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Quantum Simulations Based on Parameterized Circuit of an Antisymmetric Matrix

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arxiv 2505.01023 v1 pith:GTZVQ7NW submitted 2025-05-02 quant-ph

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keywords circuitquantummatrixusedantisymmetricapproximategatesparameterized
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abstract

Given an antisymmetric matrix $A$ or the unitary matrix $U_A = e^A$-or an oracle whose answers can be used to infer information about $A$-in this paper we present a parameterized circuit framework that can be used to approximate a quantum circuit for $e^A$. We design the circuit based on a uniform antisymmetric matrix with $\{\pm 1\}$ elements, which has an eigenbasis that is a phase-shifted version of the quantum Fourier transform, and its eigenspectrum can be constructed by using rotation $Z$ gates. Therefore, we show that it can be used to directly estimate $e^A$ and its quantum circuit representation. Since the circuit is based on $O(n^2)$ quantum gates, which form the eigendecomposition of $e^A$ with separate building blocks, it can also be used to approximate the eigenvalues of $A$.

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Cited by 1 Pith paper

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  1. Learnable quantum spectral filters for hybrid graph neural networks

    quant-ph 2025-07 reject novelty 5.0 of 10

    A parameterized quantum Fourier circuit with graph-derived gate connections acts as a convolution plus pooling layer in a hybrid quantum-classical graph neural network, achieving benchmark accuracies comparable to som...

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