Efficient LCU block encodings through Dicke states preparation

• URL: http://arxiv.org/abs/2507.20887v1
• Date: Mon, 28 Jul 2025 14:39:16 GMT
• Title: Efficient LCU block encodings through Dicke states preparation
• Authors: Filippo Della Chiara, Martina Nibbi, Yizhi Shen, Roel Van Beeumen,
• Abstract summary: Linear Combination of Unitaries (LCU) is one of the most widely studied and versatile approaches to block encoding.<n>We introduce FOQCS-LCU, which leverages the check matrix formalism to implement a constant-depth SELECT oracle.<n>We construct explicit block encoding circuits for representative spin models such as the Heisenberg and spin glass Hamiltonians.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: As algorithmic tools exemplified by the Quantum Singular Value Transformation (QSVT) continue to emerge as a unifying framework for diverse quantum speedups, the efficient construction of block encodings--their fundamental input model--becomes increasingly crucial. However, devising explicit block encoding circuits remains a well-recognized and challenging problem. One of the most widely studied and versatile approaches to block encoding is the Linear Combination of Unitaries (LCU). Despite its generality, the practical use of LCU is often limited by significant gate overhead, primarily stemming from the multi-controlled gates required in the SELECT oracle. We introduce a compact LCU formulation, dubbed FOQCS-LCU, which leverages the check matrix formalism to implement a constant-depth SELECT oracle using a linear number of singly controlled Pauli gates and ancillae. We demonstrate that, by exploiting the structure of the problem, the cost of the state preparation oracle can also be substantially reduced. We accomplish so by designing a parametrized family of efficient Dicke state preparation routines. We construct explicit block encoding circuits for representative spin models such as the Heisenberg and spin glass Hamiltonians and provide detailed, non-asymptotic gate counts. Our numerical benchmarks validate the efficiency of the FOQCS-LCU approach, illustrating an order-of-magnitude improvement in CNOT count over conventional LCU. This framework opens the door to efficient block encodings of a broad class of structured matrices beyond those explored here.

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