MétaCan
Menu
Back to cohort

A Quantum-Walk-Unitary HHL Matrix Equation Solver and Its Challenges in the NISQ Era

2023· article· en· W4385332781 on OpenAlexaff
Xinbo Li, Christopher Phillips, Ian Jeffrey, Vladimir Okhmatovski

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicQuantum Computing Algorithms and Architecture
Canadian institutionsUniversity of WaterlooUniversity of Manitoba
Fundersnot available
KeywordsInitializationQuantum phase estimation algorithmQuantum walkSolverQuantum circuitQuantum algorithmComputer scienceQuantum computerHamiltonian (control theory)Unitary matrixQuantumAlgorithmUnitary stateMathematicsQuantum error correctionQuantum mechanicsPhysicsMathematical optimizationLaw

Abstract

fetched live from OpenAlex

The Harrow/Hassidim/Lloyd algorithm is a celebrated quantum matrix equation solver. Its Hamiltonian simulation involves a quantum walk process. A newly developed Quantum Walk Unitary HHL (QWU-HHL) leverages the spectral relationship between the quantum walk operator and the system matrix, and uses the quantum walk operator as its unitary in the phase estimation directly, allowing Hamiltonian simulation in the classical HHL to be removed, hence improving its efficiency. Despite the potential of being exponentially faster than classical matrix equation solvers, HHL is not feasible in the noisy intermediate-scale quantum era because its quantum circuit is too deep to preserve an accurate solution. In this work, we investigate the error behavior of QWU-HHL on a 7-qubit quantum system. Instead of executing the entire circuit, the behaviors of its sub-circuits which each contain only an initialization and a single gate are recorded. The error caused by isolated initialization and operation are analyzed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.943
Threshold uncertainty score0.328

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.056
GPT teacher head0.277
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same topicQuantum Computing Algorithms and ArchitectureFrench-language works237,207