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Locating sources of a high energy cosmic ray extensive air shower using HiSPARC data

Aziz et al. | Oct 24, 2023

Locating sources of a high energy cosmic ray extensive air shower using HiSPARC data

Using the data provided by the University of Twente High School Project on Astrophysics Research with Cosmics (HiSPARC), an analysis of locations for possible high-energy cosmic ray air showers was conducted. An example includes an analysis conducted of the high-energy rain shower recorded in January 2014 and the use of Stellarium™ to discern its location.

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Deep learning for pulsar detection: Investigating hyperparameter effects on TensorFlow classification accuracy

Upadhyay et al. | Jan 31, 2026

Deep learning for pulsar detection: Investigating hyperparameter effects on TensorFlow classification accuracy

This study investigates how the hyperparameters epochs and batch size affect the classification accuracy of a convolutional neural network (CNN) trained on pulsar candidate data. Our results reveal that accuracy improves with increasing number of epochs and smaller batch sizes, suggesting that with optimized hyperparameters, high accuracy may be achievable with minimal training. These findings offer insights that could help create more efficient machine learning classification models for pulsar signal detection, with the potential of accelerating pulsar discovery and advancing astrophysical research.

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Determining the Hubble constant through the analysis of Abell clusters

Lee et al. | Sep 28, 2026

Determining the Hubble constant through the analysis of  Abell clusters
Image credit: NASA Hubble Space Telescope

Galaxy clusters offer several advantages for measuring H0 compared to traditional methods, such as Cepheid variables or Type Ia supernovae. Unlike individual stars or supernovae, clusters are less affected by local variations in stellar population or interstellar medium properties, providing a more stable and consistent measure over large cosmological distances. This work proposes using galaxy clusters as an alternative method for determining the H0. It provides an independent perspective on the H0 debate and contribute to ongoing efforts to reconcile the differing values obtained from the other two measurements.

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Measuring the effect of early universe dark matter on the primordial values of helium-4 and deuterium

Pal et al. | Apr 29, 2026

Measuring the effect of early universe dark matter on the primordial values of helium-4 and deuterium

Recent observations by the “Extremely Metal-Poor Representatives Explored by the Subaru Survey” (EMPRESS) collaboration found normal deuterium levels but unexpectedly low helium-4, challenging current cosmological theories. This study used simulations with the PRyMordial package to test whether dark matter particles interacting with neutrinos in the early universe could explain the discrepancy.

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The journey to Proxima Centauri b

Ramaswamy et al. | Apr 01, 2024

The journey to Proxima Centauri b
Image credit: The authors

Someday, rockets from Earth may be launched towards worlds beyond our solar system. But will these rockets be able to reach their destination within a human lifetime? Ramaswamy and Giovinazzi simulate rocket launches to an Earth-like exoplanet to uncover whether it's physically possible to complete the journey within a lifetime.

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Photometric analysis and light curve modeling of apparent transient 2020pni

Arora et al. | Oct 07, 2022

Photometric analysis and light curve modeling of apparent transient 2020pni

Supernovas are powerful explosions that result from gravitational collapse of a massive star. Using photometric analysis Arora et al. set out to investigate whether 2020pni (located in galaxy UGC 9684) was a supernova. They were ultimately able to identify 2020pni as a Type II-L supernova and determine it's distance from earth.

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Using machine learning to detect outliers of red clump stars

Meng et al. | Oct 10, 2026

Using machine learning to detect outliers of red clump stars

Machine learning offers a powerful way to analyze large astronomical datasets and identify stars with unusual properties. In this study, students used Extreme Gradient Boosting and Isolation Forest models to investigate why some red clump stars deviate from their expected luminosities. Their results show that stellar age plays a much stronger role than metallicity in driving luminosity variation, and the models successfully detected outlier stars that may affect distance measurements in galactic studies.

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