This preprint argues that the opacity of neural network training is a framework problem rather than an intrinsic property of the system. It introduces the Quantum Geometric Tensor (QGT) as the instrument for a physical description of training dynamics, with the QGT understood here as a geometric object on parameterized state families rather than as a claim about quantum hardware. The paper defines a dictionary between physics and training, situates that move within the historical construction of macroscopic physics, and shows that machine learning already uses physically meaningful state variables in fragmented form. It then introduces the Information-Geometry Balance Principle (IGBP), a scalar diagnostic measuring the balance between probe-space entropic drive and Berry-curvature resistance. The framework yields an operational event definition, the I-bit, and a set of testable predictions about critical geometric regimes in learning. It also states the key algebraic boundary sharply: standard real-valued architectures cannot produce the Berry-bearing sector required for a nontrivial IGBP, while Clifford-weighted architectures can. This is Paper I of a companion pair. Paper II provides the experimental tests of the framework and diagnostic. --Corrected April 2026 to fix bibliography entries, add public companion DOI references, and freeze the visible preprint date. No substantive scientific claims changed.-Corrected May 2026 to fix berry curvature sign convention and subsequent experiement results.
This preprint argues that the opacity of neural network training is a framework problem rather than an intrinsic property of the system. It introduces the Quantum Geometric Tensor (QGT) as the instrument for a physical description of training dynamics, with the QGT understood here as a geometric object on parameterized state families rather than as a claim about quantum hardware. The paper defines a dictionary between physics and training, situates that move within the historical construction of macroscopic physics, and shows that machine learning already uses physically meaningful state variables in fragmented form. It then introduces the Information-Geometry Balance Principle (IGBP), a scalar diagnostic measuring the balance between probe-space entropic drive and Berry-curvature resistance. The framework yields an operational event definition, the I-bit, and a set of testable predictions about critical geometric regimes in learning. It also states the key algebraic boundary sharply: standard real-valued architectures cannot produce the Berry-bearing sector required for a nontrivial IGBP, while Clifford-weighted architectures can. This is Paper I of a companion pair. Paper II provides the experimental tests of the framework and diagnostic. --Corrected April 2026 to fix bibliography entries, add public companion DOI references, and freeze the visible preprint date. No substantive scientific claims changed.-Corrected May 2026 to fix berry curvature sign convention and subsequent experiement results.
This preprint is the experimental companion to “The Quantum Geometric Tensor Reveals That Training Is a Physical Process. I. Framework and Diagnostic.” It tests the Quantum Geometric Tensor / Information-Geometry Balance Principle (QGT/IGBP) framework in a controlled three-run program on random 3-SAT, with the QGT understood here as a geometric object on parameterized state families rather than as a claim about quantum hardware. The experiment trains matched real-valued and Clifford-weighted architectures first under a physics-blind optimizer, then under physics-aware optimization, and finally under tap-aware closed-loop control with internal observability. The baseline result is exact: standard real-valued models preserve the algebraic flatline Ω = 0, while Clifford-weighted models activate the geometric instrument. Geometric events are already observed in Runs 1 and 2 under passive or lightly controlled training, while Run 3 shows that the critical regime can be steered and reveals the mature full-stack hierarchy. Across the full experiment, the paper reports 17 confirmed I-bit events across 10/18 transformer runs, 3 events across 3/18 TCN runs, and 0 events across all 36 RBM runs. A post hoc topology investigation then finds spectrally structured, Berry-active geometric events but no quantized topological transition on the tested surfaces. The experimental conclusion is that training is a measurable geometric process whose event capability depends jointly on encoding, dynamics, architecture, and observability. -Corrected April 2026 to fix bibliography entries, add public companion DOI references, and freeze the visible preprint date. No substantive scientific claims changed.-Correction May 2026 to fix berry curvature sign convention and subsequent experiment results.
The gap between the classical and quantum Fisher information matrices (CFIM and QFIM) separates what is operationally accessible through measurements from what is intrinsic to a quantum state. In the multiparameter setting, this quantum obstruction is generically not saturable. Motivated by the recently introduced semiclassical geometric tensor (SCGT), we perform an explicit information-geometric study for a class of pure four-parameter single-qutrit states (FPSQSs). These states are probed by a one-parameter family of measurements that interpolates between an uninformative POVM and a sharp projective measurement. We derive closed-form expressions for the CFIM, the quantum geometric tensor (QGT), and the SCGT. We show that the SCGT reproduces the QGT in the projective limit and vanishes in the trivial limit. The real part of the SCGT splits into two terms: the CFIM and an additional nonnegative measurement-transmitted metric in the phase sector. Its imaginary part provides a semiclassical Berry curvature. Its loss relative to the QGT is quantified by a measurement-dependent gap. Our results provide an exactly solvable four-parameter platform for the semiclassical geometric framework. They also clarify how realistic measurements read out the geometric content of quantum states, and how they partially degrade it.
A series of geometric concepts are formulated for PT-symmetric quantum mechanics and they are further unified into one entity, i.e., an extended quantum geometric tensor (QGT). The imaginary part of the extended QGT gives a Berry curvature whereas the real part induces a metric tensor on the system's parameter manifold. This results in a unified conceptual framework to understand and explore physical properties of PT-symmetric systems from a geometric perspective. To illustrate the usefulness of the extended QGT, we show how its real part, the metric tensor, can be exploited as a tool to detect quantum phase transitions as well as spontaneous PT symmetry breaking in PT-symmetric systems.
Abstract We propose physical distinguishability as the fundamental primitive underlying quantum mechanics, general relativity, and thermodynamics. A state is defined operationally: two states are physically distinct if a physical interaction or measurement can reveal a difference between them. From this principle, a geometric structure emerges on the space of physical states, generating a universal accessibility measure and a geometric notion of time. A single threshold condition appears across all three domains, corresponding to the quantum speed limit, event horizons in gravity, and critical phenomena in thermodynamics. Within this framework, the standard Schrödinger equation is recovered in the quantum sector, while Einstein gravity emerges in the thermodynamic horizon sector. The framework also provides a geometric origin for the Lorentzian structure of spacetime and identifies the roles of Planck’s constant, the speed of light, and Boltzmann’s constant as conversion factors linking different physical realizations of distinguishability dynamics. The theory predicts a characteristic vacuum distinguishability scale of approximately 103 μm and an associated energy scale of approximately 7.6 meV. These quantities connect quantum-vacuum physics, neutrino-scale phenomena, and cosmological scales within a single geometric description. The framework is tested experimentally on IBM Quantum superconducting processors. Across one-qubit, two-qubit, 127-qubit, and 156-qubit experiments performed on three independent Heron-generation backends, excitation probabilities collapse onto universal curves when parameterized by endpoint distinguishability. Protocols with identical control parameters but different endpoint distinguishabilities produce outcomes differing by up to a factor of 3.8, while protocols with identical endpoint distinguishabilities yield consistent results across independent processors. Cross-backend transfer errors remain below 1%. In addition to quantum-computing experiments, the framework suggests new tests in precision metrology, including atomic-force and scanning-tunneling microscopy, where large probe displacements may provide an independent route for testing vacuum distinguishability effects. Taken together, the theoretical construction, vacuum-sector predictions, and quantum-hardware experiments support distinguishability geometry as a unified and experimentally testable framework for physical dynamics.
Geometrical concepts in quantum mechanics, such as the Berry phase or quantum metric, have been studied extensively in the case of pure quantum states, but their generalisation to density operators is still undergoing active research. It has become clear that more than one valid approach exists and different definitions of the quantum geometric tensor (QGT) may give inequivalent results. In this report, we cover some of the foundations of quantum geometry for pure states, motivate the need for mixed-state generalisations, and examine some approaches in that direction. The final section analyses more closely a recent proposal, deemed the “Sjöqvist QGT” and argues that its imaginary part does not produce a generalisation of the Berry curvature.
We develop a detector-based framework in which quantum theory and spacetime geometry arise within a common inferential structure. Detector states and a detector kernel assign amplitudes to measurement events, allowing quantum theory to be interpreted as weighting hypothetical configurations consistent with observed detector clicks.
Using a Gaussian detector model with phase structure, we show that distinguishability induces an information geometry on detector-state space, described by the quantum geometric tensor. A Lorentzian spacetime metric is reconstructed from coupled position and time detector sectors, with both amplitude and phase deformations contributing to geometry. Scalar curvature acquires an operational interpretation as a local deficit of distinguishable outcomes.
We construct an effective consistency functional combining detector-deformation cost with a geometric term selected by locality and diffeomorphism invariance. Its stationary configurations yield the Einstein equation, with a stress-energy tensor arising from detector deformations. Vacuum configurations need not be flat, while local deformations provide an operational notion of matter and recover standard field-theoretic behavior in the scalar sector.