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Radio pulsars show remarkable clock-like stability, which make them useful astronomy tools in experiments to test equation of state of neutron stars and detecting gravitational waves using pulsar timing techniques. A brief review of relevant astrophysical experiments is provided in this paper highlighting the current state-of-the-art of these experiments. A program to monitor frequently glitching pulsars with Indian radio telescopes using high cadence observations is presented, with illustrations of glitches detected in this program, including the largest ever glitch in PSR B0531+21. An Indian initiative to discover sub-\\[\\mu \\]Hz gravitational waves, called Indian Pulsar Timing Array (InPTA), is also described briefly, where time-of-arrival uncertainties and post-fit residuals of the order of \\[\\mu \\]s are already achievable, comparable to other international pulsar timing array experiments. While timing the glitches and their recoveries are likely to provide constraints on the structure of neutron stars, InPTA will provide upper limits on sub-\\[\\mu \\]Hz gravitational waves apart from auxiliary pulsar science. Future directions for these experiments are outlined.

We present a detailed analysis of the Vela pulsar's rotational behaviour using approximately 100 months of observational data spanning from September 2016 to January 2025, during which four glitches were identified. Here, we demonstrate the post-glitch recovery of these glitches within the framework of the vortex creep model. We further present the investigation of vortex residuals (the discrepancy between observed values and those predicted by the vortex creep model) by interpreting them in the context of the vortex bending model. In addition, we report a positive correlation between the glitch magnitude and the time to the next glitch, applicable only for the large glitch events observed in the Vela pulsar. Furthermore, we estimate the braking index of the Vela pulsar to be 2.94 \\(\\) 0.55.

Apart from other types of media that offer information in the form of written text, photojournalism often does not enforce a precise evaluation on the audience; however, it merely reveals and highlights the issues, allowing the audience to form their own conclusions. The article then goes on to discuss the difficulties that photography has faced in its documentary capacity since the advent of digital media, as well as the evolving role of photojournalists, highlighting their increasing emphasis on expressing emotional facets of experience. (2010) demonstrates how to use a digital camera's viewfinder to organise a subject, including how to handle the camera correctly, angles, \"law of thirds\" lines, depth of field, background obstacles, and different types of images. The research focuses on photographs taken by international photojournalists that won the Pulitzer Prize for breaking news reporting between 2001 and 2020.The Pulitzer Prize is given to outstanding contributions in writing, fiction, and artistic composition in the United States' newspapers, magazines, and online publications.

We present the results of customised single-pulsar noise analysis of 27 millisecond pulsars from the second data release of the Indian Pulsar Timing Array (InPTA-DR2). We model various stochastic noise sources present in the dataset using stationary Gaussian processes and estimate the noise budget of the InPTA-DR2 using Bayesian inference, involving model selection, Fourier harmonics selection, and parameter estimation for each pulsar. We check the efficacy of our noise characterisation by performing the Anderson-Darling test for Gaussianity on the noise-subtracted residuals. We find that all 11 pulsars with time baseline \\(\\lesssim2.5\\,\\text{yr}\\) show Gaussian residuals and do not have evidence for any red noise process in the optimal model, except for PSR J1944\\(+\\)0907, which shows presence of DM noise. PSRs J0437\\(-\\)4715, J1909\\(-\\)3744 and J1939\\(+\\)2134 show preference for the most complicated noise model, having achromatic and chromatic red noise processes. Only 4 out of 15 pulsars with time baseline \\(\\gtrsim2.5\\,\\text{yr}\\) show significant non-Gaussianity in noise-subtracted residuals. We suspect that this may require more advanced methods to model noise processes properly. A comparative study of six pulsars with data removed near solar conjunctions showed deviations from the parameter estimates obtained with the original dataset, indicating potential bias in red noise processes due to unmodeled solar-wind effects. The results presented in this work remain broadly consistent with the InPTA-DR1 noise budget, with better constraints obtained on noise processes for several pulsars and support for achromatic red noise in PSR J1012\\(+\\)5307 due to the extended time baseline.

Glitches are the observational manifestations of superfluidity inside neutron stars. The aim of this paper is to describe an automated glitch detection pipeline, which can alert the observers on possible real-time detection of rotational glitches in pulsars. Post alert, the pulsars can be monitored at a higher cadence to measure the post-glitch recovery phase. Two algorithms namely, Median Absolute Deviation (MAD) and polynomial regression have been explored to detect glitches in real time. The pipeline has been optimized with the help of simulated timing residuals for both the algorithms. Based on the simulations, we conclude that the polynomial regression algorithm is significantly more effective for real time glitch detection. The pipeline has been tested on a few published glitches. This pipeline is presently implemented at the Ooty Radio Telescope. In the era of upcoming large telescopes like SKA, several hundreds of pulsars will be observed regularly and such a tool will be useful for both real-time detection as well as optimal utilization of observation time for such glitching pulsars.

A pulsar's pulse profile gets broadened at low frequencies due to dispersion along the line of sight or due to multi-path propagation. The dynamic nature of the interstellar medium makes both of these effects time-dependent and introduces slowly varying time delays in the measured times-of-arrival similar to those introduced by passing gravitational waves. In this article, we present an improved method to correct for such delays by obtaining unbiased dispersion measure (DM) measurements by using low-frequency estimates of the scattering parameters. We evaluate this method by comparing the obtained DM estimates with those, where scatter-broadening is ignored using simulated data. A bias is seen in the estimated DMs for simulated data with pulse-broadening with a larger variability for a data set with a variable frequency scaling index, \\(\\alpha\\), as compared to that assuming a Kolmogorov turbulence. Application of the proposed method removes this bias robustly for data with band averaged signal-to-noise ratio larger than 100. We report the measurements of the scatter-broadening time and \\(\\alpha\\) from analysis of PSR J1643\\(-\\)1224, observed with upgraded Giant Metrewave Radio Telescope as part of the Indian Pulsar Timing Array experiment. These scattering parameters were found to vary with epoch and \\(\\alpha\\) was different from that expected for Kolmogorov turbulence. Finally, we present the DM time-series after application of this technique to PSR J1643\\(-\\)1224.

High-precision pulsar timing is highly dependent on precise and accurate modeling of any effects that impact the data. It was shown that commonly used Solar Wind models do not accurately account for variability in the amplitude of the Solar wind on both short and long time scales. In this study, we test and validate a new, cutting-edge Solar wind modeling method included in the enterprise software suite through extended simulations, and we apply it to investigate temporal variability in LOFAR data. Our model testing scheme in itself provides an invaluable asset for pulsar timing array (PTA) experiments. As improperly accounting for the solar wind signature in pulsar data can induce false-positive signals, it is of fundamental importance to include in any such investigations. We employ a Bayesian approach utilizing a continuously varying Gaussian process to model the solar wind referred to as Solar Wind Gaussian Process (SWGP). We conduct noise analysis on eight pulsars from the LOFAR dataset with most pulsars having a timespan of \\( 11\\) years encompassing one full solar activity cycle. Our analysis reveals a strong correlation between the electron density at 1 AU and the ecliptic latitude (ELAT) of the pulsar. Pulsars with \\(|ELAT|< 3^\\) exhibit significantly higher average electron densities. We observe distinct temporal patterns in electron densities in different pulsars. In particular, pulsars within \\(|ELAT|< 3^\\) exhibit similar temporal variations, while the electron densities of those outside this range correlate with the solar activity cycle. The continuous variability in electron density offered in this model represents a substantial improvement over previous models, which assume a single value for piece-wise bins of time. This advancement holds promise for solar wind modeling in future International Pulsar Timing Array data combinations.

The Indian Pulsar Timing Array (InPTA) collaboration has recently made its first official data release (DR1) for a sample of 14 pulsars using 3.5 years of uGMRT observations. We present the results of single-pulsar noise analysis for each of these 14 pulsars using the InPTA DR1. For this purpose, we consider white noise, achromatic red noise, dispersion measure (DM) variations, and scattering variations in our analysis. We apply Bayesian model selection to obtain the preferred noise models among these for each pulsar. For PSR J1600\\(-\\)3053, we find no evidence of DM and scattering variations, while for PSR J1909\\(-\\)3744, we find no significant scattering variations. Properties vary dramatically among pulsars. For example, we find a strong chromatic noise with chromatic index \\(\\) 2.9 for PSR J1939+2134, indicating the possibility of a scattering index that doesn't agree with that expected for a Kolmogorov scattering medium consistent with similar results for millisecond pulsars in past studies. Despite the relatively short time baseline, the noise models broadly agree with the other PTAs and provide, at the same time, well-constrained DM and scattering variations.

We search for a stochastic gravitational wave background (SGWB) generated by a network of cosmic strings using six millisecond pulsars from Data Release 2 (DR2) of the European Pulsar Timing Array (EPTA). We perform a Bayesian analysis considering two models for the network of cosmic string loops, and compare it to a simple power-law model which is expected from the population of supermassive black hole binaries. Our main strong assumption is that the previously reported common red noise process is a SGWB. We find that the one-parameter cosmic string model is slightly favored over a power-law model thanks to its simplicity. If we assume a two-component stochastic signal in the data (supermassive black hole binary population and the signal from cosmic strings), we get a \\(95\\%\\) upper limit on the string tension of \\(\\log_{10}(G\\mu) < -9.9\\) (\\(-10.5\\)) for the two cosmic string models we consider. In extended two-parameter string models, we were unable to constrain the number of kinks. We test two approximate and fast Bayesian data analysis methods against the most rigorous analysis and find consistent results. These two fast and efficient methods are applicable to all SGWBs, independent of their source, and will be crucial for analysis of extended data sets.

Pulsar Timing Array experiments probe the presence of possible scalar or pseudoscalar ultralight dark matter particles through decade-long timing of an ensemble of galactic millisecond radio pulsars. With the second data release of the European Pulsar Timing Array, we focus on the most robust scenario, in which dark matter interacts only gravitationally with ordinary baryonic matter. Our results show that ultralight particles with masses \\(10^{-24.0}~\\text{eV} \\lesssim m \\lesssim 10^{-23.3}~\\text{eV}\\) cannot constitute \\(100\\%\\) of the measured local dark matter density, but can have at most local density \\(\\rho\\lesssim 0.3\\) GeV/cm\\(^3\\).