scholarly journals Asteroseismology of 36 Kepler subgiants – I. Oscillation frequencies, linewidths, and amplitudes

2020 ◽  
Vol 495 (2) ◽  
pp. 2363-2386 ◽  
Author(s):  
Yaguang Li ◽  
Timothy R Bedding ◽  
Tanda Li ◽  
Shaolan Bi ◽  
Dennis Stello ◽  
...  

ABSTRACT The presence of mixed modes makes subgiants excellent targets for asteroseismology, providing a probe for the internal structure of stars. Here we study 36 Kepler subgiants with solar-like oscillations and report their oscillation mode parameters. We performed a so-called peakbagging exercise, i.e. estimating oscillation mode frequencies, linewidths, and amplitudes with a power spectrum model, fitted in the Bayesian framework and sampled with a Markov chain Monte Carlo algorithm. The uncertainties of the mode frequencies have a median value of 0.180 μHz. We obtained seismic parameters from the peakbagging, analysed their correlation with stellar parameters, and examined against scaling relations. The behaviour of seismic parameters (e.g. Δν, νmax, ϵp) is in general consistent with theoretical predictions. We presented the observational p–g diagrams, namely γ1–Δν for early subgiants and ΔΠ1–Δν for late subgiants, and demonstrate their capability to estimate stellar mass. We also found a log g dependence on the linewidths and a mass dependence on the oscillation amplitudes and the widths of oscillation excess. This sample will be valuable constraints for modelling stars and studying mode physics such as excitation and damping.

2020 ◽  
Vol 34 (25) ◽  
pp. 2050271
Author(s):  
Kai-Li Xue ◽  
Yun-Feng Hu ◽  
Xu-Chen Yu ◽  
Ji-Xuan Hou

We present a simple model of ionomers, namely a single polymer chain in a series of fixed attractors. In analogy to ionized bead’s claws of surrounding chains, the set of attractors can affectively slow down the diffusion motion of the target chain. The monomer mean-square displacement of ionomers is studied by using Monte Carlo algorithm, and compared with the prediction of the sticky Rouse model. The diffusion motion properties of ionomers are explored in three aspects, including the chain length of the polymer, the depth of the potential well and the number of ionic groups. The results show that a plateau appears in the monomer diffusion function due to the attraction of the attractors to the claws. However, comparative theoretical predictions and simulation results show that there exists some discrepancy between them. Therefore, the relaxation time distribution of polymer chain motion is explored. The simulation results confirm that the association lifetime is decreasing exponentially, and the expected values of the association lifetime satisfy the Boltzmann distribution as shown by the results. These results perfectly explain the deviation between the simulation data and the theoretical results.


2008 ◽  
Vol 40 (1) ◽  
pp. 273-291 ◽  
Author(s):  
Bruno Casella ◽  
Gareth O. Roberts

We describe and implement a novel methodology for Monte Carlo simulation of one-dimensional killed diffusions. The proposed estimators represent an unbiased and efficient alternative to current Monte Carlo estimators based on discretization methods for the cases when the finite-dimensional distributions of the process are unknown. For barrier option pricing in finance, we design a suitable Monte Carlo algorithm both for the single barrier case and the double barrier case. Results from numerical investigations are in excellent agreement with the theoretical predictions.


2008 ◽  
Vol 40 (01) ◽  
pp. 273-291 ◽  
Author(s):  
Bruno Casella ◽  
Gareth O. Roberts

We describe and implement a novel methodology for Monte Carlo simulation of one-dimensional killed diffusions. The proposed estimators represent an unbiased and efficient alternative to current Monte Carlo estimators based on discretization methods for the cases when the finite-dimensional distributions of the process are unknown. For barrier option pricing in finance, we design a suitable Monte Carlo algorithm both for the single barrier case and the double barrier case. Results from numerical investigations are in excellent agreement with the theoretical predictions.


2020 ◽  
Vol 26 (3) ◽  
pp. 223-244
Author(s):  
W. John Thrasher ◽  
Michael Mascagni

AbstractIt has been shown that when using a Monte Carlo algorithm to estimate the electrostatic free energy of a biomolecule in a solution, individual random walks can become entrapped in the geometry. We examine a proposed solution, using a sharp restart during the Walk-on-Subdomains step, in more detail. We show that the point at which this solution introduces significant bias is related to properties intrinsic to the molecule being examined. We also examine two potential methods of generating a sharp restart point and show that they both cause no significant bias in the examined molecules and increase the stability of the run times of the individual walks.


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