WILLIAM CHAPLIN: The Sound of Stars, Managing NASA Data, A/B Testing the Universe

Speaker 1 (00:00:00):

Welcome to the Unstoppable Recording Machine Podcast, brought to you by Sonar Works. Sonar Works is on a mission to ensure everybody hears music the way it was meant to be across all devices. Visit sonar works.com for more info and now your host, Eyal Levi.

Speaker 2 (00:00:20):

Welcome to the URM podcast. I am Eyal Levi and I just want to tell you that this show is brought to you by URM Academy, the world's best education for rock and metal producers. Every month on Nail the Mix, we bring you one of the world's best producers to mix a song from scratch, from artists like Lama God, Ms. Shuga, periphery The Day To Remember. Bring me the Horizon, opec many, many more, and we give you the raw multi-track so you can mix along. You'll also get access to Mix Lab, our collection of bite-sized mixing tutorials and Portfolio Builder, which are pro quality multi-tracks that are cleared for use in your portfolio. You can find out [email protected]. Before we get into the show, I want to tell you about a brand new product we just launched the Complete Beginner's Guide to Recording Rock and Metal.

(00:01:06):

It's a short two hour course hosted by Ryan Fluff Bruce, where he walks you through every single step of the process for recording a complete song from scratch in a simple home studio. If you've been thinking about getting into recording but you weren't sure where to start, this is for you. It gives you a list of exactly which gear that we suggest you get, shows you how to set it all up, then gives you a step-by-step guide to record a guitar, bass and vocals and programming midi drums, everything you need to record an awesome high quality demo with no more than a few hundred dollars worth of gear. And just to make sure you have absolutely everything you need. The course includes copies of Tone Forge Menace and Gain Reduction by Joey Sturgis tones and a virtual drum plugin from Drum Forge that's over $200 in software included with the course.

(00:01:56):

So it's pretty much a no-brainer. If that sounds cool to you, you can get instant access to the course and all the included [email protected]. Welcome to the Unstoppable Recording Machine Podcast by name is Eyal Levi. And today I have a guest that I am super excited about because like I just told him, I'm getting sick of talking about microphones and if you guys want me to do another 250 episodes, I'm going to have to start getting a guest that I'm very personally interested in talking to. Not that there's anything wrong with any of our previous guests, but try doing 250 episodes on just production and you'll be in my shoes today. I've got Professor William Chaplin, who is actually a professor of astrophysics at the school of Physics and Astronomy at the University of Birmingham, England. He's inspired by the space Support program and the US Space Shuttle launches as a kid and he pursued his passion to unravel the secrets of the universe, lending him a PhD as well as involvement with several NASA missions, including the really well-known Kepler mission. And with over 150 papers under his belt and organizing the activity of nearly 170 scientists in various programs as well as an author Bill's one of the leading minds in the fields of Helio seismology, which he covers in brilliant detail in his book, the Music of the Sun, the story of Helio Seismology. I'm going to stop talking. William, thank you for joining us.

Speaker 3 (00:03:39):

Thank you very much. It's great to be here.

Speaker 2 (00:03:41):

I'm just going to get right into it. What drove you to study sound in relation to objects in space?

Speaker 3 (00:03:50):

So this was a result of what the research group that I now lead in Birmingham, the work that they were actually doing going all the way back to the actually late 1960s and early 1970s, the chap who actually led the group then who sadly no longer with us, but Professor George Isa, he had been motivated and inspired by the challenge of finding life elsewhere in the universe. And that begins, or at the time began with actually finding planets beyond our solar system. So at the time, the only planets that were known were the planets in our solar system that are orbiting the sun. Of course, we were on one of those planets, the earth. And in George's work, he actually developed an instrument that he realized could potentially be capable of discovering planets orbiting other stars. But one of the things that he was very unsure about is whether the noise, intrinsic noise from the star might prevent his instrument from being sensitive enough to actually discover signatures of the planets.

Speaker 2 (00:05:16):

So basically what we would call a noise floor in recording, it sounds like the noise floor is too great on a star.

Speaker 3 (00:05:23):

Yeah, exactly. Exactly. And so he thought, okay, the sorts of stars we're going to be interested in finding planets around if we want to find life are probably going to be stars like the sun. So he thought, I'll try out the instrument on the sun and that way we'll be able to get a proper handle on what the noise levels might be. And so he and his colleagues started doing this actually with an instrument that was on the roof of one of the buildings here in Birmingham. And they started doing this in the very early 1970s. And in the process of doing this, they found that the data they collected seemed to show evidence for a persistent periodic signal, and they spent a lot of time scratching their heads over what this might be. And it took all the way to the, I guess the mid late 1970s for them to realize that the signature they were seeing was actually a signature of global resonances of the entire sun, by which I mean signatures that were causing the sun to oscillate.

(00:06:40):

And those signatures or signals were actually caused by sound waves trapped inside the sun. So they'd actually discovered that the entire sun was resonating just like a musical instrument. And that opened up a whole new way of actually studying the interior of the sun that we can get to and talk about. And it subsequently as well opened up as well the possibility to do the same thing as well on other stars. So I guess I was here in Birmingham doing my, well thinking about doing a PhD in the beginning of the 1990s. And so I thought this sounds quite interesting. So both studying stars in this way, but also as well the search for life beginning with the search for planets around the stars. And that's sort of the story of how I got involved in the work I'm in.

Speaker 2 (00:07:38):

So the audio is more a means to an end for you?

Speaker 3 (00:07:41):

Yes, it is. It is just the fact that we're very lucky that stars do this, that they make sound naturally in their interiors. The sound gets trapped in the body of the star. So even though a star is a big ball of hot ionized gas, it doesn't have solid edges like the edges of a musical instrument. So you think of an, I dunno, an OBO or a clarinet, you've got the body of the instrument there that's actually acting as a cavity to track the sound that's in the body of the instrument and it's that sound that makes the instrument resonate and you hear it play, then it crisp clean overtones or harmonics of the instrument. So in the case of A, the star makes the sound naturally and its outermost layers that sound is trapped. The star acts as a natural cavity to trap the sound, and as a result it resonates just like a oboe or a clarinet.

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Now we can't literally listen to the star. So that sound that's trapped inside there, making it resonate, doesn't actually escape and any way if it did, it would then pass into the vacuum of space. So sound doesn't travel through a vacuum, but because a star is a big ball of gas, what happens is those trap waves make the star breathe in and out. And what that does in turn is it makes the star brighter as it breathes in and darker as it breathes out. So instead of actually listening to a musical instrument and recording the sounds that are made and recording all the tones and harmonics of the instrument here, what we do is we can measure, for example, the change in the brightness of the star, but all that information on the sound waves is actually coded then into the changes in the light from the star. And that's how we can, if you get a window on the sound waves inside the star and hence what a star looks like inside as well.

Speaker 2 (00:09:46):

Do you have any sort of idea at all what kind of amplitude these waveforms have or just how powerful these sounds would be to us?

Speaker 3 (00:09:58):

Yeah, I mean the amount of energy that's tied up in them is hugely powerful. So the kind of thing if you work out the energy levels involved and imagine that you could hear the equivalent of something like that. It's the kind of energy levels that would quite happily kill a human being

Speaker 2 (00:10:18):

For sure. That's what I was wondering.

Speaker 3 (00:10:19):

Yeah, yeah. So a huge amount of energy tied up in that. But they actually paradoxically that they're very, very hard to detect because even though there's a huge amount of energy tied up in the sound waves, and that's because these sound waves propagate through in the sun, some of the sound waves traverse the entirety of the inside of the star. So stars are big things. The sun from one edge to another is about one and a half million kilometers across something like that. So there's a huge amount of energy there, but actually when you look at the amount by which the sun is actually breathing in and out, so if you think how much bigger or smaller just does the sun become as it breathes in and out, its size changes by these modes if you like, or resonances that we observe that affect the entire sun. They make the star breathe in and out by maybe only a few tens of meters in a more than a million kilometers. So they're actually on a global scale. They're quite small changes and quite hard to detect. But nevertheless, now with clever instrumentation, we can detect these very, very small changes and then use the data and cover the stars. Hidden secrets,

Speaker 2 (00:11:39):

You said tens of meters.

Speaker 3 (00:11:41):

So really tiny and on a timescale of a few minutes. So the sun's breed going from small to large to small. Again, with this difference in size being a few tens of meters, that timescale is it takes the order of a few minutes, about five minutes to do that. So the frequencies are very low in audible, down in the milli hertz regime.

Speaker 2 (00:12:09):

So the fact that you can even detect it at all on an object that far away or something that small is kind of mind blowing.

Speaker 3 (00:12:19):

Yeah, it's really one other thing as well. Nature's been very kind to us in that. Stars do show these signals as well in that there is, normally when we study stars, we observe the light that we receive from them before we realized that that light had all this information on the sound trapped inside, we would use the light from the star to tell us something about the star. But paradoxically, we could only then really get direct information on what's happening at the surface of the star from where the light is emitted. So one was in a position of having to infer what the entire inside of a star looks like just from learning what its surface looks like. So it's almost like the tail wagging the dog thing of trying to figure out what does the rest of the dog look like if you only have information on the tail. Now we actually have a way thanks to these observations, to really see what stars actually look like inside. And that's really revolutionized our ability to be able to study stars including our own star, the sun.

Speaker 2 (00:13:30):

I guess the most logical next question is without asking you something that would take 12 hours to explain, how do you go about, I guess in your mind accurately mapping out or figuring out what is on the inside of something that's again that far away and that no one's ever been to?

Speaker 3 (00:13:56):

So we sort of figure out how do we use these resonances? We can think of a few sort of everyday analogies. So one that I often talk about is you think about the different tones or the picture of the tones that are produced by musical instruments of different sizes. So let's suppose that I had someone with me here in my office or two people, one person who was playing a little tiny piccolo trumpet, the other person was playing a big tuba. You would know from hearing the two instruments, which player was playing the little piccolo trumpet because that plays at much higher pitch tones who was playing the tuba, which produces things at much lower tone. So the pitch there, the resonances is telling you something about the size of the instrument. Also, of course its structure. It is structure, what shape it has and everything like that.

(00:14:54):

And so broadly speaking, by measuring the pitch of the resonances of the star. So here instead of pitch, because we're not literally listening to the star, remember we are measuring how quickly it's breathing in and out. So there for a high pitch of a musical instrument, think of a star that's breeding in and out pulsating very quickly for much lower pitch tones of the tuba. The equivalent of that for a star is the star that pulses or breeds in and out much more slowly. So just in the same way that with a musical instrument, small piccolo trumpet plays a higher pitch. So a smaller star will tend to have resonances that are higher pitched or where the star breathes in and out much more quickly. So that's one example of how using the information, we can say something about the fundamental properties of the star in this case, how big it's then in terms of looking inside. So another analogy of breathing in helium from a party balloon. So I dunno if you've ever done that yourself, but I'm sure you of course, how other people do it. And then your voice goes very, very squeaky.

Speaker 2 (00:16:10):

Not recently, but yeah.

Speaker 3 (00:16:13):

So the idea here right, is that your larynx, your voice box, that's a resonator and it resonates because it's got gas in there, which is usually air. You flush out the air and have helium in there, helium's lighter than air, and the sound waves move faster through helium than they do through air. And that changes the pitch of your voice. So the stuff that you have inside a your larynx or inside a musical instrument that's providing the medium through which the sound waves can travel and propagate the nature of that gas, whatever that medium is, affects as well the sound waves and hence the pitch of the tomes that will be produced by the instrument. And the same is true of stars. So stars are a mixture of gas, predominantly hydrogen gas and helium gas with a smattering of other gases that are heavier than that.

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And as a star, ages star like the sun, the ticking heartbeat of the star is in its core where there are nuclear reactions that power the star and innate in the process of doing that, convert hydrogen gas into helium gas. Now helium is heavier than hydrogen. And what that does, that process of the star aging and turning some of its hydrogen into helium, that changes the way that the sound waves propagate through the star and it changes then the pitch of the resonances of the star as well. So just in the same way that someone breathing in helium and their voice going squeaky, if you were able to measure how much squeaker that a voice got, you'd be able to say yes, that's definitely because it's helium gas and not something else that you've used there to flush out the air. You can kind of do the same thing with a star as it ages the pitch or the pitch of the tones gets higher essentially. And so we can use that as well to say something about the structure of the star, but also as well how old the star is as well. So sort of two everyday examples of how we use our data on other stars to say something about what they really look like inside.

Speaker 2 (00:18:38):

Sounds like there's some very interesting parallels between I guess the microcosm of our life down here and how sound works out there. So are you finding that as well when you study other stars and other galaxies?

Speaker 3 (00:18:56):

Yeah, so our ability to be able to do use sound as a tool to study stars is really built on an understanding of the basic fundamentals and the basic physics that's involved in how sound propagates and understanding a lot of what we do. I guess in terms of thinking about how we interpret and use the sound that's trapped in stars, it's very similar to the basic physical principles that one uses to understand resonances and tones of musical instruments. And of course the physical conditions in a star are very, very different. Different of course to the conditions in an instrument that someone's holding when sitting in a room, playing in an orchestra. But it's still all basic physics and combining that basic understanding of sound with our understanding of what's happening in the environment of a star, where at the surface of a star the temperature is about 6,000 degrees at the center of a star like the sun, the temperature is millions of degrees, so quite extreme physical conditions. But because we have the basic foundations of understanding the physics of sound, we can then use our observations of the effects of these sound waves to then say something about what stars look like inside. So it's all founded on good fundamental physics that we understand a lot about.

Speaker 2 (00:20:37):

Just out of curiosity, under extreme conditions like that, do you know at all of, and I don't know even what I totally mean, but under those types of extreme conditions, does the nature of sound change at all or in the way that it would, I don't know what the right word is come across. Does anything about it change from how we understand sound?

Speaker 3 (00:21:05):

I think in terms of the way that we would use information on the sound that we'd have inside stars, the way we might use it to understand the environment around us, I think it's still basically the same physics. I mean there are some extreme examples. I dunno something like you can have a sonic boom that's produced by an aircraft that goes super sonic in the Earth's atmosphere, and we can get similar kinds of energetic events and phenomena that can take place within stars as well due to certain events taking place. But again, it's all founded on the same sort of fundamental physics. As I said, some of the energy levels involved, if you think about the total energy bound up in the sound that's contained in the star, it's hugely, hugely, vastly bigger than the energy that you have tied up in someone playing a musical instrument. But again, it's the same fundamentals, the same principles. And so we're on a firm footing in terms of being able to interpret what we see and use that to interpret what we're seeing in terms of what a star looks like inside.

Speaker 2 (00:22:21):

So being that you feel like you're on a firm footing and it pretty much seems to work the same way almost everywhere, does that give you hope for the original purpose of the mission?

Speaker 3 (00:22:36):

It does. I mean, it really has allowed us these observations for the first time to compare the models that we have of the inside of what we think the inside of the sun looks like and what we think the insides of the stars look like. It's provided us with the first opportunity to make a real proper comparison of those predictions with really what we see. And that might seem like a, I mean there's obviously the obvious question of yeah, fine, and I guess there are two ways, two sort of ways to think about this is why it's so important. There's one facet of this which is very important to us here on earth, and that's of course the fact that without the sun being there, we wouldn't be here. And also as well, the center effects as well through its changing outputs and emissions, something called space weather that we can talk about.

(00:23:39):

And all of those, the space weather and the emissions that the sun produces, they all have their origins in things that happen inside the sun. So if we want to get a better handle on what's happening there and how the sun is actually affecting us, then we need to be able to look inside the sun and that we can do. And then there's the sort of the general more wider picture of the sun is but one star in our galaxy, stars are building blocks of the galaxy, but they also provide safe harbors for planets and planets that some of which can potentially support life. So as well, if the quest to find life elsewhere in the universe, finding life outside our solar system begins with the search for planets around stars of which many thousands have now been found. But it's also crucial as well to be able to understand the nature of the stars around which the planets are found because that determines whether these, in large part, whether or not the planets might be habitable, the impact that the stars have on those planets and so forth.

(00:24:50):

So there's the sort of wider bigger picture question of are we alone in the universe? How common is life out there? How typical is our own solar system and our own planet, the earth? A really important key to unlocking those questions is being able to understand the life cycles of stars and also to be able to measure specifically the properties of stars around which planets have been discovered that we think might perhaps be capable of harboring life. So the telescopes that we now have that can make these observations, satellites and telescopes are now providing us with the data to be able to do this and unlock, I can unlock the secrets of the previously hidden secrets of the stars.

Speaker 2 (00:25:44):

If you had to guess life or no life, what do you think?

Speaker 3 (00:25:48):

Oh, I think definitely life. I think it would be a very curious, curious if we were unique and alone. And I think there's every chance that maybe perhaps within my lifetime, but certainly within the lifetime of people that are alive now, that we will find signatures of life elsewhere in the universe. Certainly that the key of course to being able to do that is to have the technology and the ability to make observations, which could find what we call biosignatures. So observable markers that we can find when we observe planets orbiting are the stars that are maybe telltale indicators or signs of the possible presence of life. So irrespective of whether or not one believes that we will or won't find those signatures, it is true to say that we will be in a position to be able to search for and find those signatures certainly within my lifetime, I think, which is quite an exciting thought.

Speaker 2 (00:27:00):

That must be what keeps everyone going.

Speaker 3 (00:27:02):

I think it is. I mean it quite sobering to think that until the 1990s, the only planets that we knew were the planets that are in our solar system, including the earth, the planets that all bit the sun. And so prior to that, you think of all of the billions of stars in the galaxy, the millions of stars that you can see in the night sky at night, that prior to the 1990s, we just didn't know where there really planets orbiting stars in the night sky, how common are planets? And thanks to a whole new generation of observations made by ground-based telescopes. And as well observations from satellites too, we now know having discovered thousands of planets orbiting other stars in our galaxy, we now know that planets are very, very common throughout the galaxy.

Speaker 2 (00:28:04):

I mean, it is mind blowing that it took us till the nineties. It's more mind blowing to me though that there's people in 2019 that still don't believe you. But I guess that's a different conversation,

Speaker 3 (00:28:17):

But at least we'll be in a position to be able to have, as I said, have observations or have

Speaker 2 (00:28:24):

Capability

Speaker 3 (00:28:25):

To say yes or no one way or the other. I think again, hopefully within my lifetime,

Speaker 2 (00:28:29):

So does the heightened reliance on this technology. I mean, in order to get to this level of technology we're looking at I think a few more decades in which the rest of our lives will undoubtedly become even more overrun with technology. And I think if we think that we're dependent on it now, we're only going to be that much more dependent on it 20, 30, 40, 50 years from now. Does that worry you at all?

Speaker 3 (00:29:02):

I suppose in the context of what we've been talking about? I mean there's in

Speaker 2 (00:29:07):

That context. Yeah, yeah.

Speaker 3 (00:29:08):

There's one angle we can sort bring in, which is what I've mentioned earlier about this thing called space weather. So the sun produces outputs and emissions of what we call charge particles. So very energetic particles that travel through the medium, the inflammatory medium between the sun and the earth. And then what these particles do is they interact with the earth's magnetic field and that produces, for example, the northern and the southern light, so the Aurora Borealis and the Aurora Australis. So these beautiful displays that one can see at northern, very northern and southern latitudes. But also what those charge particles do as well is they can actually impact us here on earth or our more specifically our advanced technological society by doing things like affecting global communications, knocking out communication satellites. Some of these charged particles as well can knock out power grids on earth, so at very northern latitudes because these particles can get funneled down into the atmosphere by the earth's magnetic field.

(00:30:35):

So these are things that can all have an impact on us here on earth. And so governments now actually have as, for example, our own government here in the uk, which has a thing called the National Risk Register. The risks posed by space weather events are something now that features on that register. Now I should add as well that before your listeners shouldn't certainly think, oh my God, is this something that's going to fry as well? Don't worry. But these are things nevertheless, that as we have a society that is ever more reliant on advanced technology, global communications, these are things that are affected by these events and extreme events, extreme space weather events can have a tangible impact in terms of affecting communications satellites affecting global communications as well. So there are concerted efforts now to do what's called space weather forecasting. So to try and just as we endeavor to make evermore reliable forecasts of weather here on earth of trying to actually make forecasts of the space weather.

(00:31:49):

And these events ultimately have their origins, as I mentioned earlier, in processes taking place beneath and at the surface and just above the surface of the sun. So the challenge there is to be able to, can we predict when the sun is going to produce these huge emissions and predict whether or not are they going to intercept interceptors here on earth and how energetic are they likely to be so that we can make contingency planning for this sort of thing happening? But was a very, very famous event, the most famous of these space where the events actually happened in the 19th century, it's called the Carrington event, which was an event that at the time was so energetic that it had an impact on then the nascent global communication system on earth then telegraphs in terms of frying a lot of telegraph systems and wires at the time. Now that's an extremely extreme event, but nevertheless, these things happen every now and then. So our ability to be able to predict these events, understand them and predict them is I think something that is quite important.

Speaker 2 (00:33:06):

I agree.

Speaker 3 (00:33:06):

It's a nice example of how the kinds of, the sorts of stuff that pure scientists, pure science, understanding stars might seem like something that's quite esoteric. There is a blue skies aspect to it, but there's also a tangible and important aspect to it as well to us here on earth.

Speaker 2 (00:33:26):

I really do think that we are only a few steps away from chaos at all times. And the reason I think that is just because of what happens in my town, anytime there's a gas shortage, people start devolving and they start getting crazy. I can only imagine how long it would take for things to completely devolve

Speaker 4 (00:33:53):

If

Speaker 2 (00:33:53):

We didn't have our electrical systems for long enough.

Speaker 3 (00:33:56):

Yeah, yeah, exactly. So I think the kind of work that we're doing does have a bearing on us being able to safeguard ultimately some of those, the global communication systems that we have.

Speaker 2 (00:34:13):

So changing topics a little bit, I'm just curious, how did you get involved with NASA at all? How did that come up?

Speaker 3 (00:34:22):

Yeah, so that came about through, so up until about the mid two thousands, the research that I was doing within then, the group that I now lead here in Birmingham, we were exclusively studying the sun and the mid two thousands, then it was already known. I mean things were well on the way in terms of preparations for the NASA capital mission and the guy who was the PI of the mission, the Kepler mission, a guy called Bill Beru, he realized that in the method that Kepler was using to find planets, it's called the transit method. Essentially you find a planet by getting lucky. Lucky in the sense that the planet as it orbits, the star actually passes its orbit, is a line such that it passes between you, the observer and the face of the visible face of the star. So it passes across the star blocking some of the light and you detect a minuscule dimming of the light of the star.

(00:35:24):

Now what you're doing there is you are finding a planet indirectly by the effect the planet has on the light from the star. And there are various reasons why it's important to be able to understand the star in as much detail as you can. Now, bill Barki had read about the fact that you could do use resonances of the sun to understand the sun much better. And he also knew at the time as well that there were the first telescope, ground-based telescope observations were being made of these resonances on other sun-like sunlight stars. And so at the time, what he did, he actually contacted a group of astronomers in Denmark because they happened to have at the time a webpage, which was talking about a small satellite that they were trying to get together, which would've been dedicated to measuring resonances of bright sunlike stars.

(00:36:22):

So he contacted them and started the dialogue with them and said, Hey, what can we potentially use these ideas measure resonances on in some of the stars around which we're going to discover planets? If we can do that, that's going to be fantastic for being able to characterize the stars and also the planets that we find around them. So the two people that he spoke to, so Jan Christensen, DA's Guard, and Hans Kon, who are the two lead guys still at the group there in, they realized that this was going to be such a big undertaking that they thought they had the foresight. And all of the international community that I'm involved with, we thank them very much for doing that. They had the foresight to realize that heck, this had to be a big international community-wide undertaking. And so what they did is they initiated a big international consortium of people that study stars in this way. So you'd already mentioned at the top of the podcast that this is a field that we call Helio Seismology when applied to the Sun. So Helio for the Sun seismology because we're kind of studying resonances or sun quakes, it's called astro seismology when applied to other the stars. So Astro for Stars, again seismology because we're studying residences or Star works this time. So they reached out to the rest of the international Astro seismology community.

Speaker 2 (00:37:54):

How much of a community is that? How many people?

Speaker 3 (00:37:58):

It's a few hundred scientists. I think it got to laterally up to maybe 500 scientists around the world

Speaker 2 (00:38:05):

So you could kind of all know each other.

Speaker 3 (00:38:08):

And they set up this big consortium. And so I was lucky enough to be chosen to run the parts of that consortium, which were studying stars like the Sun and also Planet hosting stars as well. And then as well through that as well, I got involved working quite directly with the team that were actually running the mission. And what we've done is to actually replicate that consortium for another NASA mission, which was launched just last year called Tess. Tess is an acronym for, it's called the Transit in Exoplanet Survey Satellite, but we're also using TE to study stars as well. And so we've replicated that structure as well. So I'm involved in leading that consortium, the board that leads that consortium along with Yarn and Han and some other colleagues as well, including the lead, the US leads of the TE mission as well. So yeah, that's how we got involved with these NASA missions.

Speaker 2 (00:39:15):

Hey everybody, if you're enjoying this podcast and you should know that it's brought to you by URM Academy, URM Academy's mission is to create the next generation of audio professionals by giving them the inspiration information to hone their craft and build a career doing what they love. You've probably heard me talk about Nail the Mix before, and if you remember, you already know how amazing it is. At the beginning of the month, nail the mix members, get the raw multitracks to a new song by artists like Lama God, Opeth, masu, bring Me the Horizon Gaira asking Alexandria Machine Head and Papa Roach among many, many others. Then at the end of the month, the producer who mixed it comes on and does a live streaming walkthrough of exactly how they mix the song of the album and takes your questions live on the air. You'll also get access to Mix Lab, our collection of dozens of bite-sized mixing tutorials that cover all the basics and Portfolio Builder, which is a library of pro quality multi-tracks cleared for use of your portfolio.

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So your career will never again be held back by the quality of your source material. And for those who really, really want to step up their game, we have another membership tier called URM Enhanced, which includes everything I already told you about and access to our massive library of fast tracks, which are deep, super detailed courses on intermediate and advanced topics like game staging, mastering loan and so forth. It's over 50 hours of content in, man, let me tell you. This stuff is just insanely detailed. Enhanced members also get access to one-on-one office hours sessions with us and Mix Rescue, which is where we open up one of your mixes on a live video stream, fix it up and talk you through exactly what we're doing at every step. If any of that sounds interesting to you, if you're ready to level up your mixing skills and your audio career, head over to URM academy slash enhanced to find out more. Lemme try to understand something. So you have around 500 people around the world all working on the same thing kind of at their own universities, at their own space centers or wherever they are. Is there a central directive like some sort of delegation or is it more that you guys just compile everyone's individual data? How's the work spread out? Where does the coon come in?

Speaker 3 (00:41:48):

In the case of Kepler, initially things were organized in a very top down way, and this was actually, we were very lucky in that because we were in a position to be able to characterize some of the planet hosting stars using the seismology, that meant that as a consortium we got access to what's called proprietary data. So that's a term that means that sometimes on some space missions and Kepler was one of 'em, only a restricted number of people can actually have access to the data before they made complete public for any scientist to be able to use. So we were lucky in being able to get early access to data, but one of the things that we did in order to be able to do that was to organize the consortium in a very structured way, but that turned out to be quite a good thing and that it meant that we had teams of people who were interested in working on particular types of star.

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And that structure has been replicated in what we've done in tests. So it means that you have groups of people who have a like-minded interest in terms of the types, the different types of stars that they're interested in looking at. And then that work has mainly been sort of self-organizing in the sense that there's some work where it really is advantageous for everyone to work together. For example, the first papers and the first discoveries that are made using the data, it can be really advantageous to work as a big team towards a common goal. And then what tends to happen then as time goes by, that there will then be, once you've pick the low hanging fruit and then the big papers on the early discoveries, what happens then is that people then start to look at things in more detail and everyone has particular things that they're interested in and then things naturally then divide down into smaller teams working on things.

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But there's also across the consortium as well, the wider goal of actually being able to take the very raw data that we get from the satellite and to prepare it in a way that makes it ready for us to analyze and extract science from it. So one of the other really important things of having a big consortium like this is the coordinated activity that goes on around producing things that enable science, enable us to do everyone to do the science. And so there's been a big coordinated undertaking, particularly in tests, to have members of a team within the consortium that will provide, that will take the very raw data we get from the satellite, put it in a prepare it mask and say massaging it. That's not quite the right way of describing it, but preparing it,

Speaker 2 (00:44:48):

Prepping it,

Speaker 3 (00:44:49):

Prepping it in a way that is then in just the right form that people need to say, right, this is just what I need to be able to extract the science from it. And that's something that it's a team of people within the consortium, but they are providing a service for the rest of the everyone within the consortium and that's fantastic.

Speaker 2 (00:45:09):

So when that data is prepped, just out of curiosity, is it prepped to some, I guess universal standard that everybody works from? Just to put it in really simple production terms, just sending, for instance, everybody wave files at 24 48, that's send those to a mixer, prep the files, send them and they'll know what they're getting if that's what you send them, and it's not some oddball file format they've never heard of. For instance, just for instance, is it prepped in a way to where it's one, I guess generic prep to a universal format or is it individually done for each team's specifications and needs?

Speaker 3 (00:45:54):

So the analogy is very, very similar to that to what you said. So I think there's what the default product that one would produce, which is the standard vanilla prep where everyone knows exactly the different techniques or methodologies that have been used to produce the data that it's turned out in a standard format. And so everyone knows then the various, so we actually take the stuff is churned out in multi column files of data where one knows what each, there's a standard format, one knows what's stored in each of the different columns so that when one gets one of these files exactly what's in there and importantly as well exactly what was done to produce that file too. So for some of the science work as well, additional work can then be done to maybe layer on to add on an additional layer of preparation if that's needed to produce a bespoke preparation for a particular science goal.

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So it might be that a slightly different preparation is needed for a different type of star, or it could be that on a particular type of star one needs a bespoke preparation if what you're trying to achieve from the data is slightly different as well. And certainly different communities, I mean my community, we are interested in preparing the data in such a way that we can easily detect and extract the resonances of the data. So essentially it's in terms of visualizing essentially what looks like a waveform, that's what we want to extract from the data. But the requirements that we have on doing that and not don't entirely overlap with, for example, the requirements that you would need if you wanted to optimize the data for extracting the signatures of planets, for example. So depending upon your community, you're going to have likely different preparations of the data that are made widely available to those communities. But even within those communities there are different bespoke preparations that you'll do as well. But it's true to say that the most crucial thing is that everyone understands that irrespective of the prep you've used as a standard format that everyone understands as well, and also proper version control and all this kind of things. So that as the way that we prepare the data evolves,

Speaker 2 (00:48:34):

Your version control sounds really intimidating because I know that version control on an album will drive someone nuts. I can only imagine.

Speaker 3 (00:48:46):

So how many, just that of interest, how many different in terms of that kind of thing, how many different things might you have to go through? I mean, for us it's probably not that many.

Speaker 2 (00:48:54):

It all depends really on how complex the project is and how annoying or I guess on one end of the spectrum you have annoying. On the other spectrum, you just have visioned and detailed the client is

Speaker 3 (00:49:09):

With

Speaker 2 (00:49:09):

What they want. Some people just want a bunch of stuff because they want a bunch of stuff and it doesn't make it better or worse. And some people truly are visionaries who want every detail exactly the way they want it. And so you end up doing 100 versions, but it's not a bad thing. But sometimes you end up doing 18 versions and you want to shoot yourself. But I think that the best organized people I know tend to make a new version every single time something major gets added. So really it's hard to say that there's a standard amount because every musical arrangement or production style is unique to that project. But I've seen lots of people who do this, once they say you're doing drums, then you're adding guitars, then you have versions for guitars, then the vocals are coming in, so you have all the vocal versions, thens, et cetera, et cetera, et cetera, on and on and on. So that no matter what happens, you can always go back. You always know exactly where you're at.

Speaker 3 (00:50:24):

Yeah, it sounds like, I mean the issues that we have are very, very similar in terms of that's right of there will only be new official releases of data if something significant has been done to change the way that the processing of the raw data is, how that's made

Speaker 2 (00:50:46):

Makes sense.

Speaker 3 (00:50:48):

And also, so there's not in the lifetime of a mission, there are probably, I don't know, might be of order of maybe, I don't know, 10 to 20 maybe iterations of how the data get processed. But also as well, it's very important to be able to, that one keeps a record as well of the earlier versions so that sometimes one might discover that a particular change that's been made to benefit one type of analysis might create issues for another. And so being able to track back and compare with previous versions is really important.

Speaker 2 (00:51:27):

On that note, something that happens sometimes is, one of the reasons this is good is sometimes you mix yourself into a corner, for instance, you're working in a certain direction and for some reason you just create a problem that you just can't really get out of without just starting over. So going back in time before you created that problem is usually the best solutions, that sort of thing kind of where you just can't move forward the way it is for what you need.

Speaker 3 (00:52:00):

Yeah, I think, yeah, there are new approaches that will be developed and tested all the time, given the nature of what we're doing in terms of how we process and analyze the data and just the nature of research means that quite often one will have an idea, but it just hit a dead end. So yeah, being able to then work back through, if one's trying a new way of looking at the data or approaching how you analyze the data, if things look like they're maybe headed up a dead end at least being able to track back and figure out, well figure out at what point did things stop getting better or more useful?

Speaker 2 (00:52:41):

That just sounds so insane to me. I guess it's just because I'm unfamiliar with the field, but I am guessing that for you guys when you're approaching a dead end, but how do you know, because you're studying stuff that you're trying to discover things that you don't already know. So how do you then know that you're about to hit a dead end? How do you know that if you didn't just go a little further,

Speaker 3 (00:53:12):

You'd

Speaker 2 (00:53:12):

Find what you were looking for?

Speaker 3 (00:53:14):

I think usually it's the case that you are trying to find, or maybe there's a signature that you can already see there that's in the data and you are thinking, okay, right, I think this is real, but is there a better way that I can extract that signal or tease it out from the data? So at least you've got a benchmark for yourself already. You already having had, there's something there in the data that maybe your vanilla approach to the analysis has already uncovered and you're thinking about it a different way of teasing out that signal. So at least in that sense, whether you're doing better or worse compared to what you had before. But you're right in terms of if you are trying to discover something a new, it may be that you are, for example, I dunno, trying to discover a whole bunch of resonances on a star that you haven't found before.

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So on the sun, we know that we have not detected all its resonances. There are some that are just too weak to be seen against the intrinsic background noise that we were talking about earlier in the podcast. So there are real scientific gains to be had from actually finding those resonances. And so people are, there's actually been a renewed push actually to try and do that over the last few years in the solar field. So we are thinking, trying out new ways of trying to analyze the raw data and actually extract those signals in a completely novel ways of doing that. I guess there it's more a case of us discovering maybe trying things out with fake data. That's a good way of being able to check them. Whether or not you are hitting a dead end, something that doesn't work, either works no better or maybe even worse than what you already have or something that you think works much better.

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That's a good way of being able to use that benchmark of if I make some fake data with signals in there that are buried in the noise, I know they're definitely there because I've made the fake data myself. And then you can throw some of your new analysis techniques at it and at those fake data and see whether or not they can actually uncover something. If they fail to find something, of course, because they're fake data, you've got, it's up to you what you put in those fake data so you can crank up the amplitude of that tiny signal you're trying to find. And then at least for the new method analysis methodology you're developing, at least then you've got a handle on what kind of signal threshold do you need in order for your new technique to find something. You can then compare that new technique with something old, with your previous technique and see whether there's any better or not.

Speaker 2 (00:56:06):

The fake data, do you know what you're putting in there? So you know what you're looking for fake data wise, or is it something along the lines of someone on the team or the computer just puts some fake data in there, but you don't know what the fake data is, you just know you're going to come across some fake data at some point. And so you have to be able to determine if you do come across it, whether or not it was the real thing or what was inserted or do you know what you're inserting? That's

Speaker 3 (00:56:37):

A great question. So sometimes you do and sometimes you don't. So maybe if you are just playing around with developing the stages of developing something yourself, then you'll probably make your own fake data so you know exactly what you're putting in there and you can then test the analysis that you're doing. The real asset test of a one's ability to be able to dig out tiny, tiny signals from noise is doing the other thing that you suggested there where it's someone else that makes the data and you then are doing that exercise blind. You don't know, you're given some data, you don't even know whether or not someone has put fake signal in there. They might have done, you don't know what necessarily the nature of the signal is, although you know that the person doing it obviously is trying to make it look as realistic as possible.

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So you've got some prior knowledge, some expectation of what it is you're looking for. And those kinds of tests are really, really important. This was actually done by the, it's something that we've done, but they're called hair and hounds exercises. So the hair is, the hounds are chasing the hairs. So the idea there is that the hounds of the people who are actually then trying to dig out the signal, and that's then what we call a completely blind, that's a blind exercise where the people who are trying to extract the signal don't know what's been put in. You can also do double-blind exercises. So this is where there will be a set of people who are making the fake data, but maybe they could maybe set up a computer program or get someone completely who isn't involved in the collaboration to actually make the choices for them. So there are constrained choices over what should go in the data, but the people who've actually been, the people who've actually set up the code that makes the fake data aren't necessarily the ones that actually make that choice. So even they don't know what's gone into the data, even though they know they've developed the tools to make the data. You see what I mean?

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And that's a real stern test and of your community. So that kind of thing was done by the, so the gravitational wave communities, the gravitational waves got discovered. This is a huge big deal just a few years ago. And there they're trying to tease out and extract tiny, tiny signals from the data and they did these kind of double blind exercises where these huge communities would be analyzing data and also they wouldn't even know for some of these exercises whether or not they were analyzing real data or fake data. So that really is the odd. So there you're getting into human psychology right now around,

Speaker 2 (00:59:38):

It's so important. People

Speaker 3 (00:59:39):

Make different choices around what they do if they know what they've been given is fake versus there's the possibility they've been given something that's real, that if they find something, it may be the first real detection and is that the knowledge that it might be real might change the way you approach the analysis, how circumspect or careful you are and all those kinds of things. So yes, it is a great question. It gets into then the psychology of how a big collaboration approaches doing its analysis and verifying the results it finds.

Speaker 2 (01:00:19):

Well, that's something we have to deal with all the time. And I figured that for you guys, I know that you're supposed to approach the data in a non-biased way and just react to the data as it is, but you're a human, you're going to have biases.

Speaker 3 (01:00:37):

Yes, exactly.

Speaker 2 (01:00:38):

I'm wondering if you come across this, because actually I've had to do this, and this is a common thing because a lot of people in music have biases about stuff that is just really, really dumb. Like what a certain type of guitar amplifier is, whether it's a tube amp or a digital amp or dumb stuff, and they think that they can spot the difference and people will slow down productions and grind them to a halt over dump, things like that. And one of the best ways to get them to just stop is to give them a blind ab, let them pick what they like better. And oftentimes they'll think that what they're picking is what they were biased towards and they're wrong. And then once they realize that they were wrong, they don't bother you about it anymore. Wondering if you have any situations where you've encountered situations or maybe this is just really, really rare in your community, where sometimes people want it to be something and the data says that it's something else, but they have a real hard time letting it go because human, they want it so bad.

Speaker 3 (01:01:53):

Yeah. I think that it is that thing of around if you are expectations over what you might find in the data that may be based on for good reason on other theories or other observations that have been made, but a good scientist, this means the vast, vast, vast majority of scientists, you've got to park that prior expectation or at least use that in the right way. It's prior knowledge, right? Your expectation of what it is that you are not only searching for, but what you think that signal might look like and what it tells you, your ability to make a judgment about that and interpret it and draw conclusions is based of course on your experience, your expertise, and that's prior knowledge. So I think the crucial thing is using that prior knowledge in the right way, not in a way that is going to just blind you to say, well, this was my prior knowledge and expectation, and that it's going to completely blind you to really what the data are telling you, but to use it in a way that is informative but doesn't bias you if the data are telling you something entirely, entirely different.

(01:03:14):

And I think that's a really important skill of being a good scientist, is using that prior knowledge and that expectation of what you're going to find in the right way. Because the most important discoveries, discoveries by their very nature are usually of things that one wasn't expecting. Serendipitous discoveries, I mean the

Speaker 2 (01:03:42):

Happy accidents.

Speaker 3 (01:03:43):

Exactly. I mean, when I was talking earlier about my mentor and colleague George, George Isaac, who I was talking about how him wanting to test out his instrument on the sun to find out the noise flow level, this discovery that the sun was pulsing in and out was resonating, happened completely by accident. And so that was a great example there of exactly a scientific discovery by accident where one is a good scientist has to say, whoa, this is not what we were expecting to see at all. But to then have the insight and the foresight to realize what it is you're actually seeing, and then also to recognize the significance of that as well. And I think usually the most exciting discoveries, there are some discoveries that will be made where people are hoping, I mean like the gravitational wave discovery of gravitational waves, the signatures there of what found were matched with expectation and theory, but that's such, I mean that's just a game breaking discovery, but one that matched with expectation. But then there were the other discoveries that are made, which are made completely by accident, where you have to have the insight to realize the significance of what you've discovered and then that can open up a completely new field of endeavor, which is what happened in the case of resonating stars like the sun.

Speaker 2 (01:05:10):

Sounds like there's an artistic element to it. I mean, you are just interpreting what you're being given, so it's not like you're creating it, but the ability to understand that what you're seeing, if it's something that you weren't expecting, that you've never seen before, yet you can understand what it is that you're seeing plus infer its significance. There's something artistic to that. It's not just analytical.

Speaker 3 (01:05:37):

No, I agree. I think science is a very creative process and one has to, there's an element of finding the right inspiration. Quite often one can have a, it is having that insight or that light bulb moment, which I'm sure will be common to people working with purely creative endeavors in art, music and so forth. But I think as well, there are a lot of common features there as well. I think certainly one of the things actually on that front that I'm very interested in is the commonalities and differences that there are between artistic practice and scientific practice. And so I do quite a lot of work with artists who have different practice ranging from a sound artist through to dancers, people who sculpt all sorts of different endeavors. So we do art science collaboration in that, but also those collaborations. We're also interested in trying to understand how we can actually influence each other's practice. I mean, not through the obvious thing of, for example, the sound artist I work with. She has taken the sound data that we have on stars and incorporated that into her practice and the pieces she produces. But we're also interested as well in not just,

Speaker 2 (01:07:09):

That's kind of the low hanging fruit, I guess.

Speaker 3 (01:07:11):

Exactly, exactly. But also how can we actually, from the way that she approaches her practice and what she does with her work, can she influence how I approached you in my science and also vice versa. And so this is something that we're trying to investigate with artists from different areas, and quite often it can be much more easy to show how maybe the scientist influences the artist showing the influence in the opposite directions a bit harder. But I think that goes more to issues around how you approach doing a particular piece of work, how you structure it, how you break it down into its component parts, how you approach teamworking, the approaches that are used by artists who may be work in teams rather than on their own. That I think can provide interesting insights to how teams of scientists can actually break down and approach their work as well.

Speaker 2 (01:08:07):

I'm curious about those light bulb moments. I know that that's always been something that I go for. I'm trying to get to those moments no matter what I'm doing, whether it was when I was a guitar player or a producer or creating this school or whatever it is I'm doing, I've always tried to get to those light bulb moments, but I discovered that you can't really predict them. I mean, you can set the stage for them, but you can't predict them. And the best creative people I know are people who are just prolific, and it doesn't mean that their work is prolifically good, it just means that they are prolific in their output, and so they set the stage for the light bulb to turn on more often. And so they end up having a greater quantity of great work just because they're sitting down to do the work more often as opposed to some people I've known who are off the charts in terms of ability and talent, but were maybe kind of lazy or just waiting for inspiration. And then sometimes they would do really great work, but other times they'd be inspired by something dumb and put out something bad, and because they weren't prolific, it would really hurt their progress. I'm wondering, do you know where this inspiration comes from for you or is it a similar thing where you just do the work and it shows up when it wants to? The inspiration that is,

Speaker 3 (01:09:39):

I think it's very, that. I think you make a great point there that you can, quite often the best ideas will come out of, seemingly come out of nowhere, but if you think about it a bit more, they sort of don't in the sense that you've already loaded the dice in your favor

(01:09:55):

By putting in the groundwork there. So you put yourself in a position to be able to have those moments. And so you've got that underpinning. And quite often I actually find that when I have the occasional light bulb moment, they don't happen very often, but when they do, quite often for me it's actually my walk to work, but actually my walk in the morning down to the local train station and there, that gives me a chance just to, something about walking, walking and thinking at the same time and mulling over trying to tackle a particular research challenge or a particular problem. But that for me provides a great time to be able to just kind of mull over things in my head in a very kind of free ranging way. And quite often then I'll find you're building on the foundations of the work that you've been putting in on that, but that often provides the right environment for me for that idea to suddenly kind of seemingly pop out of nowhere just from this kind of freeform thinking and just mulling things over. And then usually approaches to, it might not be solving a problem, but it could be the realization of, ah, right, okay, maybe I should try this or maybe I should try something else. And then that will often lead to the solution to the problem. So it's not always necessarily the light bulb moment that gives you, ah, that's the solution. It's sometimes as well light bulb moments that where you realize that the approach that will actually then give you the solution to the problem as well.

Speaker 2 (01:11:36):

That's usually what they are for me too. It's a light bulb that says, illuminates the idea of why don't we try it this way and see what happens.

Speaker 4 (01:11:45):

And

Speaker 2 (01:11:45):

It's a way I didn't think of before and it either works or it doesn't, which is the fun part. So when you are taking these walks, do you record your ideas at all or do you just remember them by the time you arrive?

Speaker 3 (01:12:01):

I don't. I usually remember 'em when I, yeah, so usually I stop thinking about a specific thing usually then if it's given me an idea or something that I think, yeah, I should do that, usually then when I get into work will then usually make a note of it. I mean, sometimes it can be something I can actually right away. So it could be emailing a colleague to say, right, okay, this is what I think we should do. And actually suggesting that they have a go at doing that. If it's something that maybe needs a little bit more thought or something like that, then I'll usually make a note of it and I actually have several for different projects or different things I'm working on, then I'll have ongoing records for each of those different areas and I'll just make notes in there for myself to maybe come back to think about it.

(01:12:55):

I have thought previously about that, about recording stuff Also as well, this doesn't happen often to me, but I know some of the colleagues who when they go to bed at night, they're sort of mulling things over and might wake up in the middle of the night and have a big thinking about something. And I know some colleagues who will deliberately have a pen and paper on their bedside table so that when they wake up, they'll make a note of whatever it was and they'll find then that enables them then to, it gets it out. They go back to sleep and then they can wake up in the morning and have a look and see whether or not it's a good idea or a bad one. I've never had that issue myself in terms of things keeping me awake at night like that.

Speaker 2 (01:13:41):

I'm jealous.

Speaker 3 (01:13:42):

But I know for some colleagues that does work well for them and sometimes it can be a good way for them to, that they will actually wake up in the morning and think, oh yeah, that's a pretty good idea. Or other times they'll just wake up in the morning and think, okay, maybe not, but at least it's served its purpose. The other purpose as well, of getting it out of their system so they can get a good night's sleep.

Speaker 2 (01:14:04):

Well, I find that sometimes the bad ideas, you have to get them out of the way to clear the path for the good ideas sometimes.

Speaker 3 (01:14:12):

Yeah, that's true.

Speaker 2 (01:14:13):

I feel like sometimes they are, it's more of a maintenance thing that you get them out so that they're no longer taking up brain ram so you can focus on the task at hand.

Speaker 3 (01:14:24):

Yeah, that's true. Yeah. I usually find with those that will come out maybe, and certainly for research stuff I'm doing, if I have time to work on a particular thing, then usually if I have a bit of time to actually sit down and think properly about something, if it's an idea I've jotted down, if I don't have time to think it through, usually it'll usually be obvious if there's something that's just a really bad idea. And then if you have a chance to have a good 10, 15 minute, think about it, you can usually then put it in the no pile, but at least as you say, you've ruled it out and also as well, then there's no need then to devote any more brain time to thinking about that issue. It's gone, and then you can concentrate on other things.

Speaker 2 (01:15:07):

So does it bother you at all that you're not going to get to see the conclusion of this work or where this work is at in 300 years? I'm just wondering if that at all messes with your motivation. I think it's pretty normal for people to seek conclusions or to seek, I guess a certain level. If you are, say in the military, there are ranks, I mean, eventually you hit retirement age, but there are certain ranks, and even though obviously the military goes on, there's a structure. There's a structure that, or if you're in sports, you age out, for instance. I know that in music, music just goes on and on and on and on, but you finish albums and then there's another album, and then you finish that album. I feel like with this, you're doing work for people a hundred years from now to keep working on very, very directly. Actually. It's not like Gustav Mahler wrote a symphony, and so now Han Zimmer is writing a soundtrack and Han Zimmer's finishing Gu Gustav Mahler's work. It's not that it's, it's more that someone 100 years from now might actually be finishing your work. Does that bother you at all, or do you find that exciting?

Speaker 3 (01:16:31):

That's an interesting question. I think probably more exciting and also as well that if there's something, I think it's, I guess the sense of achievement that if you've done something that helps to adds its own little, I think it's helping solve just even a little piece of the puzzle around stars and exoplanets. There's that sense of achievement in doing that. But also as well, if you've done something as well that lays the foundation or the bedrock of someone else as well, being able to take that and push that on to make further much more exciting discoveries. If you've done your bit to help lay the foundations for that, I think that's hugely satisfying. So I think if there are people now and in the future who are doing research that builds, if only in some small way on some of the stuff that I've done, I sort of see that as a huge compliment, if you like. So even though there are clearly things that will, in terms of discoveries that will be made in what I'm no longer here, that would be great to see. I like to think more on the compliment that it will be that even if I play just a tiny, tiny, tiny role in terms of setting in train, what's done there, that's more than good enough for me.

Speaker 2 (01:18:06):

I'm glad to hear that. Otherwise it sounds like it would be torture. Yes, absolutely. One more question. I know you've got to run. We have a few questions from listeners, but I'll just ask one, I know you have the heart out. This is from Russ Mueller, and it's one of the most defining advances of modern music is autotune, and that came from the application of seismic analysis algorithms to the human voice. Are there analytical methods and tools that you use in your work which you think could creatively be applied to audio in a non-research capacity to produce new kinds of sounds?

Speaker 3 (01:18:44):

Whoa, that's a very good question. I guess so when we do turn our, so we can take our data and turn it back into sound, and it's certainly true to say that there are lots of different ways of sonifying. I mean, you will know this much more than I, and when I've discussed this as well with artists who use sonification as well, there many subtleties and many different ways of doing that. So we often will use the sonification approach very much for the purposes of outreach or the kind of creative stuff that I do with artists as well. In terms of those kinds of algorithms and the auto tuning thing and sort of analogy with what we do in terms of our science, I guess we are doing stuff with waveforms and we're trying to measure the properties of those waveforms. The closest analogy I think I can think of is that sometimes we might be dealing with, sometimes with waveforms that aren't exactly periodic or whose properties maybe change over time, and it can be then easier to actually detect and understand and extract the information from those waveforms by actually deliberately distorting them, but distorting them in a way that makes them easier to detect.

(01:20:21):

So it may be distorting the waveform to make it more periodic, for example.

Speaker 2 (01:20:26):

Is that because it brings more of it out?

Speaker 3 (01:20:28):

Yeah, essentially it just makes it easier. If you're looking for, if you imagine, say you've got a really coherent signal and that coherent signal, say it's period or wave, the waveform doesn't change over time, then that's really easy to find. But if you have a periodic signal where maybe the waveform is changing over time, perhaps the period is changing in time and you use the analysis that you would use to extract a completely coherent waveform that isn't changing over time. If you've got a signal that is changing, then it will smear out the signal. And so there are tricks you can use to actually, for example, most of the data that we have are collected as a function of time. So if you have a waveform that's changing in time and you had some idea of how it might be changing, then one approach would be to deliberately distort the time axis to make it look like it was periodic.

(01:21:25):

There are some signals that we have in the frequency domain in stars that are not evenly spaced in frequency or maybe evenly spaced in period, and you can actually distort the natural axis that you're using to look at that signal, be it time or frequency again, to make things look more regular so it's easier to extract the signal. So that's a trick that people will use so that we can actually extract the signal. But there obviously we're interested in extracting what's really there. So there, if we extract something periodic with our distorted axis, we're actually using the information on the information that we have in terms of how we have to distort the signal is then important scientific information for us as well. So

Speaker 2 (01:22:14):

Yeah, you don't want to be confusing the distortion for the information,

Speaker 3 (01:22:19):

But if you know that by distorting the time axis in a particular way that brings out the signal much more clearly, then the way that you've distorted the time axis then gives you information on what that underlying signal is. So it's a way, if you like to unpack an irregular signal that you have in the data. So sometimes that sort of approach does get used in my area.

Speaker 2 (01:22:43):

That's a great answer because distortion harmonics are used quite often for that very same purpose in mixing.

Speaker 4 (01:22:52):

Okay.

Speaker 2 (01:22:53):

There'll be certain elements at times that just aren't coming through. Maybe the mix is too dense, maybe there's just something in the same, it is just not arranged that well, and so it's being swallowed up by something in the same range. There's any number of reasons, but sometimes just adding a subtle amount of distortion will just help something pop through. But you need to be careful and not add too much because then you're just adding noise, and so you have to have just the right amount. But yeah, it works. It's great. So great answer. Well, bill Chaplin, thank you so much for taking the time to come on the podcast. It's been enlightening to speak to you, to say the least. It's

Speaker 1 (01:23:40):

Been

Speaker 3 (01:23:41):

My pleasure. Thank you very

Speaker 1 (01:23:42):

Much. This episode of the Unstoppable Recording Machine podcast was brought to you by Sonar Works. Sonar Works is on a mission to ensure everybody hears music the way it was meant to be across all devices. Visit Sonar works.com for more info to ask us questions, make suggestions and interact. Visit Academy and subscribe today.