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You know I’m a big fan of everything physics. So when I heard that Bayesian stats was especially useful in quantum physics, I had to make an episode about it!
You’ll hear from Chris Ferrie, an Associate Professor at the Centre for Quantum Software and Information of the University of Technology Sydney. Chris also has a foot in industry, as a co-founder of Eigensystems, an Australian start-up with a mission to democratize access to quantum computing.
Of course, we talked about why Bayesian stats are helpful in quantum physics research, and about the burning challenges in this line of research.
But Chris is also a renowned author — in addition to writing Bayesian Probability for Babies, he is the author of Quantum Physics for Babies and Quantum Bullsh*t: How to Ruin Your Life With Advice from Quantum Physics. So we ended up talking about science communication, science education, and a shocking revelation about Ant Man…
A big thank you to one of my best Patrons, Stefan Lorenz, for recommending me an episode with Chris!
Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !
Thank you to my Patrons for making this episode possible!
Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony, Joshua Meehl, Javier Sabio, Kristian Higgins, Alex Jones, Gregorio Aguilar, Matt Rosinski, Bart Trudeau, Luis Fonseca, Dante Gates, Matt Niccolls, Maksim Kuznecov, Michael Thomas, Luke Gorrie and Cory Kiser.
Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag 😉
Takeaways:
- Quantum computing has the potential to revolutionize various industries, but it requires specialized tools and education to fully harness its power.
- Bayesian inference plays a crucial role in understanding and solving problems in quantum physics, particularly in parameter estimation and model building.
- The field of quantum physics faces challenges in experimental design, data collection, and maintaining the state of isolated quantum systems.
- There is a need for specialized software that can accommodate the unique constraints and models in quantum physics, allowing for more efficient and accurate analysis.
- Common misconceptions in quantum physics include the idea of superposition as being in two places at once and the misinterpretation of quantum experiments. Misconceptions in quantum physics and Bayesian probability are common and can be addressed through clear explanations and analogies.
- Communicating scientific concepts to the general public requires bridging the gap between scientific papers and mainstream media.
- Simplifying complex topics for young minds involves providing relatable examples, analogies, and categories.
- Studying mathematics is essential for a deeper understanding of quantum physics and statistics.
- Taking risks and making mistakes is encouraged in the early stages of a scientific career.
Links from the show:
- Chris’ website: https://www.csferrie.com/
- Chris on Linkedin: https://www.linkedin.com/in/christopher-ferrie-63993190/
- Chris on Twitter: https://twitter.com/csferrie
- Chris on Instagram: https://www.instagram.com/drchrisferrie/
- Chris’ YouTube channel: https://www.youtube.com/csferrie
- Chris’ children’s books: https://www.amazon.com/gp/product/149267043X
- How quantum mechanics turned me into a Bayesian: https://csferrie.medium.com/how-quantum-mechanics-turned-me-into-a-bayesian-655ddf88051f
- Exoplanet, a python package for probabilistic modeling of time series data in astronomy: https://docs.exoplanet.codes/en/latest/
- Quantum Bullsh*t – How to Ruin Your Life with Advice from Quantum Physics : https://www.goodreads.com/en/book/show/61263731
- LBS #93, A CERN Odyssey, with Kevin Greif: https://www.youtube.com/watch?v=rOaqIIEtdpI
- LBS #72, Why the Universe is so Deliciously Crazy, with Daniel Whiteson: https://learnbayesstats.com/episode/72-why-the-universe-is-so-deliciously-crazy-daniel-whiteson/
- LBS #97, Probably Overthinking Statistical Paradoxes, with Allen Downey: https://learnbayesstats.com/episode/97-probably-overthinking-statistical-paradoxes-allen-downey/
- LBS #51, Bernoulli’s Fallacy & the Crisis of Modern Science, with Aubrey Clayton: https://learnbayesstats.com/episode/51-bernoullis-fallacy-crisis-modern-science-aubrey-clayton/
- LBS #50, Ta(l)king Risks & Embracing Uncertainty, with David Spiegelhalter: https://learnbayesstats.com/episode/50-talking-risks-embracing-uncertainty-david-spiegelhalter/
Transcript
This is an automatic transcript and may therefore contain errors. Please get in touch if you’re willing to correct them.
Transcript
Let me show you how to be a good lazy and
change your predictions You know I'm a big
2
fan of everything physics, so when I heard
that Bayesian stats was especially useful
3
in quantum physics, I had to make an
episode about it.
4
You'll hear from Chris Ferry, an associate
professor at the Center for Quantum
5
Software and Information of the University
of Technology, Sydney.
6
Chris also has a foot in industry, as a
co-founder of Eigen Systems, an Australian
7
startup
8
with a mission to democratize access to
quantum computing.
9
Of course, we talked about why Bayesian
stats are helpful in quantum physics
10
research, and about the burning challenges
in this line of research, but Chris is
11
also a renowned author.
12
In addition to writing Bayesian
Probability for Babies, he's the author of
13
Quantum Physics for Babies and Quantum
Bullshit, How to Ruin Your Life with
14
Advice from Quantum Physics.
15
So we ended up talking about science
communication, science education, and a
16
shocking revelation.
17
about Ant-Man.
18
A big thank you to one of my best patrons,
Stefan Lawrence, for recommending me an
19
episode with Chris.
20
This is Learning Asians Statistics,
episode 99, recorded January 15, 2024.
21
Hello my dear Asians, I want to share an
exciting webinar I have coming up on March
22
1st with Nathaniel Ford.
23
fellow Pimc Cardiff and causal inference
expert.
24
In this modeling webinar, Nathaniel will
explore the world of causal inference and
25
how propensity scores can be a powerful
tool.
26
We will learn how to estimate propensity
scores and use them to tackle selection
27
bias in our analysis.
28
If that sounds like fun, go to topmate.io
slash Alex underscore and Dora to secure
29
your seat.
30
And of course, if you're a patron of the
show, you get bonuses.
31
submitting questions in advance, early
access to the recordings, etc.
32
You are my favorite listeners after all.
33
Okay, now back to the show.
34
It's Ferry.
35
Welcome to Learning Bayesian Statistics.
36
Thanks for having me.
37
Yeah, thanks a lot for taking the time.
38
I'm personally super psyched to have you
on.
39
And also, I know a lot of my patrons will
be
40
very happy to see you and hear you on the
show because they have asked me for a
41
little while now if that was possible to
have you on the show and well apparently
42
nothing is impossible in the baysan world
so really thanks a lot for taking the time
43
Chris and actually let's start by talking
about what you're doing these days right
44
how would you define the work you're doing
nowadays?
45
and what are the topics that you're
particularly interested in.
46
Sure.
47
Yeah.
48
So I'm an associate professor at the
University of Technology, Sydney.
49
I'm also a co-founder of a tech startup
company.
50
And both of these kind of have transformed
me, like at least hopefully temporarily
51
into more of a manager than a researcher.
52
So the business is developing small,
affordable desktop quantum emulators,
53
trying to kind of beef up, enhance, enable
new forms of teaching in quantum
54
programming, which doesn't really exist.
55
And as a professor, I supervise a handful
of graduate students postdocs.
56
I made the mistake, maybe this is like
advice for early career researchers, of
57
allowing them all to select their own
projects.
58
So I'm supervising students who are all
doing separate projects, all chosen by
59
themselves.
60
That means that they get to dive deep into
their projects, but I kind of remain at
61
the surface level.
62
If I'd done it over again, I'd do it
differently with maybe.
63
fewer students and working on topics that
really interest me.
64
But unfortunately, that doesn't usually
generate much funding because I'm
65
interested in the foundations of quantum
physics, and that's more metaphysics or
66
you might even say philosophy.
67
But it's not bad.
68
I get to help young students advance their
careers and learn about new interesting
69
topics and there's always time in the
future to eventually settle down.
70
Yeah, for sure.
71
I didn't know you were also working on an
EdTech company.
72
Yeah, you want to tell us a bit more about
that?
73
That sounds like fun.
74
Well, I'm an elder millennial.
75
I was born in the really early eighties,
so that means I have to have side gigs.
76
And yeah, it was something that we were
interested in doing at the university
77
quantum computing at the university.
78
And what I realized was it's a very
abstract thing.
79
And it's usually taught from the context
of physics and physics students are happy
80
to just be, you know, do what they're
told.
81
But computer science students are a little
bit more challenging because they want to
82
see something tangible and they want to
build things and see the results of what
83
they build.
84
So we thought about building this kind of
thing that they can interact with.
85
And we made some prototypes and it worked
really well in the context of teaching the
86
teaching that I do.
87
And we thought, well, and everyone we
talked to in our field about this said
88
that they wanted one too.
89
And then that kind of led us to the idea
of starting a company.
90
So we're at the stage of, of we have, we
have customers, we've built prototypes, we
91
have customers, uh, all around the world.
92
And, uh, we'll make a big announcement
actually at an event called quantum
93
Australia and.
94
that will, and then people can pre-order
them, hopefully for shipping later this
95
year.
96
And it's, so the product is a small
desktop quantum emulator.
97
Think about like the relationship between
3D printers that are in classrooms and
98
commercial industrial scale 3D printers.
99
So our small classroom thing is emulating
the real thing.
100
So,
101
but it does everything that you need to do
in the context of teaching.
102
And it'll come with a full kit to teach
quantum programming to hopefully
103
eventually down to the high school and
elementary school levels.
104
Nice.
105
Yeah, that's super cool.
106
And I am going to be honest that I don't
think I can say I know anything about
107
quantum computing.
108
So why...
109
Why would you like to do that?
110
What are you, what do you think will that
allow for a better education, basically,
111
why would quantum computing help here?
112
Well, when we make projections into the
future, we see that we're going to need,
113
the quantum industry will need lots of
people, way more people than are in the
114
pipeline now.
115
So this addresses that market need really.
116
So the reason that we want to do it is to
address that market need and do something
117
that we think is best fit for it.
118
Now as an individual,
119
Why would you buy a desktop quantum
emulator and learn about quantum
120
programming?
121
Well, you know, I think it appeals to the
hobbyists in some sense.
122
So if you're someone who buys new tech
stuff on Kickstarter, then you, this is
123
the sort of thing that you would buy
because you're curious about it.
124
Or maybe you just want to develop new
skills.
125
Uh, eventually it will be a subject in, in
high school that students can, can choose
126
just like they can choose to do coding now
in high school and programming.
127
So quantum computing is something that is,
it's a nascent field, but the 21st century
128
will come to be known eventually as the
quantum age, as quantum technologies
129
develop.
130
Okay.
131
And what will that allow us to do?
132
I think the only thing I know about
quantum computing is that it's supposed to
133
allow you to compute way faster.
134
So first of all, the idea I understand
that well,
135
And yeah, just can you give us maybe a
rundown on quantum computing?
136
Yeah.
137
Well, it's not about speed.
138
So there are some things that a quantum
computer will be able to do that
139
conventional, we call them classical
computers, can't do.
140
So the individual steps that occur within
a quantum computer, carrying out an
141
instruction is actually slower.
142
It's the number
143
are way fewer.
144
So the device itself is slow, which means
that you wouldn't want to use it for
145
simple things like adding numbers.
146
Like there's not going to be a quantum
calculator that calculates, that does
147
addition faster.
148
It's more obscure mathematical problems
that people have connected to real world
149
things like applications in cryptography,
in the simulation of chemistry, those
150
sorts of things.
151
all boil down to these mathematical
problems that are difficult to solve when
152
you encode information digitally with ones
and zeros, as you would necessarily have
153
to do with your computer.
154
If you encode those problems into numbers
that have complex numbers and real numbers
155
and negative numbers rather than ones and
zeros, then you can carry out far fewer
156
steps to solve your problem.
157
And a quantum computer would naturally
encode those numbers.
158
and be able to carry out those steps.
159
So it's select problems that you would use
this device for.
160
It's not just, you know, it's not in the,
it's not this in the faster in the sense
161
that eventually we'll have like a iPhone
quantum or something like that.
162
It'll be a special purpose component of a
larger computer.
163
Just like your CPU outsources graphics
calculations to the GPU, it will outsource
164
some quantum
165
physics calculations to the QPU in the
future.
166
Okay, yeah, yeah.
167
Yeah, I see.
168
Thanks.
169
Much clearer now.
170
So, yeah, and I get at least the main
point.
171
So, of course, I've already started on
tensions, but I have so many questions for
172
you.
173
One of my actually planned questions was
that...
174
You have a very original origin story
because you claim and you wrote actually
175
that quantum physics actually turned you
into a Bajan.
176
So tell us why and I'm also curious if
there are any key moments that shifted
177
your perspective.
178
Right.
179
Yeah.
180
So yeah, we've been talking about quantum
physics and not Bayesian statistics.
181
So it all started when I was a graduate
student and I was interested in this field
182
called quantum foundation.
183
So it's kind of really trying to
understand the deep underlying questions
184
about quantum physics.
185
The problem is if you dig deep enough, you
find that quantum physics is just a
186
framework built on top of probability
theory.
187
You've probably heard of things like the
uncertainty principle, things like that,
188
or that quantum physics is a probabilistic
theory.
189
And if you look at all of the debates that
happen at the fundamental level and the
190
foundational level of the field, they have
more to do with the interpretation of
191
probability than they have to do with
physics.
192
So when I was a graduate student, I
thought, well, I mean, I'm not going to be
193
able to answer these questions until I
understand probability.
194
And I suppose in this...
195
podcast, I'm preaching to the choir, but I
came out on the other side of that as a
196
Bayesian.
197
Bayesian, I would put in sort of scare
quotes because I think nowadays you can
198
follow the recipes in a book that uses
priors and Bayes' rule and it has the
199
title Bayes on it without the need to
actually have an interpretation of
200
probability at all.
201
So it was more like in order to answer
these questions and have a satisfactory
202
understanding of what's going on in
quantum physics,
203
You need to have an interpretation of
probability.
204
Um, for most physicists, it's just an
implied interpretation that they don't
205
really think about.
206
But for me, it, you know, it's, it came
out with a subjective interpretation and
207
that really helped me understand it.
208
Uh, but then I think at some point I was
talking to my thesis committee and they
209
didn't like this at all.
210
And so most physicists, especially quantum
ones, think probabilities are objective.
211
So they told me to do something practical.
212
So I transitioned and then tried to start
to apply Bayesian statistics to, you know,
213
problems in quantum and quantum physics,
which yeah, they're, it's essentially just
214
classical statistics with unfamiliar
models and different loss functions and
215
you know, complex numbers are involved in
some sense.
216
Um, but yeah, it's basically just a way
to, to derive a likelihood function.
217
Now, once you have a likelihood function,
then you're just doing classical
218
statistics, it's just a weird likelihood
function.
219
Um, so I was able to apply Bayesian
statistics to problems in quantum physics.
220
Um, so it was like, I started from this
sort of philosophical point of view and
221
then was told to do something practical.
222
And so then I was able to.
223
some practical things in applying Bayesian
statistics to quantum physics problems.
224
Did that change the view that your
supervisors had?
225
I think to some extent it did.
226
Those techniques and tools that we
developed
227
that they're being used in the field,
although it's still dominated with
228
frequentist methods.
229
Yeah, interesting.
230
Yeah.
231
In my experience, that's the same.
232
So usually people I talk to came to Bass
through practical concern.
233
You know, like for instance, a PhD student
who was completely blocked on her paper
234
with the classic framework and then she
just tried Bass because while it was...
235
of her last resort and it solved all of
her problems and now she's just doing
236
that.
237
But that's a very practical motivation.
238
And yeah, I see most people coming from
that angle.
239
You're actually more in the outlier side
where you've been more interested in the
240
epistemological point of view and then
shifted to actually doing it.
241
And yeah, actually what I've
242
It's actually useful.
243
Just show them.
244
And then they'll be like, yeah, that does
look good.
245
And that does solve the problem we were
having.
246
So why not try that?
247
So in my experience, that's been the same,
too.
248
And I'm curious, when was that work you
did on practical Bayesian inference?
249
When did you do that?
250
Oh, that's gotta be 16.
251
Yeah.
252
12, 16 years ago.
253
And we, so it kind of culminated in, we
built this tool, we call it Qinfer, and
254
it's basically a sequential Monte Carlo
integrator that just naturally was able to
255
solve the kinds of problems that people
have in quantum
256
Because it's quite difficult actually to
use standard tools.
257
Often they don't play nice with complex
numbers and things like that.
258
Don't naturally have the kind of loss
functions and things that we use in
259
quantum physics, kind of matrix
manipulations that we have to do.
260
And at the time there wasn't that many,
right?
261
Computation-based statistics is a
relatively new thing.
262
There was a few tools, but not many.
263
And so we ended up building our own and
it's been used many times over the years.
264
And that was maybe 10 years ago.
265
I stepped back from that and handed it off
to the next graduate student.
266
Yeah, that's why I asked you, when did you
do that?
267
Because just a few years ago, there wasn't
a lot of tools to do that.
268
So yeah, like you had, I'm guessing you
had to write the algorithm from, from top
269
to finish on your own.
270
Yeah.
271
And honestly, sometimes that's, that's
better to do it that way.
272
I mean, if you want to really deeply
understand something, you have to build it
273
yourself.
274
You know, we can't build everything from
scratch.
275
I mean, if, if you want to understand
particle physics, you can't go build your
276
own particle collider, but, uh, for things
that you, you have the capacity to build,
277
I would always recommend building it
yourself or at least attempt to, and then
278
realize what all of the problems, uh, are
going to be if you wanted to make a really
279
slick product.
280
So get it to the point where you've built
a prototype and then you really kind of
281
deep start to deeply understand.
282
what's going on because a lot of times,
especially with really usable products,
283
they're really slick and they're just
black boxes.
284
And yeah, you can push the buttons and use
them, but you don't end up developing a
285
deep understanding of, of what's going on.
286
Yeah, yeah, for sure.
287
Even though hopefully if you had to do
that today, that would be easier.
288
You could use building blocks instead of
really just starting from scratch.
289
And thankfully- Well, I mean, an example
is I...
290
Yeah, I can give you an example.
291
So I have a student, an undergraduate
student that I suggested trying a new
292
it's jargon, but I'm sure people have
heard about it.
293
Maybe you heard about it.
294
The Stein variational gradient descent
method, which is a deterministic
295
integration method and, you know, it's
built into, um, Pi MC.
296
Uh, so I, the student can go and can go
and try that, although it is quite, it's
297
still quite difficult for them to build,
build the quantum mechanical models that
298
they have to build.
299
So first I have them do it from scratch.
300
And, uh, of course it
301
It works to some extent, but it's not very
efficient.
302
There are a lot of things that tricks that
come up in numerics.
303
Like, what do you do if you're trying to
take a logarithm and there's something
304
close to zero, right?
305
Then you don't want them to have to figure
out all those things.
306
Have them build it first and then go.
307
Yeah, yeah.
308
Yeah, basically using...
309
Yeah, I like that.
310
Basically using a version from scratch
that's...
311
Simplified and then when you need to go
industrialize that, well, just use the
312
tools you have already on the shelf and
maybe customize them if need.
313
That's the beauty of.mc where you building
blocks basically that you can personalize
314
into your own Lego construction in a way.
315
Yeah, for sure.
316
But that's awesome.
317
Well done on doing that thing.
318
And were you already using Python at the
time, 16 years ago, when you were doing
319
your own SMC or was it something else?
320
No, the first version was built in Matlab,
but as you might anticipate, we ran into
321
license issues when we ended up using
every one of the entire university's
322
global optimization toolbox licenses.
323
And so then we thought, well, this is
silly.
324
So then we moved over to Python.
325
The first one, yeah, it was kind of like
the transition.
326
So we had an early version built in 2.7,
and then we moved to 3.
327
Nice.
328
Yeah.
329
That's really fun.
330
Yeah, in SMC, I know there are also some,
like you can do that here with PMC now.
331
So yeah, if one of your students is
interested,
332
They can contact me and I'll direct them
to the persons who like doing that on the,
333
on the PIMC community.
334
And, and you personally, do you have any
specific instances to share or insights
335
that you gained by adopting a Bayesian
approach in your, in your research?
336
I mean, it's hard to know, I suppose.
337
I mean, I haven't given it a lot of
thought, right?
338
Because it wasn't like I had this problem
and classical techniques weren't working
339
for me.
340
And then I switched over and found, you
know, a particular set of Bayesian
341
techniques that ended up working.
342
I recommend it to people because a lot of
times, especially when you're thinking
343
about things deeply and foundationally,
like...
344
You know, what are these things mean in
quantum physics?
345
Um, it, I always go back to simple
classical examples and say, if you can
346
understand this, or I guess it's a more
negative thing, like if you can't
347
understand this, then you're not going to
even have a chance at understanding the
348
more complicated thing.
349
So, you know, I go back to coin tosses and
I say, okay, what does it mean in the
350
context of a coin toss?
351
And if you don't understand it there,
you're not going to understand that
352
quantum version of it.
353
And the, yeah, the subjective
interpretation of
354
of probability just makes things more
natural.
355
I mean, it gives you a framework for
thinking about things that you can always
356
build on rather than the classical
approach, which it doesn't give you that
357
framework at all.
358
It's just grasping at straws and saying,
okay, you know, what recipes work in this
359
situation?
360
And there isn't one coherent framework
sitting behind it.
361
Whereas the subjective interpretation
gives you that.
362
And so you might not, yeah, you might not
363
It's not like it gives you a specific set
of tools that you can apply in every
364
situation, but it gives you that footing,
that foundation that you can build upon
365
and always have that level of comfort,
philosophical comfort saying, I
366
understand, I know what's going on.
367
Yeah, for sure.
368
And to build on that question, do you have
a favorite study or paper of yours where
369
you used some Bayesian stuff at one point?
370
I'm curious to see, and I'm guessing
listeners too, curious to see where
371
Bayesian stats is useful when you do
research in quantum physics.
372
Yeah, there's lots of papers.
373
I think most of them would be readable for
someone coming from Bayesian statistics
374
without knowledge of quantum physics.
375
Because again, I try to frame it in this
way where the quantum physics, the only
376
point of the quantum physics is to arrive
at the likelihood function.
377
And once you have that, then you can just
do all the things that you're used to
378
doing.
379
Is it because your likelihood functions
are always extremely exotic?
380
Yeah, so the standard simple quantum
experiment would be about estimating the
381
parameter in a multinomial distribution.
382
So you can think of a quantum experiment
as rolling a die and trying to estimate
383
the probabilities for the faces of the
die.
384
Yeah, but...
385
The thing is we don't, um, the, we have
like loss functions that, I mean, yeah,
386
they, there's some, some major season
things in there.
387
And then the issue is like, we have these
loss functions that aren't, aren't ever
388
used in, in classical statistics.
389
And so a lot of the results, uh, just
don't apply.
390
So you, you know, you, you can, you can
sometimes appeal to, uh, like the law of
391
large numbers or, or some of these
392
you know, these theorems, but they,
strictly speaking, our models don't really
393
adhere to those, the assumptions that go
into those theorems.
394
So not only do we have weird loss
functions, that allowed probabilities for
395
the faces of the die are constrained in a
weird way that relates to a positivity of
396
some matrix that sits down the pipeline.
397
So it's, yeah.
398
So oftentimes you would, you would, if you
did it naively, you would end up
399
estimating, um, things that make
probabilities negative, which obviously
400
doesn't make sense.
401
So, um, yeah, there's weird constraints.
402
There's an atypical, um, statistical
models and, and then the loss functions
403
that we use are quite different.
404
So, but, you know, if, if you know enough
statistics and, and
405
can accept that there are different, you
know, that the possibilities extend beyond
406
what you're used to, then yeah, you can
you can work with it.
407
A lot of times the things that you'd
naturally try don't work.
408
But, you know, it is still just a
classical statistical problem.
409
We there was there was one paper where we
were trying to find another way to
410
problem in parameter estimation in quantum
physics is the parameter that you're
411
trying to estimate is itself a matrix.
412
So it's not a real value.
413
It's not a real value vector.
414
It's a complex value matrix.
415
And that's the thing you're trying to
estimate.
416
So I don't know if you're doing density
estimation, that sort of thing.
417
It's similar to that.
418
But we wanted to find the Bayes estimator
for a particular loss function that
419
involves square roots of
420
And if you assume that all the matrices
are diagonal, then you're back to a
421
classical statistical problem and you end
up with this funny loss function for
422
classical probabilities that's somewhat
related to some loss functions that are
423
used in learning theory.
424
And then we said, oh, well, people
actually haven't found the Bayes estimator
425
or, let's just say, the minimax estimator
for that particular function.
426
So our quantum result immediately implied
a result just that was purely classical.
427
And we, the papers titled the papers
estimating the bias of a noisy coin.
428
So it's, uh, this, this actually crops up
in, in social, uh, some social studies.
429
So if I, if I ask you, if you cheat on
your taxes, you're going to say no.
430
So how do they do the sampling?
431
What they do is they, they introduce some
randomness.
432
So they they'll say, okay.
433
roll a die, if the die comes up one, say
yes no matter what.
434
And so that the person who says yes can
always claim that the die came up one.
435
And so they feel like they can be honest.
436
But if that probability of people cheating
is really low, then you might get only one
437
or two people saying yes, but one in six
times they were supposed to say yes
438
anyway.
439
So if you just naively kind of
440
did methods of moments or some linear
inversion, you would come up with negative
441
probabilities.
442
So this is exactly a problem that's
embedded in a quantum mechanical problem.
443
And so sometimes there's some nice overlap
there.
444
Yeah, for sure.
445
That sounds like fun.
446
And for sure, if you can add these papers
to the show notes, please do, because I'm
447
pretty sure listeners are going to be
happy to.
448
to check those out.
449
I already put some cool links in the show
notes for people, but definitely papers
450
are always appreciated, so feel free to do
that.
451
This is a safe place where we can all
share our love for academic papers.
452
Great.
453
Yeah, I should warn the listeners though.
454
Yeah, a lot of them are, they're cavalier,
like a typical physicist.
455
So it's very...
456
We often take a conceptual approach to
these things.
457
Okay, interesting.
458
Well, I read it because it must be pretty
different from a statistics paper.
459
I don't think I've ever read a quantum
physics paper.
460
So yeah, for sure.
461
I think I'm going to start by your books
though, your books for children.
462
I'm embarrassed to say, I think I'm going
to learn a lot from them.
463
So I'm going to start by getting to walk
my way up to your papers.
464
Sounds much, much clearer.
465
And maybe before actually talking a bit
more about quantum physics and what you do
466
and also the work you do on your
children's books, but also science
467
communication in general, and I'd like to
keep talking a bit more about Bayesian
468
stats because I'm curious, I'm always
curious when I talk to a practitioner like
469
you and so someone who is not...
470
by training a statistician, but someone
who really uses Bayesian statistics for
471
their area of expertise.
472
What do you see as the biggest pain points
in the Bayesian workflow right now?
473
I think, as I mentioned before, the
software that is typically used off the
474
shelf doesn't accommodate the quirks and
things that come up in quantum models.
475
Some of them, they just won't accept
complex numbers, for example.
476
When I first attempted to use TensorFlow
way back, TensorFlow 1, you couldn't even
477
use complex numbers.
478
to go back to the source code.
479
And at that point, you might as well just
build it yourself.
480
So yeah, complex numbers, matrix
manipulations, we often have, as I said,
481
lots of constraints.
482
And when you attempt to use something out
of the box, if it works at all, your whole
483
screen is filled with warnings.
484
And it isn't.
485
It isn't as nice as the demos of the
software.
486
So I think for me, and possibly for people
that are running models with lots of
487
constraints, this is the biggest pain
point at the moment.
488
Obviously, the software will accommodate
constraints, but it doesn't.
489
It doesn't seem to do so in a way that's
natural and easy.
490
Yeah.
491
So ideally that like in an ideal world,
that would be what you'd like to see to
492
help adoption of patient training.
493
Yeah.
494
I mean, like a really concrete example
would be, you know, I want to do
495
sequential Monte Carlo on some simple
estimates.
496
I'm doing an experiment where I roll a die
several times and I want to estimate the
497
probabilities.
498
It's of some biased die, but the
probabilities come with a long list of
499
linear constraints.
500
So not any probability will do.
501
When you're doing the resampling, what is
it that the software is doing to
502
accommodate those constraints?
503
approach is like, what doesn't really
matter because there is no constraints.
504
And so you can just throw a Gaussian on it
and you know, it, nothing.
505
Yeah, it's simple, but when you have these
constraints, um, yeah, it makes, it makes
506
things far, far more challenging.
507
And sometimes the software just doesn't,
doesn't accommodate those.
508
Yeah, yeah, no, for sure.
509
I understand your pain.
510
And I'd like to make your wish come true,
but that's a hard one because in here,
511
you're hitting a limitation, I would say,
of the development process where you have
512
to choose at some point if your package is
going to be general or specific.
513
And packages like Stan, Climacy,
TensorFlow, they have to be general
514
because they are adopted by so many people
with so many different backgrounds and so
515
many different uses that we have to make
choices that are going to work for most
516
people and that are going to be optimal
for most use cases.
517
But that means for sure it's like
518
If you're trying to accommodate everybody,
nobody's going to be accommodated
519
perfectly.
520
Right.
521
So, yeah, like it seems to me like someone
should go there and basically build a
522
package on top of PIMC that just like
addresses what you folks pain points are
523
in quantum physics.
524
Basically.
525
I know there is such a package for
astrophysicists.
526
Of course, I don't remember the package
name right now, but I'll try to remember
527
and put that in the show notes.
528
And I know that package built on top of
times is really, really used a lot in the
529
astrophysics field.
530
I'm not aware of any package like that in
the quantum physics realm.
531
But if any listeners do, but then please
reach out to me and I'll pass that on to
532
Chris.
533
I'm sure his PhD students are going to be
grateful.
534
Yeah.
535
Or if anybody wants to do that, get in
contact with Chris, I'm sure he would have
536
valuable points for you about what he'd
like to see in particular.
537
I think it's honestly there's a research
question in there as well, right?
538
At least when we were doing it, that
particular method that we were using, it
539
was never applied or developed in the
context of constraints.
540
And so what you do when you're faced with
constraints, at the time anyway, it was
541
like sort of an open research question.
542
So yeah, it's fair that...
543
It's fair that the software just doesn't
solve it for you because it may not be a
544
there may not be an actual solution yet.
545
Yeah, that's a good point also.
546
And so now I'd like to ask you a bit more
about quantum physics per se, because,
547
well, I'm always very curious about
physics.
548
So what in your line of research, what are
the biggest questions, the biggest
549
challenging you face currently?
550
So we're at this weird transition point in
the field of quantum technology where we
551
can't in laboratories, university
laboratories, build bigger devices.
552
So we kind of count the power of a quantum
computer in the number of quantum bits or
553
qubits that we can control.
554
And nowadays it's very easy to get one
qubit.
555
was very difficult, but now there are many
different modalities, trapping atoms,
556
using states of light.
557
All of these sorts of things can now be
used to encode a single qubit, and that
558
can be done in the standard physics lab.
559
Going beyond that becomes more difficult
and you need much more funding to do it,
560
but going much further beyond that is not
a possibility within an academic.
561
context.
562
And so you need some large government
organization or collaboration to do it, or
563
you need industry to take over.
564
So we're at that cusp where the largest
devices are ones that are being developed
565
by companies, companies like IBM, Google,
startup companies like Rigetti, IonQ.
566
There's a whole host of them now.
567
And what they're doing, obviously,
568
secret now.
569
So it's a weird place to be.
570
I can't tell you, I can make guesses about
where they are, what they're doing, what
571
their problems are.
572
But if they wanted my help, I'd have to
sign an NDA, or they'd have to pay me and
573
I wouldn't be able to tell you.
574
So we've kind of transitioned into
575
We're moving out of university research
labs into government and company and
576
multinational company R&D labs.
577
They have the same problems, but at a
larger scale that university researchers
578
had, which is just that to maintain the
state of an isolated quantum system is
579
very difficult.
580
Any interaction.
581
cosmic ray that comes in that you
obviously can't control will degrade the
582
information that's being encoded in these
systems.
583
And so they're very fragile.
584
We need to work out ways to provide better
isolation, but complete isolation is not
585
good either because you have to control
them to carry out the instructions that
586
you want.
587
So it's kind of this Catch-22 where you
want it to be completely isolated from
588
everything except for when you want to
actually.
589
go in there and manipulate it in some way.
590
So yeah, these are the problems.
591
And I think theoretically there's still
that big question about can it even be
592
done?
593
Can we even build a quantum computer?
594
There doesn't seem to be a reason why.
595
If it turns out that we couldn't, we'd
learn a lot about the nature of reality
596
and the reason for why that's the case.
597
But
598
I think have the potential to be answered
in my lifetime.
599
Can we build a large scale fault tolerant
error corrected quantum computer that
600
carries out some calculation that would
have been impossible to carry out with
601
digital electronics?
602
Yeah, yeah, that's pretty fascinating.
603
And I'm really impressed by the depth and
the width.
604
of topics in the research of physics.
605
It's just incredible.
606
I would refer to listeners to episode 93
that I did at CERN, the summer, I mean,
607
2023 summer, where we went deep on what do
they do at CERN, what type of research,
608
what does that mean, why even do that.
609
And you'll see, well, some, you know,
cross topics with what Chris is talking
610
about, but also things that are completely
different.
611
And that's just incredible to see how wide
these fields are.
612
And that sounds to me that's pretty
incredible because in the end, that's
613
just, you know, trying to understand the
universe.
614
So it's kind of doing the same thing, but
it brings you...
615
to directions that are completely,
completely different.
616
And that's really the funny, one of the
fascinating things, I think, of these
617
topics.
618
And of course, go to the video version of
the episode 93.
619
You have the audio version if you have,
but that was a video documentary inside
620
CERN.
621
So I highly recommend checking out the
YouTube link that I will put in the show
622
notes.
623
And actually, I'm curious, Chris, about
also because now, as you were saying, you
624
kind of have a management role, which
implies thinking a lot about the future.
625
So I'm wondering, where do you see the
field of quantum mechanics headed in the
626
next decade?
627
Also, maybe how do you see patient stats
still helping in this endeavor?
628
That's a good question.
629
I think much like astronomy, for example,
Bayesian techniques will see a wider
630
adoption because at the moment, the way
that a laboratory quantum physics
631
experiment happens is really foreign to
someone who does machine learning or data
632
science where you have some data set and
then you need to analyze it.
633
No, what they do in labs in physics
departments is if the data isn't what you
634
wanted, then you just throw it out and
start again.
635
And, and you work until you have like
really clean data sets.
636
So all of the all of the problems with
data sets and things like that don't
637
happen in physics labs.
638
The physicists want to see the answer in
their data.
639
So the really sort of data scarce regime
is unacceptable to them.
640
They need to see it on an oscilloscope or
something.
641
The probability distributions essentially
have to be delta functions for them before
642
they accept that the experiment actually
worked.
643
But that's because we're doing really
small-scale experiments.
644
Once those experiments grow and become
large, we won't be able to do that
645
anymore.
646
If an experiment takes a week to run,
647
You're not going to say, do it over again
until you see a nicer data.
648
You're just going to have to accept that
that's the data set and you have to, you
649
know, get as much information out of it as
possible.
650
And that's going to require utilizing the
assumptions that you're making.
651
In a sensible way, which will lead you to
sort of Bayesian techniques.
652
So I think we will see wider and wider
adoption within the quantum research
653
fields.
654
of Bayesian techniques going into the
future, much like we have in the last two
655
decades in astronomy.
656
Hmm.
657
Yeah.
658
Uh-oh.
659
Yeah, fascinating and...
660
I really hope that these big questions you
were talking about are going to be
661
answered, at least some of them, because
I'm just so curious about that.
662
That would be just fascinating to have
some of these answers at least come our
663
way in the coming years.
664
um, relativity in quantum physics and how
you can merge that.
665
And so that's definitely would be
incredible to at least understand that a
666
bit better.
667
And also, and I'm also fascinated by the
fact that how do you do the experiments on
668
this realm for now is just super
complicated.
669
Yeah, I think those are huge questions.
670
I don't even think we've really formulated
the questions correctly.
671
I mean, that's my take on it.
672
We have a theory that works really well at
the moment.
673
In every regime we can test, our current
best model quantum field theory works
674
incredibly well.
675
It's places that we don't even understand
like inside the event horizon of a black
676
hole.
677
in principle, we can't even go there to
get the data that we would need to find
678
out if the theory works there.
679
There's various takes on it.
680
It's just a pessimistic take, which is
like, maybe we've hit the limits of what
681
we can understand given our capabilities
in the universe.
682
And then, yeah, a more positive view is
like, well, eventually someone will come
683
up with some idea
684
there was something that nobody could have
seen coming.
685
That's typically how paradigm shifts have
worked in the past.
686
So there's no reason to think
pessimistically that will stop.
687
But who knows, it might be the case.
688
Yeah.
689
I mean, I do hope for the second option,
but you can never know.
690
And actually now
691
I love the fact that you do a lot of
science communication, of course it's also
692
a job of these podcasts, so it's always
something I'm very happy to talk about and
693
I'm wondering if there are some common
misconceptions you've seen about quantum
694
physics, maybe even about
695
Oh, yeah.
696
Well, I wrote an entire book for, not for
children.
697
It's, yeah, you may have to edit this part
out because the book's called Quantum
698
Bullshit.
699
I don't know if that's allowed in the
podcast.
700
I'm French, so we have no worries with
swear words.
701
Yeah, in Australia it's similar.
702
Yeah, so that's the title of the book.
703
The subtitle is kind of a science comedy.
704
So the subtitle is How to Ruin Your Life
with advice from quantum physics.
705
And it kind of goes through a lot of the
common misconceptions and how each of
706
these major concepts in quantum physics
are misused.
707
Things like superposition, entanglement,
quantum energy, quantum uncertainty, these
708
sorts of things, how they typically are
misused.
709
And yeah, what's the most sensible kind of
way to understand them without having the
710
mathematical background that underpins the
framework of the theory?
711
So yeah, there's lots of them.
712
And if you want the comprehensive list,
definitely check out the book.
713
I'll give you like a typical
714
means things can be in two places at once.
715
And that just like, just saying it out
loud should make it clear that that's a
716
logical contradiction.
717
Because, you know, a dichotomy between
true and false, and you can't have
718
something that's both true and false.
719
So sort of a logical contradiction.
720
But that being said, you still, you know,
physicists will still say things
721
that sound kind of like that.
722
So an example might be this famous double
slit experiment where you have some sort
723
of screen, it has two holes in it, and you
fire electrons at it and you see an
724
interference pattern on the other side
instead of just two dots where the
725
electrons landed, suggesting that the
particles interfere with each other.
726
And if you do it one particle at a time,
that means it has to interfere with
727
itself.
728
which means it had to have gone through
both slits at the same time.
729
So the electron had, or whatever particle
it is, had to be in both of those places
730
at the same time.
731
But we always run into these problems when
we try to explain what's going on in
732
quantum physics by analogy to our everyday
world.
733
It's just a different world that we don't
have access to.
734
We don't have a language and a familiarity
with.
735
So we have to use these analogies.
736
But...
737
you know, they very quickly break down.
738
So that's absolutely not what's happening.
739
Uh, and things can't be in two places at
once.
740
And yeah, you shouldn't, uh, you should
buy a quantum crystal or something because
741
it promises that, that it can do that.
742
And for the Bayesian, I find actually, um,
uh, yeah.
743
So, you know, when you
744
You can kind of explain to people the way
I do it now is to walk through that idea
745
that in quantum physics we have these
concepts and we have to use a language
746
that we're familiar with but that language
isn't really suited for trying to do
747
anything beyond explain that one special
thing.
748
You can't extrapolate using those
analogies because you'll quickly fall prey
749
to misconceptions.
750
So
751
That's typically how I explain it in the
context of quantum physics.
752
And quantum physics is actually quite
popular in the popular culture.
753
I don't find that Bayesian probability is
so popular in popular culture.
754
So, you know, the word quantum crops up
all the time, attached to things.
755
Nobody's selling Bayesian healing
crystals.
756
So, these aren't like popular.
757
Oh, that's actually not a bad idea.
758
Yeah.
759
But so you don't need to approach it the
same way because you're not typically
760
talking to a lay audience when you're
talking about misconceptions and Bayesian
761
probability.
762
Usually it's someone technically minded
who knows something about some technical
763
topic that the probability is being
applied to or probability itself.
764
In physics, the main problem that people
have, you could call it a misconception,
765
is that Bayesian methods are subjective,
whereas frequentist methods are objective.
766
And as a scientist, you need to strive for
objectivity.
767
So that means that you shouldn't use
Bayesian methods and you have to use
768
frequentist methods.
769
But the easy thing to point out is to...
770
What you could do is just...
771
have them walk through how they would
apply frequentist methods and then point
772
out that they had options and then they
made their subjective judgments on which
773
options they were going to choose to solve
their problem.
774
So it's no less subjective.
775
And in some sense, it's worse in the sense
that you're not being honest about the
776
biases that are going into what you're
doing.
777
So yes, Bayesian methods are absolutely
subjective, but they're subjective in the
778
most honest way possible.
779
Yeah, that's usually the way I go about it
also.
780
The faster you're going to abandon the
idea that there is an objective way of
781
seeing reality, at least the way we are
made, you know, if you're homo sapiens,
782
the faster you'll be able to think about
real ways to actually try to understand
783
what's going on.
784
And so, yeah.
785
It's usually the way I go about it.
786
But yeah, I mean, these are fascinating
topics.
787
I, we've actually covered some of them in
some of the episodes we've already done on
788
the show.
789
So the one, one before you was episode 97
with Alien Downey where he actually talked
790
about that where.
791
He has also a blog post about it comparing
this idea that Bayesian results converge
792
to the frequentist results to the limit.
793
And so that was interesting to talk about
it with him because he actually argues
794
that it's never the same.
795
And that's not a problem.
796
You should still choose the Bayesian
framework, actually.
797
But that was interesting.
798
So you have that for people interested and
also I'll put in the show notes.
799
So I'll put that one and I'll put in the
show notes, episode 50 and 51.
800
50 was with Aubrey Clayton, who wrote an
amazing book called Bernoulli's Fantasy
801
and the Crisis of Modern Science.
802
So that's more about the history of
statistics and how basically, how and why
803
came to dominate the scientific world.
804
So much more epistemological, very, very
fascinating book.
805
And episode 51 with Sir, only Sir we've
had on the podcast, I think, Sir David
806
Spiegelhalter about risk communication,
how to talk about risk, especially to a
807
lay audience.
808
and people who are not educated in stats
or in the scientific method.
809
And that was, that was way closer to the
COVID pandemic.
810
So that was very interesting to talk about
that with him, because these topics were
811
absolutely important in time of pandemic
or very stressful situations.
812
Right.
813
Who would think so, right?
814
That the nerds actually had tried all
along to talk about stats and
815
probabilities.
816
This can save you during a pandemic.
817
But yeah, I mean, this is also something
that I think must be added in these
818
discussions.
819
Often, it's not really in the papers that
you see these misconceptions, but it's
820
more in the way the papers are interpreted
by people who are not equipped to read the
821
papers.
822
And so I think there is a...
823
a job in the world that needs to be
filled, which is basically making the
824
bridge between scientific papers and then
what ends up in the newspapers.
825
And that is a bridge that still has to be
built.
826
And we're trying to do that in a way with
our work, but it's still so much things to
827
do still.
828
Sometimes my game is really to do that.
829
It's trying to see what people are talking
about on Instagram or stuff like that.
830
And then actually try and go to the source
that they are supposed to quote, you know,
831
to site.
832
And then you see that basically it's just
like the first person who reported on the
833
paper did understand the paper or just
read the abstract and the title.
834
And then just everybody cite that first
source.
835
So basically the first error is just like
trickled down and that's just fascinating.
836
Yeah.
837
Yeah, I think the solution has to sort of
include actually that people write fewer
838
papers.
839
I mean, there's over a million academic
journal articles published every year, and
840
that's more than we can read, right?
841
But there's the perverse incentives in
academia now that kind of force you to do
842
this, which means also that like most of
those papers shouldn't have been written,
843
I think it would be better if we had a
more careful approach where the result is
844
fewer papers that are better written.
845
Yeah, that could have been more.
846
And also it's something we've talked about
on the podcast several times, incentives
847
in academia.
848
It's hard to change, but needs to be
changed.
849
But yeah, hopefully that will...
850
And having people like you in academia
definitely helps.
851
Well, hopefully with time, it's going to
evolve.
852
But yeah, and we could continue on that
road, but it's going to be a three-hours
853
episode, and I don't want to take too much
time to you.
854
And actually, that's a very, it's the very
first episode that we do where we are
855
actually time traveling, right?
856
Because it's still January 15 for me.
857
at night and it is January 16th in the
morning for Chris.
858
So thank you for calling from the future,
Chris.
859
We solved the glass problem.
860
The sun rises tomorrow.
861
Yeah, I can tell you that.
862
Yeah, I can see for now, no apocalypse.
863
So that's cool.
864
Glad about that.
865
Yeah, I had other things to add about your
very good points about communication and
866
so on.
867
But of course I...
868
I think I forgot about them.
869
I will just refer people to the show
notes.
870
I'm gonna put the episodes I mentioned in
there.
871
And oh yeah, one thing, I tracked down the
Python package I was talking about for
872
Astrophysics.
873
So the package is actually called
Exoplanet.
874
And yeah, it's a package that's built on
top of PymC.
875
to do probabilistic modeling of time
series data in astronomy with a focus on
876
observations of exoplanets.
877
So I put the notes, the link already in
the show notes, and that's developed
878
mainly by Dan, Ferm, and Mackey.
879
So people who are working on that
definitely take a look at a very cool
880
package, very well maintained.
881
So Chris.
882
I've already taken a lot of time from you,
but I'm curious.
883
I want to talk a bit about your children's
book.
884
Of course, you've written about quantum
physics, about general relativity.
885
Patient statistics also, you've written a
book, I think, about that.
886
First, I'm definitely going to buy those
books if one day I have kids.
887
That's for sure.
888
I'm not going to read them stories
about...
889
crystals and things like that, much more
about that kind of thing.
890
No, first, keening aside that I think
that's a very good service you're making
891
because definitely there is a big lack of
scientific culture, I would say in
892
general, in the audience, just
understanding probability.
893
The main thing I have to face is often
things like
894
Well, you said that thing would happen
with a 30% chance.
895
It didn't happen.
896
Hence the model was wrong.
897
And that's just like, this is kind of the,
this part of the misconceptions on, on the
898
part of, this is the burden of a
statistician.
899
But I think it's extremely important to
make people more aware of the scientific
900
methods, more scientific savvy.
901
First pick is way more interesting than
what pop culture makes it look like.
902
You know, you don't have to be crazy.
903
You don't have to wear a white coat.
904
You don't have to be a genius to
understand science.
905
And you don't have to be a genius to use
science.
906
So, yeah, I think it's extremely important
what you're doing.
907
And mainly to go to my question, how, how
do you approach simply
908
simplifying such complex topics for young
minds and yeah, how do you think about the
909
way you teach that?
910
Yeah, that's a good question.
911
I think you hit on a lot of good points.
912
And there's a lot of obvious traps that
people fall into, right?
913
That you might think, well, science is
boring, so we need to spice it up.
914
This happens all the time.
915
If you see scientists on daytime
television or whatever, they inevitably do
916
some chemistry experiment where there's
some explosion and gives people a really
917
distorted view of what science is.
918
Not only is it...
919
People think that it's old white dudes in
lab coats and geniuses, but also people
920
have this misconception that it's all
about excitement and explosions and
921
chemical reactions and cosmic awesomeness.
922
But science is at its core, this
fundamental framework for navigating the
923
world in the...
924
most sensible way possible.
925
So when I approach the children's books, I
try to really simplify not only the
926
concepts, but just that overall sense of
what I'm trying to do.
927
I'm not trying to create some extrapolated
vision, some way too exciting picture of
928
what science is.
929
What I try to do is I try to give
examples, analogies, categories, kind of
930
abstract things that give people some
comfort, some tools that they can use to
931
try to understand or appreciate what's
happening in these fields.
932
it becomes obvious that the books are for
parents, not necessarily for babies.
933
Um, and I think a lot of the feedback that
I get is from parents who say things like,
934
Oh, I wish I had learned this topic in
school in this way.
935
Right.
936
Uh, and you know, it all boils down to
this, this notion that when we learn
937
things, what, what we're doing is just
building up our repertoire of
938
of analogies that we can use to understand
them.
939
And the more that you have, the better,
right?
940
And the sooner you start, the better.
941
I think there is a misconception that
there's one unique special way to
942
understand a concept.
943
And if it's only told to you in that way,
some light bulb moment will happen in
944
which you all of a sudden understand it.
945
But that's just not
946
you at some point in the future, you say,
Oh, I feel like I understand that.
947
But there wasn't a, there wasn't a turning
point.
948
There wasn't a light bulb moment.
949
There wasn't a switch.
950
It was just time and, and building up
those, those analogies and examples that
951
at some point you just feel comfortable
and that's all there is to it.
952
So it's actually surprisingly easy.
953
It's a lot easier than people think.
954
Uh, you know, because the, the task that I
set myself is, is not such a high bar, you
955
know, just give a simple palatable analogy
for some core concept in the thing that
956
you're talking about that, that anyone can
understand.
957
Hmm.
958
Mm hmm.
959
Yeah.
960
Um, yeah, definitely.
961
It's.
962
Again, extremely important, so thanks a
lot for doing that.
963
And I do think that it's very important to
make science more, look more human and
964
write it more and more approachable
because I often people see that as very
965
dry endeavor, but I think actually
counting stories.
966
about science and scientists and normal
scientists, right?
967
Not the weird scientists from the movies
is extremely important because that's also
968
how we learn, right?
969
We learn a lot.
970
Our brain is like that.
971
We love stories and we love learning
through stories.
972
Like every equation you learned at school
has actually a story behind it.
973
Lots of people have worked on it.
974
Lots of people have.
975
failed and depressed because they couldn't
find the solution.
976
And thanks to their work, then afterwards
it unblocked a lot of things that you can
977
actually do now.
978
Just knowing about relativity makes us
able to be located through our phone.
979
We can use GPS very accurately because we
actually take into account relativity.
980
Well, it's pretty incredible, right?
981
I'm guessing most people don't know that.
982
So yeah, I think it's extremely important.
983
And actually I've watched very recently a
series, a Netflix series that does an
984
extremely good job, I found illustrating
science like that.
985
So it's still of course romanticized a
bit, but first the physics that's in the
986
show is pretty good and...
987
accurate, they don't refer to absolutely
completely crazy theories because the
988
series is called Lost in Space and the
beaches unite.
989
Something happened on Earth, I'm not going
to spoil it, but something happened on
990
Earth and then some people had to go and
try and colonize Alpha Centauri and we
991
follow the adventures of the families who
do that.
992
The science is pretty good on that and
also the depiction of the science is, I
993
found, very interesting.
994
We have some very interesting scenes where
it's like, oh, that's magic.
995
That's not magic.
996
That's math.
997
That was really cool.
998
I'm not going to spoil, but I definitely
recommend this series.
999
It's really well done.
Speaker:
And of course, well, your book, Chris.
Speaker:
And well, I think we could, we can call it
a show, I think, because I've already
Speaker:
taken a lot of time from you.
Speaker:
And for people watching the video, you can
see that the sun is setting down for me.
Speaker:
So the, the luminosity is getting down.
Speaker:
But I'd like, so before the last two
questions, my last question would be a bit
Speaker:
of a general one.
Speaker:
If you have any.
Speaker:
advice, Chris, for students or young
researchers interested in quantum physics
Speaker:
or even patient statistics, what advice
would you give them to start in these
Speaker:
fields?
Speaker:
Yeah, I think for young people that have
time on their hands, my advice is quite
Speaker:
simple is to study mathematics.
Speaker:
Mathematics is obviously the foundation of
statistics, also the foundation of quantum
Speaker:
physics and all of physics.
Speaker:
I see students coming into university who
are very excited about science.
Speaker:
They come in, they say, I've read all of
Brian Greene's books and Stephen Hawking's
Speaker:
books.
Speaker:
I'm here to be a scientist.
Speaker:
I live to be a quantum physicist.
Speaker:
And then you hand them a test with only
math problems on it.
Speaker:
And they get very deflated because nobody
told them that it was all about math.
Speaker:
So it's the way that I came into the
field.
Speaker:
I was never really interested in physics
or science.
Speaker:
I was a math student.
Speaker:
And when I finished my degree, it was more
about how am I going to apply my skills in
Speaker:
solving math problems.
Speaker:
And that served me very well.
Speaker:
So yeah, become proficient at mathematics.
Speaker:
There's lots of fun stuff in mathematics
when you, you know, at the surface level,
Speaker:
depending on the way it's taught can feel
boring.
Speaker:
And, but yeah, the further you dig deep
into it, the more interesting and more
Speaker:
exciting it gets, and it will provide you
with a deeper understanding of the field
Speaker:
that you end up applying it to then.
Speaker:
than you could have ever imagined and
certainly more so than the people that are
Speaker:
just still at that surface level.
Speaker:
So yeah, that would be my advice.
Speaker:
Also, especially for young people, for
students, life is very long and now is the
Speaker:
time that you're encouraged to make
mistakes.
Speaker:
And it's really the only time in your life
where you can make mistakes and get rapid
Speaker:
feedback.
Speaker:
And that's the thing that's encouraged and
that's the best way to learn.
Speaker:
So, you know, approach it from that
perspective and also drag it out as long
Speaker:
as you possibly can.
Speaker:
Yeah.
Speaker:
Completely agree with these
recommendations.
Speaker:
Learn math and learn it well and take
risks very, very young and for the most
Speaker:
time you can.
Speaker:
Because yeah, that's definitely helpful.
Speaker:
Even financially, like a good financial
advice, if you have to take risk and put
Speaker:
all most of your money on stocks, that
would be when you're young and then when
Speaker:
you get older, you get a bit less, a bit
more risk averse on your portfolio
Speaker:
investment.
Speaker:
Well, I would say that's the same thing
for life and for rapid feedback and
Speaker:
failure when you are young and not having
your responsibilities to do that, you
Speaker:
know, take the risks.
Speaker:
And learn math.
Speaker:
That's not a risk at all.
Speaker:
Awesome, Chris.
Speaker:
Well, I'm going to let you go.
Speaker:
But before that, I'm going to ask you the
last two questions I gave a guest at the
Speaker:
end of the show.
Speaker:
First one, if you had unlimited time and
resources, which problem would you try to
Speaker:
solve?
Speaker:
I think that's easy, at least in my
discipline, I would build a large scale
Speaker:
quantum computer and then I would set it
on the task of simulating various
Speaker:
materials until it found a high
temperature or room temperature
Speaker:
superconducting material.
Speaker:
And then we'd build that and go, have free
energy around the world.
Speaker:
That sounds nice.
Speaker:
I love that.
Speaker:
Yeah, awesome.
Speaker:
You're the first one to answer that, but
love it.
Speaker:
And second question, if you could have
dinner with any great scientific mind that
Speaker:
alive or fictional, who would it be?
Speaker:
Yeah, I mean, these sorts of questions I
think are difficult, especially for
Speaker:
someone with an analytical brain.
Speaker:
You know, you've got the one, the devil on
your shoulder saying, yeah, play along,
Speaker:
it's a whimsical game.
Speaker:
I thought about this actually.
Speaker:
So I think there'd be some inherent
problems with obviously with a dead
Speaker:
scientist.
Speaker:
You know, there's obvious problems, but I
think the ones that people don't think
Speaker:
about are Say, you know, I brought what I
Guess this is a magical scenario, but I
Speaker:
don't know if it's I go back in time or
they come to our time But in some sense,
Speaker:
it doesn't matter So I would prefer they
come to our time because you know, if go
Speaker:
far enough in the past and they don't even
have toilets So let's bring them to our
Speaker:
time, but there's a problem.
Speaker:
Like if I brought Einstein here what
Speaker:
what would I have to do?
Speaker:
Would I have to explain a century of
advancements in like the actual field that
Speaker:
he came up with?
Speaker:
And would he even accept it?
Speaker:
Like even in his lifetime, he refused to
accept all of the consequences of quantum
Speaker:
physics.
Speaker:
So, you know, it actually wouldn't be a
great conversation.
Speaker:
I think scientists from the past would
just be, it would be too difficult to
Speaker:
communicate.
Speaker:
magically overcome say some language
barrier.
Speaker:
Like they're, yeah, the contributions they
made obviously are timeless, but like that
Speaker:
conversation that you could have wouldn't
be very insightful.
Speaker:
So I feel like you'd have to go with a
living scientist, but then the problem
Speaker:
with a living scientist is like, I can
just email them if I had a specific
Speaker:
question.
Speaker:
So it seems like far more, far easier
than...
Speaker:
than organizing some dinner, which you can
have when you go to conferences anyway.
Speaker:
So I've been to dinner with Nobel
laureates and stuff and celebrity
Speaker:
scientists, and one of them was probably
enough.
Speaker:
So then I think you're forced to go with a
fictional character.
Speaker:
I don't know how many of your guests pick
a fictional character, but my favorite
Speaker:
fictional character with a self-proclaimed
great mind is Marvin.
Speaker:
paranoid android from the Hitchhiker's
Guide to the Galaxy.
Speaker:
So I would uh, I'd have dinner with Marvin
and I know exactly what I'd ask him to.
Speaker:
I'd ask him about AI alignment.
Speaker:
Um, because I think it seems to, he seems
to have been solved with Marvin and uh, I
Speaker:
think he would just give a wonderfully
nihilistic answer to what is AI alignment.
Speaker:
Yeah.
Speaker:
Yeah, no, that'd be fun.
Speaker:
Yeah.
Speaker:
I take part in this dinner.
Speaker:
I don't know.
Speaker:
Let me know when that happens.
Speaker:
You want, oh, you want a bonus question,
uh, physics related, a choice like that.
Speaker:
We had to make, uh, last time we did a
retreat at PIMC Labs, we do a retreat, uh,
Speaker:
every year.
Speaker:
And, uh, of course, it's just a bunch of
nerds getting together.
Speaker:
So we always end up with, uh, very nerdy
questions.
Speaker:
And, um, yeah, this year, I think one of
the main questions where
Speaker:
So yeah, the year before, one of the main
questions was who would win in a plane
Speaker:
war, so in an airplane war, Earth or
Jupiterians.
Speaker:
And this year, but the one I want your
input on is this year was, if you could
Speaker:
choose between these three options, which
one would you choose?
Speaker:
If you could know what's...
Speaker:
like what it's like to be in the quantum
realm?
Speaker:
Or if you could go inside a black hole and
know what's there?
Speaker:
Or if you could go to an alien planet and
meet them and talk with them, what would
Speaker:
you choose?
Speaker:
Right.
Speaker:
Uh, there's only one, there's only one
correct choice.
Speaker:
It's the third one because the other, the
other two, uh, would be bad.
Speaker:
bad decisions.
Speaker:
So it's the alien planet, yeah.
Speaker:
There is no quantum realm.
Speaker:
I wrote a blog post about that.
Speaker:
I'll give you the link for the listeners.
Speaker:
Oh, perfect.
Speaker:
So you can't go there, obviously.
Speaker:
There's technical challenges clearly with
shrinking a human, but also, yeah, our
Speaker:
entire sense of perception is built on our
mesoscopic relationship with the world.
Speaker:
Like clearly there'd be no sound, there'd
be no notion of sight.
Speaker:
So even if you could get around this weird
idea of shrinking yourself, it wouldn't be
Speaker:
a place to experience.
Speaker:
And then inside a black hole, every
direction points down and you'd be
Speaker:
spaghettified.
Speaker:
So it's a bad idea.
Speaker:
That'd be a problem.
Speaker:
Yeah.
Speaker:
I mean, I love that statement.
Speaker:
So let's go to the alien planet.
Speaker:
That's a technical term, actually.
Speaker:
Yeah, yeah, yeah.
Speaker:
Spaghettification.
Speaker:
Yeah, yeah, yeah.
Speaker:
And yeah, I mean, I'm shocked by the
revelation you just made on this podcast
Speaker:
that Ant-Man is not a documentary.
Speaker:
That's just, I'm just shocked.
Speaker:
So I think it's time to stop the podcast.
Speaker:
First of all, because I don't have any
more light and second, because well, I've
Speaker:
taken a lot of time from you.
Speaker:
Thanks a lot, Chris.
Speaker:
That was really awesome.
Speaker:
I learned a lot and we covered a lot of
topics so that was really perfect.
Speaker:
As usual, I put resources and a link to
our website in the show notes for those
Speaker:
who want to dig deeper.
Speaker:
Thank you again, Chris, for taking the
time and being on this show.