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September 2013 Archives

We've just had our first session at the NZ Institute of Physics Conference. The focus was on astrophysics, and we heard from Richard Easther about 'Precision Cosmology' – measuring things about the universe accurately enough to test theories and models of the universe. We ablso heard about binary stars and supernovae, and evidence for the existence of dark matter from observing high energy gamma rays.

Perhaps the most telling insight into cosmology was given in an off-the-cuff comment from one of our speakers, David Wiltshire. It went something like this. “In cosmology, if you have a model that fits all the experimental data then your model will be wrong, because you can guarantee that some of the data will be wrong.”

Testing models against experimental observation is a necessary step in their development. We call it validation. Take known experimental results for a situation and ask the model to reproduce them. If it can't (or can't get close enough) then the model is either wrong or it's missing some important factor.(s). Of course, this relies on your experimental observations being correct. And, if they're not, you're going to struggle to develop good models an good understanding about a situation.

The problem with astrophysics and cosmology is that experimental data is usually difficult and expensive to collect. There's not a lot of it – you don't tend to have twenty experiments sitting in orbit all measuring the same thing to offer you cross-checks of results – so if something goes wrong it might not be immediately apparent. And if you can't cross-check, you can't be terribly sure that your results are correct. It's a very standard idea across all of science – don't measure something just once, or just twice, (like so many of my students want to do), keep going until you are certain that you have agreement.

Little wonder why people have only very recently taken the words 'precision cosmology' at all seriously.

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Remember, if it weren't for physics, there'd be no America's cup as we know it.

It's the NZ Institute of Physics Conference this weekend (well, Friday evening to Monday lunchtime to be more precise). There's a great line-up of speakers and posters, so there should be lots to blog about in the coming days.( I won't have much else to do in the breaks considering the weather forecast  -  it doesn't exactly do credit to Nelson's claim to be the sunshine capital of New Zealand.)

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Well, I have to get in an Auld Mug post before the end of the event. Today's cancellation gives me an extra day to do it. 

Watching the coverage of the boats for the first time was very interesting for me. First of all, it was alarming the speeds that they got to. This is far from the sailing that I've done, in inefficient dinghies that might hit 5 knots on a broad reach in a good breeze (and that's scary stuff). And second, not unrelated to the first, is the position of the 'sail' ('wing' I think is a much more accurate description of what the main sponsors stick their logo over), particularly on the downwind legs. I'm used to letting the sail out when heading downwind. Watch these things and the sail position is barely changed from what it is on the beat (upwind leg). And not a spinnaker in sight.

It's to do with the relative wind. There might be 20 knots of wind, coming from a direction somewhat towards your stern, but that is not what is going to be felt by those on the boat if it's shifting at 35 knots. What's important is the wind relative to the boat. In maths terms, that's the velocity of the wind, minus the velocity of the boat. It's a vector calculation - both wind and boat speed have a direction as well as a size. The effect is that the wind as experienced on board moves towards the bow. And if you're doing 35 knots, it will move a long way towards the bow. (On the rough diagram below, that's the blue dotted line.)  That changes your sail setting quite considerably (and renders a spinnaker entirely pointless - it would just be a large brake).

It also means that the wind shadow (the dirty air) is in a place you might not immediately expect. The boat most upwind, despite being closest to the wind, may actually be in the shadow of the downwind boat. All rather tricky at these speeds.

boat.jpg

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I was talking with a PhD student yesterday (not one of my students) about her research. She's well into her second year here and things are generally going fine, but she feels she's a bit stuck. What should she do next? She's happy to do her experiments, and work through the analyses of the results, and look at what they might mean, but then deciding on what route to take from that point on isn't clear. In particular, she wanted to be more creative but her imagination isn't imaginative enough. She reads research articles and marvels at how the authors thought of the idea in the first place*. But she feels stuck doing variations on the same old thing. How can she learn to be creative?

Before you think that 'creativity' isn't something that a scientist should have, let me clarify that it's not about 'being creative with one's results' (i.e. making them up) or abandoing scientific rigour in one's method, but rather it's about thinking what to look at. What would make a good experiment to try? What would be an interesting method?

That isn't an easy thing to answer, particularly since I go through the same feelings sometimes that I'm doing the 'same old thing' all the time. But at least I have the advantage of severals years' worth of research behind me, and I can look back at the times when there has been real creativity and ask what has driven it. There is a common theme - pretty well every time I've come up with something that I'm pleased with, it's been because I've been discussing my work with someone else - often not terribly familiar with my field.  Going to conferences is a great help here (so why are conference budgets cut so readily?) - simply talking to people about your work leads to questions along the lines of "Have you tried this?", "Do you know about Smith and Jones' work on this?", "How do you think your work might impact on such-and-such a topic?", "We have this problem - do you think your research can help us here?" and so forth. It's those kind of questions that are often difficult to ask of yourself and come from a broader knowledge of the area. Likewise, having the opportunity of seeing the work of other people and asking them such questions can lead to ideas. Occasionally, it can lead to really successful collaborations. I have one that's with a group of neurophysiologists. Their physics is patchy, and my neurophysiology is no better than their physics, but as a team there are a lot of problems we can tackle. 

Reading widely around the topic is also something I've found helpful. Certainly, a lot of the things I read aren't terribly inspiring and I put them in a file and rarely look at them again, but occasionally I find an article that is really helpful in getting me to ask myself questions of my research. And that's when things start getting a bit more creative. 

So, my answer to the PhD student is: go forth and talk to people (and don't worry if they don't know your area terribly well.) Use conference opportunites, use your fellow students, write a paper on what you've done and read the reviewers' comments. The more interaction, the more creative the subsequent work is likely to be. 

*Often, research papers don't report on the most interesting thing of all - how they came up with the idea. Cases I've heard from brutally honest speakers at conferences include "We didn't calibrate the equipment properly and that meant that we measured something we didn't intend to and found what we got to be really interesting" and "Because health and safety were going to shut us down if we didn't hurry up and find a new method". You seldom find such honesty carries over into the journal article. 

 

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I've just come out of a very interesting cross-faculty discussion on effective use of 'tutors' in our courses. It's hard to define the word, because the role of 'tutor' means different things in different parts of the university. But, think of it broadly as being someone who is paid (often not very much and on a casual contract) to teach in laboratory classes, give tutorial sessions to students, mark student work, undertake administrative teaching tasks (e.g. attendance registers for laboratory classes) and so forth. Tutors are often the primary contact that students have with teaching staff at the university - students probably feel able to talk to their tutors more freely than they can talk to other academic staff - though that is quite faculty and subject specific.  

Their role within the university system is very valuable. Their close contact with students ensures that students feel that they belong and have somewhere they can go with problems. But it's not the 'soft' stuff that's the only reason for using tutors - take a look at this research paper on the effectiveness of teaching of tenure-track and non-tenure track (adjunct) staff. The work looks at teaching at Northwestern University in the US, across eight years (it's a sizeable study - looking at 15,000 students). In particular, the study looked beyond a comparison of the teaching effectiveness of the two groups of staff in the courses where both groups taught, and looked at the enrollment and performance of students in subsequent courses. What it found was that students taught by adjuncts (what we might loosely call a 'tutor' here) got better grades in subsequent courses, and were more likely to enrol in subsequent courses in that subject.  In other words, the adjuncts were more effective in terms of both long-term student learning and student motivation. The effect was most marked with the weakest students. 

The work doesn't look at why this is the case, though it offers some speculative reasons, including that the tenured staff are recruited for being leaders in their research disciplines, not for being excellent teachers. 

This article should make all universities with a two-tier teaching staff system (such as Waikato) sit up and take notice. Just what strategies are we using when it comes to ensuring excellent teaching? Should universities split staff into 'teaching only staff' and 'research only staff''? Are tutors being paid according to the value that they deliver? And, importantly for the students who fork out large amounts of money to go to university - are the students getting value for money from their teachers?

 
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At the end of last week there was a problem with the water supply to part of the science buildings here at The University of Waikato. Today, there's been work going on to fix the problems. As a result, we have a very much reduced water pressure. The tea-room on the first floor is still supplying water, at a reduced flow rate, but on the third floor,  where I have my office, it's a different story. Turn on a tap and there's some gurgling and, if you're lucky, after several seconds some water splurges out. Just a little, mind you. Then it's back to the gurgling. 

The pressure in a water supply reduces with height. The higher one needs to lift a column of water (e.g. to the third floor, rather than the first), the more pressure is required. The relationship is encompassed as part of Bernouilli's principle . The pressure change with height, assuming no water flow, is just the density of the water (1000 kg per metre cubed) times the acceleration due to gravity (about 10 metres per second squared) times the height. Three floors up is maybe about 9 metres in this building - so that comes to about 90 000 pascals pressure. 

We can compare that to atmospheric pressure, which is about 100 000 pascals. So the water pressure up on the third floor is approximately 'one atmosphere' lower than that on the ground, assuming it's all fed by the same supply. Domestic water pressure varies considerably from place to place, but a few atmospheres would be typical. But today, with the water work going on, it's clearly a lot less than this, and the supply we have is struggling to maintain and significant pressure up here at the top of the building,

Water pressure also reduces with increased flow rate (again, from Bernouilli's principle). Given that people are probably opening up the taps for longer in a desparate attempt to get enough water out to wash the soap off their hands, that's not going to help the situation. 

 

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First things first. PhysicsStop is back on-line after an enjoyable two-week break in warm and sunny southern England.

Second things second. What advice can anyone give to the parents of a fourteen-month-old with jetlag who insists that 4 am is time to get up, have breakfast, and feed the chickens (or the "Choo Chuk" as he calls them)? In the end we got up, had breakfast and let the chickens and the neighbours get some sleep. Consequently I'm rather tired and feel like it's ten past two, not ten past eleven. 

So, here's a bit of quick physics from our travels. If you're fortunate enough to fly with an airline that still gives out hot towels to its economy class passengers, you'll know that the towels can be extremely hot - almost untouchable at first. But, once you've unrolled them and used them for whatever purpose you can think of, they cool down very rapidly. They don't stay hot for long, and you hand them back cold.

In physics terms, the towel, as it is presented to you, has a high temperature, but it doesn't have a great deal of heat. While we can use these words loosely and almost synonomously in everyday conversation about the weather, in physics they are very distinct quantities. Heat is a measure of the thermal energy in something. It's measured in joules, just like any other form of energy. The energy resides in the thermal vibrations of the water molecules. Heat is an extrinsic quantity. If one doubled the amount of the material (had a towel twice as big), one would have twice the amount of heat. 

Temperature is a lot harder to define in simple terms. (Try making sense of the Wikipedia entry on it). There's a nice physical definition (rate of increase of energy with respect to entropy) but that's not terribly intuitive. It's easier to think of temperature as an 'average' thing - broadly speaking temperature is proportional to the average kinetic energy per atom in the material. Each atom in something that's hot will have more kinetic (movement) energy than something that's cold. Any physicists reading this will realise I've given a horribly simplistic definition, but it is roughly correct. A key thing is that temperature is an intrinsic quantity - if you double the amount you have (a towel twice the size), the temperature (average energy per atom) stays the same.

Our towel starts at a high temperature. However, because it is thin, there isn't actually a lot of heat in it. That means that it quickly loses what heat it had once unrolled, and the temperature, which is what you perceive on your skin, drops.  Contrast this to a lump of rock that's been sitting in your oven at 70 degrees for five hours. Pick that out and see how long you can hold it for (actually, don't try it). It contains far more heat than a hot towel, so it takes much, much longer for it to be lost.

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