Skip to content
aiqbench takeQuantum Computing

aiqbench analysis

This is a theoretical quantum-information method that uses the history state formalism and entanglement entropy as analytical tools for classical financial time series. It contains no hardware, algorithm benchmarks, or learning component, so readers should treat the volatility indicators as unvalidated against standard measures until there is broader empirical testing. The main takeaway for quantum researchers is the mathematical mapping of data series onto coherent-state overlaps, not any demonstrated computational advantage.
Sources coveringarXiv, Quantum Frontiers, InfoQ
What this isA model's reading of the article and related coverage, written for aiqbench. Not the publisher's words.

History state formalism for time series with application to finance

arXiv2 min read

arXiv:2603.12132v3 Announce Type: replace Abstract: We present a method for analyzing general time series by employing the history state formalism of quantum mechanics. This formalism allows us to describe a complete evolution based on a single quantum state, the history state, which simultaneously includes -also as a quantum system- the reference clock. It naturally leads to the concept of system-time entanglement, with the ensuing entanglement entropy constituting a measure of the effective number of distinguishable states visited in the history. Through a quantum coherent state embedding of the time series data, it is then possible to associate a quantum history state to the series. The gaussian overlap between these coherent states provides thus a smooth measure of distinguishability between the series data. The eigenvalues of the corresponding overlap matrix determine in fact the entanglement spectrum and entropy of the history state, which provide a rigorous characterization of the evolution. As illustration, the formalism is applied to typical financial time-series data. Through the entanglement entropy and spectrum, different evolution regimes can be identified. Entanglement based volatility indicators are also derived, and compared with standard volatility measures.

Abstract:We present a method for analyzing general time series by employing the history state formalism of quantum mechanics. This formalism allows us to describe a complete evolution based on a single quantum state, the history state, which simultaneously includes -also as a quantum system- the reference clock. It naturally leads to the concept of system-time entanglement, with the ensuing entanglement entropy constituting a measure of the effective number of distinguishable states visited in the history. Through a quantum coherent state embedding of the time series data, it is then possible to associate a quantum history state to the series. The gaussian overlap between these coherent states provides thus a smooth measure of distinguishability between the series data. The eigenvalues of the corresponding overlap matrix determine in fact the entanglement spectrum and entropy of the history state, which provide a rigorous characterization of the evolution. As illustration, the formalism is applied to typical financial time-series data. Through the entanglement entropy and spectrum, different evolution regimes can be identified. Entanglement based volatility indicators are also derived, and compared with standard volatility measures.

arXiv:2603.12132 [quant-ph]

(or arXiv:2603.12132v3 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2603.12132 Focus to learn more arXiv-issued DOI via DataCite

https://doi.org/10.1103/xygw-mhp6 Focus to learn more DOI(s) linking to related resources

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Full text under the publisher's open licence · 279 words

Related coverage