Deep learning to perform quantum chemical calculations.

Deep learning to perform quantum chemical calculations.

Deep learning to perform quantum chemical calculations. This blog post introduces Fermi Net [1], which uses Deep learning to perform quantum chemical calculations, and its physical background.

About this post and the paper’s summary

This blog post introduces Fermi Net [1], which uses Deep learning to perform quantum chemical calculations, and its physical background.

This paper was submitted to arXiv on May 27, 2019 by David Pfau et al. The paper is outlined below.

Fermi Net, which is a neural net for quantum chemistry computation, is proposed. Quantum chemistry computation is done via energy minimization to optimize the wave function, but the neural net is responsible for the approximation of the wave function. It incorporates a number of physical constraints, such as the Hartree-Fock approximation, infinite-frequency boundary conditions, and antisymmetry, and the energy calculation is also calculated by based on physics. Fermi Net gives good results for any system, while we had to change the method for each system with traditional quantum chemistry computation.

Quantum chemical calculations, which generally involve calculating molecules, and ab initio calculations, which involve calculating materials, are very expensive and can require days or weeks of computational time. However, since the best approximation method for each system is different and requires iterative exploration. Fermi Net gives good results for all systems, potentially eliminating the need for such iterative calculations.

Key Insight

The three main points of this paper are as follows. In particular, the idea of including the second physical constraint is common in ordinary physical computation (e.g., constant energy), and a similar concept in research using neural networks can be found in Hamiltonian Graph Networks with ODE Integrators [2], for example.

  1. The Neural nets are responsible for the wave function approximation part of quantum chemical calculations
  2. A number of physical constraints such as the antisymmetry of the wave function, electron spin, and infinite farther boundary conditions
  3. Pre-train to match the wave function of the Hartree-Fock approximation

Physical background (quantum mechanics and quantum chemical calculations)

If we want to calculate the physical properties of matter (such as the electronic state), we need to describe the state of the electron. The equations of motion that we are familiar with cannot describe the states of small objects such as electrons, so we need to use something called quantum mechanics.

machine-learning deep-learning physics

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