hey everybody welcome to another episode
of EEs Talk Tech my name is Mike Hoffman
and with me as always I'm Daniel Bogdanoff and today we have Lee Barford
and Lee is a quantum computing expert
here at keysight so today you know Mike
and I really know nothing about quantum
computing so we're very very excited to
have Lee on here we're going to talk about
what is quantum computing Lee is in
beautiful Reno but he will also be
floating somewhere over there so we have
him on the phone today so Lee thank you
for being here can you tell us a little
bit about yourself and sure first of all
I'd like to say I I consider myself very
much a quantum computing (and quantum computer) beginner I've
been learning about it and and and
helping guide some parts of keysight
into this into this into this business
into keysight helping the real experts
make some advances in in quantum
computing and quantum computers. my background is actually in
computer science despite the name of
your of your podcast I have a bachelor's
in computer science from Temple
University in Philadelphia and a
master's in PhD in computer science from
Cornell however during the next during
the 30 years that I've been with
keysight in its predecessor tis to
predecessor companies almost all that
time I've been involved in coming up
with novel kinds of software that
support other kinds of engineers most of
that time certainly all the keysight
time has been in in in in in jin
software modeling techniques simulation
techniques for electrical engineers but during for
example my part of my HP Labs time I was
involved in new kinds of software to
help mechanical engineers and
manufacturing engineers
yeah I got involved in quantum
computing and this sort of goes into so
what's some of the read what what some
of the importance of it of quantum
computing is likely could be going
forward
to back up for the what what's the the
motivation for it as you probably as you
may have noticed clock rates in CPUs it
all kinds of digital processors stopped
going up in about 2006 and and that was
because of heating limits that were
brought about that that it was no longer
at that point it was no longer possible
to increase the clock rates and maintain
any sort of reasonable thermal power
dissipation so the processor
manufactures and I'm getting back to
quantum computing from this the quanta
the processor manufacturers realized
that they had to have more parallelism
in fact since about 2006 at 2007 up
until about a year or two ago most of my
work for keysight involved power i'm
taking advantage of that parallelism and
and and and teaching and enabling
keysight engineers to improve our
product performance by taking advantage
of the parallelism rather than the clock
speed available in current in in in
microprocessors for the last decade
microprocessors GPU yeah yeah i interned
for a chipset manufacturer in high school
right of that 2005-2006 range and i did
a lot of benchmark testing in the lab
and it was right when multi-core
processors were starting to get popular
and all we did was benchmarking and it
was you could tell certain software's
were taking advantage of the parallel
process and some were basically just
using one core because it's kind of a
symbiosis you have the hardware but you
have to program for that hardware it's
not done automatically which is anneka
and then there additional additional fee
such as most processors now have vector
instructions that can do multiple
integer floating-point operations per
cycle if you have a per instruction if
you have multiple operations ganged up
in a single register there's the use of
of graphics processors as basically
vector and matrix machines that can
accelerate all sorts of signal
processing and matrix map in addition to
the graphics or which they were
originally intended now thank us thank
you thank you video games but also also
thank you physicists that went to the
graphics chip companies and said look
look we can do this neat stuff with your
with with your chip please open up the
interfaces so that we can do that and
then and the graphics chip companies saw
a market there and complied and and and
and provide a Bitcoin mining I think
they use graphic cards but that kind of
Sally this kind of block chain style
calculations because there's so much
faster yeah yeah so yeah this is with it
and so the physicists of heavy use in
physics heavy use in heavy use in well
heavy use for all kinds of simulation
including including electronics
including electronic simulation heavy
use in in in biotech also well-suited
well suited for all those things as I
might mention late a mention later we
come back to it they're also very good
on the sorts of computation you need to
simulate quantum computers which has
which which which is an important thing
because they're quite expensive to build
and yet there's a a lot of the
experimentation that's happening is with
simulating them including simulating
them with with the assistance of GPUs so
you can simulate bigger bigger ones and
why that's interesting I'll get back to
anyway we're going down the path of
having more and more parallel computers
with every tick-tock of the of the
cycles of improved
including feature size shrink in
semiconductors however when we get down
to right now depending on who you
believe there are parts out there being
made at ten maybe seven nanometers none
of the manufacturers are very specific
about what that actually means but let's
say that actually means that the actual
there's an actual feature size in the
digital transistor that say seven
nanometers today that means in not too
many more years will be heading below
five nanometers and at that point there
aren't very many unit cells of silicon
left a unit cell silicon is about half a
nanometer so at five nanometers were
down to about five unit cells I don't
know what that is 35 40 atoms something
like that of silicon and then you've got
the dopant atoms in there at that point
quantum you've got some fuel enough
atoms that you're close to or at the
point where quantum mechanical effects
are going to disturb the electronics so
one way when you take quantum mechanical
effects is that like the uncertainty
it's like the uncertainty principle it's
like it's like the uncertainty principle
and like the fact that when you measure
when you measure measure when you
measure the when you measure the
physical state that the act of
measurement in self will noticeably
perturb the state including putting
taking it from an indefinite
superimposed quantum state a la
Schrodinger's cat to a definite state
you it means having having superposition
of states well I mentioned Schrodinger's
cat already all right that's that's the
Super's ition of the states the cat the
cat alive the cat dead in in digital
electronics that would be a zero state
in a one state you have some prop
ability of being in one or the other and
the act of actually measuring the bit so
that you can do some other computation
with it as you can read it out will
force it definitely into the zero one
state even though it was formally and
one or the other and also just just the
noise that the the noise and
disturbances that come from the physical
roughness at that kind of like that kind
of level and the fact that manufacturing
errors that are relatively small will
mean you have a different number of
atoms in each replication of that
transistor say but won't be but but but
you don't have that very many
transistors to start with right so
you're going to have higher and higher
manufacturing variants just because
normal tolerance of a couple atoms one
way the other is a big is a big
difference in the number of atoms in
that your hands ister yeah your
tolerances get quantized exactly exactly
real and and and even though the
physicists wouldn't call that a quantum
mechanical effect but in in the
theoretical sense as you notice it still
has to do it still change it's still
it's still coming it's coming from the
fact that you're dealing with quanta
you're dealing with individual atoms and
the count just even the count of them
starts to matter so one way to talk
about quantum computing is that it's
just one way of moving the computer
industry past that barrier there are
there others out there they're there
they're there other approaches and and
I'm even less expert in them and so I
won't go there people for them for how
to get past that barrier one way to look
at the quantum computing and the reason
for their investments in quantum
computing is it is it is a it is one of
the potential ways past that barrier
that basically is that the barrier laws
law essentially reaching the limits of
physics moore's law reaches the limits
of physics and so there's kind of two
things you can do on the one on the one
and you can you can try you can try
workarounds and and error correction
methods and computational approaches
that can deal with high error rates in
the fundamental electronic operations
and do sorts of error correction error
correction mechanisms that deal with the
fact that the the that underlying
digital electronics are going to be very
noisy but another another another
approach is to learn to engineer with
quantum mechanical effects and take
advantage of them hmm so expect so
you're at a party and someone comes up
to you and says Lee I've never heard of
quantum computing before what is it what
is it down grab a drink
how would you go it's the use of it's
it's it's it's it's taking advantage of
it's taking it it's learn it's taking
advantage of quantum mechanical effects
engineering with them to build a new
kind of computers that for certain
problems promise but are not not proven
to do better than what we have now even
what we could build at this mot when we
when we get to the end of Moore's Law
okay yeah building do you think we will
I don't know do we will he see the end
of Moore's law it depends on how you
define Moore's law if you define Moore's
law to mean that digital CMOS shrinks
every shrink severy 18 months or now
it's somewhat longer than that which in
itself is a sign of the at the end of
the potential end
yes Moore's law hat Moore's law has to
end because you can only make a
transistor features so small if on the
other hand you use Moore's law to
colloquially mean electronics continues
to advance so that there's more
a computational capability faster wider
bandwidth analog capability the ability
to build larger parts at less cost I
don't see that that's coming to an end
because there are lots of different
there are lots of different experimental
approaches to move forward after the be
and by expert I mean being researched at
like universities around the world for
moving beyond for moving beyond the end
of digital seem the end of digital CMOS
as we have known it and continuing to to
to allow electronics to make the
electronics industry make progress
so all of those approaches would need to
fail right for an order for for progress
in electronics to stop all those
experimental approaches would need to
fail and they're not all going to fail
some of them will succeed right so I
guess the answer is if if you want
Moore's law to fail you can define it as
such that it will definitely fail and
it's your Moore's law fanboys and it
will continue to to live on well I mean
you can think back to the old days of
vacuum tubes right it's like your could
only get so small right and it's like
boom now we have transistors yes and you
could you could kind of say Moore's law
is independent of the technology being
used I think that's sad yeah yeah if I
know there's some Moore's law haters I
think again I want to draw this
distinction if you more strictly
speaking more meant as law to apply to
digital like digital electron
large-scale integration he would have
called it back in the early 60s right
and so if you're being if you're being
formal right that's that's the real
meaning of Moore's Law if you're being
informal the Moore's law just meaning
electronics gets faster cheaper better
then then you're right okay awesome so
you know we're actually nearing it's the
end of what we Exuma considered to be an
episode okay you want to take a if we
had a few minutes left is there anything
else you'd like to discuss
we talked about you know technologies
and challenges leading up to quantum
computing can you give us a little bit
of teaser for future episodes because
we'll definitely have you on another
yeah sure I think I think future future
episodes can cover things like what
sorts of what sorts of technology goes
into a goes into a quantum computer what
the current state of experimentation is
where the money where what is it what
are some more of the motivations
including where the money is coming from
and I think we probably also want to say
how is keysight already already involved
in helping those experimentals you make
progress because we've kind of you're
saying before we started we've been you
know secretly ish involved in quantum
computing up till now and you can like
you know redact your resume yes well I
think this is a bit of a coming out for
us you know that hey we are here I'd be
interested in to knowing what kind of
problems quantum computing is trying to
solve and yeah will quantum computing as
we know it today more if its way into
consumer electronics right place right
the CMOS based computing we have today
or is it purely a specialist super high
end applications yeah and that's a
that's a really that's a that's a that's
a that's a that's a question I can
probably talk about but absolutely not
give you a definitive not give you a
definitive answer because one of the
things we'll be talking about doing is
that right now all pretty much most
quantum computing experimental
approaches require very extreme
environments very high vacuums or very
cold temperatures that that you can it's
hard to see how those approaches are
going to be in consumer products yeah
yeah in the last couple minutes we have
left you talked about how we have to you
know quantum computing is about using
those quantum effects
I'm going to use the term loosely yeah
back to our advantage
can you give us a brief overview of
what's that sure not it's not a
specifics of how people are doing it but
what yeah so I think that this the
simplest one to describe is is that of
is that of a superposition of states as
a so consider even used any of the
terminology yet but in quantum computing
the fundamental storage unit is
something called a quantum bit (qubit) and in
the quantum bit it the quantum bit can
be in states that are super positions or
mixtures of 1 and 0 if you have a
quantum register consisting of so that's
that's analogous to your visit
Schrodinger cat right it's alive or dead
with some probability likewise a quantum
bit can be a 1 or 0 with some
probability that doesn't seem useful to
me that seems like ah but what happens
if you have a quantum register of n bits
and you want to store a number of n bit
data data you can store them all you
could store them all with if you if you
want to make them in differentiate it
you can store them all with equal
probability and then then then there
could be an algorithm for searching
searching all of those and there is such
an algorithm can you give us a simple so
like you attend it register and you need
the stored 10 bits you know well you
could still yeah but you can store a
number of different 10 bit numbers in
the same register and compute on them
assuming 10 factorial ones right yeah or
two does it yeah I'm still trying around
or potentially assuming that you had
incredibly accurate or physical right in
the assuming you had a sufficient
accurate quantum bits sufficiently no
noise quantum bits you could store all
the all the two to the tenth possible
ten bit not ten bit numbers in that
register usually it's going to be more
interesting how do you read them yeah
that's that's one of the trick you can
only you the bad news is you can only
read one you
can store them all but you can oh if you
have them if you have them all stored
with equal probability one way to one
model of quantum computation is just
like when you when you open the box and
Schrodinger's cat is either alive or
dead once you look inside once you read
that register you're only going to get
one of the answers and even if you
reread the register so yeah because it
would be out there because just like
Schrodinger's cat it will collapse to
being live or dead right shirting yours
cat you close the box and open it again
if your first time you looked at it the
cat was dead it's still dead when you
look at it the second time so it's the
same thing with that register when you
read it the second time it's going to be
whatever read whatever value it you read
the first time so how do you get what
you want out of it
the answer is like theoretically you're
trying to cure you're going to do you're
going to do as much of the computations
as you as you can in with it with the
with the computer operating in the
undisturbed unread mode and then only
when you when you when the algorithm
requires it or it's finished do you read
it and get an answer so you can
basically like reduce out your formulas
and your computations and how it depends
on what that is specific yeah and then
you read it out and you like okay that's
it here's answer you that's one that
yeah that's that's that that's that's
one that's that's one way it works now
typically the answer is it typically the
algorithms are random algorithms so you
were you were in you were expecting to
get that have the
that the the prop you have the following
properties either the algorithm is going
to give you the right answer with such
high probability that you don't need to
check it or the problem was one that
it's easy to check that you got the
right answer so one of the problems that
people are very interested in is
factoring very large numbers because
that can be important in cryptography
here breaking RSA
is is the two-word explanation okay so I
killed me to cut us up oh yeah okay and
you ever said here and we will
definitely be picking this up maybe we
start back up talking about security
next time yep you know we may even
instead of every other week do some
depending on how long we're yeah here
chatting do a weekly thing instead I
really think so Thank You Lee Barford
that was fantastic my brain is missing
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Bogdanoff Mike Hoffman Lee Barford we
will see you next time thanks Cheers
