Past exam of the mathematics course of the University of Cambridge / 2023 / iii / Paper 324 / 1

A strong classical simulation of a quantum circuit computes any requested output probabilityin polynomial time, to the prescribed inverse-polynomial accuracy. A weak classical simulation of a quantum circuit instead produces classical samples from the circuit's output distribution, with exact or suitably small total-variation error.

The Extended Gottesman--Knill theorem states that a unitary Clifford circuit with an arbitrary product state input and final computational-basis measurements is weakly classically simulable. It is strongly simulable when only $O(\log n)$ output qubits are measured. Indeed, each joint output projector expands into $2^k$ Pauli operators, and Clifford conjugation maps every such operator to another Pauli operator whose expectation factors over the input qubits. The factor $2^k$ is polynomial precisely for $k=O(\log n)$.

Choose a Clifford operation $D$ with $D|0^n⟩=|\sigma ⟩$ and absorb $D$ into the circuit. Push each subsequent Clifford gate forward through the computation. A computational-basis measurement made after a Clifford prefix $U$ becomes a Pauli measurementon the initial state, because Clifford conjugation preserves the Pauli group. Adaptivity merely makes the next Pauli depend on earlier classical outcomes.

It remains to eliminate the $n$ stabilizer qubits. Maintain their current stabilizer group. For a Pauli $P$ to be measured, there are two cases.

maps the old stabilizer sector into the $\lambda$ eigenspace of $P$. Updating the Clifford frame by $V_{\lambda }$ removes this measurement while conjugating every later Pauli to another Pauli.

Iterating this procedure leaves an adaptive Pauli-based computation on $|\rho ⟩$. The same classical outcomes determine every adaptive choice and final output, so this gives a weak classical simulation. Every postselected $Z$ outcome becomes either a fixed classical $+1$ branch or a postselected $+1$ Pauli measurement, as required.

Put $P_1={\sigma }_1\otimes {\sigma }_2$ and $|\psi ⟩=|A{⟩}^{\otimes 2}$. After the first Hadamard gate and the two controlled Pauli gates, the joint state isThe final Hadamard gate changes this toConditioned on ancilla outcome $s\in \{0,1\}$, the normalized data state is therefore

Write the input in the two eigenspaces of $P_1$ aswhere the displayed eigenstates are normalized. A direct PBC measurement giveswith probabilities $|\alpha {|}^2$ and $|\beta {|}^2$. Hence the ancilla circuit and the Pauli measurement have identical outcome distributions and conditional data states after identifying the Pauli outcome with $(-1{)}^s$.

Use the standard ancilla-assisted Pauli measurement. To measure a Pauli $P$, reset the ancilla to $|0⟩$, apply $H$, apply the controlled version of every nonidentity factor of $P$ with the ancilla as control, apply $H$ again, and measure the ancilla in the computational basis. The preceding calculation shows that outcome $s$ projects the data with

First use this circuit with $P_1=Z\otimes I$, obtaining $s_1$. Since the measured ancilla is $|s_1⟩$, apply the classically controlled correction $X^{s_1}$ to reset it to $|0⟩$. Reuse it to measure $P_2=Z\otimes X$, obtaining $s_2$. All controlled Pauli gates and single-qubit corrections are Clifford gates. Since $P_1{P}_2=P_2{P}_1$, the final data state isThus one resettable ancilla implements both measurements of the PBC without disturbing the already measured Pauli eigenvalue.