Past exam of the mathematics course of the University of Cambridge 2025 iii Paper 323 4 i Solution Created 2026-09-24 Updated 2026-09-25
The Umegaki relative entropy iswhen the support of is contained in that of , and otherwise. Its additivity of quantum relative entropy isits superadditivity of quantum relative entropy isand its data-processing inequality for quantum relative entropy is for every quantum channel .
Additivity follows from the logarithm of a tensor product,and the analogous identity for . For superadditivity, subtract the two marginal relative entropies from the joint one. The reference-state terms cancel, leavingThis is the nonnegativity of quantum mutual information, equivalently Subadditivity of Von Neumann entropy.
Every linear map from a qubit into the tensor product of that qubit and an environment can be expanded in the Pauli matrix orthonormal basis of operators. If and , then the four coefficient vectors areThese environment vectors need not be orthogonal, so this is an operator expansion rather than a claim that the quantum channel is a classical Pauli channel. Physical isometries additionally preserve the inner products of the two input basis states.
Pauli-string commutation parity 2026-10-14
For tensor products of Pauli factors from , let count the sites where both factors are nonidentity and different. Distinct nonidentity Pauli matrices anticommute, and equal or identity factors commute. Reversing the product site by site therefore gives . Thus two Pauli strings commute exactly when is even. The criterion applies to the perfect-correlation observables in the GHZ theorem.
Picard scheme of a curve 2026-10-14
For a smooth projective algebraic curve of genus , this smooth proper -dimensional scheme represents degree- line bundles in families. Charts come from nonspecial degree- bundles: their first sheaf cohomology vanishes, so the Riemann-Roch theorem gives exactly one independent global section, whose zero Cartier divisor varies algebraically. Twisting by fixed line bundles gives charts covering every degree- class. For degree zero the tensor product gives the Jacobian variety; other components are its torsors.
Product Laplacian eigenspace decomposition 2026-10-07
For closed manifolds with the product Riemannian metric, the positive Laplace-Beltrami operator is the sum of the two factor operators. Products of their orthonormal eigenbases form a complete basis, and eigenvalues add. Hence the product eigenspace at is the displayed finite orthogonal sum of tensor products. The discrete assertion requires a discrete spectral setting.
For a diffeomorphism, pull a type tensor field back by the inverse differential on vector slots and the dual differential on covector slots. Invertibility distinguishes this construction from pullback of purely covariant tensors along an arbitrary smooth map. This operation preserves tensor products and tensor contractions, supplying the flow definition of the Lie derivative of a tensor field.
Quantum register 2026-10-06
A quantum register is a named tensor product factor of a quantum circuit's Hilbert space, usually a collection of qubits. Registers separate data, control, output and workspace roles; uncomputation returns workspace to a fixed quantum state without destroying coherence in the data.
Rationalization of a topological space 2026-10-14
For simply connected , rationalization of a topological space is a map to a rational space inducing . It is also a rational homology equivalence. Its universal property is the bijection for every rational space . A Postnikov tower constructs it by replacing each fibre group with its rational tensor product and transporting the Postnikov invariant through the resulting cohomology isomorphism, then taking the homotopy inverse limit.
Representation ring of a compact group 2026-10-14
The representation ring is the Grothendieck group of finite-dimensional complex unitary representations of a compact group, with addition induced by direct sum and multiplication by tensor product. As an abelian group it is freely generated by the irreducible unitary representations. Taking dimension gives a ring homomorphism .
Separability of a tensor 2026-10-14
In a two-factor tensor product over a field, a pure tensor is also called a separable or decomposable tensor: it can be expressed as one product . Every tensor is a finite sum of pure tensors, but a sum need not itself be a pure tensor.[ref]
Tensor Products I by Keith Conrad. §3, printed p. 9: elementary, simple, decomposable, and pure tensors; Example 2.1, printed pp. 4–5: outer products do not fill the matrix space
For finite-dimensional vector spaces, the tensor-product coefficient matrix gives a decisive test: a nonzero tensor is a pure tensor exactly when its matrix rank is one. Indeed, every column of is a scalar multiple of . Conversely, if all columns of a nonzero matrix are multiples of one nonzero column , collect their multipliers in to obtain . The zero tensor is also a pure tensor, for example , but its matrix rank is zero.
In , the tensoris nonseparable: its matrix rank is two and its determinant is one, whereas . Directly, trying requires and . The first two equations force all four scalars nonzero, contradicting the others. In contrast, products sharing a factor do combine: . Thus being written as two summands alone does not establish nonseparability.
For finite free total chain complexes, evaluation identifies the underlying graded tensor product with the graded Hom complex of chain complexes, where is the reversed dual chain complex. Under the precomposition-first Hom differential, conjugation by the sign makes this a chain isomorphism. The identity works for every integer degree. If the grading is unbounded and only degreewise finite, products on the Hom side need not equal direct sums on the tensor side.
Sullivan fibre-model theorem 2026-10-14
For a map with simply connected base and the usual finite-type hypotheses, choose a relative Sullivan algebra modelling the path-space fibration, with acyclic total algebra. Tensor it over with a model of via . The resulting algebra models the homotopy fibre. Relative Sullivan extensions are cofibrant replacements, so this tensor product computes the derived algebraic pushout, contravariantly corresponding to the topological homotopy pullback. Linear differential pairs must be cancelled before reading rational homotopy groups from generators.
Tangle category 2026-10-14
Objects are finite words of strand orientations. Morphisms are boundary-fixed ambient-isotopy classes of oriented tangles in a slab, composed by stacking compatible boundary words; horizontal juxtaposition is the tensor product. Cups, caps, identity strands and crossings generate the category. Ordinary unframed isotopy includes all three Reidemeister moves; framed variants impose different first-move relations.
Tensor field Created 2026-10-05 Updated 2026-10-14
A tensor field is a smooth section of a vector bundle formed from tensor products of the tangent bundle and cotangent bundle. With covector factors and vector factors it belongs toIts coefficients in any local frame vary smoothly. Different conventions list the two counts in different orders, so the factor order should be specified. Tensor contractions use the canonical evaluation of a covector on a vector and are independent of the frame.
Tensor product Created 2026-09-24 Updated 2026-10-14
A tensor product turns a bilinear map into a linear map. For vector spaces over the same field , its elements are finite sums of pure tensors , subject to bilinearity:The scalar belongs to ; writing makes this choice explicit. These rules preserve separate linearity while allowing arbitrary linear combinations of products.[ref]
Linear Algebra Done Right by Sheldon Axler (4th edition). §9D, 9.71–9.74, printed pp. 372–373: tensor products, bilinearity, and bases
For a concrete example, take , with basis vectors in the first copy and in the second. The four tensor-product basis elements areThe pure tensor made from and expands toEach basis vector in one factor can interact with each basis vector in the other. This is why dimensions multiply; the tensor-product coefficient matrix displays these four interactions as a two-by-two grid.
The tensor product is different from the Cartesian product . With componentwise vector addition and scalar multiplication, the latter contains pairs and has dimension . The map is bilinear, generally neither linear on that Cartesian product nor injective nor surjective. In our example, , and ; the separability of a tensor explains why some outputs cannot be reached at all. Both spaces happen to have dimension four when , but this coincidence does not identify their structures.
Tensor-product basis Created 2026-10-05 Updated 2026-10-14
If and are bases of finite-dimensional vector spaces over , then the products form a basis of . There is one independent coordinate for every pair of indices.[ref]
Linear Algebra Done Right by Sheldon Axler (4th edition). §9D, Theorems 9.72 and 9.74, printed pp. 372–373: dimension and tensor-product basis
For a proof outline, bilinearity expands each pure tensor asso these products form a spanning set. For linear independence, take the coordinate functionals from the two dual bases. The bilinear map induces a linear functional on the tensor product, satisfying . Applying it to a proposed zero linear combination selects just , forcing every coefficient to vanish. Thus dimensions multiply, rather than add. This finite-dimensional count includes a zero factor, whose tensor product has dimension zero.
Tensor product of central simple algebras 2026-09-28
The tensor product over of two central simple -algebras is central simple. After extending scalars to an algebraic closure, both factors and their tensor product become full matrix algebras; faithful flatness then descends simplicity and the center.
Tensor product of chain complexes 2026-10-06
The tensor product of homologically graded chain complexes has differential . The sign makes the two mixed terms in cancel. Total degree is the sum of the two degrees.