At its microscopic level, the universe follows the laws of quantum mechanics. Focusing on the quantum trajectories of particles as followed from the hydrodynamical formulation of quantum mechanics, we propose that under general requirements, quantum systems follow a disrupted version of the gradient descent model, a basic machine learning algorithm, where the learning is distorted due to the self-organizing process of the quantum system. Such a learning process is possible only when we assume dissipation, i.e., that the quantum system is open. The learning parameter is the time increment of the process over the mass of the quantum particle, and a friction parameter determines the nonlinearity of the quantum system. We then provide an empirical demonstration of the proposed model.

翻译：在微观层面上，宇宙遵循量子力学定律。基于量子力学流体力学表述中粒子的量子轨迹，我们提出在一般条件下，量子系统遵循梯度下降模型（一种基本机器学习算法）的扰动版本，其中由于量子系统的自组织过程，学习过程发生扭曲。这种学习过程仅在假设存在耗散（即量子系统为开放系统）时才有可能实现。学习参数是过程时间增量与量子粒子质量之比，而摩擦参数决定了量子系统的非线性特性。随后，我们对该模型进行了实验验证。