Related Experiment Video
Updated: Jan 26, 2026

Protocol for Measuring the Thermal Properties of a Supercooled Synthetic Sand-water-gas-methane Hydrate Sample
Published on: March 21, 2016
Full Counting Statistics and Large Deviations in a Thermal 1D Bose Gas
Maksims Arzamasovs1, Dimitri M Gangardt2
1Department of Applied Physics, School of Science, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China, Shaanxi Province Key Laboratory of Quantum Information and Quantum Optoelectronic Devices, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China, and Institute of Atomic Physics and Spectroscopy, University of Latvia, Riga, LV-1586, Latvia.
We studied full counting statistics for one-dimensional interacting bosons. The atom distribution deviates from Gaussian behavior, showing enhanced fluctuations in short intervals.
Area of Science:
- Quantum physics
- Condensed matter physics
- Statistical mechanics
Background:
- Understanding quantum systems requires analyzing particle distributions.
- Interacting bosons in one dimension exhibit unique quantum phenomena.
Purpose of the Study:
- To determine the full counting statistics for interacting bosons in one dimension.
- To investigate deviations from standard statistical distributions.
Main Methods:
- Analytical derivation of particle number distribution.
- Analysis within the weakly interacting regime.
Main Results:
- Obtained the full counting statistics for one-dimensional interacting bosons.
- The distribution deviates significantly from a Gaussian, especially outside the quasicondensate regime.
- Observed strongly enhanced probability of large number fluctuations for short intervals.
Conclusions:
- The behavior of interacting bosons is non-Gaussian under specific conditions.
- Quantum fluctuations are more pronounced in confined systems or short intervals.
Related Concept Videos
Statistical Significance
Standard Deviation
Mean Absolute Deviation
Let us consider a dataset containing the number of unsold cupcakes in five shops: 10, 15, 8, 7, and 10. Initially, calculate the sample mean. Then calculate the deviation, or the difference, between each data value and the mean. Next, the absolute values of these deviations are added and divided by the sample size to...
Variation: Normal Distribution, Range, and Standard Deviation
Probability in Statistics
An example of a simple event is a coin toss. The result of a coin toss is either a head or a tail. Here, head and tail are two simple events. These two simple events make up the sample space. Further, the probability of an event occurring falls within the range of 0 to 1. The probability of an...
Standard Deviation of Calculated Results
A broad Gaussian distribution curve has a wider standard deviation, representing a data set with...

