arXiv subjects

Ujjaini Alam

Publications and source records attributed to Ujjaini Alam.

At least 19 recordsLinked to original sources

arXiv2023

An unsupervised machine learning based algorithm for detecting Weak Impulsive Narrowband Quiet Sun Emissions and characterizing their morphology

The solar corona is extremely dynamic. Every leap in observational capabilities has been accompanied by unexpected revelations of complex dynamic processes. The ever more sensitive instruments now allow us to probe events with increasingly weaker energetics. A recent leap in the low-frequency radio solar imaging ability has led to the discovery of a new class of emissions, namely Weak Impulsive Narrowband Quiet Sun Emissions \citep[WINQSEs;][]{mondal2020}. They are hypothesized to be the radio signatures of coronal nanoflares and could potentially have a bearing on the long standing coronal heating problem. In view of the significance of this discovery, this work has been followed up by multiple independent studies. These include detecting WINQSEs in multiple datasets, using independent detection techniques and software pipelines, and looking for their counterparts at other wavelengths. This work focuses on investigating morphological properties of WINQSEs and also improves upon the methodology used for detecting WINQSEs in earlier works. We present a machine learning based algorithm to detect WINQSEs, classify them based on their morphology and model the isolated ones using 2D Gaussians. We subject multiple datasets to this algorithm to test its veracity. Interestingly, despite the expectations of their arising from intrinsically compact sources, WINQSEs tend to be resolved in our observations. We propose that this angular broadening arises due to coronal scattering. WINQSEs can, hence, provide ubiquitous and ever-present diagnostic of coronal scattering (and, in turn, coronal turbulence) in the quiet sun regions, which has not been possible till date.

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arXiv2021

Exploring Coronal Heating Using Unsupervised Machine-Learning

The perplexing mystery of what maintains the solar coronal temperature at about a million K, while the visible disc of the Sun is only at 5800 K, has been a long standing problem in solar physics. A recent study by Mondal(2020) has provided the first evidence for the presence of numerous ubiquitous impulsive emissions at low radio frequencies from the quiet sun regions, which could hold the key to solving this mystery. These features occur at rates of about five hundred events per minute, and their strength is only a few percent of the background steady emission. One of the next steps for exploring the feasibility of this resolution to the coronal heating problem is to understand the morphology of these emissions. To meet this objective we have developed a technique based on an unsupervised machine learning approach for characterising the morphology of these impulsive emissions. Here we present the results of application of this technique to over 8000 images spanning 70 minutes of data in which about 34,500 features could robustly be characterised as 2D elliptical Gaussians.

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arXiv2019

Are $H_0$ and $σ_8$ tensions generic to present cosmological data?

Yes, for a wide range of cosmological models ($Λ$CDM, non-interacting $w_z$CDM or models with possible interactions between dark energy and dark matter, in either phantom or non-phantom regimes). In the recent past there have been many attempts to solve the tension between direct measurements of $H_0$ and $σ_8 \sqrt{Ω_{0 {\rm m}}}$ from the respective low redshift observables and indirect measurements of these quantities from the cosmic microwave background (CMB). In this work we reconstruct a model independent approach that boils down to different classes of cosmological models under suitable parameters choices. We test this parameterization against the latest Planck CMB data combined with recent BAO, SNeIa datasets and the R16 direct $H_0$ measurements, and compare among different cosmological models. Our analysis reveals that a strong positive correlation between $H_0$ and $σ_8$ is more or less generic, irrespective of the choice of cosmological models. We also find that present data slightly prefers a phantom equation of state for dark energy and a slight negative value for effective equation of state for dark matter (which is a direct signature of interacting models) with a relatively high value for $H_0$ consistent with R16 and simultaneously, a consistent value for $Ω_{0 {\rm m}}$. Thus, even though the tensions cannot be fully resolved, interacting models with phantom equation of state get a slight edge over the others for currently available data. We also see that allowing interaction between dark energy and dark matter may resolve the tension between the high redshift CMB data and individual low redshift datasets, but the low redshift datasets have inconsistencies between them (e.g. between BAO and $H_0$, SNeIa and BAO, and cluster counts and $H_0$) that are practically independent of the cosmological model.

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arXiv2017

An Exploration of Heterogeneity in Supernova Type Ia Samples

We examine three SNe Type Ia datasets: Union2.1, JLA and Panstarrs to check their consistency using cosmology blind statistical analyses as well as cosmological parameter fitting. We find that Panstarrs dataset is the most stable of the three to changes, although it does not, at the moment, go to high enough redshifts to tightly constrain the dark energy equation of state, $w$. Union2.1, drawn from many different sources, appears somewhat susceptible to changes within the dataset. JLA reconstructs well for a smaller number of cosmological parameters. At higher degrees of freedom, the dependence of its errors on redshift can lead to varying results between subsets. Panstarrs is inconsistent with the other two at about $2σ$, and JLA and Union2.1 are about $1σ$ away from each other. For the $Ω_{0m}-w$ cosmological reconstruction, the $1σ$ range of values in $w$ for selected subsets of each dataset is two times larger for JLA and Union2.1 as compared to Panstarrs. The range in $Ω_{0m}$ for the same subsets remains approximately similar for all three datasets. Although there are differences in the fitting and correction techniques used in the different samples, the most important criterion is SNe selection, a slightly different SNe selection can lead to noticeably different results both in the purely statistical analysis and cosmological reconstruction. We note that a single, high quality low redshift sample could help decrease the uncertainties in the result. We also note that lack of homogeneity in the magnitude errors may bias the results and should either be modeled, or its effect neutralized by using other, complementary datasets. A supernova sample with high quality data at both high and low redshifts, constructed from a few surveys to avoid heterogeneity in the sample, and with homogeneous errors, would result in a more robust cosmological reconstruction.

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arXiv2017

Constraining the Cosmology of the Phantom Brane using Distance Measures

The phantom brane has several important distinctive features: (i) Its equation of state is phantom-like, but there is no future `big rip' singularity, (ii) the effective cosmological constant on the brane is dynamically screened, because of which the expansion rate is {\em smaller} than that in $Λ$CDM at high redshifts. In this paper, we constrain the Phantom braneworld using distance measures such as Type Ia supernovae (SNeIa), Baryon Acoustic Oscillations (BAO), and the compressed Cosmic Microwave Background (CMB) data. We find that the simplest braneworld models provide a good fit to the data. For instance, BAO +SNeIa data can be accommodated by the braneworld for a large region in parameter space $0 < Ω_l < 0.3$ at $1σ$. The Hubble parameter can be as high as $H_0 < 78$ km/s/Mpc, and the effective equation of state at present can show phantom-like behaviour with $w_0 < -1.2$ at $1σ$. We note a correlation between $H_0$ and $w_0$, with higher values of $H_0$ leading to a lower, and more phantom-like, value of $w_0$. Inclusion of CMB data provides tighter constraints $Ω_l < 0.1$. (Here $Ω_l$ encodes the ratio of the five and four dimensional Planck mass.) The Hubble parameter in this case is more tightly constrained to $H_0 < 71$ km/s/Mpc, and the effective equation of state to $w_0 < -1.1$. Interestingly, we find that the universe is allowed be closed or open, with $-0.5 < Ω_κ < 0.5$, even on including the compressed CMB data. There appears to be some tension in the low and high $z$ BAO data which may either be resolved by future data, or act as a pointer to interesting new cosmology.

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arXiv2011

Nonparametric Reconstruction of the Dark Energy Equation of State from Diverse Data Sets

The cause of the accelerated expansion of the Universe poses one of the most fundamental questions in physics today. In the absence of a compelling theory to explain the observations, a first task is to develop a robust phenomenology. If the acceleration is driven by some form of dark energy, then, the phenomenology is determined by the dark energy equation of state w. A major aim of ongoing and upcoming cosmological surveys is to measure w and its time dependence at high accuracy. Since w(z) is not directly accessible to measurement, powerful reconstruction methods are needed to extract it reliably from observations. We have recently introduced a new reconstruction method for w(z) based on Gaussian process modeling. This method can capture nontrivial time-dependences in w(z) and, most importantly, it yields controlled and unbaised error estimates. In this paper we extend the method to include a diverse set of measurements: baryon acoustic oscillations, cosmic microwave background measurements, and supernova data. We analyze currently available data sets and present the resulting constraints on w(z), finding that current observations are in very good agreement with a cosmological constant. In addition we explore how well our method captures nontrivial behavior of w(z) by analyzing simulated data assuming high-quality observations from future surveys. We find that the baryon acoustic oscillation measurements by themselves already lead to remarkably good reconstruction results and that the combination of different high-quality probes allows us to reconstruct w(z) very reliably with small error bounds.

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arXiv2010

Galaxy Clusters as a probe of early dark energy

We study a class of early dark energy (EDE) models, in which, unlike in standard dark energy models, a substantial amount of dark energy exists in the matter-dominated era. We self-consistently include dark energy perturbations, and show that these models may be successfully constrained using future observations of galaxy clusters, in particular the redshift abundance, and the Sunyaev-Zel'dovich (SZ) power spectrum. We make predictions for EDE models, as well as LCDM for incoming X-ray (eROSITA) and microwave (South Pole Telescope) observations. We show that galaxy clusters' mass function and the SZ power spectrum will put strong constraints both on the equation of state of \de today and the redshift at which EDE transits to present-day LCDM like behavior for these models, thus providing complementary information to the geometric probes of dark energy. Not including perturbations in EDE models leads to those models being practically indistinguishable from LCDM. An MCMC analysis of future galaxy cluster surveys provides constraints for EDE parameters that are competitive with and complementary to background expansion observations such as supernovae.

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arXiv2010

Reconstructing Dark Energy : A Comparison of Cosmological Parameters

A large number of cosmological parameters have been suggested for obtaining information on the nature of dark energy. In this work, we study the efficacy of these different parameters in discriminating theoretical models of dark energy, using both currently available supernova (SNe) data, and simulations of future observations. We find that the current data does not put strong constraints on the nature of dark energy, irrespective of the cosmological parameter used. For future data, we find that the although deceleration parameter can accurately reconstruct some dark energy models, it is unable to discriminate between different models of dark energy, therefore limiting its usefulness. Physical parameters such as the equation of state of dark energy, or the dark energy density do a good job of both reconstruction and discrimination if the matter density is known to high accuracy. However, uncertainty in matter density reduces the efficacy of these parameters. A recently proposed parameter, Om(z), constructed from the first derivative of the SNe data, works very well in discriminating different theoretical models of dark energy, and has the added advantage of not being dependent on the value of matter density. Thus we find that a cosmological parameter constructed from the first derivative of the data, for which the theoretical models of dark energy are sufficiently distant from each other, and which is independent of the matter density, performs the best in reconstructing dark energy from SNe data.

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arXiv2010

Nonparametric Dark Energy Reconstruction from Supernova Data

Understanding the origin of the accelerated expansion of the Universe poses one of the greatest challenges in physics today. Lacking a compelling fundamental theory to test, observational efforts are targeted at a better characterization of the underlying cause. If a new form of mass-energy, dark energy, is driving the acceleration, the redshift evolution of the equation of state parameter w(z) will hold essential clues as to its origin. To best exploit data from observations it is necessary to develop a robust and accurate reconstruction approach, with controlled errors, for w(z). We introduce a new, nonparametric method for solving the associated statistical inverse problem based on Gaussian Process modeling and Markov chain Monte Carlo sampling. Applying this method to recent supernova measurements, we reconstruct the continuous history of w out to redshift z=1.5.

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arXiv2010

Nonparametric Reconstruction of the Dark Energy Equation of State

A basic aim of ongoing and upcoming cosmological surveys is to unravel the mystery of dark energy. In the absence of a compelling theory to test, a natural approach is to better characterize the properties of dark energy in search of clues that can lead to a more fundamental understanding. One way to view this characterization is the improved determination of the redshift-dependence of the dark energy equation of state parameter, w(z). To do this requires a robust and bias-free method for reconstructing w(z) from data that does not rely on restrictive expansion schemes or assumed functional forms for w(z). We present a new nonparametric reconstruction method that solves for w(z) as a statistical inverse problem, based on a Gaussian Process representation. This method reliably captures nontrivial behavior of w(z) and provides controlled error bounds. We demonstrate the power of the method on different sets of simulated supernova data; the approach can be easily extended to include diverse cosmological probes.

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arXiv2010

Constraining Perturbative Early Dark Energy with Current Observations

In this work, we study a class of early dark energy (EDE) models, in which, unlike in standard DE models, a substantial amount of DE exists in the matter-dominated era, self-consistently including DE perturbations. Our analysis shows that, marginalizing over the non DE parameters such as $Omega_m, H_0, n_s$, current CMB observations alone can constrain the scale factor of transition from early DE to late time DE to $a_t \geq 0.44$ and width of transition to $Delta_t \leq 0.37$. The equation of state at present is somewhat weakly constrained to $w_0 \leq -0.6$, if we allow $H_0 < 60$ km/s/Mpc. Taken together with other observations, such as supernovae, HST, and SDSS LRGs, the constraints are tighter-- $w_0 \leq -0.9, a_t \leq 0.19, Δ_t \leq 0.21$. The evolution of the equation of state for EDE models is thus close to $Λ$CDM at low redshifts. Incorrectly assuming DE perturbations to be negligible leads to different constraints on the equation of state parameters, thus highlighting the necessity of self-consistently including DE perturbations in the analysis. If we allow the spatial curvature to be a free parameter, then the constraints are relaxed to $w_0 \leq -0.77, a_t \leq 0.35, Δ_t \leq 0.35$ with $-0.014 < Ω_κ < 0.031$ for CMB+other observations. For perturbed EDE models, the $2σ$ lower limit on $σ_8$ ($σ_8 \geq 0.59$) is much lower than that in $Λ$CDM ($σ_8 \geq 0.72$), thus raising the interesting possibility of discriminating EDE from $Λ$CDM using future observations such as halo mass functions or the Sunyaev-Zeldovich power spectrum.

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arXiv2009

Reconstructing Cosmological Matter Perturbations using Standard Candles and Rulers

For a large class of dark energy (DE) models, for which the effective gravitational constant is a constant and there is no direct exchange of energy between DE and dark matter (DM), knowledge of the expansion history suffices to reconstruct the growth factor of linearized density perturbations in the non-relativistic matter component on scales much smaller than the Hubble distance. In this paper we develop a non-parametric method for extracting information about the perturbative growth factor from data pertaining to the luminosity or angular size distances. A comparison of the reconstructed density contrast with observations of large scale structure and gravitational lensing can help distinguish DE models such as the cosmological constant and quintessence from models based on modified gravity theories as well as models in which DE and DM are either unified, or interact directly. We show that for current SNe data, the linear growth factor at z = 0.3 can be constrained to 5%, and the linear growth rate to 6%. With future SNe data, such as expected from the JDEM mission, we may be able to constrain the growth factor to 2-3% and the growth rate to 3-4% at z = 0.3 with this unbiased, model-independent reconstruction method. For future BAO data which would deliver measurements of both the angular diameter distance and Hubble parameter, it should be possible to constrain the growth factor at z = 2.5 to 9%. These constraints grow tighter with the errors on the datasets. With a large quantity of data expected in the next few years, this method can emerge as a competitive tool for distinguishing between different models of dark energy.

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arXiv2007

Smoothing Supernova Data to Reconstruct the Expansion History of the Universe and its Age

We propose a non-parametric method of smoothing supernova data over redshift using a Gaussian kernel in order to reconstruct important cosmological quantities including H(z) and w(z) in a model independent manner. This method is shown to be successful in discriminating between different models of dark energy when the quality of data is commensurate with that expected from the future SuperNova Acceleration Probe (SNAP). We find that the Hubble parameter is especially well-determined and useful for this purpose. The look back time of the universe may also be determined to a very high degree of accuracy (\lleq 0.2 %) in this method. By refining the method, it is also possible to obtain reasonable bounds on the equation of state of dark energy. We explore a new diagnostic of dark energy-- the `w-probe'-- which can be calculated from the first derivative of the data. We find that this diagnostic is reconstructed extremely accurately for different reconstruction methods even if Ω_m is marginalized over. The w-probe can be used to successfully distinguish between $Λ$CDM and other models of dark energy to a high degree of accuracy.

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arXiv2006

Exploring the Properties of Dark Energy Using Type Ia Supernovae and Other Datasets

We reconstruct dark energy properties from two complementary supernova datasets -- the newly released Gold+HST sample and SNLS. The results obtained are consistent with standard $Λ$CDM model within $2σ$ error bars although the Gold+HST data favour evolving dark energy slightly more than SNLS. Using complementary data from baryon acoustic oscillations and the cosmic microwave background to constrain dark energy, we find that our results in this case are strongly dependent on the present value of the matter density $Ω_m$. Consequently, no firm conclusions regarding constancy or variability of dark energy density can be drawn from these data alone unless the value of $Ω_m$ is known to an accuracy of a few percent. However, possible variability is significantly restricted if this data is used in conjunction with supernova data.

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arXiv2006

Confronting Braneworld Cosmology with Supernova data and Baryon Oscillations

Braneworld cosmology has several attractive and distinctive features. For instance the effective equation of state in braneworld models can be both quintessence-like (w_0 \geq -1) as well as phantom-like (w_0 \leq -1). Models with w_0 \geq -1 (w_0 \leq -1) are referred to as Brane 2 (Brane 1) and correspond to complementary embeddings of the brane in the bulk. (The equation of state in Brane 1 can successfully cross the `phantom divide' at w = -1.) In this paper we compare the predictions of braneworld models to two recently released supernova data sets: the `Gold' data (Riess et al, 2004) and the data from the Supernova Legacy Survey (SNLS) (Astier et al, 2005). We also incorporate the recent discovery of the baryon acoustic peak in the Sloan Digital Sky Survey (Eisenstein et al, 2005) into our analysis. Our main results are that braneworld models satisfy both sets of SNe data. Brane 1 (with w_0 \leq -1) shows very good agreement with data for values of the matter density bounded {\em from below}: Ω_m \geq 0.25 (Gold) and $Ω_m \geq 0.2 (SNLS). On the other hand Brane 2 (with w_0 \geq -1) shows excellent agreement with data for values of the matter density which are bounded {\em from above}: Ω_m \leq 0.45 (Gold) and Ω_m \leq 0.35 (SNLS). The DGP model is excluded at 3σby SNLS and at 1σby the Gold dataset. Braneworld models with future `quiescent' singularities (at which the Hubble parameter and the matter density remain finite but higher derivatives of the expansion factor diverge) are excluded by both datasets.

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arXiv2004

Is there Supernova Evidence for Dark Energy Metamorphosis ?

We reconstruct the equation of state $w(z)$ of dark energy (DE) using a recently released data set containing 172 type Ia supernovae without assuming the prior $w(z) \geq -1$ (in contrast to previous studies). We find that dark energy evolves rapidly and metamorphoses from dust-like behaviour at high $z$ ($w \simeq 0$ at $z \sim 1$) to a strongly negative equation of state at present ($w \lleq -1$ at $z \simeq 0$). Dark energy metamorphosis appears to be a robust phenomenon which manifests for a large variety of SNe data samples provided one does not invoke the weak energy prior $ρ+ p \geq 0$. Invoking this prior considerably weakens the rate of growth of $w(z)$. These results demonstrate that dark energy with an evolving equation of state provides a compelling alternative to a cosmological constant if data are analysed in a prior-free manner and the weak energy condition is not imposed by hand.

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arXiv2004

Rejoinder to "No Evidence of Dark Energy Metamorphosis", astro-ph/0404468

In a recent paper (astro-ph/0311364) Alam et al argued that the SNe data of Tonry et al 2003 and Barris et al 2003 appear to favour DE which evolves in time, provided no other priors are invoked. (The effect of invoking priors such as the age of the Universe, the values of $H_0$ and $Ω_m$ and CMB/LSS observations could modify this conclusion, as demonstrated in astro-ph/0403687 and other recent papers.) The approach adopted by Alam et al to reconstruct the properties of DE was severely (and, as we shall show below -- unfairly) criticized by Jönsson et al in astro-ph/0404468. In this paper we re-examine the parametrisation used in astro-ph/0311364 and show that, contrary to the claims of Jönsson et al, the results obtained from this reconstruction are robust and therefore representative of the true nature of dark energy.

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arXiv2004

The case for dynamical dark energy revisited

We investigate the behaviour of dark energy using the recently released supernova data of Riess et al ~(2004) and a model independent parameterization for dark energy (DE). We find that, if no priors are imposed on $Ω_{0m}$ and $h$, DE which evolves with time provides a better fit to the SNe data than $Λ$CDM. This is also true if we include results from the WMAP CMB data. From a joint analysis of SNe+CMB, the best-fit DE model has $w_0 < -1$ at the present epoch and the transition from deceleration to acceleration occurs at $z_T = 0.39 \pm 0.03$. However, DE evolution becomes weaker if the $Λ$CDM based CMB results $Ω_{0m} = 0.27 \pm 0.04$, $h = 0.71 \pm 0.06$ are incorporated in the analysis. In this case, $z_T = 0.57 \pm 0.07$. Our results also show that the extent of DE evolution is sensitive to the manner in which the supernova data is sampled.

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