Architecture-Sensitive Noise Fingerprints in Classical Statistics of Quantum States

Bob Jefferson

Published Dec 29, 2025• 0 citations

Abstract

This archive accompanies the paper Architecture-Sensitive Noise Fingerprints in Classical Statistics of Quantum States. It contains the full manuscript, all figures appearing in the paper, and the Python scripts used to generate the numerical results. The project demonstrates that classical measurement statistics obtained from noisy quantum states retain reproducible, architecture-dependent structure. Even under standard local, Markovian noise models, simple low-order classical features—such as entropy, maximum probability, parity mass, and Hamming-weight distributions—encode diagnostic fingerprints of the underlying quantum state architecture. The analysis focuses on stabilizer states (including GHZ, cluster, and star graph states), fixed measurement bases, and exact probability distributions. No machine learning, optimisation, tomography, or state reconstruction is used. All results are generated using transparent, reproducible numerical simulations. The contents of this archive are: LaTeX source and compiled PDF of the manuscript All figures used in the paper (PDF/PNG) Python scripts for generating the figures and classical feature data A README describing structure and reproducibility This archive is intended to support transparency, reproducibility, and reuse of the results, and may serve as a lightweight reference for diagnostic approaches to quantum noise and state architecture.

DOI: 10.5281/zenodo.18087506

Related papers

Mapping the Limits of Architecture-Sensitive Noise Fingerprints in Quantum States

Bob Jefferson

This repository accompanies the preprint “Mapping the Limits of Architecture-Sensitive Noise Fingerprints in Quantum States.” The work investigates when and why simple classical measurement statistics obtained from noisy quantum systems retain information about the underlying quantum state architecture, and when such information collapses entirely. Building on earlier results demonstrating the existence of architecture-dependent classical fingerprints for stabilizer states under local noise, this study systematically maps the boundaries and failure modes of that phenomenon. Using exact probability distributions for small-to-moderate system sizes, we introduce controlled departures from stabilizer structure and track the degradation of classical features under dephasing and depolarizing noise. The analysis reveals sharply conditional survival of architecture sensitivity, a consistent feature-dependent collapse ordering, and a strong dependence on measurement basis and perturbation geometry. In particular, regimes of genuine diagnostic blindness are identified, where classical statistics become architecture-indistinguishable even though the underlying quantum states remain highly structured. The archive includes the full manuscript (PDF and LaTeX source), all figures appearing in the paper, the scripts required to reproduce the numerical experiments and figures, and the corresponding data outputs. All results are based on exact numerical evaluation (no sampling, optimisation, tomography, or machine learning). The work is intended as a lightweight, diagnostic limits study, providing practical guidance on when simple classical measurements are informative and when their use is fundamentally unreliable. Together with the companion papers in this series, the repository contributes to a coherent empirical and theoretical programme on the classical observability of quantum structure under noise.Version 1.1 notes.This revision clarifies the collapse criterion used to define architecture indistinguishability, explicitly specifies numerical precision and robustness checks, and adds a qualitative reliability chart summarising when different classical features remain informative. The presentation of noise-model dependence, system-size stability, and perturbation geometry has been sharpened, and the relationship to companion papers in the series has been made explicit. No new phenomena are introduced; the update improves transparency, interpretability, and practical usability of the results.

Dec 31, 20250 citations

Irreversibility and Ordering in Classical Observability of Quantum Structure

Bob Jefferson

This repository contains the source files for the paper: Irreversibility and Ordering in Classical Observability of Quantum Structure The paper develops a formal framework explaining when and why classical statistics extracted from noisy quantum systems retain architecture-dependent information, and when they inevitably lose it. Building on a trilogy of earlier empirical and operational studies, the work introduces the diagnostic pipeline as a fundamental object of analysis: a fixed composition of a noise channel, a measurement choice, and a deterministic classical feature map. Such pipelines are shown to form a preorder under information-degrading transformations, induced by standard monotonicity principles. Within this framework, several phenomena observed empirically are shown to be structural necessities rather than numerical accidents: Feature-dependent collapse arises from deterministic feature post-processing below the identity (full-distribution) pipeline. Basis-dependent diagnostic blindness corresponds to incomparability between pipelines using different fixed measurement bases. Irreversible loss of distinguishability follows from genuine noise degradation and cannot be undone by downstream measurement or feature choices. The paper proves general monotonicity results, establishes generic incomparability of measurement bases, and derives falsifiable predictions linking noise–basis alignment to collapse thresholds for population-encoded distinctions. Minimal empirical consistency checks against the companion trilogy datasets are provided. The framework yields practical design principles for lightweight diagnostics in NISQ-era experiments, clarifying fundamental limits on classical access to quantum structure under realistic constraints. Contents Irreversibility_and_Ordering_in_Classical_Observability_of_Quantum_Structure.pdfFinal compiled manuscript. Irreversibility_and_Ordering_in_Classical_Observability_of_Quantum_Structure.texLaTeX source (self-contained; bibliography and figures embedded). Relation to Other Work This paper provides the formal, structural foundation for a companion trilogy on architecture-sensitive classical fingerprints under noise, including: Feature-dependent collapse under fixed pipelines Basis-dependent diagnostic blindness Selective transcription as an operational principle The present work unifies and explains these results within a single information-theoretic preorder framework. Status Submission-ready manuscript.Intended for submission to a peer-reviewed journal in quantum information theory. Licence See LICENSE.

Jan 10, 20260 citations

Structure-Sensitive Quantum Networks: A Geometric Consistency Framework for Entanglement Stability and Quantum Internet Reliability — Reproducibility Package v3.0

Halil Özbil

This repository contains the full reproducibility package for: "Structure-Sensitive Quantum Networks: A Geometric Consistency Framework for Entanglement Stability and Quantum Internet Reliability" This work investigates a structure-sensitive approach for monitoring quantum network stability beyond conventional fidelity-only metrics. The proposed Ω_QN functional combines: • quantum state fidelity loss• geometric drift based on Bures distance• normalized entropy contribution to evaluate structural degradation in noisy quantum links. The package includes: • Python Monte Carlo simulation framework• quantum noise models using Kraus channels• Ω_QN early-warning analysis• preventive entanglement purification model• reproducible datasets• figure generation scripts• statistical validation workflow Version 3.0 includes reproducibility improvements: ✓ corrected Bures distance implementation✓ explicit Kraus-channel noise modelling✓ purification-based preventive correction mechanism✓ clean CSV outputs✓ fixed random seed configuration for reproducibility All reported numerical results should be regenerated from the released source code before citation. This release is a computational simulation and theoretical research framework. Physical quantum hardware validation remains future work. Part of:Structure-Sensitive Science Research Program (2026–2035) Author:Halil ÖzbilIndependent ResearcherElazığ, Turkey License:Creative Commons Attribution 4.0 International (CC BY 4.0)

Jun 9, 20260 citations

Artifact of Live Noise Fingerprints as an Empirical Semantics for Noisy Quantum Channels

Anonymous for Peer Review

Abstract Quantum computations execute on noisy hardware whose effective noise is opaque and varies across platforms and over time. Complete descriptions of the underlying noise channel are often too detailed for reasoning, comparison, or analysis. We therefore study the semantic problem of constructing tractable abstractions of noisy quantum channels: given a finite set of observations, how can we summarise channel behaviour while preserving properties of interest? We characterise the effective noise of a quantum channel as an abstract domain of noise fingerprints. A noise fingerprint is an observational abstraction of a quantum channel over a finite experiment interface. We formalise the relation between concrete channels and fingerprints through an approximate Galois connection and derive four abstraction properties: soundness, conciseness, efficiency, and adaptiveness. We provide an executable instantiation of the abstraction function using the classical-shadow estimator, together with a partial concretisation function that reconstructs channels from fingerprints via semidefinite programming. We evaluate this abstraction against the formal properties: the soundness bound is shown to be tight, compression over the concrete domain is exponential with near-lossless retention, sample complexity is (poly)logarithmic, and incremental updates track channel drift at the optimal rate. Additional experiments show that fingerprints preserve physically meaningful noise signatures and distinguish cross-platform behaviours. Together, this work brings abstract interpretation to the empirical semantics of noisy quantum channels, providing a lightweight, formally grounded abstraction for characterising, comparing, and monitoring noisy quantum executions. Context Characterising noisy quantum channels remains challenging: full process tomography scales exponentially with system size, while commonly used noise metrics provide limited semantic guarantees. This artifact accompanies a paper that introduces live noise fingerprints as a reusable semantic abstraction for noisy quantum channels. A noise fingerprint is defined as the matrix of deviations between observed and ideal Pauli expectation values over a fixed experimental interface. We show that these fingerprints form an abstract domain for completely positive trace-preserving (CPTP) maps through an approximate Galois connection to the concrete channel space. The framework is evaluated against four formal requirements: Soundness — a Lipschitz bound relating abstract distance to diamond-norm distance. Conciseness — substantial compression relative to the underlying channel representation. Estimation efficiency — practical estimation from finite measurements. Adaptiveness — support for incremental updates under channel drift. The concrete instantiation uses the Huang–Kueng–Preskill classical-shadow estimator with median-of-means aggregation. Every theoretical claim is machine-verified. The artifact includes exact SDP-based diamond norms for small systems, two independently validated large-system ground truths (completely bounded norm multiplicativity for single-site channel pairs and the exact Pauli-channel ℓ₁ formula), and a product-factorised classical-shadow sampler proven distribution-identical to the full sampler. All four research questions are evaluated for n = 1–8 qubits across 12 experimental configurations, combining three channel families with hardware-informed profiles derived from IBM Boston and Quantinuum H2 calibrations under both Qiskit and Cirq simulation variants. All stochastic measurements are reported as mean ± standard deviation, and every figure includes error bars. New in this version. The artifact now includes a self-contained worked example, worked_example.ipynb, which runs the abstraction end to end on small quantum programs: from OpenQASM source, through the gates and the noise a backend inserts around them, to the observation interface a program's test defines, the resulting fingerprints, and the decision they support. It is written for readers approaching the work from programming languages and software engineering rather than quantum information, and it is the shortest path into the artifact: it requires only NumPy, runs in seconds, and needs no SDP solver, quantum SDK, or hardware. The artifact also characterises the operational limits of the approach, including detectability thresholds at realistic hardware noise rates, readout-error-induced bias floors, explicit interface-blindness constructions and their informationally complete remedies, and drift regimes where warm-started updates remain beneficial. Artifact Evaluation file This artifact accompanies the paper "Live Noise Fingerprints as an Empirical Semantics for Noisy Quantum Channels" and provides the complete implementation, experiments, and evaluation pipeline used to validate the proposed noise-fingerprint abstraction. The package includes a pure Python/NumPy implementation of noisy quantum channels, classical-shadow fingerprint estimation, semidefinite-programming-based concretisation, machine-checked tests, a worked-example notebook, and scripts to reproduce every figure and quantitative claim reported in the paper. Evaluators can start from the notebook for a program-level walkthrough of the abstraction, verify correctness using an automated verification target, and regenerate all experimental results, including scalability, convergence, variance, detectability, and warm-start analyses. Precomputed datasets and figures are included to enable immediate inspection, while the full experimental pipeline can be rerun from scratch without requiring GPUs, quantum hardware, or network access after dependency installation. The artifact is released under the MIT License and is designed for reuse by allowing new quantum programs, hardware noise profiles, qubit counts, and abstraction properties to be incorporated with minimal modification. Package Contents worked_example.ipynb — a self-contained, executed walkthrough of the abstraction on small programs. It covers: an OpenQASM front end and the ideal denotation of a program; the realisation of that program on a backend, with the backend's noise inserted after every gate and rendered in the printed circuit; the observation interface, derived from what a program's test asserts rather than chosen freely; fingerprints and the equivalence decision, over five benchmark programs and five backend configurations, with a diagnostic per program naming the observation that carries the difference; interface blindness and its repair by refinement; prefix sweeping to localise which gate two realisations first disagree on; a control panel for running the whole chain on the reader's own .qasm file; measurement-reuse accounting, and numerical checks of three properties from the paper. Outputs are stored in the notebook, so it can be read without execution. src/ Pure NumPy implementation of: Quantum states and channels Noise fingerprints Literal classical-shadow estimators (full and product-factorised) Optional readout-error models Exact diamond-norm computation via Watrous SDPs Validated large-system diamond-norm ground truths General SDP-based concretisation procedures Configurable noise models Registry of all 12 experimental configurations (profiles.py) experiments/ Experiment drivers for all research questions: rq1_sweep.py — Soundness rq2_sweep.py — Conciseness rq3_sweep.py — Estimation Efficiency rq4_sweep.py — Adaptiveness Additional components include audited single-size reproductions, a stress-test suite (realistic_limits.py), a seed-sweep audit framework, and a figure-generation pipeline with shared publication styling. results/ — JSON outputs containing every measured data point for each research question. figures/ — Results figures, one file per figure. tests/ — Forty-one machine-checked tests, including validation of exact diamond-norm ground truths, verification of the product-factorised sampler, and consistency checks required before experimental execution. Additional files — README.md (overview, results summary, and reproduction guide), Dockerfile (containerised environment), requirements.txt (pinned dependencies). Installation The artifact requires Python 3.10 or later. Install dependencies: pip install -r requirements.txt Required packages: NumPy, SciPy, CVXPY, scikit-learn, matplotlib. Opening the worked-example notebook additionally requires jupyter; the notebook itself imports only NumPy and can also be read as-is, since its outputs are stored. No quantum SDK is required; all simulations use a pure NumPy density-matrix implementation. A containerised environment is also provided: docker build . Getting started: the worked example jupyter notebook notebooks/worked_example.ipynb Approximate runtime: under one minute; NumPy only. This is the recommended entry point. It takes a program in OpenQASM, shows what a backend does to it, derives the observation interface from the program's test, computes the fingerprints, and decides whether the two backends are interchangeable for that test — the abstraction of the paper, on objects small enough to check by hand. Expected results Two backends implementing the same physical noise by different means are judged interchangeable on all five programs, with deviations at machine precision (≈ 10⁻¹⁶). A leftover coherent phase rotation, of the kind an optimisation pass can introduce, is flagged on four of the five programs and correctly cleared on the fifth, whose test reads only populations and therefore cannot be affected by it. Judged on a population-only interface, the same phase rotation is invisible; refining the interface to the observables the program's test actually reads restores it. The prefix sweep localises a fault confined to the two-qubit gate at exactly that gate, and reports the earliest divergence when the

Jul 5, 20260 citations

Q-Loop-Enabled Deterministic Coherence Management for Portable Quantum Sensors

Caspian, Ethan A.

This repository contains the simulation and analysis code accompanying the manuscript “Q-Loop-Enabled Deterministic Coherence Management for Portable Quantum Sensors”. It provides a fully reproducible Python/NumPy/QuTiP workflow to evaluate Q-Loop, a continuous phase-modulation protocol for coherence protection in NV-centre magnetometers and related qubit sensors operating under “robotic” composite noise.The code computes filter functions (|F(\omega,\tau)|^2) and decoherence functionals (\chi(\tau)) for free evolution, Q-Loop, and standard pulsed dynamical decoupling sequences (CPMG, XY8, UDD), under both Lorentzian and composite (1/f +) line-rich noise spectra. It generates the main figures in the paper, including: (i) filter-function and noise-weighting plots, and (ii) jitter–flip-angle robustness heatmaps comparing Q-Loop to XY8/CPMG. A Colab-friendly script is included so all figures can be regenerated on a laptop without specialized hardware. The repository also provides example waveform generators (I/Q baseband) for implementing Q-Loop and pulsed sequences on standard AWGs, together with reference parameter sets ((\eta \simeq 3.6, T \simeq 0.97\tau_c)) that reproduce the reported (\sim 5)–(6\times) coherence extension. This archive is intended as a starting point for both numerical studies of coherence management under realistic platform noise and for experimental implementation on ensemble NV magnetometers or other driven qubit sensors.

Nov 21, 20250 citations

Distributional Signatures of Entanglement Architecture under Misaligned Decoherence and Readout

Bob Jefferson

These exploratory papers investigated distributional effects of decoherence in GHZ states. While several interesting observations were made, unresolved inconsistencies and lack of analytical grounding led us to treat these as internal exploratory work. Key conceptual lessons from these studies informed later, more general work on selective transcription.This archive contains the manuscript, figures, and reproducible simulation code accompanying the paper “Distributional Signatures of Entanglement Architecture under Misaligned Decoherence and Readout”. The work introduces a tomography-free, distribution-level diagnostic for multipartite coherence, demonstrating that endpoint Jensen–Shannon divergence under misaligned decoherence and readout provides an operational classifier of entanglement architecture.

Dec 20, 20250 citations