【New Publication】Approximate Amplitude Encoding with the Adaptive Interpolating Quantum Transform

https://arxiv.org/abs/2603.03803

This study proposes a new approximate amplitude encoding method using the Adaptive Interpolating Quantum Transform (AIQT) to improve the efficiency of classical data loading in quantum computing.

Conventional Fourier-based methods rely on fixed transform bases, which can lead to information loss. By introducing AIQT, which learns a data-adaptive transform basis, the proposed approach concentrates information into a smaller number of coefficients while maintaining efficient circuit structures.

Experiments on financial time-series data and image datasets demonstrate that the method can reduce reconstruction error by up to about 50% compared with Fourier-based approaches under the same sparsity conditions. The circuit structure remains similar to that of the Quantum Fourier Transform, allowing implementation with gate counts that scale quadratically with the number of qubits.