Tag Archives: classical music

Physicists study Bach, Mozart, and jazz

This November 5, 2024 news item on phys.org takes a while before revealing how science is involved in the research,

Physicists at the Max Planck Institute for Dynamics and Self-Organization (MPI-DS) have investigated to which extent a piece of music can evoke expectations about its progression. They were able to determine differences in how far compositions of different composers can be anticipated. In total, the scientists quantitatively analyzed more than 550 pieces from classical and jazz music.

It is common knowledge that music can evoke emotions. But how do these emotions arise and how does meaning emerge in music? Almost 70 years ago, music philosopher Leonard Meyer suggested that both are due to an interplay between expectation and surprise.

In the course of evolution, it was crucial for humans to be able to make new predictions based on past experiences. This is how we can also form expectations and predictions about the progression of music based on what we have heard. According to Meyer, emotions and meaning in music arise from the interplay of expectations and their fulfillment or (temporary) non-fulfillment.

A team of scientists led by Theo Geisel at the MPI-DS and the University of Göttingen have asked themselves whether these philosophical concepts can be quantified empirically using modern methods of data science. …

Physicists at the MPI-DS have investigated the variability in music pieces by different composers. They found a high initial autocorrelation of pitches, which ends relatively abruptly after a certain time, thus making further anticipation impossible. (image generated with AI) [less] © MPI-DS [downloaded from https://phys.org/news/2024-11-bach-mozart-jazz-scientists-quantitative.html]

A November 5, 2024 Max Planck Institute for Dynamics and Self-Organization press release (also on EurekAlert), which originated the news item, offers technical details about the work,

… In a paper published recently in Nature Communications, they used time series analysis to infer the autocorrelation function of musical pitch sequences; it measures how similar a tone sequence is to previous sequences. This results in a kind of “memory” of the piece of music. If this memory decreases only slowly with time difference, the time series is easier to anticipate; if it vanishes rapidly, the time series offers more variation and surprises. 

In total, the researchers Theo Geisel and Corentin Nelias analyzed more than 450 jazz improvisations and 99 classical compositions in this way, including multi-movement symphonies and sonatas. They found that the autocorrelation function of pitches initially decreases very slowly with the time difference. This expresses a high similarity and possibility to anticipate musical sequences. However, they found that there is a time limit, after which this similarity and predictability ends relatively abruptly. For larger time differences, the autocorrelation function and memory are both negligible.

Of particular interest here are the values of the transition times of the pieces where the more predictable behavior changes into a completely unpredictable and uncorrelated behavior. Depending on the composition or improvisation, the scientists found transition times ranging from a few quarter notes to about 100 quarter notes. Jazz improvisations typically had shorter transition times than many classical compositions, and therefore were usually less predictable. Differences could also be observed between different composers. For example, the researchers found transition times between five and twelve quarter notes in various compositions by Johann Sebastian Bach, while the transition times in various compositions by Mozart ranged from eight to 22 quarter notes. This implies that the anticipation and expectation of the musical progression tends to last longer in Mozart’s compositions than in Bach’s compositions, which offer more variability and surprises.

For Theo Geisel, the initiator and head of this research project, this also explains a very personal observation from his high school days: “In my youth, I shocked my music teacher and conductor of our school orchestra by saying that I often couldn’t show much enthusiasm for Mozart’s compositions,” he says. “With the transition times between highly correlated and uncorrelated behavior, we have now found a quantitative measure for the variability of music pieces, which helps me to understand why I liked Bach more than Mozart.”

Here’s a link to and a citation for the paper,

Stochastic properties of musical time series by Corentin Nelias & Theo Geisel. Nature Communications volume 15, Article number: 9280 (2024) DOI: https://doi.org/10.1038/s41467-024-53155-y Published: 28 October 2024

This paper is open access.

There was a Theodor Geisel who in the US and Canada was better known as Dr. Seuss.

Using music to align your nanofibers

It’s always nice to feature a ‘nano and music’ research story, my Nov. 6, 2013 posting being, until now, the most recent. A Jan. 8, 2014 news item on Nanowerk describes Japanese researchers’ efforts with nanofibers (Note: A link has been removed),

Humans create and perform music for a variety of purposes, such as aesthetic pleasure, healing, religion, and ceremony. Accordingly, a scientific question arises: Can molecules or molecular assemblies interact physically with the sound vibrations of music? In the journal ChemPlusChem (“Acoustic Alignment of a Supramolecular Nanofiber in Harmony with the Sound of Music”), Japanese researchers have now revealed their physical interaction. When classical music was playing, a designed supramolecular nanofiber in a solution dynamically aligned in harmony with the sound of music.

Sound is vibration of matter, having a frequency, in which certain physical interactions occur between the acoustically vibrating media and solute molecules or molecular assemblies. Music is an art form consisting of the sound and silence expressed through time, and characterized by rhythm, harmony, and melody. The question of whether music can cause any kind of molecular or macromolecular event is controversial, and the physical interaction between the molecules and the sound of music has never been reported.

The Jan. 8, 2014 Chemistry Views article, which originated the news item, provides more detail,

Scientists working at Kobe University and Kobe City College of Technology, Japan, have now developed a supramolecular nanofiber, composed of an anthracene derivative, which can dynamically align by sensing acoustic streaming flows generated by the sound of music. Time course linear dichroism (LD) spectroscopy could visualize spectroscopically the dynamic acoustic alignments of the nanofiber in the solution. The nanofiber aligns upon exposure to the audible sound wave, with frequencies up to 1000 Hz, with quick responses to the sound and silence, and amplitude and frequency changes of the sound wave. The sheared flows generated around glass-surface boundary layer and the crossing area of the downward and upward flows allow shear-induced alignments of the nanofiber.
Music is composed of the multi complex sounds and silence, which characteristically change in the course of its playtime. The team, led by A. Tsuda, uses “Symphony No. 5 in C minor, First movement: Allegro con brio” written by Beethoven, and “Symphony No. 40 in G minor, K. 550, First movement”, written by Mozart in the experiments. When the classical music was playing, the sample solution gave the characteristic LD profile of the music, where the nanofiber dynamically aligned in harmony with the sound of music.

Here’s an imagie illustrating the scientists’ work with music,

[downloaded from http://www.chemistryviews.org/details/ezine/5712621/Musical_Molecules.html]

[downloaded from http://www.chemistryviews.org/details/ezine/5712621/Musical_Molecules.html]

Here’s a link to and a citation for the paper,

Acoustic Alignment of a Supramolecular Nanofiber in Harmony with the Sound of Music by Ryosuke Miura, Yasunari Ando, Yasuhisa Hotta, Yoshiki Nagatani, Akihiko Tsuda, ChemPlusChem 2014.  DOI: 10.1002/cplu.201300400

This is an open access paper as of Jan. 8, 2014. If the above link does not work, try this .