Quantum Data Loading for Carleman Linearized Systems: Application to the Lattice-Boltzmann Equation
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arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866914570960896000 |
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| author | Demirdjian, Reuben Hogancamp, Thomas Gnanasekaran, Abeynaya Surana, Amit Gunlycke, Daniel |
| author_facet | Demirdjian, Reuben Hogancamp, Thomas Gnanasekaran, Abeynaya Surana, Amit Gunlycke, Daniel |
| contents | Herein, we introduce a strategy to decompose an arbitrary square matrix into a linear combination of non-unitaries (LCNU) where each non-unitary term is embedded into a unitary matrix. The result is a linear combination of unitaries (LCU) with an equal number of terms as the LCNU. Using this approach, we construct a generalized LCU framework for any Carleman linearized autonomous dynamical system with a polynomial nonlinearity. This framework is then used to construct an LCU for the 3-dimensional Carleman linearized lattice Boltzmann equation (LBE) in which the number of terms scales like $N_s \sim \mathcal{O}(α^2 Q^2)$, where $α$ is the Carleman truncation order and $Q$ is the number of discrete velocities from the LBE. Importantly, $N_s$ is completely independent of both the number of temporal and spatial discretization points. Lastly, we provide an estimate of our LCNU strategy's T gate cost in conjunction with (1) PREP and SELECT block encoding oracles, and (2) the variational quantum linear solver. In the former, the T cost scales like $\mathcal{O}(α^3 Q^2 (\log_2 n)^2)$, where $n$ is the total number of spatial grid points across all dimensions. Next, the latter requires $N_s^2(\log_2 (2n_tn^α)+1)$ circuits per iteration, with a worst case T gate cost of $\mathcal{O}(α(\log_2 Qn)^2)$ among them. We, therefore, provide an efficient decomposition strategy useful for both fault-tolerant and variational approaches. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_00302 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Quantum Data Loading for Carleman Linearized Systems: Application to the Lattice-Boltzmann Equation Demirdjian, Reuben Hogancamp, Thomas Gnanasekaran, Abeynaya Surana, Amit Gunlycke, Daniel Quantum Physics Herein, we introduce a strategy to decompose an arbitrary square matrix into a linear combination of non-unitaries (LCNU) where each non-unitary term is embedded into a unitary matrix. The result is a linear combination of unitaries (LCU) with an equal number of terms as the LCNU. Using this approach, we construct a generalized LCU framework for any Carleman linearized autonomous dynamical system with a polynomial nonlinearity. This framework is then used to construct an LCU for the 3-dimensional Carleman linearized lattice Boltzmann equation (LBE) in which the number of terms scales like $N_s \sim \mathcal{O}(α^2 Q^2)$, where $α$ is the Carleman truncation order and $Q$ is the number of discrete velocities from the LBE. Importantly, $N_s$ is completely independent of both the number of temporal and spatial discretization points. Lastly, we provide an estimate of our LCNU strategy's T gate cost in conjunction with (1) PREP and SELECT block encoding oracles, and (2) the variational quantum linear solver. In the former, the T cost scales like $\mathcal{O}(α^3 Q^2 (\log_2 n)^2)$, where $n$ is the total number of spatial grid points across all dimensions. Next, the latter requires $N_s^2(\log_2 (2n_tn^α)+1)$ circuits per iteration, with a worst case T gate cost of $\mathcal{O}(α(\log_2 Qn)^2)$ among them. We, therefore, provide an efficient decomposition strategy useful for both fault-tolerant and variational approaches. |
| title | Quantum Data Loading for Carleman Linearized Systems: Application to the Lattice-Boltzmann Equation |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2605.00302 |