# Mathematics of Deep Note

I just finished listening to the latest episode of Twenty Thousand Hertz, the story behind “Deep Note,” the THX logo sound.

There are a couple mathematical details of the sound that I’d like to explore here: random number generation, and especially Pythagorean tuning.

## Random number generation

First is that part of the construction of the sound depended on a random number generator. The voices start in a random configuration and slowly reach the target D major chord at the end.

Apparently the random number generator was not seeded in a reproducible way. This was only mentioned toward the end of the show, and a teaser implies that they’ll go more into this in the next episode.

## Pythagorean tuning

The other thing to mention is that the final chord is based on Pythagorean tuning, not the more familiar equal temperament.

The lowest note in the final chord is D1. (Here’s an explanation of musical pitch notation.) The other notes are D2, A2, D3, A3, D4, A4, D5, A5, D6, and F#6.

### Octaves

Octave frequencies are a ratio of 2:1, so if D1 is tuned to 36 Hz, then D2 is 72 Hz, D3 is 144 Hz, D4 is 288 Hz, D5 is 576 Hz, and D6 is 1152 Hz.

### Fifths

In Pythagorean tuning, fifths are in a ratio of 3:2. In equal temperament, a fifth is a ratio of 27/12 or 1.4983 [1], a little less than 3/2. So Pythagorean fifths are slightly bigger than equal temperament fifths. (I explain all this here.)

If D2 is 72 Hz, then A2 is 108 Hz. It follows that A3 would be 216 Hz, A4 would be 432 Hz (flatter than the famous A 440), and A5 would be 864 Hz.

### Major thirds

The F#6 on top is the most interesting note. Pythagorean tuning is based on fifths being a ratio of 3:2, so how do you get the major third interval for the highest note? By going up by fifths 4 times from D4, i.e. D4 -> A4 -> E5 -> B5 -> F#6.

The frequency of F#6 would be 81/16 of the frequency of D4, or 1458 Hz.

The F#6 on top has a frequency 81/64 that of the D# below it. A Pythagorean major third is a ratio of 81/64 = 1.2656, whereas an equal temperament major third is f 24/12 or 1.2599 [2]. Pythagorean tuning makes more of a difference to thirds than it does to fifths.

A Pythagorean major third is sharper than a major third in equal temperament. Some describe Pythagorean major chords as brighter or sweeter than equal temperament chords. That the effect the composer was going for and why he chose Pythagorean tuning.

### Detuning

Then after specifying the exact pitches for each note, the composer actually changed the pitches of the highest voices a little to make the chord sound fuller. This makes the three voices on each of the highest notes sound like three voices, not just one voice. Also, the chord shimmers a little bit because the random effects from the beginning of Deep Note never completely stop, they are just diminished over time.

## Related posts

[1] The exponent is 7/12 because a half step is 1/12 of an octave, and a fifth is 7 half steps.

[2] The exponent is 4/12 because a major third is 4 half steps.

Musical score above via THX Ltd on Twitter.

# How many musical scales are there?

How many musical scales are there? That’s not a simple question. It depends on how you define “scale.”

For this post, I’ll only consider scales starting on C. That is, I’ll only consider changing the intervals between notes, not changing the starting note. Also, I’ll only consider subsets of the common chromatic scale; this post won’t get into dividing the octave into more or less than 12 intervals.

First of all we have the major scale — C D E F G A B C — and the “natural” minor scale: A B C D E F G A. The word “natural” suggests there are other minor scales. More on that later.

Then we have the classical modes: Dorian, Phrygian, Lydian, Mixolydian, Aeolian, and Locrian. These have the same intervals as taking the notes of the C major scale and starting on D, E, F, G, A, and B respectively. For example, Dorian has the same intervals as D E F G A B C D. Since we said we’d start everything on C, the Dorian mode would be C D E♭ F G A B♭ C. The Aeloian mode is the same as the natural minor scale.

The harmonic minor scale adds a new wrinkle: C D E♭ F G A♭ B C. Notice that A♭ and B are three half steps apart. In all the scales above, notes were either a half step or a whole step apart. Do we want to consider scales that have such large intervals? It seems desirable to include the harmonic minor scale. But what about this: C E♭ G♭ A C. Is that a scale? Most musicians would think of that as a chord or arpeggio rather than a scale. (It’s a diminished seventh chord. And it would be more common to write the A as a B♭♭.)

We might try to put some restriction on the definition of a scale so that the harmonic minor scale is included and the diminished seventh arpeggio is excluded. Here’s what I settled on. For the purposes of this post, I’ll say that a scale is an ascending sequence of eight notes with two restrictions: the first and last are an octave apart, and no two consecutive notes are more than three half steps apart. This will include modes mentioned above, and the harmonic minor scale, but will exclude the diminished seventh arpeggio. (It also excludes pentatonic scales, which we may or may not want to include.)

One way to enumerate all possible scales would be to start with the chromatic scale and decide which notes to keep. Write out the notes C, C♯, D, … , B, C and write a ‘1’ underneath a note if you want to keep it and a ‘0’ otherwise. We have to start and end on C, so we only need to specify which of the 11 notes in the middle we are keeping. That means we can describe any potential scale as an 11-bit binary number. That’s what I did to carry out an exhaustive search for scales with a little program.

There are 266 scales that meet the criteria listed here. I’ve listed all of them on another page. Some of these scales have names and some don’t. I’ve noted some names as shown below. I imagine there are others that have names that I have not labeled. I’d appreciate your help filling these in.

```|--------------+-----------------------+-------------------|
| Scale number | Notes                 | Name              |
|--------------+-----------------------+-------------------|
|          693 | C D  E  F# G  A  B  C | Lydian mode       |
|          725 | C D  E  F  G  A  B  C | Major             |
|          726 | C D  E  F  G  A  Bb C | Mixolydian mode   |
|          825 | C D  Eb F# G  Ab B  C | Hungarian minor   |
|          826 | C D  Eb F# G  Ab Bb C | Ukrainian Dorian  |
|          854 | C D  Eb F  G  A  Bb C | Dorian mode       |
|          858 | C D  Eb F  G  Ab Bb C | Natural minor     |
|         1235 | C Db E  F  G  Ab B  C | Double harmonic   |
|         1242 | C Db E  F  G  Ab Bb C | Phrygian dominant |
|         1257 | C Db E  F  Gb Ab B  C | Persian           |
|         1370 | C Db Eb F  G  Ab Bb C | Phrygian mode     |
|         1386 | C Db Eb F  Gb Ab Bb C | Locrian mode      |
|--------------+-----------------------+-------------------|
```

Related posts:

# Saxophone with two octave keys

Last year I wrote a post about saxophone octave keys. I was surprised to discover, after playing saxophone for most of my life, that a saxophone has not one but two octave holes. Modern saxophones have one octave key, but two octave holes. Originally saxophones had a separate octave key for each octave hole; you had to use different octave keys for different notes.

I had not seen one of these old saxophones until Carlo Burkhardt sent me photos today of a Pierret Modele 5 Tenor Sax from around 1912.

Here’s a closeup of the octave keys.

And here’s a closeup of the bell where you can see the branding.

# Listening to golden angles

The other day I wrote about the golden angle, a variation on the golden ratio. If φ is the golden ratio, then a golden angle is 1/φ2 of a circle, approximately 137.5°, a little over a third of a circle.

Musical notes go around in a circle. After 12 half steps we’re back where we started. What would it sound like if we played intervals that went around this circle at golden angles? I’ll include audio files and the code that produced them below.

A golden interval, moving around the music circle by a golden angle, is a little more than a major third. And so a chord made of golden intervals is like an augmented major chord but stretched a bit.

An augmented major triad divides the musical circle exactly in thirds. For example, C E G#. Each note is four half steps, a major third, from the previous note. In terms of a circle, each interval is 120°. Here’s what these notes sound like in succession and as a chord.

If we go around the musical circle in golden angles, we get something like an augmented triad but with slightly bigger intervals. In terms of a circle, each note moves 137.5° from the previous note rather than 120°. Whereas an augmented triad goes around the musical circle at 0°, 120°, and 240° degrees, a golden triad goes around 0°, 137.5°, and 275°.

A half step corresponds to 30°, so a golden angle corresponds to a little more than 4.5 half steps. If we start on C, the next note is between E and F, and the next is just a little higher than A.

If we keep going up in golden intervals, we do not return to the note we stared on, unlike a progression of major thirds. In fact, we never get the same note twice because a golden interval is not a rational part of a circle. Four golden angle rotations amount to 412.5°, i.e. 52.5° more than a circle. In terms of music, going up four golden intervals puts us an octave and almost a whole step higher than we stared.

Here’s what a longer progression of golden intervals sounds like. Each note keeps going but decays so you can hear both the sequence of notes and how they sound in harmony. The intention was to create something like playing the notes on a piano with the sustain pedal down.

It sounds a little unusual but pleasant, better than I thought it would.

Here’s the Python code that produced the sound files in case you’d like to create your own. You might, for example, experiment by increasing or decreasing the decay rate. Or you might try using richer tones than just pure sine waves.

```from scipy.constants import golden
import numpy as np
from scipy.io.wavfile import write

N = 44100 # samples per second

# Inputs:
# frequency in cycles per second
# duration in seconds
# decay = half-life in seconds
def tone(freq, duration, decay=0):
t = np.arange(0, duration, 1.0/N)
y = np.sin(freq*2*np.pi*t)
if decay > 0:
k = np.log(2) / decay
y *= np.exp(-k*t)
return y

# Scale signal to 16-bit integers,
# values between -2^15 and 2^15 - 1.
def to_integer(signal):
signal /= max(abs(signal))
return np.int16(signal*(2**15 - 1))

C = 262 # middle C frequency in Hz

# Play notes sequentially then as a chord
def arpeggio(n, interval):
y = np.zeros((n+1)*N)
for i in range(n):
x = tone(C * interval**i, 1)
y[i*N : (i+1)*N] = x
y[n*N : (n+1)*N] += x
return y

# Play notes sequentially with each sustained
def bell(n, interval, decay):
y = np.zeros(n*N)
for i in range(n):
x = tone(C * interval**i, n-i, decay)
y[i*N:] += x
return y

major_third = 2**(1/3)
golden_interval = 2**(golden**-2)

write("augmented.wav", N, to_integer(arpeggio(3, major_third)))

write("bell.wav", N, to_integer(bell(9, golden_interval, 6)))
```

# How a couple failed auditions worked out well

When I was in high school, one year I made the Region choir. I had no intention of competing at the next level, Area, because I didn’t think I stood a chance of going all the way to State, and because the music was really hard: Stravinsky’s Symphony of Psalms.

My choir director persuaded me to try anyway, with just a few days before auditions. That wasn’t enough time for me to learn the music with all its strange intervals. But I tried out. I sang the whole thing. As awful as it was, I kept going. It was about as terrible as it could be, just good enough to not be funny. I wanted to walk out, and maybe I should have out of compassion for the judges, but I stuck it out.

I was proud of that audition, not as a musical achievement, but because I powered through something humiliating.

I did better in band than in choir. I made Area in band and tried out for State but didn’t make it. I worked hard for that one and did a fair job, but simply wasn’t good enough.

That turned out well. It was my senior year, and I was debating whether to major in math or music. I’d told myself that if I made State, I’d major in music. I didn’t make State, so I majored in math and took a few music classes for fun. We can never know how alternative paths would have worked out, but it’s hard to imagine that I would have succeeded as a musician. I didn’t have the talent or the temperament for it.

When I was in college I wondered whether I should have done something like acoustical engineering as a sort of compromise between math and music.  I could imagine that working out. Years later I got a chance to do some work in acoustics and enjoyed it, but I’m glad I made a career of math. Applied math has given me the chance to work in a lot of different areas—to play in everyone else’s back yard, as John Tukey put it—and I believe it suits me better than music or acoustics would have.

# Electric guitar distortion

The other day I asked on Google+ if someone could make an audio clip for me and Dave Jacoby graciously volunteered. I wanted a simple chord on an electric guitar played with varying levels of distortion. Dave describes the process of making the recording as

Fender Telecaster -> EHX LPB clean boost -> Washburn Soloist Distortion (when engaged) -> Fender Frontman 25R amplifier -> iPhone

Let’s look at the Fourier spectrum at four places in the recording: single note and chord, clean and distorted. These are a 0:02, 0:08, 0:39, and 0:43.

## Power spectra

The first note, without distortion, has most of it’s spectrum concentrated at 220 Hz, the A below middle C.

The same note with distortion has a power spectrum that decays much slow, i.e. the sound has more high frequency components.

Here’s the A major chord without distortion. Note that since the threshold of hearing is around 20 dB, most of the noise components are inaudible.

Here’s the same chord with distortion. Notice there’s much more noise in the audible range.

Update: See the next post an analysis of the loudness and sharpness of the audio samples in this post.

Photo via Brian Roberts CC

# The acoustics of kettledrums

Kettledrums (a.k.a. tympani) produce a definite pitch, but in theory they should not. At least the simplest mathematical model of a kettledrum would not have a definite pitch. Of course there are more accurate theories that align with reality.

Unlike many things that work in theory but not in practice, kettledrums work in practice but not in theory.

A musical sound has a definite pitch when the first several Fourier components are small integer multiples of the lowest component, the fundamental. A pitch we hear at 100 Hz would have a first overtone at 200 Hz, the second at 300 Hz, etc. It’s the relative strengths of these components give each instrument its characteristic sound.

An ideal string would make a definite pitch when you pluck it. The features of a real string discarded for the theoretical simplicity, such as stiffness, don’t make a huge difference to the tonality of the string.

An ideal circular membrane would vibrate at frequencies that are much closer together than consecutive integer multiples of the fundamental. The first few frequencies would be at 1.594, 2.136, 2.296, 2.653, and 2.918 times the fundamental. Here’s what that would sound like:

I chose amplitudes of 1, 1/2, 1/3, 1/4, 1/5, and 1/6. This was somewhat arbitrary, but not unrealistic. Including more than the first six Fourier components would make the sound even more muddled.

By comparison, here’s what it would sound like with the components at 2x up to 6x the fundamental, using the same amplitudes.

This isn’t an accurate simulation of tympani sounds, just something simple but more realistic than the vibrations of an idea membrane.

The real world complications of a kettledrum spread out its Fourier components to make it have a more definite pitch. These include the weight of air on top of the drum, the stiffness of the drum head, the air trapped in the body of the drum, etc.

If you’d like to read more about how kettle drums work, you might start with The Physics of Kettledrums by Thomas Rossing in Scientific American, November 1982.

# Octave holes on a saxophone

I’ve played saxophone since I was in high school, and I thought I knew how saxophones work, but I learned something new this evening. I was listening to a podcast [1] on musical acoustics and much of it was old hat. Then the host said that a saxophone has two octave holes.  Really?! I only thought there was only one.

When you press the octave key on the back of a saxophone with your left thumb, the pitch goes up an octave. Sometimes this causes a key on the neck to open up and sometimes it doesn’t [2]. I knew that much.

I thought that when this key didn’t open, the octaves work like they do on a flute: no mechanical change to the instrument, but a change in the way you play. And to some extent this is right: You can make the pitch go up an octave without using the octave key. However, when the octave key is pressed there is a second hole that opens up when the more visible one on the neck closes.

According to the podcast, the first saxophones had two octave keys to operate with your thumb. You had to choose the correct octave key for the note you’re playing. Modern saxophones work the same as early saxophones except there is only one octave key controlling two octave holes.

* * *

[1] Musical Acoustics from The University of Edinburgh, iTunes U.

[2] On the notes written middle C up to A flat, the octave key raises the little hole I wasn’t aware of. For higher notes the octave key raises the octave hole on the neck.

# Musical pitch notation

How can you convert the frequency of a sound to musical notation? I wrote in an earlier post how to calculate how many half steps a frequency is above or below middle C, but it would be useful go further have code to output musical pitch notation.

In scientific pitch notation, the C near the threshold of hearing, around 16 Hz, is called C0. The C an octave higher is C1, the next C2, etc. Octaves begin with C; other notes use the octave number of the closest C below.

The lowest note on a piano is A0, a major sixth up from C0. Middle C is C4 because it’s 4 octaves above C0. The highest note on a piano is C8.

## Math

A4, the A above middle C, has a frequency of 440 Hz. This is nine half steps above C4, so the pitch of C4 is 440*2-9/12. C0 is four octaves lower, so it’s 2-4 = 1/16 of the pitch of C4. (Details for this calculation and the one below are given in here.)

For a pitch P, the number of half steps from C0 to P is

h = 12 log2(P / C0).

## Software

Here is a page that will let you convert back and forth between frequency and music notation: Music, Hertz, Barks.

If you’d like code rather than just to do one calculation, see the Python code below. It calculates the number of half steps h from C0 up to a pitch, then computes the corresponding pitch notation.

```from math import log2, pow

A4 = 440
C0 = A4*pow(2, -4.75)
name = ["C", "C#", "D", "D#", "E", "F", "F#", "G", "G#", "A", "A#", "B"]

def pitch(freq):
h = round(12*log2(freq/C0))
octave = h // 12
n = h % 12
return name[n] + str(octave)
```

The pitch for A4 is its own variable in case you’d like to modify the code for a different tuning. While 440 is common, it used to be lower in the past, and you’ll sometimes see higher values like 444 today.

If you’d like to port this code to a language that doesn’t have a `log2` function, you can use `log(x)/log(2)` for `log2(x)`.

## Powers of 2

When scientific pitch notation was first introduced, C0 was defined to be exactly 16 Hz, whereas now it works out to around 16.35. The advantage of the original system is that all C’s have frequency a power of 2, i.e. Cn has frequency 2n+4 Hz. The formula above for the number of half steps a pitch is above C0 simplifies to

h = 12 log2P – 48.

If C0 has frequency 16 Hz, the A above middle C has frequency 28.75 = 430.54, a little flat compared to A 440. But using the A 440 standard, C0 = 16 Hz is a convenient and fairly accurate approximation.

# Structure in jazz and math

Last night I went to a concert by the Branford Marsalis Quartet. One of the things that impressed me about the quartet was how creative they are while also being squarely within a tradition. People who are not familiar with jazz may not realize how structured it is and how much it respects tradition. The spontaneous and creative aspects of jazz are more obvious than the structure. In some ways jazz is more tightly structured than classical music. To use Francis Schaeffer’s phrase, there is form and freedom, freedom within form.

Every field has its own structure, its tropes, its traditions. Someone unfamiliar with the field can be overwhelmed, not having the framework that an insider has to understand things. They may think something is completely original when in fact the original portion is small.

In college I used to browse the journals in the math library and be completely overwhelmed. I didn’t learn until later that usually very little in a journal article is original, and even the original part isn’t that original. There’s a typical structure for a paper in PDEs, for example, just as there are typical structures for romantic comedies, symphonies, or space operas. A paper in partial differential equations might look like this:

1. Motivation / previous work
2. Weak formulation of PDE
3. Craft function spaces and PDE as operator
4. A priori estimates imply operator properties
5. Well posedness results
6. Regularity

An expert knows these structures. They know what’s boilerplate, what’s new, and just how new the new part is. When I wrote something up for my PhD advisor I remember him saying “You know what I find most interesting?” and pointing to one inequality. The part he found interesting, the only part he found interesting, was not that special from my perspective. It was all hard work for me, but only one part of it stood out as slightly original to him. An expert in partial differential equations sees a PDE paper the way a professional musician listens to another or the way a chess master sees a chess board.

While a math journal article may look totally incomprehensible, an expert in that specialization might see 10% of it as somewhat new. An interesting contrast to this is the “abc conjecture.” Three and a half years ago Shinichi Mochizuki proposed a proof of this conjecture. But his approach is so entirely idiosyncratic that nobody has been able to understand it. Even after a recent conference held for the sole purpose of penetrating this proof, nobody but Mochizuki really understands it. So even though most original research is not that original, once in a while something really new comes out.

Related:

# Electrical hum

If you hear electrical equipment humming, it’s probably at a pitch of about 60 Hz since that’s the frequency of AC power, at least in North America. In Europe and most of Asia it’s a little lower at 50 Hz. Here’s an audio clip in a couple formats: wav, mp3.

The screen shot above comes from a tuner app taken when I was around some electrical equipment. The pitch sometimes registered at A# and sometimes as B, and for good reason. In a previous post I derived the formula for converting frequencies to musical pitches:

h = 12 log(P / C) / log 2.

Here C is the pitch of middle C, 261.626 Hz, P is the frequency of your tone, and h is the number of half steps your tone is above middle C. When we stick P = 60 Hz into this formula, we get h = -25.49, so our electrical hum is half way between 25 and 26 half-steps below middle C. So that’s between a A# and a B two octaves below middle C.

For 50 Hz hum, h = -28.65. That would be between a G and a G#, a little closer to G.

Update: So why would the frequency of the sound match the frequency of the electricity? The magnetic fields generated by the current would push and pull parts, driving mechanical vibrations at the same frequency.

Related: Accoustics consulting

# What key has 30 sharps?

Musical keys typically have 0 to 7 sharps or flats, but we can imagine adding any number of sharps or flats.

When you go up a fifth (seven half steps) you add a sharp. For example, the key of C has no sharps or flats, G has one sharp, D has two, etc. Starting from C and adding 30 sharps means going up 30*7 half-steps. Musical notes operate modulo 12 since there are 12 half-steps in an octave. 30*7 is congruent to 6 modulo 12, and six half-steps up from C is F#. So the key with 30 sharps would be the same pitches as F#.

But the key wouldn’t be called F#. It would be D quadruple sharp! I’ll explain below.

Sharps are added in the order F, C, G, D, A, E, B, and the name of key is a half step higher than the last sharp. For example, the key with three sharps is A, and the notes that are sharp are F#, C#, and G#.

In the key of C#, all seven notes are sharp. Now what happens if we add one more sharp? We start over and start adding more sharps in the same order. F was already sharp, and now it would be double sharp. So the key with eight sharps is G#. Everything is sharp except F, which is double sharp.

In a key with 28 sharps, we’ve cycled through F, C, G, D, A, E, and B four times. Everything is quadruple sharp. To add two more sharps, we sharpen F and C one more time, making them quintuple sharp. The note one half-step higher than C quintuple sharp is D quadruple sharp, which is enharmonic with F#.

You could repeat this exercise with flats. Going up a forth (five half-steps) adds a flat. Or you could think of a flat as a negative sharp.

Related posts:

# How to convert frequency to pitch

I saw somewhere that James Earl Jones’ speaking voice is around 85 Hz. What musical pitch is that?

Let P be the frequency of some pitch you’re interested in and let C = 261.626 be the frequency of middle C. If h is the number of half steps from C to P then

P / C = 2h/12.

Taking logs,

h = 12 log(P / C) / log 2.

If P = 85, then h = -19.46. That is, James Earl Jones’ voice is about 19 half-steps below middle C, around the F an octave and a half below middle C.

More details on the derivation above here.

There’s a page to do this calculation for you here. You can type in frequency or pitch and get the other back.

(The page also gives pitch on a Bark scale, something you may not care about that is important in psychoacoustics.)

Photo credit Wikipedia
Music image created using Lilypod.

# New Twitter accounts for DSP and music theory

I’ve started two new Twitter accounts this week: @DSP_fact and @MusicTheoryTip.

DSP_fact is for DSP, digital signal processing: filters, Fourier analysis, convolution, sampling, wavelets, etc.

MusicTheoryTip is for basic music theory with a little bias toward jazz. It’ll tweet about harmony, scales, tuning, notation, etc.

Here’s a full list of my 15 daily tip twitter accounts.

If you’re interested in one of these accounts but don’t use Twitter, you can subscribe to a Twitter account via RSS just as you’d subscribe to a blog.

If you’re using Google Reader to subscribe to RSS feeds, you’ll need to switch to something else by July 1. Here are 18 alternatives.