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Microsoft Quantum

Solving the quantum many-body problem with artificial neural networks 

  Working together, ETH Zurich and Microsoft QuArC researchers have provided the first application of machine-learning techniques to solve outstanding problems in quantum physics. The neural networks used in their study developed a genuine intuition of the bizarre behavior of quantum particles. For example, after the artificial intelligence is trained on the elementary rules of...

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Triple point topological metals 

  Topological materials can yield quasiparticles that behave in a manner similar to elementary particles that are part of the standard model of particle physics. In this paper, published in Physical Review X, we report on a new class of such quasiparticles—triple point fermions—which represent fermions that have mixed properties of Dirac and Weyl fermions....

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Hybrid quantum-classical approach to correlated materials 

  Recent improvements in the control of quantum systems make it seem feasible to finally build a quantum computer within a decade. While it has been shown that such a quantum computer can in principle solve certain small electronic structure problems and idealized model Hamiltonians, the highly relevant problem of directly solving a complex correlated...

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