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Quantum state preparation for multivariate functions

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arxiv 2405.21058 v2 pith:5RRAVZAA submitted 2024-05-31 quant-ph

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keywords quantummultivariatefunctionsinitialstatebivariatefourierpotential
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A fundamental step of any quantum algorithm is the preparation of qubit registers in a suitable initial state. Often qubit registers represent a discretization of continuous variables and the initial state is defined by a multivariate function. We develop protocols for preparing quantum states whose amplitudes encode multivariate functions by linearly combining block-encodings of Fourier and Chebyshev basis functions. Without relying on arithmetic circuits, quantum Fourier transforms, or multivariate quantum signal processing, our algorithms are simpler and more effective than previous proposals. We analyze requirements both asymptotically and pragmatically in terms of near/medium-term resources. Numerically, we prepare bivariate Student's t-distributions, 2D Ricker wavelets and electron wavefunctions in a 3D Coulomb potential, which are initial states with potential applications in finance, physics and chemistry simulations. Finally, we prepare bivariate Gaussian distributions on the Quantinuum H2-1 trapped-ion quantum processor using 24 qubits and up to 237 two-qubit gates.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. A simpler Gaussian state-preparation

    quant-ph 2025-08 unverdicted novelty 6.0 of 10

    A proposed n-qubit Gaussian state-preparation circuit uses exactly n-1 rotations, (n-1)(n-2)/2 controlled rotations, floor((n-1)/2) ancilla, and is optimized to linear T-depth.

  2. Arbitrary state preparation in quantum harmonic oscillators using neural networks

    quant-ph 2025-02 reject novelty 5.0 of 10

    A neural network predicts pulse sequences that prepare arbitrary qubit, qutrit, and qudit states in a harmonic oscillator, reaching 99.9% average fidelity for qubits and 97% for qutrits in simulation.

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