Setareh Maghsudi

Ruhr University Bochum

Unclaimed · AI-structured profileORCID OpenAlex

Setareh Maghsudi — quantum game theorist at Ruhr University Bochum optimizing equilibrium-finding in quantum games

papers here

reviewed by Evolve

first-author

corresponding

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works · OpenAlex

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h-index · OpenAlex

Bibliometric figures come from OpenAlex (2026-10-16) and cover the author's entire public record, not just the papers listed here. Reproducibility signal comes from Evolve's own reviews.

Research profile

Output—

Not yet scored: the available snapshot covers only two 2026 arXiv papers reviewed by Evolve, so full publication counts, venues, and productivity over time are unavailable. This axis would measure total research output and its trajectory.

Impact—

Not yet scored: no citation counts, h-index, or venue-level influence data were provided, so scholarly impact cannot be estimated. This axis would measure citations and uptake of the quantum game theory work across communities.

Focus0/100

Focus scores 0/100 in the current radar. The underlying field distribution splits evenly (0.5/0.5) between two neighboring strands of quantum game theory — quantum information × multi-agent optimization and quantum information × algorithmic game theory — and both reviewed papers pursue one theme, optimization-based equilibrium computation. With only two papers, the focus measure reflects the thin evidence base rather than scattered interests.

Collaboration28/100

The collaboration dimension scores 28/100, based on 3 distinct coauthors in the current snapshot. The listed frequent collaborators are Alireza Habibi — the only name appearing twice, marking the closest working tie — and Luis F. Abanto Leon. Maghsudi sits in the last-author position on both reviewed 2026 papers, a pattern consistent with senior/supervisory authorship in a compact, stable group rather than a broad co-authorship network; the modest score partly reflects the very small sample.

Activity—

Not yet scored: the snapshot contains no multi-year publication history, only two 2026 arXiv preprints, so research cadence and continuity cannot be assessed. This axis would measure publication frequency and recent activity over time.

Reproducibility55/100

Reproducibility scores 55/100, a mean across the 2 reviewed papers, both rated medium readiness. The MEFPIA paper reports working experiments that empirically beat MMWU but lacks proven convergence; the USMEA paper is theoretically solid yet offers no released code and small-scale tests. The score signals empirical grounding with a clear gap: releasing code and benchmarks would lift it materially.

Research summary

Setareh Maghsudi is a researcher at Ruhr University Bochum (ORCID 0000-0002-0647-611X) whose cataloged work sits at the intersection of quantum information science, algorithmic game theory, and multi-agent optimization. The Evolve snapshot is compact but coherent: two 2026 arXiv preprints, both on computing Nash equilibria in quantum games, with Maghsudi in the last-author position on each. The first, MEFPIA (matrix exponential fixed-point iteration), applies an entropy-regularized, annealed fixed-point search that guides quantum-game agents to equilibrium and empirically outperforms the MMWU baseline, although convergence remains unproven and the testbeds are small. The second, USMEA, brings Riemannian optimization to multiplayer mixed-strategy quantum games on product unitary manifolds within the Eisert-Wilkens-Lewenstein framework; its theory is rated solid and honest, but the experiments are incremental and no code is released. Bibliometrically, the profile scores 28/100 on collaboration (3 distinct coauthors; frequent partners Alireza Habibi and Luis F. Abanto Leon), 0/100 on focus, and 55/100 on reproducibility (a mean over 2 reviewed papers, both rated medium readiness), while output, impact, and activity lack sufficient data to score. This is therefore an early-stage profile: a tightly themed line of work on optimization for quantum-game equilibria, awaiting a broader publication record for full assessment.

Collaboration pattern

Within the Evolve snapshot, Setareh Maghsudi works with a small, stable circle: 3 distinct coauthors in total. Alireza Habibi is the most frequent (appearing twice in the frequency list), and Luis F. Abanto Leon is the other listed collaborator. Maghsudi holds the last-author position on both reviewed 2026 arXiv papers, consistent with a senior or supervisory role. Collaboration is concentrated rather than distributed — likely group-internal — and the picture may change as more papers enter the catalog.

Research keywords

quantum game theoryquantum informationalgorithmic game theoryNash equilibriumGutoski-Watrous gamesmatrix exponential learningentropy regularizationsimulated annealingEisert-Wilkens-Lewenstein gameRiemannian optimizationunitary manifoldmixed strategies

Highlights

MEFPIA: annealed fixed-point iteration for quantum-game equilibria
In a 2026 arXiv paper, Maghsudi's group (last author) proposes an entropy-regularized, annealed matrix-exponential fixed-point iteration that guides quantum-game agents toward Nash equilibrium in Gutoski-Watrous-type games, empirically outperforming the MMWU baseline; Evolve flags unproven convergence and small testbeds, and rates reproducibility medium.
USMEA: Riemannian optimization for multiplayer quantum games
A second 2026 arXiv preprint develops geometry-aware learning on product unitary manifolds for multiplayer mixed-strategy quantum games in the Eisert-Wilkens-Lewenstein framework. Evolve rates the theory solid and honest, but incremental, with small-scale experiments and no released code; reproducibility readiness is medium.
A concentrated agenda: optimization for quantum-game equilibrium computation
Both cataloged 2026 papers attack the same problem — driving quantum-game agents to Nash equilibrium — from complementary optimization angles (fixed-point iteration vs. Riemannian methods on unitary manifolds). Evolve's verdicts converge on the same caveats: strong theory, small testbeds, and unreleased code limit current verification.

Timeline

2026Posts USMEA on arXiv: Riemannian optimization for multiplayer quantum games on product unitary manifolds, with Maghsudi as last author.
2026Posts the MEFPIA paper on arXiv, using entropy-regularized matrix-exponential fixed-point iteration to guide quantum-game agents to equilibrium.
2026Both preprints enter the Evolve review catalog, each rated medium reproducibility readiness; the collaboration footprint shows 3 distinct coauthors, led by Alireza Habibi.

Papers in the Evolve catalog

Frequent co-authors

Alireza Habibi×1 Alireza Habibi×1 Luis F. Abanto Leon×1

About this profile

This profile is AI-structured by Evolve.Pub from public bibliographic data (OpenAlex) and Evolve's own paper reviews. It is not written or endorsed by the researcher unless the profile is claimed. Radar dimensions are computed from real bibliometrics with fixed formulas — raw figures are shown alongside; missing dimensions mean insufficient data, never zero. Errors? Claim the profile to correct or hide it.

Bibliometric scores are computed from a very small snapshot: only 2 reviewed papers and 3 distinct coauthors, so all radar values are fragile.
Output, impact, and activity dimensions are unscored because citation counts, publication history, and venue data were not available in the input.
Both cataloged papers are 2026 arXiv preprints; peer-reviewed publication status is unknown and country metadata is missing (null in the source).
Field distribution is derived from Evolve's own review labels for the two papers, not from a broader subject classification of the full publication record.