IndexAbstractIntroductionMethodExpected resultsSeasonal temperature and differences in summer and winterCorrelation in muon detection in summer and winterReduction of uncertainty in muon detectionConclusionAbstractThe purpose of the experiment is to determine the relationship between the number of muon detections for a given period of time during summer and winter and how temperature and pressure affect the muon shower. The project provides evidence that winter has a higher average muon detection rate of 47±2.95 per hour than summer. The result also shows that summer has an average temperature 13.37° higher than winter, while the average pressure remains relatively the same (1014 hPa). Only one station was chosen to reduce the effect of altitude since muon production differs with height {3} I developed a linear model that attributes the number of events per hour using outside temperature and pressure to a altitude of 56.18 m above sea level. I found a strong negative correlation (r = -.80) between the number of muons detected per hour and the outside temperature while only a weak negative correlation (r = -0.13) between the number of muons detected and the outside temperature. The number of events can be calculated using (-3.906±0133)T +(-12.068±0.095)P +(4616.6±151.665) assuming pressure and temperature are the only factor. I found that the most likely muon detection number is around 2273 -2301 per hour. The project answers the question regarding the correlation between the number of muons detected in summer and winter and (pressure and temperature), but further studies are needed to determine the average energy of muons in summer and winter. Say no to plagiarism. Get a tailor-made essay on "Why Violent Video Games Shouldn't Be Banned"? Get an original essayIt has been hypothesized that there is no statistically significant relationship between (summer and winter) and number of events. Furthermore, there is no statistically significant relationship between (pressure and temperature) and number of events. The number of muon detections is random and occurs at a constant rate regardless of temperature and pressure. {1}IntroductionCosmic radiation comes from our Sun and other stars, but high-energy cosmic radiation (10^15eV) is created during the explosion of supernovae and the excretion of black holes. The lower spectrum of cosmic radiation ( Φ=aE −b [1]Where Φ is the flux density of the muon, E is the energy of the muon and a&b are constants. The HiSPARC project started in the Netherlands in 2002 where all the detector is connected to the main server of the Nikhef scientific institute via the Internet and forming a larger network. The aim of the HiSPARC project was to provide the opportunity for interested young students to take part in scientific research on very high energy cosmic rays. is installed on the roofs of the university and school building. This ultra-high cosmic radiation has a rain surface of 1 Km, which is the average distance between two high schools. The number of muons detected in each nearby detector can be used to approximate the location of the cosmic radiation source {11} The result calculated throughout the project is based only on the 501 Nikhef station. The Nikhef station is located in the Netherlands, Amsterdam, at the latitude of 52.36° and the latitude of 4.95098 °. The detector is positioned 56.18 m above sea level and the threshold frequency is set from 81ADC to 150ADC. {4}MethodData is downloaded from the HiSPARC 501 Nikhef station. The downloaded data is recorded every time a muon is detected with reference to time, external temperature,external pressure and other data. It is possible for students to perform data analysis using Excel, however Excel is not designed for large data sets, where Python is. The data is encoded using Python where it saves the file in Excel with the time, the number of events at that given time, the average temperature at that given time, and the average pressure at that given time in each column. The Python code and flowchart are provided in the appendix. The data is analyzed using Excel features. Expected Results Where Io, To, Po and Ho represent the average intensity, the temperature, pressure and production rate and other represent constants. The first term represents the atmospheric mass above the detector and the subsequent terms show the dependence of pressure, temperature and muon surviving at a given altitude. Using only 501 Nikhef stations reduces the dependence on altitude and counts as they are always constant and can be ignored when calculating the dependence on pressure, temperature and number of events. {5}The atmosphere is not isothermal, therefore there is a variation in temperature and pressure depending on the altitude and the surrounding environment.{6} The external temperature is measured using a temperature sensor positioned outside the detector and measured with an accuracy of ±0.5°. The external pressure is calculated using the barometric formula with an accuracy of ±1hPa.P=Po×e^(-(gMh)/(R.To)) [3] Where P is the pressure at a certain altitude Po is the pressure at the reference point, g is the gravitational field strength, M is the molar mass of the air, R is the gas constant of the air, and To is the external temperature {7}The muon count is inversely proportional to the temperature atmospheric. The increase in temperature causes the atmosphere to expand and increases the likelihood that primary radiation will interact at higher altitudes. This causes the muon to travel a longer distance which increases the chance of decaying before reaching the detector. {6} On the other hand, the expansion of the atmosphere causes the number of particles in a given unit of volume to decrease (decreases the pressure), thus reducing the probability that cosmic radiation interacts with atmospheric molecules. As the pressure decreases, the muon count increases.Seasonal temperature and differences in summer and winterAs the average temperature and pressure calculated during winter and summer form, it shows that summer had a temperature 13.37° higher than winter while the pressure was relatively the same (1014hPa) which is explained by equation 3. This suggests that winter should have a higher average number of detected events for a given time period. Data is collected for summer (June, July and August) and winter (December, January and February) over a three-year period from December 2016 to August 2018. The line graph (N_frequency) represents the expected value of the frequency for a given bin and is calculated using the Excel function "Normal Random Number Generator" with observed mean and standard deviation. According to the data, winter has a mean of 2342.846±2.981 and a standard deviation of 190.623 while summer has a mean of 2300.031±1.852 and a standard deviation of 118.353. As expected, it shows that winter has the largest number of muon events in a given time period, but the result excludes the energy of the muon swarm, so there is a lack of evidence to provide whether summer or winter has higher energy medium muon. The number of muons detected for a given time interval is Gaussian. This can be interpreted by calculating the mean, median and mode and the closer the values ​​are the better the Gaussian fit. The uncertainty in the Gaussian mean over three years shows acorrelation of 2298.05±0.1 in muon detection in summer and winter. Data is collected for summer (June, July and August) and winter (December, January and February) over the three years from December 2016 to August 2018. For the data provided, the p-value is less than 0.05 , so there is 95% confidence that the slope is not zero, so the data can reject the null hypothesis and shows that there is a relationship between counts and temperature. The p-values ​​for Intercept and Pressure are zero so there is no effect. The standard error for counts, pressure, and temperature is 1.769, 0.119, and 0.085, respectively. I found a strong negative correlation (r = -.80) between the number of muons detected per hour and the outside temperature while only a weak negative correlation (r = -0.13) between the number of muons detected and the outside temperature. As a linear residual graph for (Counts and Temperature) and (Counts and Pressure), the data shows a linear fit. Assuming that there is a perfectly linear fit between (temperature + pressure) and that the number of events and other factors are ignored, the number of events can be calculated using equation 4. As the data shapes, the number of events has mean of 2321.48±1.77 and standard deviation of 160.16. counts=(-3.906±0133)T +(-12.068±0.095)P +(4616.6±151.665) [4]The light intensity achieved by the Earth's atmosphere is relatively the same, however the radiation emitted by the sun differs. There are several factors that influence muon detection such as the position of the detector relative to the sun (angle), atmospheric pressure {5}, distance between the sun and the detector, atmospheric temperature, magnetic activity on the surface of the sun and solar activity. rockets. {10}The HISPARC scintillator contains a small amount of scintillating organic substance that uses muon energy to generate visible light. The visible light created by the glittering plate is collected by the photomultiplier where the light energy is converted into electrons by the process of the photoelectric effect. The electron is accelerated by the electric field and amplified by the dynodes. {10} ,{1} This allows the current to be detected, and the strength of the current over time can be used to measure the number of muons detected and the energy of the pulse. The current fluctuation depends on the energy and trajectory of the electron as well as the material of the diode.{1} The work function of the metal varies depending on the material, so the rate at which the electron is ejected (current) depends on the photocathode and diode material. Where h is Planck's constant, m is the mass of the electron, v is the velocity of the electron, Φ is the work function of the material, f is the frequency of the incident light, I is the current, Δe/Δt is the number of electrons in a given time interval. {8} The shower front is not flat as it has a certain thickness so it is not known whether the detected cosmic ray particle front is close or delayed, so it has a percentage uncertainty in measuring time. Reduction of uncertainty in the detection of muons We can reduce the uncertainty of the detection of muons by setting the threshold at this value, the real events are not lost and the energetic radiation of the lower spectrum, well below the energy of the muon, is not taken into account . Station 501 Nikhef was set from 81ADC to 150ADC. There is a random error in the detection of other charged particles and radiation created by the Earth's surface that are not muons. These particles are also capable of inducing charge in the scintillator. To reduce the false event, multiple detectors are available at close range. With the increase in the number of simultaneous detections of muons through the detector, the data can be guaranteed with the high probability. 68-83.