Supplementary Material for "Sonification of Markov-chain Monte Carlo Simulations"

##### **Example E0:** Using audification of particle trajectories (section 3.3 in the paper). Listen to a single particle converging to a mode in a three-modal density function p. This example corresponds to figure 2 in the paper. Files:[WAVE-file](https://pub.uni-bielefeld.de/download/2930310/2930311/E0a.wav). Listen to a similar particle with an increased friction coefficient of 0.9996. On each step, the kinetic energy is reduced to E(t+1) = 0.9996 E(t), resulting in an exponential decay of energy. Sounds: [WAVE-file](https://pub.uni-bielefeld.de/download/2930310/2930312/E0b.wav) ##### **Example E1:** Audification of particle trajectories started at McMC steps (section 5.1 in the paper). The Audification of 100 McMC steps in a distribution p with 3 modes - Soundfile: [WAVE-File](https://pub.uni-bielefeld.de/download/2930310/2930313/E1.wav) ##### **Example E2:** Using McMC process stream, AIB stream and McMC details stream as introduced in the paper This examples are discussed in the paper in section 5.2. <br> **(a)** dataset: 3 clusters in 6 dimensional space. T = 0.01 - McMC stream: [WAVE-file](https://pub.uni-bielefeld.de/download/2930310/2930322/E2a_stream1.wav) - McMC details stream: [WAVE-file](https://pub.uni-bielefeld.de/download/2930310/2930323/E2a_stream2.wav) - AIB stream: [WAVE-file](https://pub.uni-bielefeld.de/download/2930310/2930324/E2a_stream3.wav) - All streams together: [WAVE-file](https://pub.uni-bielefeld.de/download/2930310/2930321/E2a_mix.wav) **(b)** dataset: 3 clusters in 6 dimensional space. T = 0.002 - McMC stream: [WAVE-file](https://pub.uni-bielefeld.de/download/2930310/2930326/E2b_stream1.wav) - McMC details stream: [WAVE-file](https://pub.uni-bielefeld.de/download/2930310/2930327/E2b_stream2.wav) - AIB stream: [WAVE-file](https://pub.uni-bielefeld.de/download/2930310/2930328/E2b_stream3.wav) - All streams together: [WAVE-file](https://pub.uni-bielefeld.de/download/2930310/2930325/E2b_mix.wav) **(c)** dataset: 6 clusters in 6 dimensional space, T = 0.008 - McMC stream: [WAVE-file](https://pub.uni-bielefeld.de/download/2930310/2930330/E2c_stream1.wav) - McMC details stream: [WAVE-file](https://pub.uni-bielefeld.de/download/2930310/2930331/E2c_stream2.wav) - AIB stream: [WAVE-file](https://pub.uni-bielefeld.de/download/2930310/2930332/E2c_stream3.wav) - All streams together: [WAVE-file](https://pub.uni-bielefeld.de/download/2930310/2930329/E2c_mix.wav) **(d)** dataset: 3 clusters in 6 dim. space, T = 0.002, p computed by kernel density estimation but now with a kernel of bandwidth sigma such that p is unimodal. - All streams together: [WAVE-file](https://pub.uni-bielefeld.de/download/2930310/2930333/E2d_mix.wav) ##### **Example E3:** Sonification of McMC simulations for handwritten digits (section 5.3 in the paper) ##### **Example E4:** Sonification of McMC simulations for Bayesian Models (section 5.4 in the paper) ##### **Example E5:** Sonification of McMC simulation on iris dataset This examples are discussed in the paper in section 5.5. The following examples are sonification with bandwidth scaling exponent soundfile 0.5 WAVE-file 0.25 WAVE-file 0 WAVE-file -0.25 WAVE-file -0.5 WAVE-file -0.75 WAVE-file -1 WAVE-file