Trending Research
Promoting global stability in data-driven models of quadratic nonlinear dynamics
Second, we illustrate how to modify the objective function in machine learning algorithms to promote globally stable models, with implications for the modeling of fluid and plasma flows.
Fluid Dynamics Computational Physics Plasma Physics
The agglomeration and dispersion dichotomy of human settlements on Earth
To explain the observed spatial patterns, we also propose a model that combines two agglomeration forces and simulates human settlements' historical growth.
Physics and Society
Investigating Quantum Approximate Optimization Algorithms under Bang-bang Protocols
google-research/google-research
•
•
The quantum approximate optimization algorithm (QAOA) is widely seen as a possible usage of noisy intermediate-scale quantum (NISQ) devices.
Quantum Physics
A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data
lululxvi/deepxde
•
•
Neural operators can learn nonlinear mappings between function spaces and offer a new simulation paradigm for real-time prediction of complex dynamics for realistic diverse applications as well as for system identification in science and engineering.
Computational Physics
Machine Learning and Quantum Devices
FlorianMarquardt/machine-learning-for-physicists
•
•
These brief lecture notes cover the basics of neural networks and deep learning as well as their applications in the quantum domain, for physicists without prior knowledge.
Quantum Physics
Visualizing and Interpreting Unsupervised Solar Wind Classifications
The manual and semi-automatic classification of millions of hours of solar wind data from multiple missions can be replaced by automatic algorithms that can discover, in mountains of multi-dimensional data, the real differences in the solar wind properties.
Space Physics Solar and Stellar Astrophysics
Build your own tensor network library: DMRjulia I. Basic library for the density matrix renormalization group
The code can be used as an educational tool to understand how tensor network computations are done in the context of entanglement renormalization or as a template for other codes in low level languages.
Quantum Physics
Optimal synthesis into fixed XX interactions
We describe an optimal procedure, as well as its efficient software implementation, for exact and approximate synthesis of two-qubit unitary operations into any prescribed discrete family of XX-type interactions and local gates.
Quantum Physics Symplectic Geometry 81Q99, 53D45
PyPSA: Python for Power System Analysis
In this paper the basic functionality of PyPSA is described, including the formulation of the full power flow equations and the multi-period optimisation of operation and investment with linear power flow equations.
Physics and Society
OpenQASM 3: A broader and deeper quantum assembly language
In principle, any quantum computation could be described using OpenQASM 2, but there is a need to describe a broader set of quantum circuits beyond the language of qubits and gates.
Quantum Physics