Paper

{
  "raw_xml": "<entry>\n    <id>http://arxiv.org/abs/2602.23976v1</id>\n    <title>Large-scale portfolio optimization on a trapped-ion quantum computer</title>\n    <updated>2026-02-27T12:36:14Z</updated>\n    <link href='https://arxiv.org/abs/2602.23976v1' rel='alternate' type='text/html'/>\n    <link href='https://arxiv.org/pdf/2602.23976v1' rel='related' title='pdf' type='application/pdf'/>\n    <summary>We present an end-to-end pipeline for large-scale portfolio selection with cardinality constraints and experimentally demonstrate it on trapped-ion quantum processors using hardware-aware decomposition. Building on RMT-based correlation-matrix denoising and community detection, we identify correlated asset groups and introduce a correlation-guided greedy splitting scheme that caps each cluster by the executable qubit budget. Each cluster defines a hardware-embeddable QUBO subproblem that we solve using bias-field digitized counterdiabatic quantum optimization (BF-DCQO), a non-variational method that avoids classical parameter-training loops. We recombine low-energy candidates into global portfolios and enforce feasibility with a two-stage post-processing routine: fast repair followed by a cardinality-preserving swap local search. We benchmark the workflow on a 250-asset universe taken from the S&amp;P 500 and execute subproblems on a 64-qubit Barium development system similar to the forthcoming IonQ Tempo line. We observe that larger executable subproblem sizes reduce decomposition error and systematically improve final objective values and risk-return trade-offs relative to randomized baselines under identical post-processing. Overall, the results establish a hardware-tested route for scaling financial optimization problems, defined by a trade space in which executable problem size and circuit cost are balanced against the resulting solution quality.</summary>\n    <category scheme='http://arxiv.org/schemas/atom' term='quant-ph'/>\n    <published>2026-02-27T12:36:14Z</published>\n    <arxiv:comment>10 pages, 6 figures</arxiv:comment>\n    <arxiv:primary_category term='quant-ph'/>\n    <author>\n      <name>Alejandro Gomez Cadavid</name>\n    </author>\n    <author>\n      <name>Ananth Kaushik</name>\n    </author>\n    <author>\n      <name>Pranav Chandarana</name>\n    </author>\n    <author>\n      <name>Miguel Angel Lopez-Ruiz</name>\n    </author>\n    <author>\n      <name>Gaurav Dev</name>\n    </author>\n    <author>\n      <name>Willie Aboumrad</name>\n    </author>\n    <author>\n      <name>Qi Zhang</name>\n    </author>\n    <author>\n      <name>Claudio Girotto</name>\n    </author>\n    <author>\n      <name>Sebastián V. Romero</name>\n    </author>\n    <author>\n      <name>Martin Roetteler</name>\n    </author>\n    <author>\n      <name>Enrique Solano</name>\n    </author>\n    <author>\n      <name>Marco Pistoia</name>\n    </author>\n    <author>\n      <name>Narendra N. Hegade</name>\n    </author>\n  </entry>"
}