scholarly journals Hints for possible low redshift oscillation around the best fit ΛCDM model in the expansion history of the universe

2020 ◽  
Author(s):  
L Kazantzidis ◽  
H Koo ◽  
S Nesseris ◽  
L Perivolaropoulos ◽  
A Shafieloo
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Absolute Magnitude ◽  
Density Parameter ◽  
Statistical Fluctuations ◽  
Full Dataset ◽  
Λcdm Model ◽  
History Of ◽  
Best Fit ◽  
The Universe

Abstract We search for possible deviations from the expectations of the concordance ΛCDM model in the expansion history of the Universe by analysing the Pantheon Type Ia Supernovae (SnIa) compilation along with its Monte Carlo simulations using redshift binning. We demonstrate that the redshift binned best fit ΛCDM matter density parameter Ω0m and the best fit effective absolute magnitude $\cal M$ oscillate about their full dataset best fit values with considerably large amplitudes. Using the full covariance matrix of the data taking into account systematic and statistical errors, we show that at the redshifts below z ≈ 0.5 such oscillations can only occur in 4 to 5% of the Monte Carlo simulations. While statistical fluctuations can be responsible for this apparent oscillation, we might have observed a hint for some behaviour beyond the expectations of the concordance model or a possible additional systematic in the data. If this apparent oscillation is not due to statistical or systematic effects, it could be due to either the presence of coherent inhomogeneities at low z or due to oscillations of a quintessence scalar field.

ON THE CALCULATION OF THE HEAT CAPACITY IN PATH INTEGRAL MONTE CARLO SIMULATIONS

1992 ◽  
Vol 03 (02) ◽  
pp. 337-346 ◽  
Author(s):  
D. MARX ◽  
P. NIELABA ◽  
K. BINDER
Keyword(s):  
Heat Capacity ◽  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Path Integral ◽  
General Relation ◽  
Absolute Magnitude ◽  
Computational Effort ◽  
Imaginary Time ◽  
Time Dimension ◽  
Path Integral Monte Carlo

In Path Integral Monte Carlo simulations the systems partition function is mapped to an equivalent classical one at the expense of a temperature-dependent Hamiltonian with an additional imaginary time dimension. As a consequence the standard relation linking the heat capacity Cv to the energy fluctuations, <E2>−<E>2, which is useful in standard classical problems with temperature-independent Hamiltonian, becomes invalid. Instead, it gets replaced by the general relation [Formula: see text] for the intensive heat capacity estimator; β being the inverse temperature and the subscript P indicates the P-fold discretization in the imaginary time direction. This heatcapacity estimator has the advantage of being based directly on the energy estimatorand thus requires no extra computational effort and is suited for extensive phase diagramstudies. As an example, numerical results are presented for a two-dimensional fluid withinternal magnetic quantum degrees of freedom. We discuss in detail origin and consequences of the excess term. Due to the subtraction of two relatively large contributions ofsimilar absolute magnitude a large statistical effort would be necessary for very accurateheat capacity estimates.

scholarly journals A Confront between Amati and Combo Correlations at Intermediate and Early Redshifts

Symmetry ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1118
Author(s):  
Marco Muccino
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Predictive Power ◽  
Energy Equation ◽  
Gamma Ray ◽  
Zero Curvature ◽  
Level 3 ◽  
The Difference ◽  
Best Fit ◽  
The Universe

I consider two gamma-ray burst (GRB) correlations: Amati and Combo. After calibrating them in a cosmology-independent way by employing Beziér polynomials to approximate the Observational Hubble Dataset (OHD), I perform Markov Chain Monte Carlo (MCMC) simulations within the Λ CDM and the wCDM models. The results from the Amati GRB dataset do not agree with the standard Λ CDM model at a confidence level ≥ 3 – σ . For the Combo correlation, all MCMC simulations give best-fit parameters which are consistent within 1– σ with the Λ CDM model. Pending the clarification of whether the diversity of these results is statistical, due to the difference in the dataset sizes, or astrophysical, implying the search for the most suited correlation for cosmological analyses, future investigations require larger datasets to increase the predictive power of both correlations and enable more refined analyses on the possible non-zero curvature of the Universe and the dark energy equation of state and evolution.

scholarly journals Monte Carlo simulations of globular cluster red giant branches

1984 ◽  
Vol 105 ◽  
pp. 159-161
Author(s):  
Deborah A. Crocker ◽  
Robert T. Rood
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Globular Cluster ◽  
Physical Parameters ◽  
Statistical Fluctuations ◽  
Luminosity Functions ◽  
Red Giant

Simulations of globular cluster luminosity functions have shown that many of the features observed in actual clusters are probably statistical fluctuations. We suggest one new way of looking at the data which may ultimately lead to some information about the physical parameters of clusters.

scholarly journals Modified Statistical Analysis of SNe1a Data

2020 ◽  
Vol 240 ◽  
pp. 02001
Author(s):  
Lisa Goh ◽  
Cindy Ng
Keyword(s):  
Profile Likelihood ◽  
Cosmic Acceleration ◽  
Confidence Levels ◽  
Accelerating Expansion ◽  
Original Analysis ◽  
Λcdm Model ◽  
Contour Plots ◽  
Expansion Of The Universe ◽  
Best Fit ◽  
The Universe

We review an improved maximum likelihood analysis of the Type 1a Supernova (SNe1a) data. We calculate the profile likelihood in the Ωm -ΩΛ pa- rameter space by conducting a parameter sweep across the 8 SNe1a parameters, using a Markov Chain Monte Carlo (MCMC) optimization algorithm. This im- proved analysis, which does not assume arbitrary values for the uncertainties, has the advantage of being bias-free as compared to the original analysis. We use the Joint Lightcurve Analysis (JLA) dataset containing 740 SN1a data sam- ples for our study, and compare among 5 different models: the ΛCDM model, the flat wCDM model, its non-flat generalization, as well as two dynamical w(z) parametrizations. We find that the ΛCDM model is favoured over the other models, and the best fit values based on this model are Ωm =0.40 and ΩΛ =0.55. Interestingly, in most of the contour plots we obtain, the line of no acceleration is crossed at 2∼3σ confidence levels, which is similar to the results published by Nielsen et al, the original authors who introduced the improved maximum like- lihood analysis. When we generalize the wCDM model to the dynamical w(z) parametrizations, the evidence for cosmic acceleration becomes even weaker. This raises the question of how secure we can be of an accelerating expansion of the universe.

scholarly journals Hints for a Gravitational Transition in Tully–Fisher Data

Universe ◽  
2021 ◽  
Vol 7 (10) ◽  
pp. 366
Author(s):  
George Alestas ◽  
Ioannis Antoniou ◽  
Leandros Perivolaropoulos
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Gravitational Constant ◽  
The Other ◽  
Full Sample ◽  
Data Compilation ◽  
Fisher Relation ◽  
Best Fit ◽  
Splitting Distance

We use an up-to-date compilation of Tully–Fisher data to search for transitions in the evolution of the Tully–Fisher relation. Using an up-to-date data compilation, we find hints at ≈3σ level for a transition at critical distances Dc≃9 Mpc and Dc≃17 Mpc. We split the full sample in two subsamples, according to the measured galaxy distance with respect to splitting distance Dc, and identify the likelihood of the best-fit slope and intercept of one sample with respect to the best-fit corresponding values of the other sample. For Dc≃9 Mpc and Dc≃17 Mpc, we find a tension between the two subsamples at a level of Δχ2>17(3.5σ). Using Monte Carlo simulations, we demonstrate that this result is robust with respect to random statistical and systematic variations of the galactic distances and is unlikely in the context of a homogeneous dataset constructed using the Tully–Fisher relation. If the tension is interpreted as being due to a gravitational strength transition, it would imply a shift in the effective gravitational constant to lower values for distances larger than Dc by ΔGG≃−0.1. Such a shift is of the anticipated sign and magnitude but at a somewhat lower distance (redshift) than the gravitational transition recently proposed to address the Hubble and growth tensions (ΔGG≃−0.1 at the transition redshift of zt≲0.01 (Dc≲40 Mpc)).

A METHOD FOR MEASURING ELLIPTIC FLOW FLUCTUATIONS WITH THE PHOBOS DETECTOR

2007 ◽  
Vol 16 (07n08) ◽  
pp. 1852-1858
Author(s):  
◽  
BURAK ALVER
Keyword(s):  
Monte Carlo ◽  
Maximum Likelihood ◽  
Monte Carlo Simulations ◽  
Elliptic Flow ◽  
Monte Carlo Event ◽  
Event Generator ◽  
Analysis Method ◽  
Statistical Fluctuations ◽  
Flow Fluctuations ◽  
Dynamical Fluctuations

We have performed the first measurement of elliptic flow (v2) fluctuations in nucleus-nucleus collisions. In this paper, we describe the analysis method we have developed for this measurement. In this method, v2 is determined event-by-event by a maximum likelihood fit. The non-statistical fluctuations are determined by unfolding the contribution of statistical fluctuations and detector effects using Monte Carlo simulations. Application of this method to measure dynamical fluctuations in events from a different Monte Carlo event generator is presented.

scholarly journals PARAMETRIZATION OF THE DARK ENERGY EQUATION OF STATE

2007 ◽  
Vol 16 (10) ◽  
pp. 1581-1591 ◽  
Author(s):  
VINOD B. JOHRI ◽  
P. K. RATH
Keyword(s):  
Dark Energy ◽  
Equation Of State ◽  
Energy Density ◽  
Comparative Study ◽  
Energy Equation ◽  
Critical Evaluation ◽  
Density Parameter ◽  
Dark Energy Density ◽  
History Of ◽  
The Universe

A comparative study of various parametrizations of the dark energy equation of state is made. Astrophysical constraints from LSS, CMB and BBN are laid down to test the physical viability and cosmological compatibility of these parametrizations. A critical evaluation of the four-index parametrizations reveals that Hannestad–Mörtsell as well as Lee parametrizations are simple and transparent in probing the evolution of the dark energy during the expansion history of the universe and they satisfy the LSS, CMB and BBN constraints on the dark energy density parameter.

scholarly journals Windowing artefacts likely account for recent claimed detection of oscillating cosmic scale factor

2020 ◽  
Vol 498 (4) ◽  
pp. 5512-5516
Author(s):  
Sasha R Brownsberger ◽  
Christopher W Stubbs ◽  
Daniel M Scolnic
Keyword(s):  
Type Ia Supernovae ◽  
Data Sets ◽  
Analysis Method ◽  
Data Set ◽  
Statistical Fluctuations ◽  
Data Analyses ◽  
Type Ia ◽  
History Of ◽  
Ia Supernovae ◽  
The Universe

ABSTRACT Using the Pantheon data set of Type Ia supernovae, a recent publication (R20 in this work) reports a  2σ detection of oscillations in the expansion history of the Universe. The study conducted by R20 is wholly worthwhile. However, we demonstrate that there is a $\gt 10{{\ \rm per\ cent}}$ chance of statistical fluctuations in the Pantheon data producing a false oscillatory signal larger than the oscillatory signal that R20 report. Their results are a less than 2σ detection. Applying the R20 methodology to simulated Pantheon data, we determine that these oscillations could arise due to analysis artefacts. The uneven spacing of Type Ia supernovae in redshift space and the complicated analysis method of R20 impose a structured throughput function. When analysed with the R20 prescription, about $11{{\ \rm per\ cent}}$ of artificial ΛCDM data sets produce a stronger oscillatory signal than the actual Pantheon data. Our results underscore the importance of understanding the false ‘signals’ that can be introduced by complicated data analyses.

COSMIC CONSTRAINTS ON HOLOGRAPHIC DARK ENERGY IN BRANS–DICKE THEORY VIA MARKOV-CHAIN MONTE-CARLO METHOD

2010 ◽  
Vol 25 (17) ◽  
pp. 1441-1454 ◽  
Author(s):  
LIXIN XU ◽  
ZHAOFEI LIU ◽  
JIANBO LU ◽  
WENBO LI
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Dark Energy ◽  
Markov Chain Monte Carlo ◽  
Holographic Dark Energy ◽  
Accelerated Expansion ◽  
Energy Formula ◽  
Current Value ◽  
Best Fit ◽  
The Universe

In this paper, the holographic dark energy in Brans–Dicke theory is confronted by cosmic observations from SN Ia, BAO, OHD and CMB via Markov-Chain Monte-Carlo (MCMC) method. The best fit parameters are found in 1σ region: [Formula: see text] and [Formula: see text] (equivalently ω = 2415.653 which is less than the solar system bound and consistent with other constraint results). With these best fit values of the parameters, it is found that the universe is undergoing accelerated expansion, and the current value of equation of state of holographic dark energy [Formula: see text] which is phantom like in Brans–Dicke theory. The effective Newton's constant decreases with the expansion of our universe for the negative value of model parameter α.

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