(Phys.org) A research collaboration between the groups of Garnet Chan, Fernando Brandao, and Austin Minnich at the California Institute of Technology (Caltech) has recently led to the development of three new algorithms that could help to overcome the limitations of existing phase estimation and variational methods. These algorithms are dubbed quantum imaginary time evolution, quantum Lanczos and quantum METTS algorithms.
The key aim of the recent study carried out by the researchers at Caltech was to develop new quantum algorithms for determining ground, excited and thermal states on quantum computers. The researchers tried to circumvent the practical limitations of existing techniques for computing Hamiltonian states by leveraging notions from classical computer physics, such as imaginary-time evolution, exact diagonalization and finite-temperature state sampling, ultimately extending these
notions to quantum computing algorithms beyond what previously accomplished.
Determining the quantum mechanical behavior of many interacting particles is essential to solving important problems in a variety of scientific fields, including physics, chemistry and mathematics.

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