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Related papers: qnm: A Python package for calculating Kerr quasino…

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We revisit the computation of quasinormal modes (QNMs) of the Kerr black hole using a numerical approach exploiting a representation of the Teukolsky equation as a $2D$ elliptic partial differential equation. By combining the hyperboloidal…

General Relativity and Quantum Cosmology · Physics 2025-06-06 Jamil Assaad , Rodrigo Panosso Macedo

Quasinormal mode (QNM) spectra of black holes exhibit two open problems [Conf. Proc. C 0405132, 145 (2004); CQG 26, 163001 (2009)]: (i) the discontinuity in highly damped QNMs between Schwarzschild and Kerr solutions as $a \to 0$, and (ii)…

General Relativity and Quantum Cosmology · Physics 2025-11-20 Changkai Chen , Jiliang Jing , Zhoujian Cao , Mengjie Wang

A program package, which facilitates computations in the framework of Analytic approach to QCD, is developed and described in details. The package includes the explicit expressions for relevant spectral functions calculated up to the…

High Energy Physics - Phenomenology · Physics 2014-11-20 A. V. Nesterenko , C. Simolo

As we enter a new era of quantum technology, it is increasingly important to develop methods to aid in the accurate preparation of quantum states for a variety of materials, matter, and devices. Computational techniques can be used to…

We compute the high frequency quasi-normal modes (QNM) for scalar perturbations of spherically symmetric single horizon black-holes in $(D+2)$-space-time dimensions with generic curvature singularities and having metrics of the form $ds^2 =…

High Energy Physics - Theory · Physics 2010-11-23 Saurya Das , S. Shankaranarayanan

This paper presents the basics of the QQ-onia package, a software based upon the Numerov method which can be used to solve the Schrodinger radial equation using a suitable potential V(r) for the heavy quarkonium system. This package also…

High Energy Physics - Phenomenology · Physics 2009-03-24 Juan-Luis Domenech-Garret , Miguel-Angel Sanchis-Lozano

We present a new Python package that uses the established notion of geometric quantum complexity to numerically compute the difficulty associated with preparing a given unitary transformation on a quantum computer. The numerical procedure…

Quantum convolutional neural networks (QCNNs) offer a promising architecture for near-term quantum machine learning by combining hierarchical feature extraction with modest parameter growth. However, any QCNN operating on classical data…

Quantum Physics · Physics 2025-12-16 Xingyun Feng

Fractional calculus has become widely studied and applied to physical problems in recent years. As a result, many methods for the numerical computation of fractional derivatives and integrals have been defined. However, these algorithms are…

Mathematical Software · Computer Science 2019-12-12 Matthew Adams

This work presents an updated version of the previously released freeware MAN (Modal Analysis of Nanoresonators) [Comput Phys Commun 284, 108627 (2023)], a software package designed to efficiently compute and normalize quasinormal modes…

Optics · Physics 2026-04-17 Thomas Christopoulos , Tong Wu , P. Lalanne

We use physics-informed neural networks (PINNs) to compute the first quasi-normal modes of the Kerr geometry via the Teukolsky equation. This technique allows us to extract the complex frequencies and separation constants of the equation…

General Relativity and Quantum Cosmology · Physics 2024-04-09 Raimon Luna , Juan Calderón Bustillo , Juan José Seoane Martínez , Alejandro Torres-Forné , José A. Font

In this letter, a matrix method is employed to study the scalar quasinormal modes of Kerr as well as Kerr-Sen black holes. Discretization is applied to transfer the scalar perturbation equation into a matrix form eigenvalue problem, where…

General Relativity and Quantum Cosmology · Physics 2017-08-02 Kai Lin , Wei-Liang Qian , Alan B. Pavan , Elcio Abdalla

Quantum computation consists of a quantum state corresponding to a solution, and measurements with some observables. To obtain a solution with an accuracy $\epsilon$, measurements $O(n/\epsilon^2)$ are required, where $n$ is the size of a…

Quantum Physics · Physics 2023-04-13 Yoshiyuki Saito , Xinwei Lee , Dongsheng Cai , Nobuyoshi Asai

We present the Python Tree Tensor Network package (pyTTN) for the evaluation of dynamical properties of closed and open quantum systems that makes use of Tree Tensor Network (TTN), or equivalently the multi-layer multiconfiguration…

Quantum Physics · Physics 2025-03-20 Lachlan P Lindoy , Daniel Rodrigo-Albert , Yannic Rath , Ivan Rungger

QMetro++ is a Python package that provides a set of tools for identifying optimal estimation protocols that maximize quantum Fisher information (QFI). Optimization can be performed for arbitrary configurations of input states,…

Quantum Physics · Physics 2026-02-04 Piotr Dulian , Stanisław Kurdziałek , Rafał Demkowicz-Dobrzański

In general relativity, when two black holes merge they produce a rotating (Kerr) black hole remnant. According to perturbation theory, the remnant emits "ringdown" radiation: a superposition of exponentials with characteristic complex…

General Relativity and Quantum Cosmology · Physics 2025-07-15 Mark Ho-Yeuk Cheung , Emanuele Berti , Vishal Baibhav , Roberto Cotesta

We present an introduction to the Quantum Toolbox in Python (QuTiP) in the context of an undergraduate quantum mechanics class and potential senior research projects. QuTiP provides ready-to-use definitions of standard quantum states and…

Physics Education · Physics 2019-10-01 Andrew M. C. Dawes

Recently, an exact rotating black hole solution in a parity-violating theory of gravity was obtained via a conformal transformation of the Kerr solution in general relativity, with parity-violating effects encoded in the conformal factor.…

General Relativity and Quantum Cosmology · Physics 2026-03-05 Hiroaki W. H. Tahara , Hayato Motohashi , Kazufumi Takahashi , Vicharit Yingcharoenrat

We introduce QSTToolkit, a Python library for performing quantum state tomography (QST) on optical quantum state measurement data. The toolkit integrates traditional Maximum Likelihood Estimation (MLE) with deep learning-based techniques to…

Quantum Physics · Physics 2025-03-19 George FitzGerald , Will Yeadon

We introduce SpectralPINN, a hybrid pseudo-spectral/physics-informed neural network (PINN) solver for Kerr quasinormal modes that targets the Teukolsky equation in both the separated (radial/angular) and joint two-dimensional formulations.…

General Relativity and Quantum Cosmology · Physics 2025-11-21 Alexandre M. Pombo , Lorenzo Pizzuti