Efficient Thermal State Preparation for Many-Body Systems with Quantum Processors.

Researchers have demonstrated an efficient algorithm for preparing thermal states in many-body systems, which is crucial for simulations in physics and chemistry. The method, utilising engineered bath resetting and modulated coupling, successfully generates the Gibbs state, verified numerically using the 2D Ising model across its entire temperature range.

The accurate simulation of thermal states, crucial for modelling complex systems in physics, chemistry and optimisation problems, presents a significant challenge for contemporary quantum computing. Achieving this requires preparing quantum systems in equilibrium states characterised by a distribution of energy levels, a task complicated by the inherent limitations of current and near-term quantum processors. Researchers at the University of Geneva, Google Research, Princeton University and the École Polytechnique Fédérale de Lausanne (EPFL) address this issue in their work, ‘Quantum thermal state preparation for near-term quantum processors’. Jerome Lloyd, alongside Dmitry A. Abanin and colleagues, details an algorithm utilising engineered bath resetting and modulated system-bath coupling, demonstrating successful thermal state preparation for the 2D Ising model across its finite-temperature phase diagram, and offering a potential pathway to simulating strongly-correlated states with existing quantum hardware. The algorithm achieves this by creating a channel that approximates the Gibbs state, where the accuracy improves as the system-bath coupling increases.

Researchers present a novel algorithm for preparing thermal states within many-body quantum systems, a persistent challenge in the field of quantum simulation. The method centres on a combination of engineered bath resetting and modulated system-bath coupling, effectively constructing a quantum channel that approximates a condition known as detailed balance. Detailed balance, a principle from statistical mechanics, ensures a stable equilibrium distribution of states.

The algorithm successfully generates thermal states, which are essential for accurately simulating systems at equilibrium, and crucially, for modelling their behaviour across a range of temperatures. Validation of the technique occurs through numerical simulations employing the two-dimensional Ising model, a standard benchmark in statistical physics used to study magnetism and phase transitions. Results demonstrate the algorithm’s accuracy across the entire finite-temperature phase diagram, including the particularly demanding region near critical points where systems undergo abrupt changes in behaviour.

This approach leverages engineered dissipation, the controlled removal of energy from a quantum system, and tailored interactions between the system and its environment, known as the ‘bath’. These interactions function as powerful control mechanisms, enabling the precise preparation of desired quantum states. The development offers a potential pathway towards the efficient simulation of strongly correlated states, those where interactions between particles are significant, on current and near-term quantum processors —devices that harness the principles of quantum mechanics to perform computations.