Optimal Space-Depth Trade-Off of CNOT Circuits in Quantum Logic Synthesis. (arXiv:1907.05087v1 [quant-ph])

Due to the decoherence of the state-of-the-art physical implementations of
quantum computers, it is essential to parallelize the quantum circuits to
reduce their depth. Two decades ago, Moore et al. demonstrated that additional
qubits (or ancillae) could be used to design "shallow" parallel circuits for
quantum operators. They proved that any $n$-qubit CNOT circuit could be
parallelized to $O(\log n)$ depth, with $O(n^2)$ ancillae. However, the
near-term quantum technologies can only support limited amount of qubits,
making space-depth trade-off a fundamental research subject for quantum-circuit

In this work, we establish an asymptotically optimal space-depth trade-off
for the design of CNOT circuits. We prove that for any $m\geq0$, any $n$-qubit
CNOT circuit can be parallelized to $O\left(\max \left\{\log n,
\frac{n^{2}}{(n+m)\log (n+m)}\right\} \right)$ depth, with $O(m)$ ancillae. We
show that this bound is tight by a counting argument, and further show that
even with arbitrary two-qubit quantum gates to approximate CNOT circuits, the
depth lower bound still meets our construction, illustrating the robustness of
our result. Our work improves upon two previous results, one by Moore et al.
for $O(\log n)$-depth quantum synthesis, and one by Patel et al. for $m = 0$:
for the former, we reduce the need of ancillae by a factor of $\log^2 n$ by
showing that $m=O(n^2/\log^2 n)$ additional qubits suffice to build $O(\log
n)$-depth, $O(n^2/\log n)$ size --- which is asymptotically optimal --- CNOT
circuits; for the later, we reduce the depth by a factor of $n$ to the
asymptotically optimal bound $O(n/\log n)$. Our results can be directly
extended to stabilizer circuits using an earlier result by Aaronson et al. In
addition, we provide relevant hardness evidences for synthesis optimization of
CNOT circuits in term of both size and depth.

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