Promise of Graph Sparsification and Decomposition for Noise Reduction in QAOA: Analysis for Trapped-Ion Compilations
- URL: http://arxiv.org/abs/2406.14330v1
- Date: Thu, 20 Jun 2024 14:00:09 GMT
- Title: Promise of Graph Sparsification and Decomposition for Noise Reduction in QAOA: Analysis for Trapped-Ion Compilations
- Authors: Jai Moondra, Philip C. Lotshaw, Greg Mohler, Swati Gupta,
- Abstract summary: We develop new approximate compilation schemes to solve the Max-Cut problem.
Results are based on principles of graph sparsification and decomposition.
We demonstrate significant reductions in noise are obtained in our new compilation approaches.
- Score: 5.451583832235867
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: We develop new approximate compilation schemes that significantly reduce the expense of compiling the Quantum Approximate Optimization Algorithm (QAOA) for solving the Max-Cut problem. Our main focus is on compilation with trapped-ion simulators using Pauli-$X$ operations and all-to-all Ising Hamiltonian $H_\text{Ising}$ evolution generated by Molmer-Sorensen or optical dipole force interactions, though some of our results also apply to standard gate-based compilations. Our results are based on principles of graph sparsification and decomposition; the former reduces the number of edges in a graph while maintaining its cut structure, while the latter breaks a weighted graph into a small number of unweighted graphs. Though these techniques have been used as heuristics in various hybrid quantum algorithms, there have been no guarantees on their performance, to the best of our knowledge. This work provides the first provable guarantees using sparsification and decomposition to improve quantum noise resilience and reduce quantum circuit complexity. For quantum hardware that uses edge-by-edge QAOA compilations, sparsification leads to a direct reduction in circuit complexity. For trapped-ion quantum simulators implementing all-to-all $H_\text{Ising}$ pulses, we show that for a $(1-\epsilon)$ factor loss in the Max-Cut approximation ($\epsilon>0)$, our compilations improve the (worst-case) number of $H_\text{Ising}$ pulses from $O(n^2)$ to $O(n\log(n/\epsilon))$ and the (worst-case) number of Pauli-$X$ bit flips from $O(n^2)$ to $O\left(\frac{n\log(n/\epsilon)}{\epsilon^2}\right)$ for $n$-node graphs. We demonstrate significant reductions in noise are obtained in our new compilation approaches using theory and numerical calculations for trapped-ion hardware. We anticipate these approximate compilation techniques will be useful tools in a variety of future quantum computing experiments.
Related papers
- Obtaining Lower Query Complexities through Lightweight Zeroth-Order Proximal Gradient Algorithms [65.42376001308064]
We propose two variance reduced ZO estimators for complex gradient problems.
We improve the state-of-the-art function complexities from $mathcalOleft(minfracdn1/2epsilon2, fracdepsilon3right)$ to $tildecalOleft(fracdepsilon2right)$.
arXiv Detail & Related papers (2024-10-03T15:04:01Z) - Non-Iterative Disentangled Unitary Coupled-Cluster based on Lie-algebraic structure [0.0]
Fixed Unitary Coupled-Cluster (UCC) ans"atze are attractive for performing quantum chemistry Variational Quantumsolver (VQE) computations.
We introduce $k$-NI-DUCC, a fixed and Non-iterative Disentangled Unitary Coupled-Cluster compact ansatz.
arXiv Detail & Related papers (2024-08-26T14:19:53Z) - Quantum encoder for fixed Hamming-weight subspaces [0.0]
We present an exact $n$-qubit computational-basis amplitude encoder of real- or complex-principle data vectors of $d=binomnk$ provided in analytical form.
We also perform an experimental proof-of-principle demonstration of our scheme on a commercial trapped-ion quantum computer.
arXiv Detail & Related papers (2024-05-30T18:26:41Z) - Towards large-scale quantum optimization solvers with few qubits [59.63282173947468]
We introduce a variational quantum solver for optimizations over $m=mathcalO(nk)$ binary variables using only $n$ qubits, with tunable $k>1$.
We analytically prove that the specific qubit-efficient encoding brings in a super-polynomial mitigation of barren plateaus as a built-in feature.
arXiv Detail & Related papers (2024-01-17T18:59:38Z) - Quantum Simulation of the First-Quantized Pauli-Fierz Hamiltonian [0.5097809301149342]
We show that a na"ive partitioning and low-order splitting formula can yield, through our divide and conquer formalism, superior scaling to qubitization for large $Lambda$.
We also give new algorithmic and circuit level techniques for gate optimization including a new way of implementing a group of multi-controlled-X gates.
arXiv Detail & Related papers (2023-06-19T23:20:30Z) - Quantum Resources Required to Block-Encode a Matrix of Classical Data [56.508135743727934]
We provide circuit-level implementations and resource estimates for several methods of block-encoding a dense $Ntimes N$ matrix of classical data to precision $epsilon$.
We examine resource tradeoffs between the different approaches and explore implementations of two separate models of quantum random access memory (QRAM)
Our results go beyond simple query complexity and provide a clear picture into the resource costs when large amounts of classical data are assumed to be accessible to quantum algorithms.
arXiv Detail & Related papers (2022-06-07T18:00:01Z) - A lower bound on the space overhead of fault-tolerant quantum computation [51.723084600243716]
The threshold theorem is a fundamental result in the theory of fault-tolerant quantum computation.
We prove an exponential upper bound on the maximal length of fault-tolerant quantum computation with amplitude noise.
arXiv Detail & Related papers (2022-01-31T22:19:49Z) - Solving correlation clustering with QAOA and a Rydberg qudit system: a
full-stack approach [94.37521840642141]
We study the correlation clustering problem using the quantum approximate optimization algorithm (QAOA) and qudits.
Specifically, we consider a neutral atom quantum computer and propose a full stack approach for correlation clustering.
We show the qudit implementation is superior to the qubit encoding as quantified by the gate count.
arXiv Detail & Related papers (2021-06-22T11:07:38Z) - Generating Target Graph Couplings for QAOA from Native Quantum Hardware
Couplings [3.2622301272834524]
We present methods for constructing any target coupling graph using limited global controls in an Ising-like quantum spin system.
Our approach is motivated by implementing the quantum approximate optimization algorithm (QAOA) on trapped ion quantum hardware.
Noisy simulations of Max-Cut QAOA show that our implementation is less susceptible to noise than the standard gate-based compilation.
arXiv Detail & Related papers (2020-11-16T18:43:09Z) - Hybrid Stochastic-Deterministic Minibatch Proximal Gradient:
Less-Than-Single-Pass Optimization with Nearly Optimal Generalization [83.80460802169999]
We show that HSDMPG can attain an $mathcalObig (1/sttnbig)$ which is at the order of excess error on a learning model.
For loss factors, we prove that HSDMPG can attain an $mathcalObig (1/sttnbig)$ which is at the order of excess error on a learning model.
arXiv Detail & Related papers (2020-09-18T02:18:44Z) - Quantum Speedup for Graph Sparsification, Cut Approximation and
Laplacian Solving [1.0660480034605238]
"spectral sparsification" reduces number of edges to near-linear in number of nodes.
We show a quantum speedup for spectral sparsification and many of its applications.
Our algorithm implies a quantum speedup for solving Laplacian systems.
arXiv Detail & Related papers (2019-11-17T17:29:40Z)
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.