aiqbench analysis
This paper proposes a foundational framework for quantum theory based on the principle of bounded information and measurement independence, effectively reconstructing quantum mechanics through statistical estimators and manifold metrics. By employing a divide-and-conquer approach to partition Hamiltonian variables, the authors derive the linear and probabilistic structures inherent to quantum systems from these axiomatic constraints. The work advances theoretical understanding by formalizing how limited information capacity defines the architecture of physical reality within quantum mechanics.
Bounded information as a foundation for quantum theory
arXiv:2506.18549v3 Announce Type: replace Abstract: The purpose of this paper is to formalize the concept that best synthesizes our intuitive understanding of quantum mechanics - that the information carried by a system is limited - and, from this principle, to construct the foundations of quantum theory. In our discussion, we also introduce a second important hypothesis: if a measurement closely approximates an ideal one in terms of experimental precision, the information it provides about a physical system is independent of the measurement method and, specifically, of the system's physical quantities being measured. This principle can be expressed in terms of metric properties of a manifold whose points represent the state of the system. These and other reasonable hypotheses provide the foundation for a framework of quantum reconstruction. The theory presented in this paper is based on a description of physical systems in terms of their statistical properties, specifically statistical parameters, and focuses on the study of estimators for these parameters. To achieve the goal of quantum reconstruction, a divide-and-conquer approach is employed, wherein the space of two discrete conjugate Hamiltonian variables is partitioned into a binary tree of nested sets. This approach naturally leads to the reconstruction of the linear and probabilistic structure of quantum mechanics.
Abstract:The purpose of this paper is to formalize the concept that best synthesizes our intuitive understanding of quantum mechanics - that the information carried by a system is limited - and, from this principle, to construct the foundations of quantum theory. In our discussion, we also introduce a second important hypothesis: if a measurement closely approximates an ideal one in terms of experimental precision, the information it provides about a physical system is independent of the measurement method and, specifically, of the system's physical quantities being measured. This principle can be expressed in terms of metric properties of a manifold whose points represent the state of the system. These and other reasonable hypotheses provide the foundation for a framework of quantum reconstruction. The theory presented in this paper is based on a description of physical systems in terms of their statistical properties, specifically statistical parameters, and focuses on the study of estimators for these parameters. To achieve the goal of quantum reconstruction, a divide-and-conquer approach is employed, wherein the space of two discrete conjugate Hamiltonian variables is partitioned into a binary tree of nested sets. This approach naturally leads to the reconstruction of the linear and probabilistic structure of quantum mechanics.
arXiv:2506.18549 [quant-ph]
(or arXiv:2506.18549v3 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2506.18549 Focus to learn more arXiv-issued DOI via DataCite
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 · 290 words
Related coverage

Measurement incompatibility in Bayesian multiparameter quantum estimation
Quantum Journal · Aug 13, 2026

Lattice-Based Cryptography Explained
Quantum Zeitgeist · Aug 15, 2026

Nature’s speed limit for thermalization is rooted in quantum information
Quantum Zeitgeist · Sep 24, 2026

Fisher matrix reveals limits of quantum learning speed
Quantum Zeitgeist · Sep 26, 2026