Efficient explicit gate construction of block-encoding for Hamiltonians needed for simulating partial differential equations
Nikita Guseynov, Xiajie Huang, Nana Liu

TL;DR
This paper presents an explicit, efficient quantum block-encoding method for Hamiltonians used in simulating PDEs, achieving polynomial and exponential speedups in spatial and dimensional complexity.
Contribution
It introduces a novel explicit construction of block-encoding for Hamiltonians of PDEs, enabling efficient quantum simulation with significant speedups.
Findings
Achieves squared logarithmic scaling in spatial partitioning
Provides polynomial speedup over classical methods
Extends to multi-dimensional PDEs with exponential acceleration
Abstract
One of the most promising applications of quantum computers is solving partial differential equations (PDEs). By using the Schrodingerisation technique - which converts non-conservative PDEs into Schrodinger equations - the problem can be reduced to Hamiltonian simulations. The particular class of Hamiltonians we consider is shown to be sufficient for simulating almost any linear PDE. In particular, these Hamiltonians consist of discretizations of polynomial products and sums of position and momentum operators. This paper addresses an important gap by efficiently loading these Hamiltonians into the quantum computer through block-encoding. The construction is explicit and efficient in terms of one- and two-qubit operations, forming a fundamental building block for constructing the unitary evolution operator for that class of Hamiltonians. The proposed algorithm demonstrates a squared…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsNumerical methods for differential equations · Electromagnetic Simulation and Numerical Methods · Control and Stability of Dynamical Systems
