Category Archives: Physics

Seeing with Mathematics

Our brain uses sensory data to sift for patterns in space and time that help us create a mental model of the world through which we can navigate and stay alive. At some point, this model of the external world becomes our basis for thinking symbolically and mathematically about it.

Mathematics is an amazingly detailed, concise and accurate way of examining the world to state the logical relationships we find there, but many physicists and mathematicians have been astonished about why this is the case. The physicist Eugene Wigner wrote an article about this in 1960 titled ‘The Unreasonable Effectiveness of Mathematics in the Natural Sciences’. In fact, since the enormous successes of Sir Isaac Newton in mathematically explaining a host of physical phenomena, physicists now accept that mathematics actually serves as a microscope (or telescope!) for describing things and hidden relationships we cannot directly experience. This amazing ability for describing relationships in the world (both real and imagined!) presents us with a new problem.

parabola

Mathematics is a symbolic way of describing patterns our world, and sometimes these symbolically-defined descriptions actually look like the things we are studying. For example, the path of a football is a parabola, but the equation representing its path, y(x), is also that of a parabolic curve drawn on a piece of paper. But what happens when the mathematical description takes you to places where you cannot see or confirm the shape of the object?

Mathematics is a tool for understanding the world and symbolically stating its many logical interconnections, but the tool can sometimes be mistaken for the thing itself. Here is a very important example that comes up again and again when physicists try to ‘popularize’ science.

In the late-1940s, physicist Richard Feynman created a new kind of mathematics for making very precise calculations about how light (photons) and charged particles (such as electrons) behave. His famous ‘Feynman Diagrams’ like the one below, are very suggestive of particles moving in space, colliding, and emitting light. This diagram, with time flowing from left to right, shows a quark colliding with an anti-quark, which generates a photon that eventually produces an electron and anti-electron pair.

feynman_qqgamee1

The problem is that this is not at all a ‘photograph’ of what is actually happening. Instead, this is a tool used for setting up the problem and cranking through the calculation. Nothing more. It is a purely symbolic representation of the actual world! You are not supposed to look at it and say that for the solid lines, ‘particles are like billiard balls moving on a table top’ or that the photon of light they exchange is a ‘wiggly wave traveling through space’. What these objects are in themselves is completely hidden behind this diagram. This is a perfect example of what philosopher Immanuel Kant was talking about back in the 1700s. He said that there is a behind-the-scenes world of noumena where the things-in-themselves (ding-an-sich) exist, but our senses and observations can never really access them directly. The Feynman diagram lets us predict with enormous precision how particles will interact across space and time, but hides completely from view what these particles actually look like.

Another example of how math lets us ‘see’ the world we cannot directly access is the answer to the simple question: What does an electron actually look like?

Since the 1800’s, electricity increasingly runs our civilization, and electricity is merely a measure of the flow of electrons through space inside a wire. Each of us thinks of electrons as tiny, invisible spheres like microscopic marbles that roll through our wires wicked fast, but this is an example of where the human brain has created a cartoon version of reality based upon our ‘common sense’ ideas about microscopic particles of matter. In both physics and mathematics, which are based upon a variety of observations of how electrons behave, it is quite clear that electrons can be thought of as both localized particles and distributed waves that carry the two qualities we call mass and charge. They emit electric fields, but if you try to stuff their properties inside a tiny sphere, that sphere would explode instantly. So it really does not behave like an ordinary kind of particle at all. Also, electrons travel through space as matter waves and so cannot be localized into discrete sphere-like particles. This is seen in the famous Double Slit experiment where electrons produce distinct wave-like interference patterns.

electronwave

So the bottom line is that we have two completely independent, mathematical ways of visualizing what an electron looks like, particles and matter waves, and each can facilitate highly accurate calculations about how electrons interact, but the two images (particle and wave – localized versus distributed in space) are incompatible with each other, and so we cannot form a single, consistent impression of what an electron looks like.

Next time we will have a look at  Einstein and his ideas about relativity, which completely revolutionized our common-sense understanding of space created by the brain over millions of years of evolution.

Check back here on Tuesday, December 13 for the next installment!

Rules-of-thumb

There are at least two basic ways that we create associations. The first is associations in space. The second is associations in time.

Associations in space include recognizing static objects like chairs, trees, cars and people. The reason this works so well is that we live in a world filled with many different kinds of more-or-less fixed objects so that two or more people can agree they have similar attributes.

Associations in time include musical tunes and sounds, or associating one thing (cause) with another thing in the future (effect). For many of these dynamic associations like music, two people with normal hearing senses hear the same sequence of notes in time and can agree that what they heard was a portion of a familiar song, which they may independently be able to name if they have heard it before and made the appropriate associations in memory. But your exact associations related to the song will be different than mine because I associate songs with episodes in my life that you do not also share. Remember, the brain tags everything with patterns of associations unique to the individual.

The human brain is adept at pattern recognition. It can dissect its sensory information and see patterns in space and time that it can then associate with abstract categories such as a chair or a bird, and even specific sub-categories of these if it has been adequately trained (at school, or by reading a book on ornithology!). An upside-down chair seen in the remote distance is recognized as a chair no matter what its orientation in the visual field. A garbled song heard on an iPhone in a loud concert hall, or a particular conversation between two people in a noisy crowd, can also be detected as a pattern in time and recognized. The figure shows some of the brain connection pathways identified in the Human Connectome Project that help to interpret sensory data as patterns in space and time.

brainmapping

Patterns in space let us recognize the many different kinds of objects that fill our world. In the association cortex, once these identifications have been made, they are also sent on to the language centers where they are tagged with words that can be spoken or read. Once this step happens, two individuals can have a meaningful conversation about the world beyond their bodies that the senses can detect. Of course when both people say they have a specific category of objects called Siamese cats, they are most certainly associating that name with slightly different set of events and qualities corresponding to their cat’s personalities , fur patterns, etc..

The next step is even more interesting.

Just as the brain generalizes a collection of associations in space to define the concept of ‘cat’, it can detect patterns in time in the outside world and begin to see how one event leads to another as a rule-of-thumb or a law of nature. If I drop a stone off a tall cliff, it will fall downwards to the valley below. If the sun rises and sets today, it will do so again tomorrow. There are many such patterns of events in time that reoccur with such regularity that they form their own category-in-time much as ‘cat’ and ‘chair’ did in the space context. ‘If I visit a waterhole with lots of animals, there is a good chance that tigers or lions may also be present’. More recently, ‘If I stick my finger in an unprotected electrical outlet, I will probably be electrocuted!’. This perception of relationships is one of cause-and-effect. It has been studied by neurophysiologists, and is due to stimulation of part of the cerebellum and the right hippocampus. These brain regions are both involved with processing durations in time.

Over the centuries and millennia, the patterns in time we have been able to discern about the outside world have become so numerous  we have to write them down in books, and also put our children through longer and longer training periods to master them. This also tells us something very basic about our world.

Instead of being a random collection of events, our physical world contains a basic collection of rules that follow a ‘logical’ If A happens then B happens pattern in time. Physicists call these relationships ‘laws’ and their particular patterns in time and space can be discerned from measurements and observations made of phenomena in the world outside our brains. The brain can also work with these laws symbolically and logically, not by describing them through the usual language centers of the brain, but through a parallel set of centers that make us adept at mathematical reasoning.

In my next blog, I will discuss how mathematics and logic are intertwined and help us think symbolically about our world.

Check back here on Friday, December 9 for the next installment!

Space, Time, and Causality in the Human Brain
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4008651/