The Galois group of a parameterized polynomial system of equations encodes the structure of the solutions. This monodromy group acts on the set of solutions for a general set of parameters, that is, on the fiber of a projection from the incidence variety of parameters and solutions onto the space of parameters. When this projection is decomposable, the Galois group is imprimitive, and we show that the structure can be exploited for computational improvements. Furthermore, we develop a new algorithm for solving these systems based on a suitable trace test. We illustrate our method on examples in statistics, kinematics, and benchmark problems in computational algebra. In particular, we resolve a conjecture on the number of solutions of the moment system associated to a mixture of Gaussian distributions.
翻译:由参数化多元方程式组成的 Galois 组群对解决方案结构进行编码。 这个单质区系组对一套通用参数的解决方案进行操作, 即从各种参数和解决方案的发生率预测纤维到参数空间。 当该预测可分解时, Galois 组即为暗淡, 我们显示该结构可以用来进行计算改进。 此外, 我们开发了一种新的算法, 以基于合适的跟踪测试来解决这些系统。 我们用统计、 运动学和计算代数基准问题等示例来说明我们的方法。 特别是, 我们解决了与高斯分布混合相关的瞬时系统解决方案数的猜想。