Paper -11 - A Reproducible Method for Checking Earlier Events and Later Choices in Quantum Experiments

A Reproducible Method for Checking Earlier Events and Later Choices in Quantum Experiments QDL Research Program — Paper 11 | Version V1.0.0 DOI: https://doi.org/10.5281/zenodo.23261100 Overview Quantum experiments can produce surprising results. Sometimes, an event is recorded first, and a measurement choice is made later. If these two events appear connected, an important question arises: Is this connection supported by the experimental data, or could it be explained by statistical variation, event selection, or measurement conditions? This paper presents a clear and reproducible method for investigating that question. It combines real experimental data, exact statistical calculations, source verification, and computer-based testing. The main goal is simple: make quantum-data calculations easier to understand, repeat, and independently check. What Does This Paper Study? The study examines how researchers can correctly compare an earlier recorded event with a later measurement setting. It focuses on five important questions: Were the earlier events and later settings correctly identified? Were all eligible events included using the original experimental rules? Do the observed numbers show a meaningful statistical relationship? Could selection effects, detection differences, or data-matching errors explain the result? Can another researcher reproduce the same calculations using the available sources? The paper provides mathematical formulas, numerical examples, source checks, and reproducible software for these questions. Three Main Research Applications 1. Munich Event-Ready Bell Experiment The first application studies data from a published quantum Bell experiment involving entangled atoms. The published dataset contains 55,568 events. We independently recalculated four-sector statistics from the published count tables. The main results are: Measurement Odds Ratio Fisher p-value Lab 1 0.997122 0.8653 Lab 2 0.980578 0.2486 These results do not provide stable evidence of an association between the selected variables in the full published counts. We also analyzed original event-level records from two experimental runs in April and June 2016. These files contain 20,403 valid paired events. By applying the original selection rule of 5,000 events per Bell-state class, we exactly reproduced the historical results. All 16 published sector counts matched, with zero differences. This demonstrates why correct event selection and source verification are important for reliable scientific calculations. 2. Photonic Quantum-Switch Experiment The second application examines published data from a 2026 photonic quantum-switch experiment. The original study reported a Bell-like causal-inequality value of approximately 1.8090 ± 0.0024, compared with a fixed-order bound of 1.75. We independently recalculated the relevant quantity using 256 published probability entries. Our calculated value was: 1.808954375 This agrees with the reported result at its published precision. We also examined six statistical comparisons involving measurement settings and marginal probabilities. These checks help distinguish an experimental causal-inequality result from a possible statistical relationship between an earlier event and a later setting. The two questions are different and should not be confused. 3. Testing the Method with 80,000 Synthetic Trials The third application uses 80,000 computer-generated trials, divided into four controlled scenarios. The scenarios represent: A system with no inserted effect. A system with a deliberately inserted statistical difference. A system affected by detection-efficiency differences. A system with information leakage before the earlier result was fully recorded. The software reproduced the expected numerical results for all four scenarios. These tests show how the method can identify known statistical patterns and distinguish them from possible experimental artifacts. The synthetic trials are software-validation data, not new laboratory observations. Main Contributions This paper brings together several important elements in one reproducible research workflow. 1. Clear event identification It defines which event happened earlier, which setting was chosen later, and how the records should be matched. 2. Exact statistical calculations It uses four-sector count tables, odds ratios, log-affinity measures, uncertainty estimates, and Fisher's exact tests. 3. Original-data verification It demonstrates how the correct historical event-selection rule can reproduce published results exactly. 4. Independent source comparisons It uses different quantum datasets without incorrectly treating their measurements as equivalent. 5. Reproducible software It provides a computational framework for repeating the calculations, checking results, and recording source limitations. Why Is This Work Useful? Scientific results become more valuable when other researchers can independently verify them. This paper offers a practical way to investigate complex quantum-data questions without depending only on interpretations or assumptions. The method can help researchers: Recheck published quantum experiments. Find problems caused by event selection or data matching. Compare statistical results across experimental runs. Separate real experimental measurements from simulated examples. Design more reliable tests for future quantum experiments. Understand which conclusions are supported by the available evidence. Scientific Scope This work is primarily about statistical verification, experimental-data interpretation, and reproducibility. It does not establish backwards-time signalling or a new fundamental physical law. The Munich published-count analysis and the two recovered original runs have different levels of source access. The quantum-switch experiment measures a different physical quantity. The synthetic trials are used only to test the software. These distinctions are maintained throughout the study. Data and Software Availability The calculations are supported by QDL Research Suite, a Python-based scientific software package containing tools for reproducible mathematical and statistical analysis. QDL Research Suite — All Versions: https://doi.org/10.5281/zenodo.22952901 QDL Research Suite v1.10.0 — Version Used: https://doi.org/10.5281/zenodo.23256494 The software provides calculation modules, reproducibility tools, automated tests, and verification outputs. The study also identifies the original experimental publications and available source datasets so that the calculations can be checked against their sources. Conclusion The central contribution of Paper 11 is a clear, source-linked method for checking quantum experimental data. It combines published experimental results, original event records, exact statistical methods, and controlled software tests. The work shows how careful data selection, transparent calculations, and independent verification can improve confidence in scientific analysis. Its purpose is to help make complex quantum research more understandable, reproducible, and reliable, while keeping mathematical results, experimental evidence, and physical interpretations clearly separated. Author: Roshankumar Chandaliya Research Program: Quantum Diverter Loop (QDL) Paper: 11 Version: V1.0.0 DOI: https://doi.org/10.5281/zenodo.23261100