Bipartite Systems
A bipartite system is a composite system with two named subsystems, usually called and . Its Hilbert space is
Bipartite notation is the first serious test of tensor-product discipline. Once the subsystem order, product basis, coefficient matrix, and local measurement conventions are fixed, product states, entanglement, reduced states, and Schmidt decomposition become much easier to use.
This page is the canonical guide to notation and first calculations for two-part systems. The mathematical construction of tensor products belongs to Tensor Products, while the classification of states belongs to Product States and Entangled States.
Subsystems A and B
Section titled “Subsystems A and B”The labels and identify the two tensor factors. They may denote two particles, two qubits, two modes, spin and position, a system and an ancilla, or a subsystem and an environment. The labels are not merely decorative: they determine which Hilbert space an operator acts on and how basis labels are ordered.
The standard convention in this chapter is
with the label written first and the label second. If a calculation uses the opposite order, it must say so before writing compact basis labels.
For more than two subsystems, the same idea generalizes, but bipartite systems are special because they have powerful tools such as the Schmidt decomposition.
For finite-dimensional factors, write
Then
The subsystem labels also determine dimensions. An operator on is a matrix, whereas an operator on is a matrix.
Changing the order of tensor factors is not a typographical rearrangement. The swap map
is a unitary map from to . Coordinates and matrix representations must be reordered with it. The site-wide convention is recorded in Tensor-Product Ordering.
Product Basis
Section titled “Product Basis”Choose orthonormal bases
Their tensor products
form an orthonormal basis of . Indeed,
and completeness reads
One often suppresses the comma and subsystem labels,
but the compact notation is meaningful only after the subsystem order has been fixed.
For two qubits, the computational product basis is
Here means
not a two-digit number and not a single qubit state.
For a qubit and a qutrit , the product basis has six vectors:
This example is a useful reminder that the two factors need not have equal dimensions.
Flattened coordinate order
Section titled “Flattened coordinate order”With the index first and the index changing fastest, the pair is assigned the zero-based coordinate
For two qubits,
Thus the ordered basis is
Other software or references may flatten indices differently. State the ordering before comparing component vectors or Kronecker-product matrices.
Coefficient Matrix
Section titled “Coefficient Matrix”In a chosen product basis, a finite-dimensional bipartite pure state has the unique expansion
The amplitudes form a coefficient matrix : the index labels rows and the index labels columns. In the flattened order above, the coordinate column of is
Normalization is the Frobenius-norm condition
If another state has coefficient matrix , then
For two qubits,
and the coefficient matrix is
The matrix depends on the chosen local bases, but its rank is invariant under invertible changes of local basis. This is why matrix rank is useful for diagnosing product versus entangled pure states.
The coefficient matrix also packages partial amplitudes. Projecting the factor onto selects column :
Projecting onto selects row :
The matrix is a reshaping of a state vector. It is not the joint density matrix, which is
and has dimension by .
Product Versus Entangled States
Section titled “Product Versus Entangled States”A product pure state has the form
If
then
So a product pure state has a rank-one coefficient matrix. Conversely, a nonzero finite-dimensional bipartite pure state with rank-one coefficient matrix is product.
For two qubits, this becomes the determinant test:
The state is product exactly when
If the coefficient matrix has rank greater than one, the state is entangled across the chosen -versus- split. The Schmidt Decomposition Overview is the basis-independent way to put this statement into canonical form.
Operators on Two Subsystems
Section titled “Operators on Two Subsystems”An operator that acts only on is embedded into the joint space as
Similarly, an operator local to is
Their action on a product vector is
Matrix elements factor in a product basis:
Operators local to different factors commute:
This algebraic commutativity does not say that all joint states are uncorrelated. It says that the two local operations can be applied in either order.
If has coefficient matrix , then
The transpose appears because the index labels the columns of . Consequently,
A general joint operator need not factor as one tensor product. In finite dimensions it can be expanded as a sum,
Terms that cannot be reduced to an -only contribution plus a -only contribution describe genuinely joint couplings or observables. The detailed operator calculus belongs to Operators on Composite Systems.
Reduced States from the Coefficient Matrix
Section titled “Reduced States from the Coefficient Matrix”For a pure bipartite state,
the reduced density matrices can be read directly from . Their components are
With the convention that labels rows and labels columns,
The transpose in the second formula is convention-dependent. It is the correct form for the coefficient matrix and row-column assignment used on this page. Writing the component formulas first is the safest way to translate between conventions.
Both reduced states are positive, have unit trace, and share the same nonzero eigenvalues. These eigenvalues are the squared singular values of , or equivalently the squared Schmidt coefficients.
For a product state , both reduced states have rank one. For an entangled pure state, their rank exceeds one. The Reduced States page explains their physical interpretation; Partial Trace: First Encounter derives the trace operation itself.
Local Measurements
Section titled “Local Measurements”A measurement performed only on subsystem is represented on the composite system by adding the identity on . If is a POVM on , then
and the corresponding joint-space effects are
For a joint density operator , the probability of outcome is
If and are measured with local POVMs and , their joint probability is
The marginal probability for follows by summing over the complete set of outcomes:
The local statistics of can therefore be computed from its reduced state
using
Conditional outcomes and states
Section titled “Conditional outcomes and states”When , the conditional probability is
For a projective measurement on , the unnormalized conditional state of is
Its trace is the outcome probability,
and the normalized conditional state is
A POVM specifies outcome probabilities but does not, by itself, specify the post-measurement state; that requires a measurement instrument or Kraus operators. This distinction prevents a common overinterpretation of effects as state-update rules.
Marginal and conditional statistics answer different questions. Entanglement can make depend strongly on , while the unconditioned state remains independent of which complete local measurement is performed on . That is the operational core of no-signaling.
Examples
Section titled “Examples”Product two-qubit state
Section titled “Product two-qubit state”The two-qubit product state
has coefficient matrix
Its determinant vanishes:
The Bell state
has coefficient matrix
Its determinant is , so the state is entangled.
Its reduced states follow immediately from the coefficient matrix:
and likewise .
Qubit–qutrit system
Section titled “Qubit–qutrit system”Let and , and consider
Its coefficient matrix is
The two rows are linearly independent, so the state is entangled. Measuring in its computational basis gives
Conditioned on outcome , the qutrit is in
Conditioned on outcome , it is in . The reduced states are
and
Their nonzero eigenvalues are and , as required.
Position and spin
Section titled “Position and spin”A bipartite split need not describe two particles. For one spin- particle,
separates position and spin. A general state can be written formally as
Normalization requires
The probability of spin up, without resolving position, is
This is the continuous-index analogue of summing over the unobserved index. The state is product across position and spin only when both component wavefunctions are proportional to one common spatial wavefunction.
Practical Workflow
Section titled “Practical Workflow”- Name the two subsystems and fix the order .
- Record , , and the chosen local bases.
- Declare how the pair is flattened into one coordinate index.
- Reshape pure-state amplitudes into a coefficient matrix.
- Insert identity operators explicitly for local operations and measurements.
- Use and for pure-state marginals in this convention.
- Distinguish joint, marginal, and conditional probabilities.
- Check dimensions and normalization before interpreting a result.
Common Mistakes
Section titled “Common Mistakes”- Writing compact labels such as before declaring the subsystem order.
- Assuming that and must have equal dimensions.
- Mixing different flattened basis orders in state vectors and Kronecker-product matrices.
- Treating the coefficient matrix as basis-independent rather than basis-dependent with basis-independent rank.
- Confusing the coefficient matrix with the density matrix.
- Thinking every two-term superposition is entangled.
- Forgetting identity factors in local measurements.
- Treating a POVM effect as if it uniquely specified a state-update rule.
- Confusing a local probability with a joint probability .
- Confusing a marginal state with a state conditioned on a remote outcome.
- Applying the two-qubit determinant test to larger bipartite systems instead of using matrix rank or Schmidt decomposition.
Cross-Links
Section titled “Cross-Links”- Composite Systems
- Tensor Products
- Product States
- Entangled States
- Reduced States
- Partial Trace: First Encounter
- Subsystems and Local Observables
- Schmidt Decomposition Overview
- Tensor-Product Ordering
- Subsystem Labels and Notation
- Product Bases
- Operators on Composite Systems
- Reduced Density Operators
- Schmidt Rank
References
Section titled “References”- R. Shankar, Principles of Quantum Mechanics, 2nd ed., Springer, 1994.
- J. J. Sakurai and J. Napolitano, Modern Quantum Mechanics, 3rd ed., Cambridge University Press, 2020.
- A. Peres, Quantum Theory: Concepts and Methods, Kluwer Academic Publishers, 1995.
- M. A. Nielsen and I. L. Chuang, Quantum Computation and Quantum Information, Cambridge University Press, 2010.
- J. Watrous, The Theory of Quantum Information, Cambridge University Press, 2018.
Exercises
Section titled “Exercises”- In the -first convention, what does mean?
Solution
It means
The first label belongs to subsystem , and the second belongs to subsystem .
- For
write the coefficient matrix and decide whether the state is product.
Solution
The coefficient matrix is
It has rank one, so the state is product. Explicitly,
- Use the determinant test to decide whether
is product.
Solution
Here
The determinant is zero, so the state is product:
- Let a local measurement on have projector . What full-system projector represents the same outcome on ?
Solution
The full-system projector is
The identity acts on subsystem , indicating that the measurement is local to .
- A qubit and qutrit use the flattened index . Which coordinate corresponds to ? Find the ordered coordinate vector of the state
Solution
Here , so
In the ordered basis
the coordinate vector is
- For two qubits, evaluate
Then verify on this basis vector that the two local operators commute.
Solution
The first operator flips subsystem , while the second flips subsystem :
Applying both in either order gives
Thus their commutator annihilates this vector, as expected from the general identity.
- For the qubit–qutrit state
find , , and . What are the local computational-basis probabilities?
Solution
The coefficient matrix is
Therefore
while
Hence
and
- The two qubits are prepared in
Subsystem is measured in the basis . Find the conditional state of for each outcome and compare their average with .
Solution
In the basis,
Each outcome on has probability . The conditional states are
If the outcome is not retained, their probability-weighted average is
The conditional state depends on the remote outcome, while the unconditioned marginal remains maximally mixed.