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Shallow Quantum Circuit Implementation of Symmetric Functions with Limited Ancillary Qubits
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In quantum computation, optimizing depth and number of ancillary qubits in quantum circuits is crucial due to constraints imposed by current quantum devices. This paper presents an innovative approach to implementing arbitrary symmetric Boolean functions using poly-logarithmic depth quantum circuits with logarithmic number of ancillary qubits. Symmetric functions are those whose outputs rely solely on the Hamming weight of the inputs. These functions find applications across diverse domains, including quantum machine learning, arithmetic circuit synthesis, and quantum algorithm design (e.g., Grover's algorithm). Moreover, by fully leveraging the potential of qutrits (an additional energy level), the ancilla count can be further reduced to 1. The key technique involves a novel poly-logarithmic depth quantum circuit designed to compute Hamming weight without the need for ancillary qubits. The quantum circuit for Hamming weight is of independent interest because of its broad applications, such as quantum memory and quantum machine learning.
Forward citations
Cited by 2 Pith papers
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Accelerated spin-adapted ground state preparation with non-variational quantum algorithms
A two-step penalty and post-processing scheme cuts the gate complexity of non-variational spin-adapted ground state preparation from quartic to quadratic scaling for spin-rotationally symmetric Hamiltonians.
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CNOT Oriented Synthesis for Small-Scale Boolean Functions Using Spatial Structures of Parallelotopes
SSHR uses parallelotopes (affine subspaces) in the Boolean hypercube to synthesize quantum oracles for <=8-bit functions and reports large CNOT reductions, but the provided construction does not uncompute its CNOTs.
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