Quantum computing 101: What it is and why it matters for energy

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This episode dives deep into the world of quantum computing and its transformative power beyond classical computing methods. Understanding quantum properties like superposition and entanglement not only excites but also invites practical applications in various fields, especially energy.

• Exploring the foundational principles of quantum computing 
• Comparing classical computing to quantum computing 
• Discussing real-world applications, particularly in energy sectors 

You can check out more on our entire podcast series at cgi.com and subscribe on your favorite podcast platform!  

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Episode Transcript

Maida Zahid (00:00):
Hi everybody, welcome back to another episode
of the Energy Transition Talkspodcast.
I'm your host, maida Zahid, andI'm part of the marketing team
here at CGI Canada.
Today we're going to be divinginto the fascinating world of
quantum computing with CurtisNaibo.
Curtis is our talented Canadianexpert who leads quantum

(00:22):
computing here in Canada.
And over to you, curtis.

Curtis Nybo (00:25):
Hi everybody.
My name is Curtis Naibel.
I'm a director of AI andquantum computing at CGI and
I've been spending most of mytime in the AI space and quantum
computing space providingsolutions to clients and
building these out in production.

Maida Zahid (00:44):
Thanks, curtis.
Well, very excited to have youhere today, and this is a really
cool topic and very abstract,for sure.
So before, like as we get intoit, can you kick it off by
telling us what quantumcomputing even is?

Curtis Nybo (00:59):
Yeah, absolutely.
So it is quite abstract andit's a very kind of exciting
field.
I get really pumped up about itwhen I talk about it and as I
go through it.
Feel free to interject and askany questions.
But what we'll probably do iscompare it to classical
computing and go through whatthe difference is between
quantum and classical.
So quantum computing mostpeople have probably heard of it

(01:22):
, but it is a relatively newfield that leverages the
principles of quantum mechanicsto process information in
fundamentally new ways.
So, although it's actually notreally new, it's been around
since, I think like 1981, whereRichard Feynman and Paul Benioff
, two well-renowned physicists,started thinking about how to

(01:43):
simulate quantum phenomena in amore accurate way than using
conventional computing models,and so they kind of built the
framework for quantum computing,and then they shortly realized
that it's actually quite good atthe usual computational
problems that we try and solvetoday in addition to simulating
that quantum phenomena.
So to really understand thedifference between classical and

(02:06):
quantum computers, let's startwith where the classical
computers are and how they work.
So a classical computer itprocesses information using bits
, and these bits are in one oftwo states.
So you got your binary digits,zeros and ones.
Every operation is performedusing this binary logic, and so
the way these zero and onesactually occur is it's literally

(02:27):
flipping a switch in your CPUor applying a voltage to a
switch in a CPU to go betweenthese two states to execute
calculations.
So you're getting your usualzero and ones when you're using
your classical computers.
A quantum computer, on the otherhand, is pretty similar, but it
doesn't use classical bits.
They use what's called aquantum bit or a qubit, and so

(02:49):
quantum bits, they takeadvantage of several quantum
mechanical phenomena that existwithin the realm of quantum
mechanics, and so we'll talkabout three specific ones today
for our understanding.
But it's important to note thatat a high level, qubits are
just.
They're not restricted to justa zero or one, like a classic
bit is.
Instead, they can exist in aposition called superposition,

(03:10):
which allows them to be in statesimultaneously.
They can they take advantage ofwhat's called entanglement,
which allows them to kind ofcorrelate from with each other
over long distances, and theyalso a big part of it is also
the interference between thosequbits.
So we'll talk about all threeof these really quickly, just to
set the stage of what'sdifferent.

(03:30):
So we talked about how aclassical computer has a bit
that's in a zero or one state,no matter what, it's just a
switch flipping on and off,essentially.
But in a quantum system it canbe in what's called the state of
superposition, where they canbe in a state of both zero and
one simultaneously.
So if you imagine flipping acoin, a classical computer, it's
either going to be heads ortails, but in a quantum system

(03:53):
it's like the coin is spinningin the air, it's existing in
both heads and tails at the sametime.
Until you observe it, or untilyou knock it over and you
essentially measure it.
You measure the value of thatbit, and so for it'll either
come up as heads or tails orwith a qubit, it'll either be
zero or one.
So its ability to exist inmultiple states at once really
allow it to exist computeproblems in parallel.

(04:17):
So instead of processing justone variable at a time like a
classical bit, a qubit insuperposition can process
multiple values simultaneously.
So if you have two qubits, theycan represent four possible
states at the same time.
You're 0, 0, 0, 1, 1, 0, 1, 1.
With three qubits you get eightstates, because they can be in
all those states at the sametime.

(04:37):
So you get n qubits with two tothe n states.
Just to kind of narrow thisdown a little bit further, if
you say you're in a maze thathas three decision points, a
classical computer needs tocheck two to the three possible
paths, so eight possible pathsone by one, whereas a quantum
computer, with the same threebits but qubits, can explore all

(04:58):
eight paths simultaneously dueto superposition.
So this allows for exponentialscaling in some circumstances,
and it gives quantum computersthe potential for solving
problems that would take aclassical computer potentially
millions of years, and that's areally important, important
aspect of it, and it also tiesinto we talked about
superposition.
The second quantum phenomenonthat allows quantum computers to

(05:20):
be so powerful is calledentanglement, and so it's one of
the more bizarre properties.
But when, essentially when twoqubits become entangled, their
states become intrinsicallylinked.
So no matter how far apart theyare, if you measure one qubit,
if you measure the state of onequbit, the state of the other is
also instantly determined.
So even if it's 100 light yearsaway, it will still be

(05:41):
determined, and so this allowsquantum computers to perform
coordinated computations acrossmultiple qubits without direct
communication, which issomething that classical
computers really, really can'tdo, and so an example of that
would be going using kind of aflipping a coin.
Again, an example ofentanglement would be say, we're
um, maida has a coin, I have acoin.
We're separated by, you know,800 miles.

(06:03):
If we both start spinning thecoin, each coin that's spinning
exists in a superposition ofheads and tails.
Beforehand we entangled thecoins, so now they kind of are
correlated with each other.
So we each have our entangledcoins.
When I check my coin and I seethat it lands on heads, the
other coin instantly also wouldland on heads that Mida has, no

(06:24):
matter how far apart they are.
So the key difference is thatneither coin had a definite
state.
It was neither a zero or a onewhile it was spinning.
Only upon measurement does thatstate actually lock in.
But my state would correlatewith the one of my does, no
matter how far, no matter howbig the distance is.
And this is actually quitefascinating because that's what
Einstein called spooky action ata distance, because when they

(06:46):
discovered it it was quite acounterintuitive type of process
.
But some like to.
There's a commonmisunderstanding out there that
this allows for faster thanlight travel, but it really
doesn't.
So while the effect seemsinstantaneous, there's no actual
information being transmittedbetween the particles, in no way

(07:06):
, especially that it violatesrelativity.
So it can't travel faster thanlight.
And so the reason is that youcan't control what outcome you
get.
When you measure the firstparticle it's still a 50-50
result.
But what happens is that onceyou compare the results using
regular communication if I wasto phone MITA and say what did
you get, it would be the same.
So those particles are alwayscorrelated.

(07:27):
The measurements, the resultswe get from the measurements,
are always correlated.
So we've talked aboutsuperposition, we've talked
about entanglement, and thethird thing is kind of bringing
a little bit of them alltogether.
So quantum computing isn't justthrowing qubits into
superposition, you know, andhoping they do the best.
Quantum interference plays apretty critical role in ensuring
that quantum computers reachthat right answer as efficiently

(07:49):
as possible.
So they interfere, they're ableto communicate with each other.
They're trying to cancel outthe wrong ones and amplify the
probabilities of the correctones.
So if you think of throwing apebble into a pond, the
probabilities of the correctones.
So if you think of throwing apebble into a pond, the waves
can interfere constructively, sothey can amplify each other, or
they can interferedestructively and they can
cancel each other out.
So quantum computers use thatinterference in a similar way to

(08:12):
enhance the probability of acorrect answer, while still
canceling out incorrect answers,and so this is a pretty crucial
aspect of it for certainalgorithms that take advantage
of this aspect.
But overall we've talked aboutsuperposition, entanglement and
interference, and so hopefullyMaida, that was a lot, hopefully

(08:32):
it made a little bit of sense.

Maida Zahid (08:34):
That was a lot, but it was very fascinating.
I think the theory behind it isvery fascinating and definitely
very applicable.
So that takes me to my nextquestion is can you help take
that theory and apply it to realworld use cases, and what are
you seeing in your work?
What industries, where are weapplying these Especially?

(08:55):
Let's start with, let's say,the energy utility sector.
What are some of the common usecases?

Curtis Nybo (09:01):
So, like I said, we've talked about how the
quantum computer differs fromthe classical computer.
Before talking about the actualuse cases, it is important to
note that there's differenttypes of quantum computers and
they each apply to different usecases.
So they're usually splitbetween quantum annealers and
gate-based quantum computers.
So quantum annealers arequantum computers that use

(09:25):
quantum fluctuations to find theglobal minimum of a given
objective function.
So it tries to find the lowestenergy state of an energy
landscape.
So this works off of afundamental rule in physics that
everything seeks a minimumenergy state a rock falling to
the ground or water runningdownhill losing gravitational
potential, energy Electrons inatoms seeking a lower energy

(09:47):
state by emitting a photon,planets that settle into stable
orbits by gravity pulling theminto the lowest possible energy
orbit.
Everything in physics seeks aminimum energy state, and so a
quantum annealing quantumcomputer tries to take advantage
of that, and so we try toformulate a problem and
translate it into an energyminimization problem, and then
we're able to use someinteresting quantum phenomena to

(10:09):
be able to interact with thatproblem.
So quantum annealers can alsouse things like quantum
tunneling, which is anotherphenomenon where a particle can
pass through an energy barrierif it doesn't have enough
classical energy to overcome it.
So if a ball is rollingdownhill and doesn't have enough
energy to climb the other side,it'll roll back down, whereas a
quantum annealing computer hasthe capability to essentially

(10:31):
have that ball tunnel throughthat local minima of the problem
of the hill, to keep continuingdown the hill into a smaller
energy or a lower energy state.
And then the second one is thegate-based quantum computers
that I mentioned.
Second one is the gate-basedquantum computers that I
mentioned before.
So a gate-based quantumcomputer is more similar to our
current computers that we use,that are using, like our

(10:53):
classical computer will uselogic gates.
And so a quantum computerthat's gate-based has the
similar type of logic gates, butthey're built to handle qubits.
And through using qubits andproviding transformations
through gates on those qubits,they can take advantage of the
same quantum phenomena that wejust talked about before.
And so gate-based quantumcomputers, they require some

(11:17):
different error correctiontechniques, but they're much
more universal, whereas aquantum annealer is mainly
geared towards optimizationproblems.
So when we talk about findingthat local minima, that local,
that small lowest energy state,we're to optimize a problem,
whereas a gate-based quantumcomputer is a lot more universal

(11:37):
.
It can tackle your quantum,your um, your cryptography
problems.
It can do simulation problems.
It essentially can handle a lotmore variety in computational
problems.
So when we talk since we've nowyou know there's a little bit
of a difference between quantumcomputers.
Why quantum computing mattersfor the energy and utility

(12:01):
sector?
Well, because they have thisunique ability to take advantage
of these quantum phenomena.
They can also directly simulatequantum mechanical systems.
So this is something that when Italked about Richard Feynman
earlier in the 80s, this was theoriginal purpose of quantum
computers.
So there's there's a equationcalled the Schrodinger equation,

(12:22):
which is kind of thefundamental equation in quantum
mechanics that describes howquantum systems behave.
And so when they tried toinitially solve the Schrodinger
equation for certain molecules,which you know encompasses all
the information of that molecule, classical computers have a lot
of trouble, especially as themolecule gets larger.
And so quantum computers canactually solve the Schrodinger

(12:44):
equation for quite complexmolecules.
And this is crucial for thedevelopments in battery
development, drug discovery,material science, that sort of
thing.
And so when we're trying tomodel, when scientists are
trying to model the atoms oflike hydrogen or helium, a

(13:04):
classical computer can do thatpretty good, but it uses a lot
of approximations.
So when we're usingapproximations we're taking a
trade-off of compute time foraccuracy of the result, whereas
a quantum computer doesn't needto necessarily have that
trade-off.
It can accurately model theseatoms and these molecules

(13:27):
through the shortening equationwithout having to do that
trade-off of putting in a bunchof assumptions to try and make
that calculation actually beable to run.
And so the amount ofinformation required to model
these molecules scalesexponentially with the number of
electrons.
So it just gets quitecomplicated.
And whereas quantum computersoffer that new approach to mimic

(13:53):
nature at a quantum level thatallows for exact solutions, you
know, to that Schrodingerequation to actually be solved.
And so this leads to, especiallyin the space of energy and
utilities, the discovery of newbattery materials, so we can
simulate lithium, we cansimulate sodium and different
battery chemistries at an atomiclevel, things we've never been
able to do before, that havetaken a huge amount of

(14:13):
computational power to do.
It enables discovery of highdensity materials, better
electrode stability.
Overall.
We're seeing a lot of use inespecially the automotive use
case, as when it comes to energystorage, not only for electric
cars, where the carmanufacturers are really leaning
into using quantum to solvethese problems, but also things

(14:33):
like renewable energy, where thewind might not be blowing as
hard one day.
We need to be able to storethat energy and be able to
disperse it at a later time, andthat's where a lot of this the
new battery material comes in.
Another one is hydrogen fuelcells.
So quantum simulations havebeen known and been used to
identify catalysts for thosehydrogen fuel cells, and same

(14:55):
with solar panels betterdiscovery of the photovoltaic
materials that are used withinthose solar panels.
When it comes to oil and gasand coal that carbon capture
technology we're able to modelthose molecules and how they
behave and how we cansuccessfully harness those.
So overall it's prettyapplicable to a lot of different

(15:17):
areas in energy and utilities.
But I should say it's not asilver bullet, it's not magic.

Maida Zahid (15:22):
Well, thank you for your time, Curtis, and thanks
everybody for listening.
You can find the rest of theepisodes in our series on cgicom
and you can subscribe to ourpodcast on Apple Podcasts and
Spotify or wherever you get yourpodcast from.
Thanks very much.