부산대학교 도서관

Quantum state preparation (QSP) is a fundamental task in quantum computation to prepare a quantum state for a given classical description of the quantum state. The classical description of an $n$-qubit quantum state may have $\exp(O(n))$ parameters in general, which are inherently inefficient to prepare the corresponding state in the worst case. However, in many practical cases, we may be able to employ suitable data structures for QSP. An ordered binary decision diagram (OBDD) and a free BDD (FBDD) are such data structures to represent the large-scale data in a compressed way. An efficient QSP for a subclass of OBDDs is known, but requires an $O(2^n)$-sized quantum circuit in general, while QSP based on FBDDs, which includes OBDDs as a special case, remains unexplored. We here construct a quantum algorithm for QSP when the classical description of a quantum state is given by an FBDD with weighted edges, and analyze the space, and time complexity of QSP in this setting. We provide a nontrivial example of an $n$-qubit state that can be represented by a weighted FBDD with $N=O(\mathrm{poly}(n))$ nodes rather than $\mathrm{exp}(O(n))$. We show that any quantum state represented by the weighted FBDD with $N$ nodes can be prepared by an $O(N)$-sized quantum circuit using $N$ ancillary qubits, exponentially improving the required circuit size for QSP compared to other BDD-based QSPs. We also provide another example of an $n$-qubit state that can be represented by a weighted FBDD with $N=O(n^2)$ nodes, and $O(n^2)$ ancillary qubits, but cannot be prepared efficiently by a QSP based on the amplitude amplification. These results provide techniques to employ FBDDs as a tool for broadening the possibility of efficient QSP.
Comment: 19 pages with 1 table and 9 figures