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Optimization

Magnetic Lattice Design Under Uncertainty Using QIO

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Challenges
  • Magnetic materials are modeled using discrete spin states (up/down)  
  • A lattice with n × n spins creates a high-dimensional combinatorial optimization problem Temperature and magnetic field uncertainty further increase complexity  
  • Long-range spin interactions must be considered for accurate predictions  
  • Classical optimization methods become increasingly difficult to scale as system size and uncertainty grow.

Results

  • Up to 2× faster optimization compared with Genetic Algorithms  
  • Consistent solution quality across increasing lattice sizes

  • Significant reduction in computational cost for uncertainty-driven optimization  
  • Improved scalability for large discrete systems

Accelerating Large-Scale Magnetic Lattice Optimization

Speed

Up to 2X faster than Classical Algorithms

Solution Quality
Achieved Better optimum free-energy solutions across all lattice sizes
Scalability
Successfully optimized systems up to 50 × 50 spin lattices and it is scalable
Go Beyond Classical Limits.
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