7–11 Dec 2026
The University of Sydney
Australia/Sydney timezone
AIP Congress 2026

Quantum Algorithm for solving differential equations using SLAC derivatives.

Not scheduled
20m
Belinda Hutchinson Building (The University of Sydney )

Belinda Hutchinson Building

The University of Sydney

Abercrombie St & Codrington St NSW 2008
Contributed Oral AIP | Quantum Science and Technology (QST)

Description

In numerical approaches to solving differential equations on a lattice, a representation of the derivative operator that correctly matches the continuum behaviour of momentum up to the band limit must be non-local. We present the construction of efficient linear-combination-of-unitaries ($\mathrm{LCU}$)-based block-encodings for the first-order derivative and Laplacian operators in the non-local (N=2^n)-dimensional SLAC representation. We use state-preparation techniques designed for smoothly decaying functions to prepare the dense $\mathrm{LCU}$ amplitudes with high success probability and low gate cost. Furthermore, we demonstrate how Shannon wavelet transforms can be applied to these block-encodings to obtain multiscale representations of the SLAC derivative operators. We then show how to apply a diagonal preconditioner that reduces the condition number of these matrices in the multiscale wavelet basis to a small constant. This enables the solution of a large class of partial differential equations (PDEs) with SLAC-discretised derivative operators on a finite lattice using the quantum linear solving algorithm ($\mathrm{QLSA}$). For a $d$-dimensional PDE, after projection away from the nullspace, the resulting quantum linear-system algorithm has overall gate complexity $\mathcal{O}(dn^3\alpha^{(k)}\log(1/\varepsilon))$, where $\alpha^{(k)}$ is the subnormalisation factor of the order-$k$ SLAC block-encoding and $\varepsilon$ denotes the algorithmic approximation error.

I am the presenting author Yes

Author

Rakshit Gharat (Macuqarie University)

Co-authors

Dominic Berry (Macquarie University) Gavin Brennen Gopikrishnan Muraleedharan (BTQ technologies)

Presentation materials

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