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We explore the anomaly detection framework based on Normalizing Flows (NF) models introduced in \cite{PhysRevC.106.065802} to detect the presence of a large (destabilising) dense matter phase transition in neutron star (NS) observations of…

Nuclear Theory · Physics 2024-09-27 Valéria Carvalho , Márcio Ferreira , Constança Providência , Michał Bejger

Astrophysical observations of neutron stars probe the structure of dense nuclear matter and have the potential to reveal phase transitions at high densities. Most recent analyses are based on parametrized models of the equation of state…

High Energy Astrophysical Phenomena · Physics 2025-05-13 Reed Essick , Isaac Legred , Katerina Chatziioannou , Sophia Han , Philippe Landry

We develop methodology and theory for the detection of a phase transition in a time-series of high-dimensional random matrices. In the model we study, at each time point \( t = 1,2,\ldots \), we observe a deformed Wigner matrix \(…

Statistics Theory · Mathematics 2025-07-08 Nina Dörnemann , Piotr Kokoszka , Tim Kutta , Sunmin Lee

The accurate detection of small deviations in given density matrices is important for quantum information processing. Here we propose a new method based on the concept of data mining. We demonstrate that the proposed method can more…

Quantum Physics · Physics 2015-06-18 Satoshi Hara , Takafumi Ono , Ryo Okamoto , Takashi Washio , Shigeki Takeuchi

In recent years, researchers have become increasingly interested in understanding how dark matter affects neutron stars, helping them to better understand complex astrophysical phenomena. In this paper, we delve deeper into this problem by…

High Energy Physics - Phenomenology · Physics 2024-01-17 Prashant Thakur , Tuhin Malik , T. K. Jha

In this letter, we present a new, weakly model-dependent, test for ``standard" equations of state (EoS) models that disfavor sharp and strong phase-transitions, by using neutron star mass and radius observations. We show the radii of two…

High Energy Astrophysical Phenomena · Physics 2024-09-24 Zidu Lin , Andrew Steiner

We discuss a methodology of machine learning to deduce the neutron star equation of state from a set of mass-radius observational data. We propose an efficient procedure to deal with a mapping from finite data points with observational…

Nuclear Theory · Physics 2018-08-08 Yuki Fujimoto , Kenji Fukushima , Koichi Murase

With central densities as high as 5-10 times the nuclear saturation density, neutron stars exhibit extreme conditions that cannot be observed elsewhere. They are ideal astrophysical laboratories for probing the composition and properties of…

Solar and Stellar Astrophysics · Physics 2019-09-04 Sophia Han

The internal composition of neutron stars is still an open issue in astrophysics. Their innermost regions are impervious to light propagation and gravitational waves mostly carry global aspects of stars, meaning that only indirect…

High Energy Astrophysical Phenomena · Physics 2022-06-29 Jonas P. Pereira , Michał Bejger , J. Leszek Zdunik , Paweł Haensel

Understanding the equation of state of dense QCD matter remains a major challenge in both nuclear physics and astrophysics. Neutron star observations from electromagnetic and gravitational wave spectra provide critical insights into the…

Nuclear Theory · Physics 2023-03-31 Plamen G. Krastev

Performing Bayesian inference on quarkyonic equation-of-state models for neutron star matter, we find they satisfy all current astrophysical observations, thus reinforcing the argument for the use of such neutron star matter…

Nuclear Theory · Physics 2026-01-07 Probit J Kalita , Tuhin Malik , Tianqi Zhao , Bharat Kumar , James M. Lattimer

We develop a new method to measure neutron star parameters and derive constraints on the equation of state of dense matter by fitting the frequencies of simultaneous Quasi Periodic Oscillation modes observed in the X-ray flux of accreting…

High Energy Astrophysical Phenomena · Physics 2020-09-02 Andrea Maselli , George Pappas , Paolo Pani , Leonardo Gualtieri , Sara Motta , Valeria Ferrari , Luigi Stella

Identifying phase transitions and classifying phases of matter is central to understanding the properties and behavior of a broad range of material systems. In recent years, machine-learning (ML) techniques have been successfully applied to…

Disordered Systems and Neural Networks · Physics 2023-06-23 Julian Arnold , Frank Schäfer

At supranuclear densities, explored in the core of neutron stars, a strong phase transition from hadronic matter to more exotic forms of matter might be present. To test this hypothesis, binary neutron-star mergers offer a unique…

High Energy Astrophysical Phenomena · Physics 2020-10-02 Peter T. H. Pang , Tim Dietrich , Ingo Tews , Chris Van Den Broeck

One of the primary science goals of the next generation of hard X-ray timing instruments is to determine the equation of state of the matter at supranuclear densities inside neutron stars, by measuring the radius of neutron stars with…

The trace anomaly of dense matter, $\Delta \equiv 1/3 - P/\varepsilon$, defined through the ratio $w \equiv P/\varepsilon$ of pressure $P$ to energy density $\varepsilon$, quantifies deviations from conformal symmetry and provides a…

Nuclear Theory · Physics 2026-05-18 Bao-An Li

This book chapter explores key aspects of neutron stars, pulsar glitches, tidal deformability, fast pulsars, the equation of state, and strange quark matter stars. Challenges in directly measuring neutron star radius have led to reliance on…

Neutron stars are the densest, directly observable stellar objects in the universe and serve as unique astrophysical laboratories to study the behavior of matter under extreme physical conditions. This book chapter is devoted to describing…

High Energy Astrophysical Phenomena · Physics 2018-06-11 N. Degenaar , V. F. Suleimanov

Neutron stars explore matter at the highest densities in the universe such that their inner cores might undergo a phase transition from hadronic to exotic phases, e.g., quark matter. Such a transition could be associated with non-trivial…

Nuclear Theory · Physics 2023-03-22 Rahul Somasundaram , Ingo Tews , Jérôme Margueron

We propose a systematic methodology to identify the topological phase transition through a self-supervised machine learning model, which is trained to correlate system parameters to the non-local observables in time-of-flight experiments of…

Quantum Gases · Physics 2021-09-01 Chi-Ting Ho , Daw-Wei Wang
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