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arxiv: 2603.19130 · v2 · pith:272RO7VLnew · submitted 2026-03-19 · 🪐 quant-ph · cs.NA· math.NA· math.QA

Quantum block encoding for one-pair semiseparable matrices

classification 🪐 quant-ph cs.NAmath.NAmath.QA
keywords matrixmatricesblockencodingquantumdevelopmentgiveninput
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Quantum block encoding (QBE) is a crucial step in the development of most quantum algorithms, as it provides an embedding of a given matrix into a suitable larger unitary matrix. Historically, the development of efficient techniques for QBE has mostly focused on sparse matrices; less effort has been devoted to data-sparse (e.g., rank-structured) matrices. In this work we examine a particular case of rank structure, namely, one-pair semiseparable matrices. We present a new block encoding approach that relies on a suitable factorization of the given matrix as the product of triangular and diagonal factors. To encode the matrix, the algorithm needs $2\log(N)+7$ ancillary qubits. Assuming that the data input oracles can be implemented with polylogarithmic depth, or that a QRAM input model is available, our proposed method requires $\mathcal{O}({\rm polylog} (N))$ time and has an error of $\mathcal{O}(N^2)$, where $N$ is the matrix size.

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    A quantum method solves linear PDEs by block-encoding Fourier filters with reversible arithmetic, positioned as a structure-exploiting alternative to standard QSVT-based matrix inversion.