Past exam of the mathematics course of the University of Cambridge 2017 iii Paper 303 2 a Solution Created 2026-10-03 Updated 2026-10-05
Take the couplings in the Hamiltonian to include inverse temperature, so the Boltzmann factor is . If physical energies are used instead, first replace by their products with . Split the on-site term equally between its two bonds. For spin states the spin-chain transfer matrix has entriesUsing the specified coupling coordinates, in the order this isFor example, and . This is the nearest-neighbour Blume–Emery–Griffiths model with an additive constant and the paper's sign convention for .
Summing the periodic spin chain gives the partition function . For finite real couplings all entries of are strictly positive; the Perron–Frobenius theorem gives a unique positive dominant eigenvalue with for . Since is a symmetric matrix, all its eigenvalues are real. Thus in the thermodynamic limit,The positivity condition is stronger and more useful than mere ordering by signed value: subdominant eigenvalues can be negative. Also, the printed strict ordering between the other two is not guaranteed for all couplings. For instance, makes the positive constant matrix with two equal zero eigenvalues. Degeneracy there does not affect the largest-eigenvalue limit; no explicit generic eigenvalues are needed.
For spin magnetization, introduce a dimensionless field through , or insert into the trace. Thenwhere is a normalized eigenvector of the largest eigenvalue and . Spin inversion symmetry gives , since the positive eigenvector of the largest eigenvalue is unique. Thereforeat zero field, both at finite and in the finite-coupling thermodynamic limit. The finite- result follows directly by pairing each configuration with its spin-reversed partner. Eigenvalues at a single fixed field do not determine a general observable: a field derivative of the largest eigenvalue, or its eigenvector, is required. Positivity and the real analytic dependence on the couplings exclude a finite-temperature spontaneous symmetry breaking transition in this one-dimensional finite-range chain; singular zero-temperature coupling limits require separate treatment.
For even , spin decimation on alternate sites sums the middle spin of each two-bond segment, hence the coarse spin-chain transfer matrix is . DefineDirect multiplication gives . Matching its entry ratios to the original parameterization yields the spin-1 chain decimation recursionThe remaining overall positive factor is absorbed into . Keeping that factor preserves the free energy as well as normalized spin probabilities. Indeed , exactly; on an odd ring an unmatched boundary segment needs separate handling rather than assuming a uniform two-site block decomposition.
Past exam of the mathematics course of the University of Cambridge 2025 ii Paper 1 41D b ii Solution Created 2026-09-24 Updated 2026-10-03
The first row of the tridiagonal eigenvalue equation isIn the generic case , the two dominant coefficient vectors are independent, sinceHere , since otherwise the displayed eigenvalue equation and the nonzero would force all eigenvalues to equal . The strict spectral gap below the dominant pair now impliesThis is two-dimensional subspace iteration. If the dominant eigenvalue is repeated, acts as a scalar on ; the same QR argument either captures all of or separates its missing direction from the strictly smaller eigenspaces, and the conclusion below is unchanged.
Past exam of the mathematics course of the University of Cambridge 2026 ii Paper 1 41B a Solution Created 2026-09-24 Updated 2026-09-25
The power method repeatedly normalizes and estimates the eigenvalue with the Rayleigh quotient . It converges when the dominant eigenvalue is unique in modulus and the initial vector has a nonzero component in its eigendirection.
Power method Created 2026-09-24 Updated 2026-09-24
Iterate . With a unique dominant eigenvalue separated by a spectral gap and a starting vector that is nonorthogonal to its eigenvector, the directions converge at the spectral-ratio rate.
Spectral gap Created 2026-09-24 Updated 2026-09-24
A spectral gap is a positive separation between designated parts of the spectrum of a linear operator. For the power method, the relevant gap separates the modulus of the dominant eigenvalue from the other eigenvalue moduli.