Predicting the properties of a molecule or material requires calculating the collective behavior of its electrons. Such predictions could one day help researchers develop new pharmaceuticals or design materials with sought-after properties such as superconductivity. The problem is that electrons can become ‘quantum mechanically’ entangled with one another, meaning they can no longer be treated individually. The entangled web of connections becomes absurdly tricky for even the most powerful computers to unravel directly for any system with more than a handful of particles.
The post Neural Networks and ‘Ghost’ Electrons Accurately Reconstruct Behavior of Quantum Systems appeared first on HPCwire.
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