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Spectral gap
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Classroom Contents
Approximate Matrix Eigenvalues, Subspace Iteration With Repeated Random Sparsification
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- 1 Introduction
- 2 Background
- 3 Traditional methods
- 4 Full configuration interaction
- 5 Convergence
- 6 Projective estimator
- 7 Random sparsification
- 8 Bias
- 9 Sparsification
- 10 Fri algorithm
- 11 Population mixing
- 12 Random matrix multiplication
- 13 Spectral gap
- 14 Step 2 random sparsification
- 15 Orthogonalization
- 16 Summary
- 17 Conclusion
