Earlier, we have explored how power-law distributed detrapping times lead to 1/f noise. Moreover, we have also established that power-law distribution can be obtained from the superposition of exponential distributions (see this post). Now, what implications does the synthesis of these findings hold?

The following video bears some relevance to our recent discussions on modeling 1/f noise. While it doesn't delve directly into the topic of 1/f noise, it offers insights into relevant physics and engineering challenges which arose when trying to make an efficient blue LED.

This year we have finally managed to attend DPG Spring Meeting of the Condensed Matter Section 2024. We have listened to quite a few interesting contributions and received valuable feedback on our own research.

Fig. 1:Justas (left) and myself (right) giving our presentations.

My master's degree student Justas Kvedaravičius showcased his research endeavors spanning both his bachelor's and master's studies in a compelling poster presentation. His research delved into the measurement of spatio-hierarchical heterogeneity and the analysis of rank dynamics within the compartmental voter model. Notably, his most recent exploration of rank dynamics, along with his journey to present at the conference, received a financial support from the Research Council of Lithuania through the student research project (during the semester) grant titled "Analysis of the compartmental voter model in terms of rank dynamics" (Grant No. S-ST-23-122).

I myself have presented my recent endeavors (in collaboration with a member of our group prof. B. Kaulakys) on modeling 1/f noise using model with non-overlapping rectangular pulses (although I have broken this assumption in my presentation), and exploration of the poll-induced delays in the voter model (in collaboration with R. Astrauskas, M. Radavičius and F. Ivanauskas from Faculty of Mathematics and Informatics). Notably, my trip was supported by Vilnius universties Science Promotion Fund.

I have presented my collaborative research efforts, conducted with prof. B. Kaulakys from our group, focusing on modeling 1/f noise. Our approach involved utilizing a model with non-overlapping rectangular pulses (things we have been writing about recently, for example, see this post, although I also did address the breaking of this assumption during my talk. I gave another talk as well, in which I discussed the impliciations of poll-induced delays to the phenomenology of the voter model, research conducted in collaboration with R. Astrauskas, M. Radavičius, and F. Ivanauskas from the Faculty of Mathematics and Informatics. Notably, my attendance at the event was made possible through support from the Vilnius University Science Promotion Fund.

Last time we have seen that we can recover power-law distribution from a superposition of exponential distributions. This idea served a basis for our [1] paper. When presenting some of these results at a conference I was asked question if exponential distribution is necessary, can't one use normal distribution instead?

Would you like to code your own cellular automata program? Similar to our Wolfram's elementary automatons or (more than likely (partially because our app is really old)) better? Watch the following video by the Coding Train channel to learn how to do that using p5.js library.