Block encoding bosons by signal processing

Block Encoding (BE) is a crucial subroutine in many modern quantum algorithms, including those with near-optimal scaling for simulating quantum many-body systems, which often rely on Quantum Signal Processing (QSP). Currently, the primary methods for constructing BEs are the Linear Combination of Unitaries (LCU) and the sparse oracle approach. In this work, we demonstrate that QSP-based techniques, such as Quantum Singular Value Transformation (QSVT) and Quantum Eigenvalue Transformation for Unitary Matrices (QETU), can themselves be efficiently utilized for BE implementation. Specifically, we present several examples of using QSVT and QETU algorithms, along with their combinations, to block encode Hamiltonians for lattice bosons, an essential ingredient in simulations of high-energy physics. We also introduce a straightforward approach to BE based on the exact implementation of Linear Operators Via Exponentiation and LCU (LOVE-LCU). We find that, while using QSVT for BE results in the best asymptotic gate count scaling with the number of qubits per site, LOVE-LCU outperforms all other methods for operators acting on up to <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mo>&amp;#x2272;</mml:mo><mml:mn>11</mml:mn></mml:math> qubits, highlighting the importance of concrete circuit constructions over mere comparisons of asymptotic scalings. Using LOVE-LCU to implement the BE, we simulate the time evolution of single-site and two-site systems in the lattice <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mi>&amp;#x03C6;</mml:mi><mml:mn>4</mml:mn></mml:msup></mml:math> theory using the Generalized QSP algorithm and compare the gate counts to those required for Trotter simulation.

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Publication Details

Journal
Quantum
Published
2025-05-15
DOI
https://doi.org/10.22331/q-2025-05-15-1747
Citations
4
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
9.92

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Block encoding bosons by signal processing

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Quantum
Quantum Computing Algorithms and Architecture
9.92
article

Block encoding bosons by signal processing

C. Bauer, Christopher F. Kane, Michael Kreshchuk, Siddharth Hariprakash, Neel S. Modi
article en
4 citations

Abstract

Block Encoding (BE) is a crucial subroutine in many modern quantum algorithms, including those with near-optimal scaling for simulating quantum many-body systems, which often rely on Quantum Signal Processing (QSP). Currently, the primary methods for constructing BEs are the Linear Combination of Unitaries (LCU) and the sparse oracle approach. In this work, we demonstrate that QSP-based techniques, such as Quantum Singular Value Transformation (QSVT) and Quantum Eigenvalue Transformation for Unitary Matrices (QETU), can themselves be efficiently utilized for BE implementation. Specifically, we present several examples of using QSVT and QETU algorithms, along with their combinations, to block encode Hamiltonians for lattice bosons, an essential ingredient in simulations of high-energy physics. We also introduce a straightforward approach to BE based on the exact implementation of Linear Operators Via Exponentiation and LCU (LOVE-LCU). We find that, while using QSVT for BE results in the best asymptotic gate count scaling with the number of qubits per site, LOVE-LCU outperforms all other methods for operators acting on up to <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mo>&amp;#x2272;</mml:mo><mml:mn>11</mml:mn></mml:math> qubits, highlighting the importance of concrete circuit constructions over mere comparisons of asymptotic scalings. Using LOVE-LCU to implement the BE, we simulate the time evolution of single-site and two-site systems in the lattice <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mi>&amp;#x03C6;</mml:mi><mml:mn>4</mml:mn></mml:msup></mml:math> theory using the Generalized QSP algorithm and compare the gate counts to those required for Trotter simulation.

QuantumVol. 9
University of Arizona (US), Lawrence Berkeley National Laboratory (US), Center for Theoretical Biological Physics (US), National Energy Research Scientific Computing Center (US), Computercraft (United States) (US), University of California, Berkeley (US)
U.S. Department of Energy, National Energy Research Scientific Computing Center, Office of Science, Advanced Scientific Computing Research, High Energy Physics
Openalex Percentile: Top 2%
Quantum Computing Algorithms and Architecture
9.92
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