Measured distribution of cloud chamber tracks from radioactive decay: a new empirical approach to investigating the quantum measurement problem

Using publicly available video of a diffusion cloud chamber with a very smallradioactive source, I measure the spatial distribution of where tracks start, and consider possibleimplications. This is directly relevant to the quantum measurement problem and its possibleresolution, and appears never to have been done before. The raw data are relatively uncontrolled,leading to caveats that should guide future, more tailored experiments. Results may suggest amodification to Born’s rule at very small wavefunction, with possibly profound implications forthe detection of extremely rare events such as proton decay. I introduce two candidate smallwavefunctionBorn rule modifications, a hard cutoff and an offset model; the data may favor theoffset model, which has a stronger underlying physical rationale. Track distributions from decaysin cloud chambers represent a previously unappreciated way to probe the foundations of quantummechanics, and a novel case of wavefunctions with macroscopic signatures.

Measured distribution of cloud chamber tracks from radioactive decay: a new empirical approach to investigating the quantum measurement problem

Using publically available video of a cloud chamber with a very small radioactive source, I measure the spatial distribution of where tracks start, and consider possible implications. This is directly relevant to the quantum measurement problem and its possible resolution, and appears never to have been done before. The raw data are relatively uncontrolled, leading to caveats that should guide future, more tailored experiments. Track distributions from decays in cloud chambers represent a previously unappreciated way to probe the foundations of quantum mechanics, and a novel case of wavefunctions with macroscopic signatures.

Measured distribution of cloud chamber tracks from radioactive decay

Using publically available video of a cloud chamber with a very small radioactive source, I measure the spatial distribution of where tracks start, and consider possible implications. This is directly relevant to the quantum measurement problem and its possible resolution, and appears never to have been done before. The raw data are relatively uncontrolled, leading to caveats that should guide future, more tailored experiments. Track distributions from decays in cloud chambers represent a previously unappreciated way to probe the foundations of quantum mechanics, and a novel case of wavefunctions with macroscopic signatures.

Predicting the Number of Days With Visibility in a Specific Range in Warsaw (Poland) Based on Meteorological and Air Quality Data

Atmospheric visibility is an important parameter of the environment which is dependent on meteorological and air quality conditions. Forecasting of visibility is a complex task due to the multitude of parameters and nonlinear relations between these parameters. In this study, meteorological, air quality, and atmospheric visibility data were analyzed together to demonstrate the capabilities of the multidimensional logistic regression model for visibility prediction. This approach allowed determining independent variables and their significance to the value of the atmospheric visibility in four ranges (i.e., 0–10, 10–20, 20–30, and ≥ 30 km). We proved that the Iman–Conover (IC) method can be used to simulate a time series of meteorological and air quality parameters. The visibility in Warsaw (Poland) is dependent mainly on air temperature and humidity, precipitation, and ambient concentration of PM10. Three logistic models of visibility allowed us to determine precisely the number of days in a month with visibility in a specific range. The sensitivity of the models was between 75.53 and 90.21%, and the specificity 78.51 and 96.65%. The comparison of the theoretical (modeled) with empirical (measured) distribution with the Kolmogorov–Smirnov test yielded p-values always above 0.27 and, in half of the cases, above 0.52.

A Bidirectional Scattering Function Reconstruction Method Based on Optimization of Microrelief Heights Distribution

The work is devoted to the development of a new method for reconstructing the scattering properties of a rough surface, which is described using the bi-directional scattering distribution function (BSDF). There are several different methods of BSDF reconstruction using various approaches. However, they all have their drawbacks: for example, a method based on modeling the measured distribution of heights often requires a complicated fit apart from the expensive measurements themselves, various analytical methods are usu-ally operable within the average roughness values with their standard distribution, and a rather good and universal method for optimizing the normals distribution density does not support internal reflections on the elements of the roughest surface. The proposed solution uses the geometry models of the rough surface, which allows simulating a physically more accurate propagation of light through the rough surface taking into account internal reflections, and hence a more accurate reconstruction of the bidirectional scattering distribution function. The results of BSDF reconstruction with the new method are proved by comparison with measurement results.

Two-Dimensional Correlation Function of Binary Black Hole Coalescences

We compute the two-dimensional correlation functions of the binary black hole coalescence detections in LIGO-Virgo’s first and second observation runs. The sky distribution of binary black hole coalescence events is tested for correlations at different angular scales by comparing the observed correlation function to two reference functions that are obtained from mock datasets of localization error regions uniformly distributed in the sky. No excess correlation at any angular scale is found. The power-law slope of the correlation function is estimated to be γ = 2.24 ± 0.33 at the three- σ confidence level, a value consistent with the measured distribution of galaxies.

A Local Approach to Assess Temperature Effects on Fracture Toughness Incorporating the Measured Distribution of Microcracks

This work describes a local approach to cleavage fracture (LAF) incorporating the statistics of microcracks to characterize the cleavage fracture toughness distribution in structural steels. Fracture toughness testing conducted on standard compact tension C(T) specimens for a 22NiMoCr37 pressure vessel steel provides the cleavage fracture resistance data needed to determine the measured toughness distribution. Metallographic examination of etched surfaces for the tested steel also provides the distribution of carbides, which are assumed as the Griffith fracture-initiating particles, dispersed in the material from which the cleavage fracture toughness distribution is predicted. Overall, the analyses conducted in the present work show that LAFs incorporating the statistics of microcracks are a viable engineering procedure to describe the dependence of fracture toughness on temperature in the DBT region for ferritic steels.

Modeling the deformed state of the roadway on permafrost

For economic efficiency, the authors offer to conduct an experimental study of the deformed state of thesub-grade model on permafrost soils in the laboratory environment in a closed system (without a water flow) applying a geometric scale value of M 1:30 and time scale of M 1:900. The description of the research flume, which allows simulating not only the deformed state of the linear structure, but also the temperature regime, is given. During the study, the defects were photo-recorded and the deformations of the structure were measured. Distribution isolines of vertical movements while freezing-thawing were built in the software system «Python», a thermogram of temperature changes in the body of the roadbed and the base of the road is given. The main conclusions of the research are formulated.