Block Encoding Linear Combinations of Pauli Strings Using the Stabilizer Formalism

• URL: http://arxiv.org/abs/2601.05740v1
• Date: Fri, 09 Jan 2026 11:41:46 GMT
• Title: Block Encoding Linear Combinations of Pauli Strings Using the Stabilizer Formalism
• Authors: Niclas Schillo, Andreas Sturm, Rüdiger Quay,
• Abstract summary: We introduce a novel method for constructing quantum circuits that block encode linear combinations of Pauli strings.<n>We present four concrete examples and use numerical simulations to compare our method's circuit complexity with that of the Linear Combination of Unitaries (LCU) approach.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The Quantum Singular Value Transformation (QSVT) provides a powerful framework with the potential for quantum speedups across a wide range of applications. Its core input model is the block encoding framework, in which non-unitary matrices are embedded into larger unitary matrices. Because the gate complexity of the block-encoding subroutine largely determines the overall cost of QSVT-based algorithms, developing new and more efficient block encodings is crucial for achieving practical quantum advantage. In this paper, we introduce a novel method for constructing quantum circuits that block encode linear combinations of Pauli strings. Our approach relies on two key components. First, we apply a transformation that converts the Pauli strings into pairwise anti-commuting ones, making the transformed linear combination unitary and thus directly implementable as a quantum circuit. Second, we employ a correction transformation based on the stabilizer formalism which uses an ancilla register to restore the original Pauli strings. Our method can be implemented with an ancilla register whose size scales logarithmically with the number of system qubits. It can also be extended to larger ancilla registers, which can substantially reduce the overall quantum circuit complexity. We present four concrete examples and use numerical simulations to compare our method's circuit complexity with that of the Linear Combination of Unitaries (LCU) approach. We find that our method achieves circuit complexities comparable to or better than LCU, with possible advantages when the structure of the target operators can be exploited. These results suggest that our approach could enable more efficient block encodings for a range of relevant problems extending beyond the examples analyzed in this work.

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