Physicists attempt to understand how the universe works. I say ‘attempt’ because our understanding of what the universe is can only be as good as what our senses and extension of our senses can make of it. Anything beyond that can either be irrelevant or can simply be another opportunity to push our boundaries even further. A true picture of nature (whatever ‘true’ means) cannot be envisaged. Who is to say what is and is not the ‘truth’? We can have endless arguments about what is true or not, or whether truth can ever be purely objective. The point is, instead of trying to figure out how close we are to reaching the ‘truth’, we should appreciate how far we’ve come from ‘not understanding’ the universe. Rather than belittling how far we are from the tantalising ‘truth’, we should praise how far we’ve come from not knowing what is around us and appreciating how elegant the universe is. Without science, we would not have reached such heights of understanding and such depths in appreciating the universe. Indeed, we’ve come so far with the help of science. What is even more interesting is that the rate at which we are moving away from this state of ‘not understanding’ to clarifying our understanding of the universe is getting faster and faster. Which is to say that, not only are we able to understand how things work but we are getting better at understanding things.

We might deplore the fact that we haven’t had another Albert Einstein since he passed away in 1955. But back in 1900, just over a century ago, we could have said that we haven’t had another Isaac Newton since he passed away in 1727, some 170 years ago. Now we have the likes of Stephen Hawking who, less than a quarter of a century after Einstein’s death, is regarded as a giant of scientific prowess. This is a generalisation and should not be interpreted as stating that there were no other scientists in history who contributed to the progress of society. We have a whole hosts of notable scientists and engineers who have pulled humanity from the dumps of darkness to the lofts of enlightenment. What we should be proud of is that there are more and more such people who are able to push our boundaries even further and expand our understanding of the universe, at an increasing rate.

The scientific method has remained the same ever since we started questioning and analysing the world around us. We are born scientists for we naturally analyse the sights and sounds as soon as we are old enough to distinguish them. We are curious by nature, inquisitive even. Some of us go further by breaking things down, that is, by analysing things. Children are often reprimanded as a result of their analysing stuff but they are curious to find out how things work. And as such, start questioning the world around them. Not only do they break things down but they also like to put things together, that is, synthesising things. This also allows them to figure out how things work. They question the sound they hear, the colours they see, the flavours they taste, the textures they feel, the fragrances they smell and, more importantly, they question their immediate authority which happen to be their parents. This tendency to analyse and synthesise the world in is all of us, right from an early age and has to be nurtured and cultivated so as to better our understanding of the world and of ourselves.

The scientific method is not just about analysing and synthesising. Sometimes it helps to simplify what we observe in order to get a grasp of what is essential. Later on, we can then add the details. This simplification and representation of the world is what we call a ‘model’. The more accurate it is, the better but all models are approximations of reality. There are no absolute models; no models that are completely accurate. Otherwise they would not be models. They would be the real stuff itself. Think of a house. An architect can design a house and make a very good model of it. Yet that is all it remains: a model. For the model to be absolutely 100% accurate it has to become the house itself. It has to be constructed brick by brick, block by block at the exact scale that it’s meant for.

Likewise, if we consider the most basic of stuff, the building blocks of matter, we have what we call the atomic model. We have a very good model of how an atom is but that is all it remains, a model. We have certainly come a long way in improving the accuracy of the model but it is a model after all. That, however, doesn’t make it wrong or weak. On the contrary, this is the closest we’ve managed to get to in understanding the reality of atoms.

We have models for almost every system we can think of. How heat is transferred from one region to another, how sound propagates through different media, how planets form, how the whole panoply of known matter is composed of only 4 fundamental, basic building blocks, etc. Every model has its limitations but also its strengths. It allows us to simplify and understand what would otherwise be a complicated thing to comprehend. It allows us to draw similarities with other systems and compare how they behave and perhaps make predictions on the outcome of one based on the other. Models are indeed powerful in that sense.

But models they remain, nevertheless. When we say that light, for example, sometimes behaves as though it is a wave (when it interferes with itself to produce bright and dark patterns) and sometimes as though it is composed of particles (when it kicks electrons off a metal surface, a phenomenon otherwise known as the photoelectric effect), then that is exactly what we mean. We cannot say for definite what it is but all we can say is that, under certain circumstances, light is as if it is a wave or as if it is made up of particles. Light is neither a wave nor a particle but some other type of thing for which we do not have a name yet (see my blog on light and the electromagnetic spectrum for more on this). However, that doesn’t stop us from understanding how light behaves.

One of the aims of science is to make those models more and more accurate or to come up with a different yet better model altogether. Models are not permanent. They can certainly withstand the test of time but the timescale is something which we tend to measure by human standards. A model which is improved upon after only a few years (a fraction of a human lifetime) was not a good model to begin with, relatively speaking. Another which remained unchanged for centuries (several human lifetimes) can be deemed to be a good model. It is not only about time but also about space. A model can work fine if constrained by some physical boundary. That is, it is a model which only works for a local set of conditions. Take that to some other place or try and fit this model over a wider region and it becomes less accurate. This, again, doesn’t make the model wrong. It only tells us how to analyse something within a given set of conditions. We can generalise some models and test them if they still work or still make sense. For example, Newton’s model for the law of gravity can be verified on some simple apparatus in a laboratory. This model works fine under such conditions. We could also test it over a much larger region: the whole of the Solar system, for instance. Again, through observation and measurement we can verify that the model holds. Had the model not worked over such a large scale, it would not make it wrong; it would simply imply that it works for a limited region of space only – in this case, a laboratory. As it turns out, the model works fine for most part of the universe, not just our Solar system.

Yet, it is not the most accurate model we have for gravity. For about 230 years Newton’s model for gravity stood the test of time for being the best model out there. Then came Albert Einstein with his General Theory of Relativity and he proposed a new model for gravity. His model didn’t disprove Newton’s model, it only made it better. Also, Einstein’s model was able to explain the bits and pieces which remained inexplicable by Newton’s model. Here again we have a good example of how progress in science is driven by the refinement of a model. Einstein’s model led to a much better understanding of how the universe works and it opened the doors to many more questions.

In a similar fashion, the model for the building blocks of matter, atoms and subatomic particles, got better and better, that is, more accurate, over time. The model of the Solar system and how the planets were formed has also improved over the centuries. Science does not claim to hold the final answer (assuming there is one) but it thrives at getting further and further away from the unknown. One analogy to this is the needle-haystack paradigm. Suppose the needle is the right answer to some question we’ve posed and the haystack is a pile of wrong answers. We could go about eliminating each blade of dried grass, each wrong answer, to be left, eventually, with the needle, the right answer. So we can go on like this, picking each wrong answer, one by one, and throwing it away until we’re done with the whole haystack and be left with the one right answer. Or, we can be clever and find clever ways to pick the needle out of the haystack. With each pick, we come up with a better method to do so, with each pick, we learn a little bit more about the hay and where the needle could be, with each pick, we refine our understanding of the whole process and system. Now, there might not be a needle at all. But at least with each pick, we are discarding that which is wrong and learning a bit more about the system. Someone else can be even more ingenious and come up with a much simpler way to find the needle. Perhaps that someone has a better technology at her disposal. With the help of a magnet, the needle can be easily plucked out of the hay. Science, therefore, is a human endeavour to weed out that which does not make sense and to seek out that which adds value to our understanding of the world, using the best tools and machines available.

Seeking the ‘truth’…

Models should also be independent of any subjective bias. A model which cannot be independently and consistently replicated and verified cannot be accepted as a good scientific model. Whether it is a theoretical model or a practical one, it has to be objective, it has to be verifiable and it has to be able to set out clearly under what conditions it is valid. A model has to fit the data and not the other way round. We cannot come up with a model that puts Venus as the centre of the Solar system and then try and fit our observation and data to that model. We should be as accurate and reliable as possible with our measurements and observations and be as scrutinising as possible with our data before we can devise any model that would fit the system. Then, and only then, can we begin to understand and appreciate what we are analysing.

The best models are those that can be disputed objectively. If a model is dogmatic and not verifiable, it cannot be scientific. Whichever of these two types of model is closer to the ‘truth’ is irrelevant. What matters (to reiterate my earlier point) is that we should always be striving to get further and further away from the unknown using the most discriminating and objective methods possible. The ‘truth’, then, will show up – assuming it does exist in the first place.

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