Related papers: PYESSENCE - Generalised Coupled Quintessence Linea…
We present the largest set of N-body and hydrodynamical simulations to date for cosmological models featuring a direct interaction between the Dark Energy (DE) scalar field, responsible of the observed cosmic acceleration, and the Cold Dark…
Inference on time series data is a common requirement in many scientific disciplines and internet of things (IoT) applications, yet there are few resources available to domain scientists to easily, robustly, and repeatably build such…
We bring forward a generalized pressure dark energy (GPDE) model to explore the evolution of the universe. This model has covered three common pressure parameterization types and can be reconstructed as quintessence and phantom scalar…
SparseChem provides fast and accurate machine learning models for biochemical applications. Especially, the package supports very high-dimensional sparse inputs, e.g., millions of features and millions of compounds. It is possible to train…
In this work we propose a simple general parametrization scheme of the Hubble parameter for the scalar field dark energy models. In our approach it is possible to incorporate both the quintessence and phantom scalar field in a single…
Deep learning has achieved remarkable success in diverse applications; however, its use in solving partial differential equations (PDEs) has emerged only recently. Here, we present an overview of physics-informed neural networks (PINNs),…
The combination of machine learning and physical laws has shown immense potential for solving scientific problems driven by partial differential equations (PDEs) with the promise of fast inference, zero-shot generalisation, and the ability…
TeNPy (short for 'Tensor Network Python') is a python library for the simulation of strongly correlated quantum systems with tensor networks. The philosophy of this library is to achieve a balance of readability and usability for…
Recently \citet{PEDE:2019ApJ} proposed a phenomenologically emergent dark energy (PEDE) which consider that the dark energy density evolves as $\widetilde{\Omega}_{\rm{DE}}(z)\,=\,\Omega_{\rm{DE,0}}\left[ 1 - {\rm{tanh}}\left(…
Reliable parameter extraction from experimental data is central to quantitative analysis in spectroscopy, diffraction, photoluminescence, chromatography, microscopy, and time-resolved measurements. We present FitED, a Python-based desktop…
Quintessence, a scalar field model, has been proposed to account for the acceleration of the Universe at present. We discuss how accurately quintessence models are discriminated by future cosmological surveys, which include experiments of…
The standard cosmological model currently in force, aka $\Lambda$CDM, has been plagued with a variety of tensions in the last decade or so, which puts it against the wall. At the core of the $\Lambda$CDM we have a rigid cosmological term,…
This paper introduces pycvxset, a new Python package to manipulate and visualize convex sets. We support polytopes and ellipsoids, and provide user-friendly methods to perform a variety of set operations. For polytopes, pycvxset supports…
Dark energy as a quintessence component causes a typical modification of the background cosmic expansion, which in addition to its clustering properties, can leave a potentially distinctive signature on large scale structures. Many previous…
Analysis of emission lines in gaseous nebulae yields direct measures of physical conditions and chemical abundances and is the cornerstone of nebular astrophysics. Although the physical problem is conceptually simple, its practical…
Eisen is an open source python package making the implementation of deep learning methods easy. It is specifically tailored to medical image analysis and computer vision tasks, but its flexibility allows extension to any application. Eisen…
Mechanistic models are important tools to describe and understand biological processes. However, they typically rely on unknown parameters, the estimation of which can be challenging for large and complex systems. We present pyPESTO, a…
PySensors is a Python package for selecting and placing a sparse set of sensors for reconstruction and classification tasks. In this major update to PySensors, we introduce spatially constrained sensor placement capabilities, allowing users…
In the context of the induced matter theory of gravity, we investigate the possibility of deriving a 4D quintessential scenario where an interaction between dark energy and dark matter is allowed, and the dark energy component is modeled by…
Recently, we introduced the notion of "tracker fields," a form of quintessence which has an attractor-like solution. Using this concept, we showed how to construct models in which the ratio of quintessence to matter densities today is…