arXiv subjects

Victor V. Golovko

Publications and source records attributed to Victor V. Golovko.

10 recordsLinked to original sources

arXiv2026

Information-Loss Location Estimation and Curvature-Scale Analysis of Physical Measurements: A Gaussian, Cauchy, and Logistic Neutron-Lifetime Benchmark

We develop and implement a two-step location-scale analysis for repeated physical measurements when the underlying distribution is not known. For a chosen substitute distribution, stationarity of population Kullback-Leibler information loss at fixed scale motivates the location score, which we apply to the observed measurements through empirical cross-entropy. Steiner's curvature rule then defines a companion scale separately. We place Gaussian, Cauchy, and logistic substitutes in one common construction and implement them reproducibly on a physics benchmark. For the logistic substitute, we pair the established bounded location score with a scale defined by the curvature rule rather than by a fitted tuning constant or a scale-likelihood equation. For Gaussian measurements with different quoted uncertainties, an experiment-level curvature convention and a stated variance mapping give an exact algebraic connection to a standard residual-based variance estimate for a weighted fit. Applied to a published 21-measurement neutron-lifetime compilation, the inverse-variance weighted, most frequent value, and logistic locations are 878.689, 881.164, and 882.835 s, respectively. These values are benchmark results of the compared constructions and are not proposed as a new recommended neutron lifetime.

physics.data-an↗

arXiv2026

Profile-Likelihood and Baseline-Sensitivity Diagnostics for Digitized Radiation-Sensor Decay Datasets

Accurate interpretation of radiation-sensor decay data is important for environmental monitoring, site remediation, radiation metrology, detector quality assurance, and nuclear data evaluation. When the original gamma-spectrometry records are unavailable, a published decay plot may be the only source that can be reanalyzed independently. This study presents a reproducible reduced-data workflow for testing half-life estimates from a digitized 198-Au decay dataset. A weighted exponential fit to the digitized data points reproduces the published room-temperature half-life, indicating that the main decay scale is retained in the figure-level dataset. The analysis then tests how the fitted result changes under plausible figure-level effects, including baseline-like offsets, time-axis reconstruction, finite-window leverage, and ratio-based robustness checks using pairwise summaries and Steiner's most frequent value statistics. The no-offset fit is locally well constrained, but small constant offsets can shift the fitted half-life because the normalization, decay constant, and residual baseline are partly degenerate over the limited time window. Toy Monte Carlo diagnostics show that some estimator shifts are expected for finite-window exponential data. This study does not revise recommended nuclear data or replace the original experiment. Instead, it shows how published radiation-sensor decay data can be tested for reproducibility, identifiability, and sensitivity to analysis choices when only reduced or figure-level information is available.

physics.data-an↗

arXiv2025

Robust Lifetime Estimation from HPGe Radiation-Sensor Time Series Using Pairwise Ratios and MFV Statistics

High-purity germanium (HPGe) gamma-ray detectors are core instruments in nuclear physics and astrophysics experiments, where long-term stability and reliable extraction of decay parameters are essential. However, the standard exponential decay analyses of the detector time-series data are often affected by the strong correlations between the fitted parameters and the sensitivity to detector-related fluctuations and outliers. In this study, we present a robust analysis framework for HPGe detector decay data based on pairwise ratios and the Steiner's most frequent value (MFV) statistic. By forming point-to-point ratios of background-subtracted net counts, the dependence on the absolute detector response is eliminated, removing the amplitude-lifetime correlation inherent to conventional regression. The resulting pairwise lifetime estimates exhibit heavy-tailed behavior, which is efficiently summarized using the MFV, a robust estimator designed for such distributions. For the case study, a long and stable dataset from an HPGe detector was used. This data was gathered during a low-temperature nuclear physics experiment focused on observing the 216 keV gamma-ray line in 97-Ru. Using measurements spanning approximately 10 half-lives, we obtain a mean lifetime of tau = 4.0959 +/- 0.0007 (stat) +/- 0.0110 (syst) d, corresponding to a half-life of T1/2 = 2.8391 +/- 0.0005 (stat) +/- 0.0076 (syst) d. These results demonstrate that the pairwise-MFV approach provides a robust and reproducible tool for analyzing long-duration HPGe detector data in nuclear physics and nuclear astrophysics experiments, particularly for precision decay measurements, detector-stability studies, and low-background monitoring.

physics.ins-det↗

arXiv2025

Robust Method for Confidence Interval Estimation in Outlier-Prone Datasets: Application to Molecular and Biophysical Data

Estimating confidence intervals in small or noisy datasets is a challenge in biomolecular research when data contain outliers or high variability. We introduce a robust method combining a hybrid bootstrap procedure with Steiner's most frequent value (MFV) approach to estimate confidence intervals without removing outliers or altering the dataset. The MFV identifies the most representative value while minimizing information loss, ideal for limited or non-Gaussian samples. To demonstrate robustness, we apply the MFV-hybrid parametric bootstrapping (MFV-HPB) framework to the fast-neutron activation cross-section of the 109Ag(n,2n)108mAg reaction, a nuclear physics dataset with large uncertainties and evaluation difficulties. Repeated resampling and uncertainty-based simulations yield a robust MFV of 709 mb with a 68.27% confidence interval of [691, 744] mb, illustrating the method's interpretability in complex scenarios. Although the example is from nuclear science, similar issues arise in enzymatic kinetics, molecular assays, and biomarker studies. The MFV-HPB framework offers a generalizable approach for extracting central estimates and confidence intervals in small or noisy datasets, with resilience to outliers, minimal distributional assumptions, and suitability for small samples-making it valuable in molecular medicine, bioengineering, and biophysics.

nucl-ex↗

arXiv2025

Optimizing Sensor Data Interpretation via Hybrid Parametric Bootstrapping

The Chalk River Laboratories (CRL) site in Ontario, Canada, has long been a hub for nuclear research, which has resulted in the accumulation of legacy nuclear waste, including radioactive materials such as uranium, plutonium, and other radionuclides. Effective management of this legacy requires precise contamination and risk assessments, with a particular focus on the concentration levels of fissile materials such as U-235. These assessments are essential for maintaining nuclear criticality safety. This study estimates the upper bounds of U-235 concentrations. We investigated the use of a hybrid parametric bootstrapping method and robust statistical techniques to analyze datasets with outliers, then compared these outcomes with those derived from nonparametric bootstrapping. This study underscores the significance of measuring U-235 for ensuring safety, conducting environmental monitoring, and adhering to regulatory compliance requirements at nuclear legacy sites. We used publicly accessible U-235 data from the Eastern Desert of Egypt to demonstrate the application of these statistical methods to small datasets, providing reliable upper limit estimates that are vital for remediation and decommissioning efforts. This method seeks to enhance the interpretation of sensor data, ultimately supporting safer nuclear waste management practices at legacy sites such as CRL.

stat.AP↗

arXiv2024

Estimation of Ru-97 Half-Life Using the Most Frequent Value Method and Bootstrapping Techniques

A new and robust statistics was applied to previous measurements of the 97Ru half-life. This process incorporates the most frequent value (MFV) technique along with hybrid parametric bootstrap (HPB) method to deliver a more precise estimate of the 97Ru half-life. The derived value is T1/2,MFV(HPB) = 2.8385+0.0022-0.0075 days. This estimate corresponds to a 68.27% confidence interval ranging from 2.8310 to 2.8407 days, and a 95.45% confidence interval ranging from 2.8036 to 2.8485 days, calculated using the percentile method. This level of uncertainty is significantly lower-over 30 times-than the uncertainty in the previously recognized half-life value found in nuclear data sheets. Employing an alternate approach to minimization could further cut down the statistical uncertainty by 44% for the 97Ru half-life. In particular, the HPB method accounts for uncertainties in small datasets when determining the confidence interval. When the HPB method, in combination with the MFV approach, was used to review a four-element dataset of the specific activity of 39Ar based on underground data, the result was SA_MFV(HPB) = 0.966 +0.027 -0.020 Bq/kg_atmAr. This value results in a 68.27% confidence interval of 0.946 to 0.993, along with a 95.45% confidence interval of 0.921 to 1.029, also determined using the percentile method.

physics.data-an↗

arXiv2024

Simplified Efficiency Calibration Methods for Scintillation Detectors Used in Nuclear Remediation

Our study introduces innovative methods to address waste reduction and enhance resource efficiency in nuclear cleanup processes. We focus on sustainable nuclear technology, aligning with goals for cleaner production and environmental protection. We developed two novel methods, termed "oversimplified" and "simplified," for easily determining the photopeak efficiency of NaI(Tl) scintillation detectors. These methods, along with a "general" solution method, were validated with calibrated radioactive sources such as 241Am, 57Co, 133Ba, 137Cs, and 60Co, and were used to commission a NaI(Tl) scintillation detector system at Chalk River Laboratories (CRL) for nuclear remediation. The system demonstrated high accuracy, making it suitable for screening unstable isotopes at contaminated sites. This screening tool significantly reduces the number of soil samples requiring detailed characterization, thereby lowering operational costs. The NaI(Tl) detector system was calibrated for near-contact geometry, which is commonly used at CRL. Detection limits were established for this configuration. By improving the efficiency calibration of scintillation detectors, our study advances sustainable nuclear remediation practices, promoting environmental sustainability and cleaner production processes.

physics.ins-det↗

arXiv2024

Ambient Dose and Dose Rate Measurement in SNOLAB Underground Laboratory at Sudbury, Ontario, Canada

The paper describes a system and experimental procedure that use integrating passive detectors, such as thermoluminescent dosimeters (TLDs), for the measurement of ultra-low-level ambient dose equivalent rate values at the underground SNOLAB facility located in Sudbury, Ontario, Canada. Because these detectors are passive and can be exposed for relatively long periods of time, they can provide better sensitivity for measuring ultra-low activity levels. The final characterization of ultra-low-level ambient dose around water shielding for ongoing direct dark matter search experiments in Cube Hall at SNOLAB underground laboratory is given. The conclusion is that TLDs provide reliable results in the measurement of the ultra-low-level environmental radiation background.

physics.ins-det↗

arXiv2023

Application of the Most Frequent Value Method for $^{39}$Ar Half-Life Determination

An evaluation method supported by robust statistical analysis was used to analyze historical measurements of $^{39}$Ar half-life. The method, which combines the most frequent value (MFV) approach with bootstrap analysis, provides a more reliable way to estimate the half-life of $^{39}$Ar. The results show that the half-life is T1/2(MFV) = 268.2 + (3.1) - (2.9) years, with an uncertainty corresponding to the 68% confidence level. This uncertainty is three times smaller than the most precise re-calculated measurements by Stoenner et al. (1965) and 2.7 times smaller than the adopted half-life value in nuclear data sheets. Recently, the specific activity of the beta decay of $^{39}$Ar in atmospheric argon was measured in various underground facilities. Applying the MFV method to these measurements gives a specific activity of SA($^{39}$Ar/Ar)(MFV) = 0.966 + (0.010) - (0.018) Bq/kg(atmAr), with an uncertainty corresponding to the 68% confidence level. This paper also discusses the method used to determine the half-life of $^{39}$Ar using the specific activity of $^{39}$Ar in atmospheric argon.

physics.geo-ph↗

arXiv2022

Simplified Efficiency Calibration Methods for Semiconductor Detectors used in Criticality Dosimetry

``Oversimplified'' and ``simplified'' methods based on true coincidence summing effect used in uncomplicated determination of the photo-peak efficiency of the semiconductor High Purity Germanium (HPGe) detector system are suggested and verified. The methods and calibrated $^{60}$Co radioactive source may be used to commission any HPGe detector to use during potential criticality event. The determined accuracy of the semiconductor HPGe detector system using this method is a few percent (for the detector system used in this study it was $\simeq$8\% for oversimplified and $\simeq$5\% for simplified methods accordingly) reasonable, expected, and good enough to use for estimation of neutron dose from irradiated human blood in a potential criticality event. Moreover, if one can experimentally deduce the photo-peak efficiency for $^{60}$Co 1333 keV $γ$-ray line using the suggested methods, then with a few percent accuracy this efficiency could be also used for 1369 keV $γ$-ray line in the decay of $^{24}$Na isotope.

physics.ins-det↗