Common roots of multivariate polynomials

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SUMMARY

The discussion centers on efficiently solving the common roots of four polynomials in four variables. The user currently employs a gradient descent method, which is effective but raises concerns about local minima. They have explored the Cayley-Dixon and Macaulay resultant methods, but these require excessive memory. The conversation highlights Grobner bases and Buchberger's algorithm as promising alternatives for solving systems of polynomial equations.

PREREQUISITES
  • Understanding of polynomial equations and their roots
  • Familiarity with gradient descent optimization techniques
  • Knowledge of Cayley-Dixon and Macaulay resultant methods
  • Basic concepts of Grobner bases and Buchberger's algorithm
NEXT STEPS
  • Research Grobner bases and their applications in solving polynomial systems
  • Study Buchberger's algorithm for efficient computation of Grobner bases
  • Explore alternative optimization techniques to gradient descent for polynomial root finding
  • Investigate memory-efficient algorithms for polynomial resultants
USEFUL FOR

Mathematicians, computer scientists, and researchers focused on algebraic geometry, particularly those working on polynomial equations and optimization methods.

psyloe
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I was wondering if it were possible to efficiently solve the common root of 4 polynomials in 4 variables algebraically. I am currently using a gradient descent method, which can find these roots in a couple seconds; however, I am concerned about local minima.

So far I have attempted to use the Caylay-Dixon and Macaualy resultant to solve this problem, but these methods take far more memory to compute than is available. Is there a method that is more efficient than the ones I have tried?
 
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I think that learning about Grobner bases / Buchberger's algorithm will help you.

There are algorithms based on these concepts for solving systems of polynomial equations.
 

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