PHASE: Pauli Hierarchical Assembly on Subdivided Elements for Quantum-Compatible Operator Synthesis
- URL: http://arxiv.org/abs/2606.11478v1
- Date: Tue, 09 Jun 2026 22:13:50 GMT
- Title: PHASE: Pauli Hierarchical Assembly on Subdivided Elements for Quantum-Compatible Operator Synthesis
- Abstract summary: A naive Pauli expansion requires $(8lceil log with N rceil)$ operations, where $N$ denotes the number of degrees of freedom.<n>Existing approaches exploit algebraic sparsity or operator structure but do not incorporate the organization intrinsic to finite element discretizations.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Efficiently decomposing finite element stiffness matrices into the Pauli basis is challenging due to the exponential growth of Pauli strings with problem size. A naive Pauli expansion requires $Θ(8^{\lceil \log_2 N \rceil})$ operations, where $N$ denotes the number of degrees of freedom, rendering direct decomposition infeasible for large systems. Existing approaches exploit algebraic sparsity or operator structure but do not incorporate the geometric organization intrinsic to finite element discretizations, and consequently exhibit poor scaling for stiffness matrices. To address this problem, we introduce PHASE, a hierarchical, geometry-aware Pauli decomposition algorithm that leverages recursive mesh partitioning to organize element contributions across multiple spatial scales. PHASE employs a hybrid strategy that combines full- and reduced-space Tensorized Pauli Decomposition with Fast Walsh-Hadamard Transform-based aggregation to assemble global Pauli coefficients efficiently. We show that this approach yields a dimension-dependent reduction in the exponential scaling exponent of Pauli assembly asymptotic complexity relative to existing methods, reducing the cost from $2^{2{\lceil \log_2 N \rceil}}$ to $2^{γ_d{\lceil \log_2 N \rceil}}$ with $γ_d < 2$ under standard mesh regularity and balanced partition assumptions. These results substantially improve the feasibility of quantum-compatible operator synthesis for large-scale finite element models.
Related papers
- Efficient Compilation for Hamiltonian Simulation via Global Binary Symplectic Form Simplification [24.878868093642307]
Hamiltonian simulation is a core quantum workload, underpinning variational quantum algorithms and Trotterized time evolution.<n>We present Symphony, a holistic compilation approach built on the binary symplectic form (BSF) representation of Pauli strings.
arXiv Detail & Related papers (2026-08-12T02:38:42Z) - Efficient Pauli-decomposition and multistage state-refinement for tensor network based differential equation solver [0.0]
tensor network (TN) methods can be highly productive for PDEs giving rise to Sturm--Liouville problems.<n>Most methods for generating MPOs of large operators without explicit tensor-product structure require prohibitively large memory.<n>We present techniques to mitigate both challenges for certain sparse, structured differential operators.
arXiv Detail & Related papers (2026-07-09T07:10:01Z) - An efficient Pauli decomposition algorithm for structured matrices [0.12744523252873352]
We consider a promise version of a Pauli decomposition problem in which the matrix is guaranteed to have support on only $k = mathsfpoly(n)$ Pauli strings.<n>We present a randomized classical algorithm that does take advantage of this sparsity and recovers the exact Pauli decomposition with success probability of at least $1 - $.
arXiv Detail & Related papers (2026-06-30T16:57:07Z) - SILAGE: Memory-Efficient, Full-Gradient-Free Nonconvex Optimization for Nested Finite Sums [51.49970814177172]
Empirical risk on datasets naturally exhibits similarities in $N=nm$ total samples.<n>We provide an analysis that avoids pessimistic convergence analysis.<n>Our results improve existing state-of-the-art regimes.
arXiv Detail & Related papers (2026-06-14T14:11:07Z) - Block encoding of sparse matrices with a periodic diagonal structure [67.45502291821956]
We provide an explicit quantum circuit for block encoding a sparse matrix with a periodic diagonal structure.<n>Various applications for the presented methodology are discussed in the context of solving differential problems.
arXiv Detail & Related papers (2026-02-11T07:24:33Z) - A Quantum Algorithm for the Finite Element Method [0.0]
finite element method (FEM) is a cornerstone numerical technique for solving partial differential equations (PDEs)<n>We present $textbfQu-FEM$, a fault-tolerant era quantum algorithm for the finite element method.
arXiv Detail & Related papers (2025-10-20T23:00:12Z) - Efficient Quantum Access Model for Sparse Structured Matrices using Linear Combination of Things [0.6138671548064355]
We present a novel framework for Linear Combination of Unitaries (LCU)-style decomposition tailored to structured sparse matrices.<n>LCU is a foundational primitive in both variational and fault-tolerant quantum algorithms.<n>We introduce the Sigma basis, a compact set of simple, non-unitary operators that can better capture sparsity and structure.
arXiv Detail & Related papers (2025-07-04T17:05:07Z) - Stochastic Momentum Methods for Non-smooth Non-Convex Finite-Sum Coupled Compositional Optimization [68.22688819802622]
We propose a new state-of-the-art complexity of $O(/epsilon)$ for finding an (nearly) $'level KKT solution.<n>By applying our hinge-of-the-art complexity of $O(/epsilon)$ for finding an (nearly) $'level KKT solution, we achieve a new state-of-the-art complexity of $O(/epsilon)$ for finding an (nearly) $'level KKT solution.
arXiv Detail & Related papers (2025-06-03T06:31:59Z) - On The Sample Complexity Bounds In Bilevel Reinforcement Learning [49.19950489963245]
Bilevel reinforcement learning (BRL) has emerged as a powerful framework for aligning generative models.<n>We present the first sample of $mathcalO(epsilon)$ in continuous state-action complexity.<n>Our analysis also extends complexity improving upon existing bounds of $mathcalO(epsilon)$.
arXiv Detail & Related papers (2025-03-22T04:22:04Z) - Quantum many-body simulations with PauliStrings.jl [0.0]
We present the Julia package PauliStrings for quantum many-body simulations.<n>It performs fast operations on the Pauli group by encoding Pauli strings in binary.<n>We show that this representation allows for easy encoding of any geometry.
arXiv Detail & Related papers (2024-10-12T21:18:47Z) - Pauli weight requirement of the matrix elements in time-evolved local operators: dependence beyond the equilibration temperature [0.0]
We investigate whether "light" Pauli strings can be applied to quenches starting from homogeneous product states.
In some cases, the light Pauli strings suffice to describe the dynamics, enabling efficient simulation with current algorithms.
We analyze this behavior using a newly introduced measure of complexity, the Operator Weight Entropy.
arXiv Detail & Related papers (2024-09-20T16:02:19Z) - On the Constant Depth Implementation of Pauli Exponentials [49.48516314472825]
We decompose $Zotimes n$ exponentials of arbitrary length into circuits of constant depth using $mathcalO(n)$ ancillae and two-body XX and ZZ interactions.<n>We prove the correctness of our approach, after introducing novel rewrite rules for circuits which benefit from qubit recycling.
arXiv Detail & Related papers (2024-08-15T17:09:08Z) - Quantum Realization of the Finite Element Method [0.0]
This paper presents a quantum algorithm for the solution of second-order linear elliptic partial differential equations discretized by $d$-linear finite elements.<n>An essential step in the construction is a BPX preconditioner, which transforms the linear system into a sufficiently well-conditioned one.<n>We provide a constructive proof demonstrating that, for any fixed dimension, our quantum algorithm can compute suitable functionals of the solution to a given tolerance.
arXiv Detail & Related papers (2024-03-28T15:44:20Z) - Poly-NL: Linear Complexity Non-local Layers with Polynomials [76.21832434001759]
We formulate novel fast NonLocal blocks, capable of reducing complexity from quadratic to linear with no loss in performance.
The proposed method, which we dub as "Poly-NL", is competitive with state-of-the-art performance across image recognition, instance segmentation, and face detection tasks.
arXiv Detail & Related papers (2021-07-06T19:51:37Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.