在YbCu,YbAg和YbAu中的P ,T-odd效应
Johan David Polet1, Yuly Chamorro1,2, Lukáš F Pašteka1,2,3
1Van Swinderen Institute for Particle Physics and Gravity, University of Groningen, Nijenborgh 4, 9747 AG Groningen, The Netherlands.
The Journal of chemical physics
|December 17, 2024
概括
计算了YbCu,YbAg和YbAu的P,T-odd相互作用的分子增强因子. 这些计算对于开发新的冷分子和探测基本物理学至关重要.
科学领域:
- 原子和分子物理 原子和分子物理
- 量子化学 是一个量子化学.
- 凝聚物质物理学 凝聚物质物理学
背景情况:
- 像YbCu,YbAg和YbAu这样的双金属分子有望通过激光冷却的原子创建冷分子.
- 了解P,T-odd相互作用是寻找超越标准模型的新物理学的关键.
研究的目的:
- 在YbCu,YbAg和YbAu中计算电子电偶极时刻 (Wd) 和标量级-伪标量级核子-电子合 (Ws) 的分子增强因子.
- 调查影响这些增强因素的电子结构效应.
- 为了比较Wd的两个计算方案.
主要方法:
- 对于高精度的电子结构计算,采用了相对论合集群方法.
- 进行了全面的不确定性分析,以确保结果的可靠性.
- 对比了计算Wd的两种不同的方法.
主要成果:
- 计算的增强因子为Wd: (13.32±0.13) ×10^24, (12.19±0.12) ×10^24,和 (2.36±0.48) ×10^24hHzecm的YbCu,YbAg,和YbAu,分别.
- 对Ws的计算增强因子: (-48.63 ± 0.53), (-45.68 ± 0.60),和 (3.81 ± 2.58) 的HkHz对YbCu,YbAg,和YbAu,分别.
- 对电子结构对增强因素的贡献进行了详细分析.
结论:
- 计算的分子增强因子为寻找P,T-奇相互作用的实验提供了关键数据.
- 该研究验证了相对论合集群方法,并提供了对这些双金属系统的电子结构的见解.
- 这些结果有助于开发用于精确测量的新型冷分子技术.
相关概念视频
Comparing Experimental Results: Student's t-Test
1.5K
The t-test is a statistical method used to compare the sample mean with a population mean or compare two means from two data sets. The test statistic is calculated from the standard deviation, mean, and number of measurements in the data set at a selected confidence interval and then compared to a table of critical values at this confidence level. If the test statistic is smaller than the critical value, the null hypothesis is accepted. In this case, we state that the difference between the...
1.5K
Student t Distribution
5.9K
The population standard deviation is rarely known in many day-to-day examples of statistics. When the sample sizes are large, it is easy to estimate the population standard deviation using a confidence interval, which provides results close enough to the original value. However, statisticians ran into problems when the sample size was small. A small sample size caused inaccuracies in the confidence interval.
The Student t distribution was developed by William S. Goset (1876–1937) of the...
The Student t distribution was developed by William S. Goset (1876–1937) of the...
5.9K
BIBO stability of continuous and discrete -time systems
337
System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
337
Variation
6.7K
An important characteristic of any set of data is the variation in the data. In some data sets, the data values are concentrated closely near the mean; in other data sets, the data values are more widely spread out from the mean. The most common measure of variation, or spread, is the standard deviation, which is the square root of variance.
When independent and dependent variables are plotted on a scatter plot, the slope of a line is a value that describes the rate of change between the two...
When independent and dependent variables are plotted on a scatter plot, the slope of a line is a value that describes the rate of change between the two...
6.7K
Contingency Table
2.4K
A contingency table provides a way of portraying data that can facilitate calculating probabilities. It is a method of displaying a frequency distribution as a table with rows and columns to show how two variables may be dependent (contingent) upon each other; The table helps determine conditional probabilities quite quickly and can help systematically organize, analyze and quantify data. The table displays sample values concerning two variables that may be dependent or contingent on one...
2.4K
Choosing Between z and t Distribution
2.7K
The z and the Student t distribution estimate the population mean using the sample mean and standard deviation. However, to decide which distribution to use for a calculation, one needs to determine the sample size, the nature of the distribution, and whether the population standard deviation is known. If the population standard deviation is known and the population is normally distributed, or if the sample size is greater than 30, the z distribution is preferred. The Student t distribution is...
2.7K


