Quantum dynamics of a fully-blockaded Rydberg atom ensemble

Classical simulation of quantum systems plays an important role in the study of many-body phenomena and in the benchmarking and verification of quantum technologies. Exact simulation is often limited to small systems because the dimension of the Hilbert space increases exponentially with the size of the system. For systems that possess a high degree of symmetry, however, classical simulation can reach much larger sizes. Here, we consider an ensemble of strongly interacting atoms with permutation symmetry, enabling the simulation of dynamics of hundreds of atoms at arbitrarily long evolution times. The system is realized by an ensemble of three-level atoms, where one of the levels corresponds to a highly excited Rydberg state. In the limit of all-to-all Rydberg blockade, the Hamiltonian is invariant under permutation of the atoms. Using techniques from representation theory, we construct a block-diagonal form of the Hamiltonian, where the size of the largest block increases only linearly with the system size. We apply this formalism to derive efficient pulse sequences to prepare arbitrary permutation-invariant quantum states. Moreover, we study the quantum dynamics following a quench, uncovering a parameter regime in which the system thermalizes slowly and exhibits pronounced revivals. Our results create new opportunities for the experimental and theoretical study of large interacting and nonintegrable quantum systems

Structural attributes of individual trees for identifying homogeneouspatches in a tropical rainforest

Mapping and monitoring tropical rainforests and quantifying their carbon stocks are important, bothfor devising strategies for their conservation and mitigating the effects of climate change. AirborneLaser Scanning (ALS) has advantages over other remote sensing techniques for describing the three-dimensional structure of forests. This study identifies forest patches using ALS-based structural attributesin a tropical rainforest in Sumatra, Indonesia. A method to group trees with similar attributes into forestpatches based on Thiessen polygons and k-medoids clustering is developed, combining the advantagesof both raster and individual tree–based methods. The structural composition of the patches could be anindicator of habitat type and quality. The patches could also be a basis for developing allometric modelsfor more accurate estimation of carbon stock than is currently possible with generalised models