arXiv subjects

Soumen Roy

Publications and source records attributed to Soumen Roy.

At least 37 records · Page 2Linked to original sources

arXiv2023

Unraveling information about supranuclear-dense matter from the complete binary neutron star coalescence process using future gravitational-wave detector networks

Gravitational waves provide us with an extraordinary tool to study the matter inside neutron stars. In particular, the postmerger signal probes an extreme temperature and density regime and will help reveal information about the equation of state of supranuclear-dense matter. Although current detectors are most sensitive to the signal emitted by binary neutron stars before the merger, the upgrades of existing detectors and the construction of the next generation of detectors will make postmerger detections feasible. For this purpose, we present a new analytical, frequency-domain model for the inspiral-merger-postmerger signal emitted by binary neutron stars systems. The inspiral and merger part of the signals are modeled with IMRPhenomD_NRTidalv2, and we describe the main emission peak of postmerger with a three-parameter Lorentzian, using two different approaches: one in which the Lorentzian parameters are kept free, and one in which we model them via quasi-universal relations. We test the performance of our new complete waveform model in parameter estimation analyses, studying simulated signals obtained from both our developed model and by injecting numerical relativity waveforms. We investigate the performance of different detector networks to determine the improvement that future detectors will bring to our analysis. We consider Advanced LIGO+ and Advanced Virgo+, KAGRA, and LIGO-India. We also study the possible impact of a detector with high sensitivity in the kilohertz band like NEMO, and finally we compare these results to the ones we obtain with third-generation detectors, the Einstein Telescope and the Cosmic Explorer.

gr-qc↗

arXiv2022

Nonorthogonal wavelet transformation for reconstructing gravitational wave signals

Detections of gravitational-wave signals from compact binary coalescences have enabled us to study extreme astrophysical phenomena and explore fundamental physics. A crucial requisite for these studies is to have accurate signal models with characteristic morphologies, which have been challenging for many decades, and researchers are still endeavoring to incorporate important physics. Therefore, morphology-independent methods have been developed for identifying a signal and its reconstruction. The reconstructed signal allows us to test the agreement between the observed signal and the waveform posterior samples from parameter estimation. These methods model observed signals using a nearly orthogonal wavelet basis in the frame of continuous wavelet transformation. Here, we propose log-uniform scales to construct the wavelets, which are are highly redundant (nonorthogonal) compared to the conventional octave scales but more efficient for reconstructing the signals at high frequencies. And we introduce a semi-model-dependent reconstruction method using the posterior samples of the events, where we model the signal using Gabor-Morlet wavelets with log-uniform scales. We demonstrate the ability to detect deviation using a numerical simulation of an eccentric binary black hole merger, where the signal in the data does not belong to the search template waveform manifold. Finally, we apply this method to each binary black hole merger event in GWTC-1. We have found that the signal produced by the GW150914 event has 96% agreement with the waveform posterior samples. As the detector sensitivity improves and the detected population of black hole mergers grows, we expect the proposed method will provide even stronger tests.

gr-qc↗

arXiv2022

Beyond general relativity: designing a template-based search for exotic gravitational wave signals

Accurate waveform models describing the complete evolution of compact binaries are crucial for the maximum likelihood detection framework, testing the predictions of General Relativity (GR) and investigating the possibility of an alternative theory of gravity. Deviations from GR could manifest in subtle variations of the numerical value of the GW signal's post-Newtonian (PN) phasing coefficients. Once the search pipelines confirm an unambiguous signal detection, deviations of the signal phasing coefficients at various PN orders are routinely measured and reported. As the search templates themselves do not incorporate any deviations from GR, they may miss astrophysical signals carrying a significant departure from general relativity. We present a parametrized template-based search for exotic gravitational-wave signals beyond General Relativity by incorporating deviations to the signal's phasing coefficients at different post-Newtonian orders in the search templates. We present critical aspects of the new search, such as improvements in search volume and its effect on various parts of the parameter space. In particular, we demonstrate a factor x2 increase in search sensitivity (at a fixed false-alarm rate) to beyond-GR exotic signals by using search templates that admit a range of departures from general relativity. We also present the results from a re-analysis of the 10-days long duration of LIGO's O1 data, including the epoch of the GW150914 event, highlighting the differences from a standard search. We indicate several directions for future research, including ways of making the proposed new search computationally more efficient.

gr-qc↗

arXiv2022

Testing general relativity using higher-order modes of gravitational waves from binary black holes

Recently, strong evidence was found for the presence of higher-order modes in the gravitational wave signals GW190412 and GW190814, which originated from compact binary coalescences with significantly asymmetric component masses. This has opened up the possibility of new tests of general relativity by looking at the way in which the higher-order modes are related to the basic signal. Here we further develop a test which assesses whether the amplitudes of sub-dominant harmonics are consistent with what is predicted by general relativity. To this end we incorporate a state-of-the-art waveform model with higher-order modes and precessing spins into a Bayesian parameter estimation and model selection framework. The analysis methodology is tested extensively through simulations. We investigate to what extent deviations in the relative amplitudes of the harmonics will be measurable depending on the properties of the source, and we map out correlations between our testing parameters and the inclination of the source with respect to the observer. Finally, we apply the test to GW190412 and GW190814, finding no evidence for violations of general relativity.

gr-qc↗

arXiv2021

Scale-free networks may not necessarily witness cooperation

Networks with a scale-free degree distribution are widely thought to promote cooperation in various games. Herein, by studying the well-known prisoner's dilemma game, we demonstrate that this need not necessarily be true. For the very same degree sequence and degree distribution, we present a variety of possible behaviour. We reassess the perceived importance of hubs in a network towards the maintenance of cooperation. We also reevaluate the dependence of cooperation on network clustering and assortativity.

physics.soc-ph↗

arXiv2021

Mass testing and proactiveness affect epidemic spreading

The detection and management of diseases become quite complicated when pathogens contain asymptomatic phenotypes amongst their ranks, as evident during the recent COVID-19 pandemic. Spreading of diseases has been studied extensively under the paradigm of Susceptible - Infected - Recovered - Deceased (SIRD) dynamics. Various game-theoretic approaches have also addressed disease spread, many of which consider S, I, R, and D as strategies rather than as states. Remarkably, most studies from the above approaches do not account for the distinction between the symptomatic or asymptomatic aspect of the disease. It is well-known that precautionary measures like washing hands, wearing masks and social distancing significantly mitigate the spread of many contagious diseases. Herein, we consider the adoption of such precautions as strategies and treat S, I, R, and D as states. We also attempt to capture the differences in epidemic spreading arising from symptomatic and asymptomatic diseases on various network topologies. Through extensive computer simulations, we examine that the cost of maintaining precautionary measures as well as the extent of mass testing in a population affects the final fraction of socially responsible individuals. We observe that the lack of mass testing could potentially lead to a pandemic in case of asymptomatic diseases. Network topology also seems to play an important role. We further observe that the final fraction of proactive individuals depends on the initial fraction of both infected as well as proactive individuals. Additionally, edge density can significantly influence the overall outcome. Our findings are in broad agreement with the lessons learnt from the ongoing COVID-19 pandemic.

physics.soc-ph↗

arXiv2021

Topology dependent payoffs can lead to escape from prisoner's dilemma

The maintenance of cooperation in the presence of spatial restrictions has been studied extensively. It is well-established that the underlying graph topology can significantly influence the outcome of games on graphs. Maintenance of cooperation could be difficult, especially in the absence of spatial restrictions. The evolution of cooperation would naturally depend on payoffs. However, payoffs are generally considered to be invariant in a given game. A natural yet unexplored question is whether the topology of the underlying structures on which the games are played, possesses no role whatsoever in the determination of payoffs. Herein, we introduce the notion of cooperator graphs and defector graphs as well as a new form of game payoff, which is weakly dependent on the underlying network topology. These concepts are inspired by the well-known microbial phenomenon of quorum sensing. We demonstrate that even with such a weak dependence, the fundamental game dynamics and indeed the very nature of the game may be altered. Such changes in the nature of a game have been well-reported in theoretical and experimental studies.

physics.soc-ph↗

arXiv2021

An Introduction to Fluid Dynamics and Numerical Solution of Shock Tube Problem by Using Roe Solver

The study of fluids has been a topic of intense research for several hundred years. Over the years, this has further increased due to improved computational facility, which makes it easy to numerically simulate the fluid dynamics, which was beyond the analytical reach before. In this project, we discuss the general transport theorem for moving control volume system, apply this theory to control mass system which gives the continuity equation, and on momentum conservation from which we get the Navier-Stokes equation and energy conservation. By approximating the three equations for the ideal gas flow, we get one dimensional Euler equation. These equations are non-linear, and their analytic solutions are highly non-trivial. We will use Riemann solvers to get the exact solution numerically. In this project, we have considered only the Sod's Shock Tube problem. Finally, we focus on the exact and approximate solution of density, pressure, velocity, entropy, and Mach number using Python code.

physics.flu-dyn↗

arXiv2021

Unveiling the spectrum of inspiralling binary black holes

The higher-multipoles of gravitational wave signals from coalescing compact binaries play a vital role in the accurate reconstruction of source properties, bringing about a deeper and nuanced understanding of fundamental physics and astrophysics. Their effect is most pronounced in systems with asymmetric masses having an orbital geometry that is not face-on. The detection of higher-multipoles of GW signals from any single, isolated merger event is challenging, as there is much less power in comparison to the dominant quadrupole mode. In this paper, we present a new method for their detection by combining multiple events observed in interferometric gravitational wave detectors. Sub-dominant modes present in (the inspiral part of) the signal from separate events are stacked using time-frequency spectrogram of the data. We demonstrate that this procedure enhances the signal-to-noise ratio of the higher-multipole components and thereby leads to increased chances of their detection. From Monte-Carlo simulations, we estimate that a combination of $\sim 100$ events observed in two-detector coincidence can lead to the detection of the higher-multipole components with a $\geq$ 95\% detection probability. The advanced-LIGO detectors are expected to record these many binary black hole merger events within a month of operation at design sensitivity. We also present results from the analysis of data from O1 and O2 science runs containing previously detected events using our new method.

gr-qc↗

arXiv2018

Effectual gravitational-wave template banks for coalescing compact binaries using a hybrid placement algorithm

Recent discoveries of gravitational wave (GW) signals from astrophysical compact binary systems of neutron stars and black holes have firmly established them as prime sources for advanced GW detectors. Theoretical templates of expected signals from such systems have been used to filter the detector data using the \emph{matched filtering} technique. An efficient grid over the parameter space at a fixed minimal match has a direct impact on improving the computational efficiency of these searches. We present the construction of three-dimensional template banks (in component masses and an effective spin parameter) by incorporating several new optimizations to the hybrid geometric-random template placement algorithm that we proposed recently. These optimizations allow us to create more efficient template banks in future compact binary searches by shrinking the hybrid banks by $\sim 34\%$ in comparison to the basic algorithm. Such optimized banks are also found to be $\sim 22\%$ smaller than the optimized stochastic bank constructed over a nominal range of parameters. We also construct an explicit hybrid template bank with parameters identical to the `uber-bank' used in the recently-concluded CBC searches in the second observation run of the Advanced LIGO and Virgo detectors. We demonstrate a reduction of more than 53,000 templates over the stochastic template bank at a near-identical coverage as determined by fitting factor studies. A computationally efficient technique for semi-numerical calculation of the parameter space metric, applicable for aligned-spin waveform family, is also outlined. The resulting hybrid template banks can be generated much faster in comparison to the stochastic banks, and are ready to be used in the upcoming observation runs of Advanced LIGO and Virgo.

gr-qc↗

arXiv2017

Hybrid geometric-random template placement algorithm for gravitational wave searches from compact binary coalescences

Astrophysical compact binary systems consisting of neutron stars and blackholes are an important class of gravitational wave (GW) sources for advanced LIGO detectors. Accurate theoretical waveform models from the inspiral, merger and ringdown phases of such systems, are used to filter detector data under the template based matched filtering paradigm. An efficient grid over the parameter space at a fixed minimal match has a direct impact on the overall time taken by these searches. We present a new hybrid geometric-random template placement algorithm for signals described by two masses and one spin magnitude parameters. Such template banks could potentially be used in GW searches from binary neutron stars and neutron star-blackhole systems. The template placement is robust and is able to automatically accommodate curvature and boundary effects with no fine tuning. We also compare these banks against vanilla-stochastic template banks and show that while both are equally efficient in the fitting-factor sense, the bank sizes are $\sim 25 \%$ larger in the stochastic method. Further, we show that the generation of the proposed hybrid banks can be sped-up by nearly an order of magnitude over the stochastic bank. Generic issues related to optimal implementation are discussed in detail. These improvements are expected to directly reduce the computational cost of gravitational wave searches.

gr-qc↗

arXiv2015

Using complex networks towards information retrieval and diagnostics in multidimensional imaging

We present a fresh and broad yet simple approach towards information retrieval in general and diagnostics in particular by applying the theory of complex networks on multidimensional, dynamic images. We demonstrate a successful use of our method with the time series generated from high content thermal imaging videos of patients suffering from the aqueous deficient dry eye (ADDE) disease. Remarkably, network analyses of thermal imaging time series of contact lens users and patients upon whom Laser-Assisted in situ Keratomileusis (Lasik) surgery has been conducted, exhibit pronounced similarity with results obtained from ADDE patients. We also propose a general framework for the transformation of multidimensional images to networks for futuristic biometry. Our approach is general and scalable to other fluctuation-based devices where network parameters derived from fluctuations, act as effective discriminators and diagnostic markers.

cs.IR↗

arXiv2015

Slow poisoning and destruction of networks: Edge proximity and its implications for biological and infrastructure networks

We propose a network metric, edge proximity, ${\cal P}_e$, which demonstrates the importance of specific edges in a network, hitherto not captured by existing network metrics. The effects of removing edges with high ${\cal P}_e$ might initially seem inconspicuous but are eventually shown to be very harmful for networks. Compared to existing strategies, the removal of edges by ${\cal P}_e$ leads to a remarkable increase in the diameter and average shortest path length in undirected real and random networks till the first disconnection and well beyond. ${\cal P}_e$ can be consistently used to rupture the network into two nearly equal parts, thus presenting a very potent strategy to greatly harm a network. Targeting by ${\cal P}_e$ causes notable efficiency loss in U.S. and European power grid networks. ${\cal P}_e$ identifies proteins with essential cellular functions in protein-protein interaction networks. It pinpoints regulatory neural connections and important portions of the neural and brain networks, respectively. Energy flow interactions identified by ${\cal P}_e$ form the backbone of long food web chains. Finally, we scrutinize the potential of ${\cal P}_e$ in edge controllability dynamics of directed networks.

physics.soc-ph↗

arXiv2012

Key to Network Controllability

Liu et al recently proposed a minimum number of driver nodes needed to obtain full structural controllability over a directed network. Driver nodes are unmatched nodes, from which there are directed paths to all matched nodes. Their most important assertion is that a system's controllability is to a great extent encoded by the underlying network's degree distribution, $P(k_{in}, k_{out})$. Is the controllability of a network decided almost completely by the immediate neighbourhood of a node, while, even slightly distant nodes play no role at all? Motivated by the above question, in this communication, we argue that an effective understanding of controllability in directed networks can be reached using distance based measures of closeness centrality and betweenness centrality and may not require the knowledge of local connectivity measures like in-degree and out-degree.

physics.soc-ph↗

arXiv2012

Efficient scheduling using complex networks

We consider the problem of efficiently scheduling the production of goods for a model steel manufacturing company. We propose a new approach for solving this classic problem, using techniques from the statistical physics of complex networks in conjunction with depth-first search to generate a successful, flexible, schedule. The schedule generated by our algorithm is more efficient and outperforms schedules selected at random from those observed in real steel manufacturing processes. Finally, we explore whether the proposed approach could be beneficial for long term planning.

physics.soc-ph↗

arXiv2012

Systems biology beyond degree, hubs and scale-free networks: the case for multiple metrics in complex networks

Modeling and topological analysis of networks in biological and other complex systems, must venture beyond the limited consideration of very few network metrics like degree, betweenness or assortativity. A proper identification of informative and redundant entities from many different metrics, using recently demonstrated techniques, is essential. A holistic comparison of networks and growth models is best achieved only with the use of such methods.

q-bio.QM↗

arXiv2010

Resilience and rewiring of the passenger airline networks in the United States

The air transportation network, a fundamental component of critical infrastructure, is formed from a collection of individual air carriers, each one with a methodically designed and engineered network structure. We analyze the individual structures of the seven largest passenger carriers in the USA and find that networks with dense interconnectivity, as quantified by large k-cores for high values of k, are extremely resilient to both targeted removal of airports (nodes) and random removal of flight paths paths (edges). Such networks stay connected and incur minimal increase in an heuristic travel time despite removal of a majority of nodes or edges. Similar results are obtained for targeted removal based on either node degree or centrality. We introduce network rewiring schemes that boost resilience to different levels of perturbation while preserving total number of flight and gate requirements. Recent studies have focused on the asymptotic optimality of hub-and-spoke spatial networks under normal operating conditions, yet our results indicate that point-to-point architectures can be much more resilient to perturbations.

physics.soc-ph↗

arXiv2009

Strong associations between microbe phenotypes and their network architecture

Understanding the dependence and interplay between architecture and function in biological networks has great relevance to disease progression, biological fabrication and biological systems in general. We propose methods to assess the association of various microbe characteristics and phenotypes with the topology of their networks. We adopt an automated approach to characterize metabolic networks of 32 microbial species using 11 topological metrics from complex networks. Clustering allows us to extract the indispensable, independent and informative metrics. Using hierarchical linear modeling, we identify relevant subgroups of these metrics and establish that they associate with microbial phenotypes surprisingly well. This work can serve as a stepping stone to cataloging biologically relevant topological properties of networks and towards better modeling of phenotypes. The methods we use can also be applied to networks from other disciplines.

q-bio.QM↗