QuTiP: An open-source Python framework for the dynamics of open quantum systems

By J. Johansson, Paul D. Nation, Franco Nori. Computer Physics Communications, 2011

2,201 citations recorded by the source corpus.

Article history: We present an object-oriented open-source framework for solving the dynamics of open quantum systems written in Python. Arbitrary Hamiltonians, including time-dependent systems, may be built up from operators and states defined by a quantum object class, and then passed on to a choice of master equation or Monte Carlo solvers. We give an overview of the basic structure for the framework before detailing the numerical simulation of open system dynamics. Several examples are given to illustrate the build up to a complete calculation. Finally, we measure the performance of our library against that of current implementations. The framework described here is particularly well suited to the fields of quantum optics, superconducting circuit devices, nanomechanics, and trapped ions, while also being ideal for use in classroom instruction.

Subfields: Artificial Intelligence, Atomic and Molecular Physics, and Optics

View Paper: https://www.semanticscholar.org/paper/9ebb2b7c829e8aed2279231f5a9f681faac5c916

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Atomic and Molecular Physics, and Optics

Citations in the corpus

QuSpin: a Python Package for Dynamics and Exact Diagonalisation of Quantum Many Body Systems part I: spin chains (2016, background): “Over the last years, there have appeared freely accessible numerical packages and libraries which contribute to widespread the use of such numerical techniques among the condensed matter community: the Algorithms and Libraries for Physics Simulations [10–13] (ALPS), C++ libraries for tensor networks”
Open quantum systems with local and collective incoherent processes: Efficient numerical simulations using permutational invariance (2018, methodology): “PIQS is a robustly tested library developed in Python, designed to be memory efficient, fast, and easy to use.”
Quantum Electrodynamics in a Topological Waveguide (2020, neutral): “[80] J.”
Hybrid-Liouvillian formalism connecting exceptional points of non-Hermitian Hamiltonians and Liouvillians via postselection of quantum trajectories (2020, background): “The above interpretation allows also for simple efficient Monte Carlo simulation of the ensuing dynamics [19,21,26,55,56].”
Realizing repeated quantum error correction in a distance-three surface code (2021, methodology): “To make the simulation of the 17-qubit chip numerically tractable, with each qubit modeled as a ddimensional Kerr-nonlinear oscillator, we employ the method of Monte Carlo wavefunctions [75–77] as implemented in QuTiP’s mcsolve [78].”
Theory of variational quantum simulation (2018, methodology): “ween the exact result and the result obtained from variational algorithm. We set the time step δt= 0.01 and simulated from t= 0 to t= 10. We used a software package QuTIP for the numerical simulation [61,62]. 7 Discussion In this work, we focus on the theory of variational quantum simulation. We rst”
Probing many-body dynamics on a 51-atom quantum simulator (2017, background): “Repeated optimization of these parameters often leads to better crystal preparation fidelities [56].”