simulating their mutual interactions and opposite movements for hierarchical clustering. Enlightened by the field in physical space, data field to simulate nuclear field is presented to illuminate the interaction between objects in data space. In the data field, the self-organized process of equipotential lines on many data objects discovers their hierarchical clustering-characteristics. During the clustering process, a random sample is first generated to optimize the impact factor. The masses of data objects are then estimated to select core data object with nonzero masses. Taking the core data objects as the initial clusters, the clusters are iteratively merged hierarchy by hierarchy with good performance. The results of a case study show that the data field is capable of hierarchical clustering on objects varying size, shape or granularity without user-specified parameters, as well as considering the object features inside the clusters and removing the outliers from noisy data. The comparisons illustrate that the data field clustering performs better than K-means, BIRCH, CURE, and CHAMELEON.

A Study on impact of smartphone addiction on academic performance

2018 ◽  
Vol 7 (2.6) ◽  
pp. 50 ◽  
Author(s):  
Pamela Chaudhury ◽  
Hrudaya Kumar Tripathy
Keyword(s):  
Academic Performance ◽  
Negative Impact ◽  
Pearson Correlation ◽  
Machine Learning Techniques ◽  
Smartphone Addiction ◽  
Active Involvement ◽  
Outdoor Sports ◽  
Using Data ◽  
The Masses ◽  
The Impact

Smartphone addiction is increasingly affecting the masses and is negatively impacting the younger generation. Several researches have been done to study the impact of internet and smartphone addiction. However no work has been done to predetermine academic performance from smartphone addiction using data mining techniques. A total of 222 University students participated in the questionnaire. The survey questionnaire consisted of demographic information, internet access pattern and smartphone addiction pattern. Data was analysed using machine learning techniques using classification models. The results further encouraged us to find the correlation between smartphone addiction and academic performance. Pearson’ correlation was used to establish that smartphone usage had a negative impact on academic performance. Additionally other attributes like internet connectivity and active involvement in outdoor sports activities were investigated. Experimental results confirmed a negative correlation of these attributes with academic performance. The findings were of immense use and could be used to reduce the internet addiction amongst the student community and also enhance their academic performance

Languages on Stage: Linguistic Pluralism and Community Formation in the Nineteenth-Century Parsi Theatre

2003 ◽  
Vol 37 (2) ◽  
pp. 381-405 ◽  
Author(s):  
Kathryn Hansen
Keyword(s):  
Catalytic Effect ◽  
Community Formation ◽  
Economic Base ◽  
Modern Drama ◽  
Dominant Form ◽  
Middle Classes ◽  
Indian Cinema ◽  
The Masses ◽  
Commercial Organization ◽  
The Impact

The Parsi theatre was the dominant form of dramatic entertainment in urban India from the 1860s to the 1930s. Named for its Bombay-based pioneers, the Parsi theatre blended certain European practices of stagecraft and commercial organization with Indic, Persian, and English stories, music, and poetry. Through the impact of its touring companies, it had a catalytic effect on the development of modern drama and regional theatre throughout South and Southeast Asia. Moreover, Parsi theatre is widely credited with contributing to popular Indian cinema its genres, aesthetic, and economic base. With Hindi films now the major cultural signifier for the middle classes and the ‘masses’ in South Asia and its diaspora, documentation and evaluation of the Parsi theatre is much needed, especially to connect it convincingly to the cinematic medium that followed.

Applicability of an extant batch respirometric assay in describing dynamics of ammonia and nitrite oxidation in a nitrifying bioreactor

2005 ◽  
Vol 52 (10-11) ◽  
pp. 503-508 ◽  
Author(s):  
K. Chandran ◽  
Z. Hu ◽  
B.F. Smets
Keyword(s):  
Kinetic Parameter ◽  
Sensitivity Analyses ◽  
Continuous Reactor ◽  
Parameter Estimates ◽  
Additional Parameter ◽  
Reactor Performance ◽  
Estimation Techniques ◽  
The Difference ◽  
The Impact ◽  
Best Fit

Several techniques have been proposed for biokinetic estimation of nitrification. Recently, an extant respirometric assay has been presented that yields kinetic parameters for both nitrification steps with minimal physiological change to the microorganisms during the assay. Herein, the ability of biokinetic parameter estimates from the extant respirometric assay to adequately describe concurrently obtained NH4+-N and NO2−-N substrate depletion profiles is evaluated. Based on our results, in general, the substrate depletion profiles resulted in a higher estimate of the maximum specific growth rate coefficient, μmax for both NH4+-N to NO2−-N oxidation and NO2−-N to NO3−-N oxidation compared to estimates from the extant respirograms. The trends in the kinetic parameter estimates from the different biokinetic estimation techniques are paralleled in the nature of substrate depletion profiles obtained from best-fit parameters. Based on a visual inspection, in general, best-fit parameters from optimally designed complete respirograms provided a better description of the substrate depletion profiles than estimates from isolated respirograms. Nevertheless, the sum of the squared errors for the best-fit respirometry based parameters was outside the 95% joint confidence interval computed for the best-fit substrate depletion based parameters. Notwithstanding the difference in kinetic parameter estimates determined in this study, the different biokinetic estimation techniques still are close to estimates reported in literature. Additional parameter identifiability and sensitivity analysis of parameters from substrate depletion assays revealed high precision of parameters and high parameter correlation. Although biokinetic estimation via automated extant respirometry is far more facile than via manual substrate depletion measurements, additional sensitivity analyses are needed to test the impact of differences in the resulting parameter values on continuous reactor performance.

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