Quantum Computing · Chapter 04
Quantum States and Measurement
How do path calculations become a geometry of states, and what happens when we observe a quantum system?
Mithilesh Kumar
→ or Space to advance · N for notes · F for fullscreen
4.1
Vectors and Matrices
States become vectors, amplitudes between states become inner products, and steps become matrices, each built from the path rules.
State vectors
A state \(\ket\psi=\sum_iv_i\ket i\) gives each configuration an amplitude. Its bookkeeping rules are those of vector arithmetic, so we treat \(\ket\psi\) as a vector. A two-configuration quantum system is a qubit; a weighted sum of kets is a superposition.
Order the configurations (0 first) and list the amplitudes:
\(\ket0,\ket1\) form the computational basis. Adding states adds coordinates; multiplying by a number multiplies every coordinate.
Example: \(\tfrac35\ket0+\tfrac45\ket1\) has probabilities \(\tfrac9{25}\) and \(\tfrac{16}{25}\). The coordinates describe one state, not two outcomes at once.
The amplitude between two states
Write \(\braket j\psi=\psi_j\) for the amplitude of \(j\) in \(\ket\psi\). Each path to a final state \(\ket\phi\) passes through one \(j\), so
What is \(\braket\phi j\)? Normalization, \(\sum_j\braket j\psi^*\braket j\psi=1\), matches the path formula for \(\braket\psi\psi\) if we choose
Inner products
Definition
The inner product (transition amplitude from \(\ket\psi\) to \(\ket\phi\)) is \(\displaystyle\braket\phi\psi=\sum_j\phi_j^*\psi_j\).
The bra \(\bra\phi\) is the conjugated row of \(\ket\phi\). Row times column performs the path sum:
Exchanging initial and final states conjugates the amplitude (conjugate symmetry):
Example: for \(\ket\psi=(\ket0+i\ket1)/\sqrt2\), \(\braket1\psi=i/\sqrt2\) but \(\braket\psi1=-i/\sqrt2\). The magnitude is unchanged; for real vectors the order does not matter.
This definition is chosen for consistency with the probability rule; its physical meaning for a general final state comes with the measurement postulate.
Length, orthogonality, and projection
The norm is \(\|\psi\|=\sqrt{\braket\psi\psi}\); normalized states are unit vectors. Vectors with \(\braket\phi\psi=0\) are orthogonal; mutually orthogonal unit vectors are orthonormal.
Split a unit vector \(\ket\psi\) into a part along a unit vector \(\ket\phi\) and a part orthogonal to it:
The parts are perpendicular, so their squared lengths add:
Hence \(0\le|\braket\phi\psi|^2\le1\): equal to 1 when the states differ by a global phase, 0 when orthogonal. For real unit vectors \(\braket\phi\psi=\cos\theta\).
Coordinates are components
Doing the split along every basis direction gives the coordinates: \(\braket j\psi\) is the component of \(\ket\psi\) along \(\ket j\). Because the basis is orthonormal,
The probabilities of the configurations are the squared lengths of these perpendicular components.
Example: \(\ket\psi=\tfrac{\sqrt3}2\ket0+\tfrac12\ket1\) and \(\ket\phi=\ket0\). Then \(\braket0\psi=\tfrac{\sqrt3}2=\cos30^\circ\), with probability \(\tfrac34\); the remainder \(\tfrac12\ket1\) is orthogonal to \(\ket0\).
The picture is a plane in state space, not physical space. Complex vectors keep this geometry while the inner product also carries phase.
Linearity and transition matrices
A step sends each configuration to the weighted sum of its successors and a state to the same combination of these images:
This is linearity. The transition matrix stores the arrow weights: \(U_{ji}=\bra jU\ket i\), with column \(i\) for the input and row \(j\) for the output.
Matrix–vector multiplication performs the path sums:
Unitary matrices
Every normalized input must give a normalized output. The two conditions of Chapter 3 say:
- each column has unit length (outgoing normalization);
- distinct columns are orthogonal (cross-sum condition).
A square matrix with orthonormal columns is unitary. Example:
Gate matrices and composition
\(X\) exchanges the basis directions, \(Z\) flips the sign of the \(\ket1\) component, \(H\) sends them to the two diagonals:
After a step, comparing with \(\ket\phi\) gives the amplitude
Two steps, \(U\) first and \(V\) second, give \(VU\ket\psi\). The two-step sum rule is the matrix product:
The rightmost matrix acts first. For example \(HH=I\), the identity matrix:
Undoing a step: the adjoint
Reversing arrows undoes CNOT. Try it on \(\sqrt X\) (stay \(a=\tfrac{1+i}2\), switch \(b=\tfrac{1-i}2\)): its arrows look the same both ways, so reversing gives \(\sqrt X\) again and \(\sqrt X\sqrt X=X\), not \(I\). The return paths give \(a^2+b^2=0\).
Reverse and also conjugate the weights. Return paths: \(a^*a+b^*b=1\); crossing paths: \(b^*a+a^*b=0\). The step is undone.
Adjoint
\(U^\dagger\) reverses every arrow of \(U\) and conjugates its weight: \(\bra iU^\dagger\ket j=\bra jU\ket i^*\). As a matrix, \(U^\dagger\) is the conjugate transpose.
This is the rule \(\braket\phi j=\braket j\phi^*\) applied to the arrows of a step: going backward conjugates.
Unitary steps are undone by their adjoint
Apply \(U\), then \(U^\dagger\), and use the sum rule:
This is 1 for \(i=k\) (normalization) and 0 for \(i\ne k\) (cross sum). Hence
Moving an operator across an inner product: \(\bra\phi U\ket\psi=\braket{U^\dagger\phi}\psi\). With \(\ket\phi=U\ket\chi\):
A unitary step preserves every length and angle: it moves state space rigidly, like a rotation. Example: \(H^\dagger=H\), so \(H\) undoes itself.
The adjoint is not always the inverse
Every matrix has an adjoint, but it undoes the matrix only when the matrix is unitary. Take the shear
\(A\) slides points sideways by their height; \(A^\dagger\) slides them upward by their horizontal position. Neither \(AA^\dagger\) nor \(A^\dagger A\) returns \(\tfrac35\ket0+\tfrac45\ket1\): they give \((2,\tfrac75)\) and \((\tfrac75,\tfrac{11}5)\).
Undoing \(A\) needs \(A^{-1}=\begin{pmatrix}1&-1\\0&1\end{pmatrix}\). The identity \(\bra\phi A\ket\psi=\braket{A^\dagger\phi}\psi\) still holds; the adjoint always moves an operator across an inner product. A shear stretches lengths, so it cannot be a step of a closed quantum system.
4.2
Postulates
Which of these calculations describe nature: states, closed evolution, measurement, and composite systems.
The state postulate
Multiplying every amplitude by the same \(e^{i\theta}\) changes no probability, now or after any later step, because every path sum gains the same factor. Such vectors cannot be told apart.
State postulate
A state of a finite quantum system is a unit vector of complex amplitudes, with the inner product above. Vectors differing only by a global phase represent the same physical state.
For a qubit, normalization ties the two magnitudes and the global phase can make the first amplitude real and nonnegative. One angle and one relative phase remain:
At \(\theta=0\) or \(\pi\) one amplitude vanishes and no relative phase remains.
The evolution postulate
The mathematics shows that probability-preserving steps are unitary. The postulate asserts that nature uses them.
Evolution postulate
The evolution of a closed system is unitary: \(\ket\psi\mapsto U\ket\psi\) with \(U^\dagger U=I\).
With real amplitudes, unit vectors end on a circle and a unitary is a rotation:
Lengths and angles between states are kept; in general \(\braket{U\chi}{U\psi}=\braket\chi\psi\).
The measurement postulate
Measurement postulate
For a normalized \(\ket\psi=\sum_jv_j\ket j\), an ideal measurement in the computational basis gives outcome \(j\) with probability \(|\braket j\psi|^2=|v_j|^2\). Conditional on that outcome, the state becomes \(\ket j\).
Both the probability and the update are physical assumptions, not consequences of path arithmetic.
Example: \(\tfrac{\sqrt3}2\ket0+\tfrac12\ket1\) gives 0 with probability \(\tfrac34\), 1 with \(\tfrac14\). After outcome 1 the state is \(\ket1\), so an immediate repeat gives 1.
Measurement as projection
A state is the sum of its components along the basis directions, \(\ket\psi=\sum_j\ket j\braket j\psi\). Measurement picks one component, with probability equal to its squared length, keeps it, and rescales it to unit length.
The projector \(P_j=\ketbra jj\) keeps the component along \(\ket j\): \(P_j\ket\psi=\ket j\braket j\psi\). As a matrix it is a column times a row, e.g.
In this language,
Measuring in other bases
Let a unitary \(U\) carry an orthonormal basis \(\ket{b_j}\) to the computational basis. Measuring in the \(b\) basis means applying \(U\) and then measuring:
So \(|\braket\phi\psi|^2\) is the probability of outcome \(\phi\) in any orthonormal basis containing \(\ket\phi\); afterwards the state is \(\ket\phi\).
Real example: \(\ket\psi=\cos\alpha\ket0+\sin\alpha\ket1\), \(\ket{b_0}=\cos\beta\ket0+\sin\beta\ket1\), \(\ket{b_1}=-\sin\beta\ket0+\cos\beta\ket1\) give amplitudes \(\cos(\alpha-\beta)\) and \(\sin(\alpha-\beta)\).
\(\beta=0\) is the Z measurement; \(\beta=45^\circ\) is the X measurement, with \(\ket\pm=(\ket0\pm\ket1)/\sqrt2\). Preparing \(\ket+\): X gives \(+\) with certainty, Z gives each outcome half the time. The measurement asks a different question; the state is the same.
With \(\beta=45^\circ\), \(\ket{b_1}=-\ket-\); an overall sign does not change the projector.
Evolution and measurement together
A history alternates the two kinds of change: unitary evolution between measurements, and at each measurement the observed outcome selects a component, which is rescaled to unit length.
Example: from \(\ket0\), \(H\) gives \((\ket0+\ket1)/\sqrt2\). Uninterrupted, a second \(H\) returns \(\ket0\) with certainty. Measured in between, the state becomes \(\ket0\) or \(\ket1\), and the second \(H\) gives equal probabilities.
The update cannot be undone: after outcome 0, an initial \(\ket0\) and an initial \((\ket0+\ket1)/\sqrt2\) both leave \(\ket0\).
The larger system, including the device and its record, may still evolve unitarily; the conditional description keeps only the reported branch. In the figure, vertical drops are schematic and do not mean a loss of norm or energy.
Composite systems
A complete configuration of two qubits names one configuration of each: \(00,01,10,11\). A joint state assigns an amplitude to each:
with \(\sum_{i,j}|c_{ij}|^2=1\).
Independent preparations \(a\ket0+b\ket1\) and \(c\ket0+d\ket1\): reaching 01 means 0 in \(A\) and 1 in \(B\), so its amplitude is \(ad\). This is the tensor product:
The composite-state postulate and entanglement
Composite-state postulate
The state space of a composite system is the tensor product of the state spaces of its parts, with basis \(\ket{ij}=\ket i\otimes\ket j\). Every unit vector in it is an allowed state.
Dimensions multiply: parts with \(m\) and \(n\) basis states give \(mn\). Are there allowed states that are not products? Take
A product would need \(ac\ne0\) and \(bd\ne0\), so all of \(a,b,c,d\ne0\); then \(ad\) and \(bc\) could not vanish. But this state has no 01 or 10 term. A pure joint state that is not a product is entangled.
Measuring both qubits gives 00 or 11, each half the time. A classical coin choosing 00 or 11 gives the same counts, so correlation alone does not reveal entanglement; the difference lies in the amplitudes of the whole state.
Summary
- A state is a vector of amplitudes; the inner product \(\braket\phi\psi=\sum_j\phi_j^*\psi_j\) is the transition amplitude, with the conjugate forced by the probability rule.
- A step is a matrix \(U_{ji}=\bra jU\ket i\); composition is the matrix product; probability is preserved exactly when \(U\) is unitary, and then \(U^{-1}=U^\dagger\).
- Postulates: unit vectors up to global phase; unitary closed evolution; measurement with probability \(|\braket\phi\psi|^2\) and state update.
- Composite systems live in the tensor product; states that do not factor are entangled.