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<video class="stretch" controls data-autoplay src="media/IPSOS_demo_video.mp4" style="background:none; border:none; box-shadow:none; min-width:460px; zoom:200%;" title="IPSOS app" width="55%" height="auto">Oops! Sorry, it seems your browser is old! Try updating or using a different one to play this video.</video>
								<figcaption align="center" style="opacity:0.5; font-size:0.75em;">TURN YOUR SOUND ON!</figcaption>

The <a href="/ipsosboard.html" style="color:#d1a727">IPSOS App</a> was developed as part of the Dark Matter project, a collaboration between CERN and the laptop group, the Birmingham Ensemble for Electroacoustic Research. The idea of this project was to develop ways of transforming data from experiments at the Large Hadron into electronic music and visuals, allowing us to hear and see the results of this cutting-edge research into the nature of the universe. 
								Here you can explore and play! The website also holds information on physics, dark matter, sonification and sound synthesis, if you would like to discover more about the theory behind the app.
								 
								Use the UP/DOWN buttons on your keyboard or at the bottom-right corner of the screen to navigate between sections within a topic.

Use the RIGHT/LEFT buttons to navigate between topics.

Use the menu button at the bottom-left corner of the screen to access any of the resources.

<a href="#/instructions">Click here for detailed instructions on how to use the app!</a>

The Dark Matter project is a collaboration between:

The University of Birmingham

Istanbul Technical University (MIAM - Center for Advanced Studies in Music)

CERN

The Birmingham Ensemble for Electroacoustic Research (BEER)

art@CMS

QuarkNet

----

Team members:

Thomas McCauley (Physicist)

Kostas Nikolopoulos (Physicist)

Maurizio Pierini (Physicist)

Konstantinos Vasilakos (Composer)

Scott Wilson (Composer)

----

Content and Website design:

Emma Margetson

Milad K. Mardakheh

----
												 
						
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							<a href="http://www.beast.bham.ac.uk/offspring/beer/" style="margin-right:130px" id="beer" target="_blank"><img src="media/BEER_logo.png" style="background:none; border:none; box-shadow:none; min-width:80px; max-width:140px;" width="5.4%" height="auto" title="BEER" alt="BEER_logo"></a>
							<a href="http://artcms.web.cern.ch/artcms/dark-matter-music-meets-physics/" id="artcms" target="_blank"><img src="media/artcms_logo.png" style="background:none; border:none; box-shadow:none; min-width:320px; max-width:580px;" width="20%" height="auto" title="art@CMS" alt="art@CMS_logo"></a>

## What is it?

Particle physics (also known as high-energy physics) is a branch of physics that
							studies the nature of the particles that form matter and radiation. Particle
							physics investigates the smallest detectable particles and the fundamental
							interactions necessary to explain their behaviour. It also looks for entirely
							new particles and interactions.

<img src="media/Atom.png" style="background:none; border:none; box-shadow:none; min-width:350px; max-width:500px;" title="An atom" width="20%">
								<figcaption align="center" style="opacity:0.5; font-size:0.75em;"> Image: Wikimedia Commons: Palomca</figcaption>

It was thought at one time that atoms were the smallest fundamental particles. By "fundamental" we mean that they are not compsed of smaller
							particles. We know now that
							atoms have a tiny but dense, positive nucleus and a cloud of negative electrons (e-).
							The nucleus consists of protons (p+), which are positively charged,
							and neutrons (n), which have no charge. The protons and neutrons themselves are not fundamental particles.
							They are composed of even smaller particles called quarks.

<div align="center">
								 
								"Did you know: The nucleus is ten thousand times smaller than the atom and
								 the quarks and electrons are at least ten thousand times smaller than that!" 
							</div>

## The Standard Model

The theory called the Standard Model of Particle Physics (often just called the Standard Model) explains what the world is made up of and
							what holds it together.

The fundamental parts of the model include:

* 6 quarks
							* 6 leptons (the best-known lepton is the electron!)
							* Force carrier particles corresponding to three of the four fundamental forces
							* The Higgs boson (only just discovered in 2012)

All stable, known matter is made up of quarks and leptons. In fact, all of atomic matter is made up only of up and down quarks
							(combinations of which make up protons and neutrons) and electrons.

Interactions between particles can be thought of in terms of exchanging force carrier particles. There are three fundamental forces in the Standard Model:

* Electromagnetism, combining electricity and magnetism, mediated by the photon
							* Strong force, which holds together quarks and the nuclei, mediated by gluons
							* Weak force, which govern particle decay, mediated by the W and Z boson

There is a fourth force, gravity, which is not included in the Standard Model. How gravity fits together with the other three forces is one of the fundamental questions in physics.

Quarks 
							Quarks only exist in groups with other quarks and are never found alone.
							The heaviest known fundamental particle is the top quark, which is as heavy as a gold nucleus.
							Composite particles made of two or more quarks are called hadrons. Protons and neutrons are examples of hadrons.

Leptons 
							The best-known lepton is the electron (e-). The other two charged leptons are the muon(μ)
							and the tau(τ), which are charged like electrons but have more mass. The muon is heavier
							than the electron and tau is heavier still.
							The other leptons are the three types of neutrinos (ν).
							They have no electrical charge, very little mass, and are not easily detected.

For every type of matter particle found, there also exists a corresponding **antimatter** particle, or **antiparticle**.
							their masses are the same, but properties such as charge are opposite.
							For example an electron is negatively charged whereas an anti-electron (called a positron) is positively charged.
							When a matter particle meets its antiparticle they annihilate and convert into pure **ENERGY** in the form of photons.

## What is Dark Matter?

<img src="media/dark_matter.jpg" style="background: none; border:none; box-shadow: none; min-width:900px; max-width:1350px; padding-right:2px;" title="Dark Matter" width="46%">
								<figcaption align="center" style="opacity:0.5; font-size:0.75em;"> Image: NASA, ESA, M. J. Jee and H. Ford et al. (Johns Hopkins Univ.) </figcaption>

The visible matter we are familiar with only makes up less than 5% of the universe.
							The rest of the matter does not interact via the electromagnetic force. This means that this unknown matter does not absorb,
							reflect or emit light, making it extremely hard to spot, and has therefore been given the name "dark matter".
							Researchers have been able to infer the existence of dark matter only from the gravitational effect it seems to have on visible matter.

Dark matter it and in of itself makes up only another 27% of the universe. Something called dark
							energy is believed to make up the rest. So most of what makes up the universe is of an unknown nature and "dark".

<div align="center" style="color: #d1a727">
							 Fact: The matter we know and that makes up all stars and galaxies only accounts
							 for 5% of the content of the universe!
							</div>

## How are scientists searching for New Physics and Dark Matter?

One way particle physicist search for new particles and interactions is to smash other particles together
							and to study what happens. This is an extremely simplified way to describe it, but it's not inaccurate.

A good analogy of how physicists study particles through colliding is the car crash example.
							Imagine a person wanted to look inside cars. By crashing two cars together at very high speeds, we can break the
							cars apart and see inside. In the same way, physicists crash two particles together in order to break them and study the inside.

Reality is even stranger, as what really could happen is that the pieces of the car combine to make entirely new things
							that weren't even originally part of the car. It could be like crashing togther two cars head-on and producing a dinosaur!
							It's best not to take this analogy too far though.

One way to explain this through the well-known equation E = mc2.
							Mass is simply a form of energy. Matter can be converted into energy and vice-versa.
							As stated before, if one combines an electron and a positron they annihilate and leave behind energy.
							This energy can then be used to form new particles, but only with a combined mass up to the initial energy.
							If one gives the initial particles more and more energy and collide them, then more and heavier particles
							can be created from their collisions.

One way particle physicists look for dark matter is to search for entirely new particles, ones that
							could possibly be dark matter.

Accelerators 
							The particles are given more and more energy in a process known as acceleration, in which the particles' speeds
							are increased more and more until they can nearly (but never reach) the speed of light c.
							At the points where the particles collide are detectors that record the "debris" from the collisions.

Detectors 
							A detector (actually multiple detectors) is large complicated device that consist of layers of material that exploit the
							different properties of particles to catch and measure the energy and momentum of each one. In general, they
							can detect the stable particles left over from decays of unstable (and perhaps more interesting!) particles like W, Z, and Higgs bosons
							that get created in the collisions.

Events 
							The detector are like massive digital cameras that take snapshots of the collisions (which happen billions of times a second).
							Each snapshot is called an event. Each collected event is analyzed and "reconstructed" to see what was produced in the event.

## CERN and the Large Hadron Collider

<img src="media/LHC_tunnel.jpg" style="background:none; border:none; box-shadow:none; min-width:900px; max-width:1900px;" title="View of the LHC tunnel" width="84.6%">
								<figcaption align="center" style="opacity:0.5; font-size:0.75em;"> Image: CERN</figcaption>

The most powerful accelerator ever built is the Large Hadron Collider (LHC) at CERN in Geneva,
							accelerating protons and colliding them with a total energy of 13 TeV.

It accelerates protons to nearly the speed of light -- in clockwise and anti-clockwise directions -- and then
							collides them at four locations around its ring. At these points, the energy of the particle collisions gets transformed into mass,
							spraying particles in all directions. At each of these points are large detectors. One such detector is the called the Compact Muon Solenoid
							or simply CMS.

<img src="media/D810_NEF_3483.jpg" style="background:none; border:none; box-shadow:none; min-width:900px; max-width:1900px;" title="The Compact Muon Solenoid (CMS) detector at CERN" width="79.5%">
							 <figcaption align="center" style="opacity:0.5; font-size:0.75em;"> Image: CERN</figcaption>

A few facts about the Large Hadron Collider:

* It is located 174 metres underground.
							 * It is 27 kilometres in circumference - so big it runs underneath the French-Swiss
							 border, near Geneva.
							 * It is filled with 2000 giant super-conducting magnets that are at 1.9 Kelvin. That's colder
							 than the space between the stars!

<img src="media/LHC_map-s.jpg" style="background:none; border:none; box-shadow:none; min-width:900px; max-width:1900px;" title="Aerial view of the LHC tunnel" width="85%" height="100%">
								<figcaption align="center" style="opacity:0.5; font-size:0.75em;"> Image: CERN</figcaption>

## What parameters are we working with?

<img src="media/eemm_run195099_evt137440354_ispy_3d-annotated-2.png" style="background:none; border:none; box-shadow:none; min-width:920px; max-width:1800px;" title="CMS Higgs event" width="40%">
								<figcaption align="center" style="opacity:0.5; font-size:0.75em;"> Image: CERN</figcaption>

The Large Hadron Collider accelerates protons to nearly the speed of light, in clockwise and anti-clockwise directions,
							and then collides them at four locations around its ring. At these points, detectors such as CMS detect and measure the
							"debris".

The "visible" particles from these collisions such as electrons, muons, and photons come from the decay of heavier unstable
							particles such as W, Z, and Higgs bosons. Quarks are produced as well but quickly interact with other quarks to form "jets"
							of particles.

By measuring precisely as possible properties of these electrons, muon, photons, and jets we can reconstruct the properties
							of the particles that produced them such as their mass. This includes measuring how much energy they have, their charge (where applicable),
							where they were produced, and in which direction they went.

The protons in the collisions travel along the beam pipe (depicted in the image below; this is along the z axis of our coordinate system).
							The detectors themselves form a "cylindrical onion"
							of layers of detectors in order to detect all that comes out of the collision. One such layer (the electromagnetic calorimeter, which measures energy)
							is shown in blue below.

Before each collision, the protons travel along the direction of the Large Hadron Collider beams, and not in
							directions perpendicular to the beams (which are defined as the x and y directions). This means that their momenta in these perpendicular
							directions – their "transverse momentum" – is zero. A fundamental principle of physics is that momentum is
							conserved (constant) and so, after the collision, the sum of the transverse momenta of the products of the
							collision should still be zero. Therefore, if we add up the transverse momenta of all the visible particles
							produced in the collision and find it not to be zero, then this could be because we have missed the momentum
							carried away by invisible particles.

The objects and parameters you will find in the data include: 
							<ul>
								<li>Jet A jet is a narrow cone of hadrons and other particles produced by the hadronisation of a quark or gluon</li>
								<li>Constituents The different components of the jet</li>
								<li>Mass The mass of the particle, measured in units of GeV (Recall E = mc2 where GeV is a unit of energy. Physicist often set c=1)</li>
								<li>Phi The azimuth angle (or angle from the x-axis in the x-y plane), measured in radians</li>
								<li>Eta Pseudorapidity: a measure of the angle of a particle in relation the particle beam</li>
							 	<li>Pt Transverse momentum: the momentum perpendicular to the path of the colliding particles, measured in GeV</li>
								<li>Charge The charge of the particle</li>
							</ul>

Sound synthesis is the technique of generating sound, using electronic hardware or software, from scratch. The most common use of synthesis is musical, where electronic instruments called synthesizers are used in the performance and recording of music.

Sound is the perceived vibration (oscillation) of air resulting from the vibration of a sound source. Vibration at a regular (periodic) rate can be perceived as a pitch.  A common example of a pitch is the A note that orchestras tune to. This is called A440 as it corresponds to 440 cycles of vibration per second (its frequency). Sounds consisting of vibration at only one rate are called sine waves. In the real world, however, sounds usually consist of multiple vibrations. We can describe such complex sounds in terms of the sum of simpler vibrations (partials) at different rates and loudnesses (amplitude). Each partial is a simple sine wave (often called a pure tone) with its own respective frequency and amplitude.

<img src="media/Simple_harmonic_motion.png" style="background:none; border:none; box-shadow:none; min-width:900px; max-width:1900px;" title="Simple harmonic motion" width="60%">
								<figcaption align="center" style="opacity:0.5; font-size:0.75em;"> Image: Wikimedia Commons: Maksim</figcaption>

This oscillator creates sound through looping this waveform at a particular frequency. The shape of its waveform can change the sound produced which furthermore changes the timbre (tone colour) of the sound:

**1. Sine Wave**
							
								<img src="media/Simple_sine_wave.png" style="background:none; border:none; box-shadow:none; min-width:500px; max-width:700px;" title="Sine wave" width="25%">

<audio controls style="min-width:500px; max-width:900px; zoom:180%;">
										<source data-src="media/Sine.mp3" type="audio/mpeg">
										Your browser does not support the audio element.
									</audio>

**2. Square Wave**
							
								<img src="media/Square_wave.png" style="background:none; border:none; box-shadow:none; min-width:500px; max-width:700px;" title="Square wave" width="25%">

<audio controls style="min-width:500px; max-width:900px; zoom:180%;">
										<source data-src="media/Square.mp3" type="audio/mpeg">
										Your browser does not support the audio element.
									</audio>

**3. Triangle Wave**
							
								<img src="media/Triangle_wave.png" style="background:none; border:none; box-shadow:none; min-width:500px; max-width:700px;" title="Triangle wave" width="25%">

<audio controls style="min-width:500px; max-width:900px; zoom:180%;">
										<source data-src="media/Triangle.mp3" type="audio/mpeg">
										Your browser does not support the audio element.
									</audio>

**4. Sawtooth Wave**
							
								<img src="media/Sawtooth_wave.png" style="background:none; border:none; box-shadow:none; min-width:500px; max-width:700px;" title="Sawtooth wave" width="25%">

<audio controls style="min-width:500px; max-width:900px; zoom:180%;">
										<source data-src="media/sawtooth.mp3" type="audio/mpeg">
										Your browser does not support the audio element.
									</audio>
							
							<figcaption align="center" style="opacity:0.5; font-size:0.75em;"> All waveform images: Wikimedia Commons: Omegatron</figcaption>

## ADSR envelope

An envelope describes how a sound changes over time in terms of its amplitude (loudness). Different instruments have different shapes, with for example long, slow starts (like violins slowly fading in), or immediate ones with a slower fadeout (like a drum). Using an ASDR envelope we can control and tailor the sound of the synthesizer as we prefer using the parameters below:

+ **Attack** is the time taken for initial run-up of level from silence to the loudest level.

+ **Decay** is the time taken for the subsequent run down from the attack level to the designated sustain level after the initial attack.

+ **Sustain** is the level during the main sequence of the sound's duration. This corresponds to the held part of a sound in instruments such as strings or winds.

+ **Release** is the time taken for the level to decay from the sustain level to silence after the note is released. This can be very quick, or fade away slowly, as in a bell for example.

While, attack, decay, and release refer to time, sustain refers to level.

<img src="media/ADSR_parameter.png" style="background:none; border:none; box-shadow:none; min-width:900px; max-width:1400px;" title="ADSR parameter" width="60%">
								<figcaption align="center" style="opacity:0.5; font-size:0.75em;"> Image: Wikimedia Commons: Abdull</figcaption>

**Examples**:
							 
 						1.Short, attack sound.
							 
							<audio controls style="width: 500px; zoom: 180%;">
								<source data-src="media/short attack sound.mp3" type="audio/mpeg">
								Your browser does not support the audio element.
							</audio> 
 						2.Long, sustained, low sound.
							 
							<audio controls style="width: 500px; zoom: 180%;">
								<source data-src="media/long sustained sound.mp3" type="audio/mpeg">
								Your browser does not support the audio element.
							</audio> 
 						3.Sequence sound.
							 
							<audio controls style="width: 500px; zoom: 180%;">
								<source data-src="media/Sequence.mp3" type="audio/mpeg">
								Your browser does not support the audio element.
							</audio>

**Other parameters included in IPSOS:**

+ **Detune**: This describes the effect heard when tuning one oscillator sharp or flat in respect to a second oscillator. This produces a fattening of the sound or it may produce a harmonic effect if the interval of the tuning is wide enough.

+ **MIDInote**: Musical pitch (how low or high). Pitch of the pressed key with a value between 0 and 127. Higher values correspond to higher pitches. 'Middle C' on a piano is 60.

+ **Duration**: Amount of time a sound will play for.

+ **Chord**: Sonify all particles simultaneously.

+ **Sequence**: Sonify all particles one at a time in order, perhaps creating a melody or fragment.

## What is it?

Like the one in the above image, data visualisation displays communicate information (the data) through visual means, e.g. charts, graphs, diagrams, etc. An auditory display is any display that uses sound instead of images (dots, lines, shapes, etc.) to demonstrate the data. Sonification is the transformation of data of any kind (numbers, images, text) into non-speech audio, to represent information.

Human beings naturally have a superior capability to recognize changes and patterns in the different properties of sound through time, such as pitch (frequency), loudness, timbre, texture, etc. This is called Auditory Perception. Sonification, takes advantage of this ability and translates data relationships into changes in sound properties so that they could be understood by the listener.

A very simple example of sonification is a doorbell! The information, which is the fact that someone is at the door, is being transformed into a distinctive sound so that whenever we hear it, we can immediately interpret and understand it.

Below is another simple example of sonification. Listen to how the pitch of the sound changes according to the position of the y variable as we move along the x axis on the parabola graph.

<img src="media/Parabolic_graph_convex.png" style="background:none; border:none; box-shadow:none; min-width:750px; max-width:1000px" title="Parabolic arc" width="50%" height="auto">
								<figcaption align="center" style="opacity:0.5; font-size:0.75em;"> Image: Wikimedia Commons: Nicostella</figcaption>

<audio controls style="width: 500px; zoom: 180%;">
										<source data-src="media/parabola pitch.mp3" type="audio/mpeg">
										Your browser does not support the audio element.
									</audio>

## What is it for?

Sonification is a very useful and also common process in our daily lives. From the simplest of functions such as tapping on a watermelon in order to find out whether it is ripe or sweet, to alert sounds produced by different technologies and devices such as alarms, phones, computers, cars, etc. to analysing changes and patterns in complex data, we use and rely on sonification in a wide variety of jobs and tasks.

## Functions of sonification

1. **Alarms, alerts, and warnings**

Alerts and notifications are sounds used to indicate that something has
							        occurred, or is about to occur, or that the listener should immediately
							        attend to something in the environment. Alerts and notifications tend to be
							        simple and particularly overt. For instance, the beeping sound of the
							        microwave is a sonification which indicates that the cooking time has
							        finished.

2. **Status, process, and monitoring messages**

There are situations in which the human listener needs to constantly be
							        aware of the current or ongoing state of a system or process. For example,
							        surgeons needs to be aware of the heart-rate of patients at all times
							        during surgery, and therefore use heart-monitoring systems which in
							        addition to visualisations, use sonification to represent heart beats.

3. **Data exploration**

This is what is generally meant by the term “sonification”, and the
							        intention is to convey information about an entire data set or relevant
							        aspects of the data set. Sonifications for data exploration differ from
							        status or process indicators in that they use sound to show how the values
							        in the data are connected to one-another rather than giving information
							        about a momentary state such as with alerts and process indicators.

4. **Art, entertainment, sports, and exercise**

Notable among their different applications, sonification and auditory
							        displays have been used to enable the visually-impaired children and adults
							        to take part in team sports, or as a means of bringing some of the
							        experience and excitement of dynamic exhibits to the visually impaired.

In addition, sonifications of events and datasets can be used as the basis
							        for musical compositions, installations and sound-art works. While the
							        designers and/or composers often attempt to convey something to the
							        listener through these sonifications, it is not for the pure purpose of
							        information delivery.

## Sonification techniques and approaches

+ **Auditory icons and Earcons**

+ _Auditory icons_, are short communicative sounds that have an analogical relationship with the process or action they represent. In other words, it is as if the sound that you hear actually _sounds_ like what it is meant to represent. For example emptying the trash folder on your computer making the sound of crumpling up paper, or the example below indicating the flow of water or liquid in a system.

<audio controls style="width: 450px; zoom: 180%;">
											<source data-src="media/Auditory Icon - river flowing.mp3" type="audio/mpeg">
												Your browser does not support the audio element.
										</audio>

+ _Earcons_, on the other hand, use sounds only as symbols for actions or processes; so the sounds do not necessarily _sound_ like the actions or processes. For instance, the simple beeping of your phone when you receive a text message. Below is an example of an earcon representing the action of minimizing or making something smaller.

<audio controls style="width: 450px; zoom: 180%;">
											<source data-src="media/Earcon - minimizing.mp3" type="audio/mpeg">
											Your browser does not support the audio element.
										</audio>

+ **Audification** is the most primary method of direct sonification, whereby waveforms are directly translated into sound. For example, seismic waves, travelling through the Earth’s crust as a result of the vibrations of the tectonic plates over an extended period of time, have been audified so that we can hear actual earthquakes! This approach may require that the waveforms be frequency- or time-shifted [sped up or slowed down] into the range of frequencies which humans can hear and percieve as pitches.

+ **Model-based sonification** is a more complex technique of sonification  using computer simulations, whereby a virtual model of the data is built which produces sounds according to the relationships within the data, as the user interacts with it. A model, then, is like an instrument that the user ‘plays’ and their interaction drives the sonification.

+ **Parameter mapping sonification** represents changes in some dimension of the data with changes in an acoustic dimension (of sound) to produce a sonification. As we have already learned, synthesized sound has a multitude of changeable dimensions or parameters such as waveform, pitch, duration, ADSR envelope parameters, etc. This is the form of sonification which IPSOS uses.

**What is a ‘mapping’?**

Mapping or data-mapping is the process of creating direct/indirect relationships between two distinct datasets, whereby a change in one dataset would cause a relative change in the other.

Remember the earlier example of the sonification of the parabola graph? This is a parameter mapping sonification since the position parameter of y is directly mapped to the pitch of the sound. We can create a different mapping for the same parabola graph, this time to the loudness (amplitude) of the sound, instead of its pitch.

<img src="media/Parabolic_graph_convex.png" style="background:none; border:none; box-shadow:none; min-width:750px; max-width:1000px" title="Parabolic arc" width="50%" height="auto">
									<figcaption align="center" style="opacity:0.5; font-size:0.75em;"> Image: Wikimedia Commons: Nicostella</figcaption>

<audio controls style="width: 500px; zoom: 180%;">
										<source data-src="media/parabola amp.mp3" type="audio/mpeg">
											Your browser does not support the audio element.
									</audio>

### Mapping Topology

<img src="media/BGP_map.jpg" style="background:none; border:none; box-shadow:none; min-width:920px; max-width:2000px;" title="Mapping topology" width="60%">
							 <figcaption align="center" style="opacity:0.5; font-size:0.75em;"> Image: Wikimedia Commons: Niau33</figcaption>

The term topology is used in many different fields of study and has a distinct meaning and application in each. However, in general mathematics, topology tells us how elements of one set relate spatially to each other.

Now take for example, the sound produced from the state change of water in a whistling tea kettle as it approaches boiling point. With the rise of the water temperature and increase in steam pressure, the frequency (pitch) of the whistling sound also increases until it reaches a point where the user knows it is time to turn off the stove and pour the boiling water into the teacup. Here, we have a simple **one-to-one mapping** between one parameter, which is the water temperature, and another which is sound frequency/pitch.

One-to-one mappings are not the only kind of mapping data features to sound parameters. A second type, is mapping one data feature (e.g the steam pressure in the same example) to not one but multiple sound parameters at the same time. For instance, waveform, pitch and duration. This is known as **one-to-many** or **divergent mapping**

A third type is **many-to-one** or **convergent mapping** which is the reverse of the above: Multiple different data features (water temperature, pressure, acidity) are mapped to one sound parameter (pitch) and have a collective effect on it

## Functions of parameter mapping sonification

Parameter-mapping sonification is useful in a wide range of complex applications and tasks including navigation, kinematic tracking, medical, environmental, geophysical, oceanographical and astrophysical sensing. In addition to numerical datasets, parameter mapping sonification has been used to sonify static and moving images. Sonification of human movement, for example, is used in medicine for diagnosis and rehabilitation, and also for athletic training (including golf, rowing, ice-skating, and tai-chi).

### In Arts and Music

<img src="media/musical_performance.jpg" style="background:none; border:none; box-shadow:none; min-width:915px; max-width:1900px" title="A musical performance" width="65%">
							 <figcaption align="center" style="opacity:0.5; font-size:0.75em;"> Image: Flickr: smokeghost</figcaption>
						 
						 
							 <img src="media/MusicForSoloPerformer.jpg" style="background:none; border:none; box-shadow:none; min-width:915px; max-width:1900px" title="Alvin Lucier music for solo performer" width="65%">
							 <figcaption align="center" style="opacity:0.5; font-size:0.75em;"> Image: Flickr: pablosanz</figcaption>

Parameter-mapping is one of the most commonly used techniques of sonification in music, and is sometimes also referred to as **musification**. Here are some examples of musical works that use this technique.

-	Iannis Xenakis’ mapping of statistical and stochastic processes to sound in his _Metastasis_ (1965) and other works.

-	Alvin Lucier (above image) played an ensemble of percussion instruments using the alpha waves generated by his brain (EEG sonification), in his piece called _Music for Solo Performer_ (1965).

-	Charles Dodge composed the work titled, _The Earth’s Magnetic Field_ (1970), where the _Kp_ index, describing the fluctuations of the Earth's magnetic field, caused by solar winds, is mapped to the pitches of both diatonic and chromatic scales.

-	John Dunn and Mary Anne Clarke composed the extended work called _Life Music: The Sonification of Proteins_ (1999), in which different amino acid and protein folding patterns are mapped to pitch and instrumentation.

-	Frank Halbig’s _Antarktika_ (2006) translates ice-core data reflecting the climatic development of our planet into the score for a string quartet.

-	Jonathan Berger’s _Jiyeh_ (2008), maps the contours of oil dispersion patterns from a catastrophic oil spill in the Mediterranean Sea. Using a sequence of satellite images, the spread of the oil over a period of time was, sonified and scaled to provide a sense of the enormity of the environmental event.

-	Chris Chafe’s _Tomato Quintet_ (2007, 2011) sonifies the ripening process of tomatoes. The sonification process mapped carbon dioxide, temperature and light readings from sensors in each vat to synthesis and processing parameters. Subsequently, the duration of the resulting sonification was accelerated to different time scales.

1. Choose a Collision Event. There is a drop down menu of events to choose from.

2. Choose which synthesis parameters are addressed to the constituents of each particle. There will be different numbers of particles for each collision, and they may be of different types (e.g. electron or muon)

3. Choose whether this sonification is to be played as a chord or sequence.

4. Choose the synth type:

4.1 Sine 
								4.2 Square 
								4.3 Triangle 
								4.4 Sawtooth

5. Press PLAY to take a listen to the sound.

6. Press STOP to stop the sound.

7. Adjust the mapping range of parameters for the following:

7.1 Attack 
								7.2 Decay 
								7.3 Sustain 
								7.4 Release 
								7.5 Detune 
								7.6 Midinote 
								7.7 Duration

8. Once you are happy with the sound press the plus button. This will save the sound to a button bottom right and it will change colour to green.

9. Press the button to hear the sound again.

10. Create up to 9 sounds. Press the buttons to start to create a rhythm, combination, music sequence from the sounds. You can also use the corresponding keyboard number buttons (1-9) to trigger the sounds.

NOTE: You can currently overwrite the sounds in order if you go over nine.

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##  Teacher Activity Suggestion

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**Activity 1: Explore**

- Discuss and explain the IPSOS app (30 minutes), showing examples.

- Split the class into 3 groups (or more): Proton, Neutron, Electron, Quarks etc.

- Each group to create 6 sounds (1 each) and discuss in groups.

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**Activity 2: Develop**

- Each group to be assigned a particular energy/ colour/ shape to consider. This will furthermore provide 3 (or more) contrasting groups of sounds.

- Participants to explore and create 9 sounds each.

- Share within groups the sounds created. Each group to choose and then share 2 sounds with the class to discuss.

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**Activity 3: Plan**

- Create a plan/ structure for the performance.

- Consider; how will the different groups interact (maybe this can be directed through numbers or atoms colliding?). Will this be 3 separate sections or will these overlap? Will the performers be sat or will they be moving around the space? Does the group need a conductor or will this be random?

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**Activity 4: Practice**

- Practice a series of run throughs of the performance. Consider using a tablet/laptop and moving around whilst performing to mirror colliding particles.

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**Activity 5: Performance**

-	Performance Time!