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Area of Science:

  • Quantum Computing
  • Computational Physics
  • Numerical Analysis

Background:

  • Variational quantum algorithms (VQAs) are hybrid approaches for noisy quantum hardware.
  • Their practical application and comparison to quantum-inspired methods are under investigation.

Purpose of the Study:

  • To apply the variational quantum linear solver (VQLS) and its classical counterpart (VNLS) to rigid-body contact modeling.
  • To assess the performance of these solvers in simulating collision dynamics.

Main Methods:

  • Implementation of VQLS and VNLS within a minimum map Newton solver.
  • Utilizing a complementarity-based model for rigid-body contact.
  • Simulation of dynamics for rigid spherical bodies during collisions.

Main Results:

  • The variational neural linear solver (VNLS) accurately simulated rigid body collision dynamics.
  • Demonstrated the viability of VNLS as a component in physics-based solvers.

Conclusions:

  • Quantum and quantum-inspired linear algebra algorithms offer viable alternatives to traditional solvers for specific physical system modeling.
  • This work highlights the potential of VQAs and related methods in computational physics.