9th Les Houches School in Computational Physics: Open Quantum Systems

comp-quant-2026 : 9th Les Houches School in Computational Physics: Open Quantum Systems

8-19 Jun 2026 Les Houches (France)

Open Quantum Systems

This school will introduce students to the physics of open quantum systems, and in particular to emergent phenomena such as environment-stabilized many-body physics, and driven-dissipative phase transitions, all from the point of computational approaches. It will provide fundamental aspects and practical introductions to numerical methods including semi-classical approaches, MPS and Tensor networks, diagrammatic Monte Carlo and neural network states. The numerical methods will be applied to the study of quantum circuits, quantum simulation / quantum computing platforms, as well as to the more general topics of condensed matter physics, quantum optics and quantum information.

Scientific Context

Quantitative understanding of open quantum many-body systems has grown to an important field of theoretical and computational condensed matter physics in recent years. On the one hand, the effects of the environment, i.e., decoherence and dissipation, are fundamental limiting factors for the coherent manipulation of quantum many-body systems, at the core of quantum computing and quantum simulation. Hence predicting how these factors affect specific protocols for the preparation of target many-body states (e.g., ground states of many-body Hamiltonians, highly entangled states, etc.) is of crucial importance to prepare future experiments. An important goal in this context is the design of most efficient preparation schemes, optimized so as to be resilient to the environment; or the identification of forms of entanglement which can survive the presence of the environment.

On the other hand, an important emergent subject in the context of open quantum systems is the use of the environment to explore new quantum many-body physics away from equilibrium, and to potentially stabilize specific quantum states. This can be done e.g., by projectively measuring the system and conditioning coherent operations on the measurement outcome ; or by driving the system across dissipative phase transitions, in which different forms of coupling to the environment compete with each other ; or in which the coupling to the environment competes with the Hamiltonian evolution.

Hence understanding of noise and decoherence in quantum systems is pivotal for quantum information and quantum technological applications ; and it is an important emergent subject in quantum statistical mechanics, at the interface with quantum information and quantum optics. Still, the development of efficient computational techniques for open quantum many-body systems out of equilibrium is far more challenging than for equilibrium systems. From a technical point of view, the brute-force description of an open quantum system is the most computationally intensive problem across the whole of spectrum of physics. Indeed the density matrix of a N-body system contains a number of coefficients given by the square of the number necessary to describe a wavefunction, namely the problem is exponentially harder than solving the Schrödinger's equation. Clearly, clever computational schemes need to be devised to tackle system sizes beyond a few (O(10)) degrees of freedom.

Significant advance in the simulation of out-of equilibrium dynamics and asymptotic steady states has been obtained recently, based on the generalization of computational methods for closed (Hamiltonian) quantum many-body systems. Relevant examples are matrix-product and tensor network schemes, semi-classical approaches, diagrammatic and variational Monte Carlo calculations, including machine-learned neural network quantum states.

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