Hi, I'm Judy Cole, the
Executive Vice President
and CEO of the MIT
Alumni Association,
and I'm delighted to welcome
you to this web production
of the MIT Alumni Association.
Okay, welcome to the MIT
faculty forum alumni edition.
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and former Knight Science
Fellow at MIT.
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so we encourage your questions.
Use the Google forum below the
livestream to ask a question,
or tweet your question
to #MITbetterworld.
We'll get to as many of
your questions as we can.
This month we delve into the
future of quantum computing.
A very interesting topic, and
one that's been in the news
quite a lot in recent years.
And we'll look at how
quantum computers will
change our lives.
Does the first quantum
computer already exist?
And if not, when might
we expect to have one?
And how can we
know if a computer
is in fact, a quantum computer?
Our guests will share
some of their research
on quantum information,
and probably
on quantum physics
more generally with us,
and they'll address
these and other questions
in today's forum.
So I'm just going to briefly
mention our three panelists,
and then they'll
introduce themselves
in a bit more detail.
We have Stephen Jordan from
National Institute of Standards
and Technology, we have Ramis
Movassagh from the T.J. Watson
Research Center of
IBM, and we have
Dmitry Pushin, a professor
at the University of Waterloo
in Ontario.
So to begin with,
I'll have each of you,
just again to
reiterate who you are,
and just to give a
little two minute
blurb about the kind of
research that you do.
And I think we decided
that Stephen was going
to go first, so take it away.
Sure.
So my name is Stephen Jordan.
I work with the
National Institute
of Standards and
Technology in Maryland,
also at the University
of Maryland, which
is where I am at the moment.
And I did my PhD with
Eddie Farkee at MIT
in 2008, in theoretical physics.
And what I worked on then, which
is also that I work on now,
is basically quantum
algorithms and quauntum
computational complexity.
So the quantum algorithm side of
things, the essential question
is, suppose we do have a large
scale working quantum computer,
what would it be good for?
What are the things that we
can do with it that we couldn't
do with conventional computers?
The complexity side is
a little bit more broad.
It has to do with, what's
the computational power
of different systems?
An aspect of that
that I usually study
is different physical systems.
So if we have something
that might not quite
be a quantum computer, maybe
it is at a high temperature,
it's not in a tightly
controlled state,
might we still be able to
compute some things with it
that we couldn't with
classical computers?
Or maybe, if we had
some more exotic system,
involving relativistic physics,
could that compute things that
ordinary quantum
computers cannot?
So we're basically comparing
the power-- computational
power of different systems.
OK, thank you.
And Ramis, did you
want to go ahead?
Sure.
I'm Ramis Movassagh,
I'm currently
at IBM T.J. Watson Research
Center in Yorktown Heights.
I did my undergraduate and
applied physics at Cornell,
then I spent some
time in Switzerland
doing neuroscience and
mathematical physics.
Then like Stephen,
I did my PhD at MIT.
I was in the math
department, and I
work with Peter Shore
who's factoring algorithm
you might have heard of.
And so my research
interests are applied
math and mathematical tools
applied to physical sciences,
including say, chemistry.
So in the quantum information
aspect of my work,
I'm mostly interested in
quantum many body systems.
So what are the
questions you ask?
Or how can we describe
and simulate, or predict,
the behavior of many
interacting quantum particles?
Now, everything in
the world is quantum,
because we're made up of
atoms, and electrons, etc.
But the mechanics and
the laws of physics
that we require for everyday
objects, like the pen,
you know, being
thrown into the air
or what have you, the
classical laws that we have
are sufficient.
But if you have atoms,
electrons, they're interacting,
then the laws that
apply to describe
their physics and
their behavior,
is described by quantum
mechanics and quantum physics.
And there is some
inherent difficulties
in simulating quantum
many body systems.
So it turns out that the amount
of work and resources you need
are exponential.
They grow exponentially with
the number of particles,
whereas you know,
for ordinary matter,
you're looking at something
that scales linearly.
So just to be able to
describe and simulate quantum
many body systems is
a very daunting task.
So then the question is, can you
give an effective description,
some effective
theory, some reduction
in the number of parameters,
that would allow you to,
with high accuracy, predict
the behavior of these many body
systems?
Now some of the particular
incidences that I've worked on
are disordered systems.
These are you know,
when an interaction has
randomness in them.
And a big part of my work is
in applying mathematical tools,
say from random matrix theory
and numerical linear algebra,
operator theory, to
better understand
the properties of these
quantum many body systems.
OK, thanks.
And Dmitry, why don't
you take it away.
Hi.
So my name is Dmitry Pushin,
and I received my undergraduate
and bachelor degree in
Russia, in Moscow Institute
of physics and technology.
Where I kind of studied
condensed matter,
specifically high
[? electricity ?]
superconductivity.
I also spent some time in
Switzerland studying magnetism,
so I'm experimentalists,
just to say.
And I finished my PhD at MIT
with Professor David Cory,
and I was studying
coherent control
of how we can manipulate
a quantum particle,
such as a neutron.
And why neutron?
Neutrons is the most common
building blocks of matter.
It's also a unique probe
for studying materials
and fundamental interactions.
It's the one that
electrically neutral nucleus,
and the neutron processes
through most of material
with ease, even at the
lowest neutron energies.
Now with these neutrons,
even with a lifetime
of about 15 minutes,
you can tell yourself
if that's a long
time or a short time.
I used to study problems
ranging from a discharge
of the common batteries and,
too, cosmological dark energy.
And my research is
focused on the neutron
as a quantum particle
that exhibit coherence.
So the ultimate manifestation
of coherence is interference,
and ultimate measurement
of interference
is interferometric.
So in my group we use
neutron interferometers.
One example is Mach-Zender
interferometer.
To form neutron into
superposition states, which
are separated by decimeters, to
explore my microscopic quantum
interference.
And some of the recent examples
which we started there,
it includes search
for the dark energy
using quantum
information concepts
to enhance the device itself.
So we actually build just
kind of neutron interferometer
based on the quantum
information which
is insensitive to
specific kind of notes
we employ decoherence
through subspace.
And we also try to explore
different degrees of freedom
of the single particles.
So we kind of
start in of neutron
which can have several
different paths it takes.
Neutron also has a magnetic
moment, so it has a skew.
So we can use that
degree of freedom.
It also could be seeded in
a different energy levels,
that people use different
energy levels to add
an additional degree of freedom.
So having one particles with
many degrees of freedom,
you can think of single
particle entanglement.
Where you can start
with a single particle
or several qubit systems.
OK thanks, Dmitry.
And why don't we
go back to Stephen.
And if you could
just give us sort
of a two, two to three minute
overview of why people are
excited about
quantum computation,
and how it's different
from classical computation?
I appreciate that, perhaps for
some people in our audience,
this is old news.
But on the other
hand, we may have
some folks who really aren't
too familiar with these ideas.
So just give us a little
introduction to the field,
and what the promise is.
Why people are excited about it.
Sure.
Well people have been
thinking about computation
for a long time.
Back in the 30's, people like
Turing, and Gardell, and Alonzo
Church, were formulating
mathematical definitions to try
to understand what is
computation, what's
not computation,
what can computers
do, what can they not do?
And in the subsequent
decades a consensus
emerged that the set of
problems that you could solve
with computers was very much
insensitive to the details
of what the computer was.
Whether it was built out
of silicon, or built out of
tinkertoys.
And really no exception was
found to that for many years,
up until sort of a
bombshell arrived,
which was the idea of
quantum computation.
It was the first
challenge to this notion
that all computers are
basically equivalent.
They can all do the
same set of things.
One might run twice as fast,
or even a thousand times
as fast as another one,
but which problems can
you solve in polynomial
time, and which
are the problems that are
just totally intractable that
take exponential time to solve?
That dividing line seemed
to be independent of how
you built your computer.
But computers are so far
the only real challenge
to this idea.
And so that's one reason,
sort of a theorist's reason,
why people are excited about it.
Now there's also a
more practical reason
to be excited about
quantum computers, which
is the list of specific
things that they apparently
should be able to do
exponentially faster
than classical computers.
The most famous of
these is the one
that was discovered by
Ramis's advisor who's
now at MIT, Peter Shore,
which is factoring integers.
So if you have an integer
that's n bits long,
the best classical
algorithm for solving this
requires time that scales as
two to the n to the one-third,
roughly.
So it's almost an
exponential time algorithm.
Beyond about a, I don't
know, 500 or 1,000 bits,
you just can't do it, even
with the biggest super computer
in the world, spending
millions of dollars
on CPU hours and stuff.
Whereas a quantum computer
can solve this problem in time
which scales like the cube
of the number of bits.
So that's a huge difference.
So for example, I once ran the
numbers and computed, what's
the largest integer
that you could factor,
if you took all of the
silicon in Earth's crust,
and converted it into like,
present day CPU's, two GHZ type
things, ran it for the
age of the universe,
and made optimistic
assumptions about how
paralyzable this problem was?
That was about 5,000 bits.
If you had a single
quantum processor that
ran at one GHZ
intrinsic clock speed,
factoring that number would take
you, like two and half hours.
So you know, it's a really
dramatic thing if you plug
in actual numbers there,
which people usually don't.
So you might ask, why do you
care about factoring integers?
So one class of people
who care about that
is cryptographers, because
they can write codes.
But from a fundamental
computer science point of view,
it just points to
the fact that here
are these exotic,
new machines, which
can do things, that are
way beyond the reach
of ordinary computers.
No one was expecting to ever
find any machine like that.
People really thought that
all computers were equivalent,
in terms of what they could
solve in polynomial time.
And so the big question
became, all right number one,
how do we build these things?
and number two, what else
might they be able to do?
Maybe the most compelling
other example besides factoring
is simulating other
physical systems,
predicting the outcomes
of chemical reactions,
et cetera, et cetera.
OK.
Thanks very much for
that introduction.
And I think we can see where the
promise of quantum computation
can sort of lead in many,
many different directions
right from the get go.
And of course we
can also point out
that this field is
sort of in its infancy,
whereas classical computers
have been around for,
well 75 years maybe, I
might be off by a few years,
but this field is
just getting started.
I want to go to Dmitry now,
who is the experimentalist
of our group.
And Dmitry, can you say
a few words about how
you take this from you know,
theory, this very clever idea
that we've had for
a little while,
and actually implementing it?
For example, what with
classical computers, you know,
we went through this phase all
right, we'll try vacuum tubes,
and then, we'll try transistors,
and things sort of evolved.
But I understand with
quantum computation,
it's kind of like, you know,
a struggle even to figure out,
what a qubit ought to be.
What should they be?
How do you connect
them to each other?
So can you talk, Dmitry,
about the struggle of actually
building one of these things?
Yeah, so if you think
of normal computers,
what we have again with the
silicon and most of them
are based on just
simple transistors.
Where we either
have a signal or not
have a signal, so it's basically
beats 1 0, and any calculations
you do is, of course.
And the transistor will
have a charge or not.
So we use the electric field
to control these devices.
And still we're trying
to reduce these devices
to go faster and, faster
and eventually, nowadays I
guess, what with this
sense of nanometers,
it's really harness
of the few, I
don't know few thousand,
few hundred thousand
maybe millions, of
the atoms themselves,
in a single transistors.
So let's remember that in the
atomic space in all the silicon
devices is in the order
of [INAUDIBLE],, so it's
an order of nanometers or less.
So you can try to reduce these
devices to make them smaller
and smaller, then the quantum
mechanics starts to kicks in.
And we have to kind of
think of transistors
a little bit different.
Even though nowadays, the
transistors are kind of small,
we still not use their
integrated quantum properties.
Like for example,
in the silicon that
will be the steam
of the electron.
And if people harness
this electron of course,
there will be some gain
maybe, in using less energy.
And of course, it
could be also faster.
And again, in this case, that
was quantum, what will be,
it's a superposition
state of this fume.
It's either in the
up state or down.
In case for example, in
the neutron interferometer,
I send neutron into path,
so it can take two paths.
It's again, like
I can control it
if it's going to
be spending more
time in one path or
another, and that I
can try use some [INAUDIBLE].
So this is kind of basic idea
of what a quantum beat would be.
So instead of having one and
zero, you have a superposition,
and that's kind of
inherited properties
of quantum mechanics.
So you can have a superposition
of a distant one qubit,
if you have several
qubits which are coherent,
you can have a superposition
of many qubit states.
And that was one of the
explanation I guess,
by Stephen to say, like we can
really just having a few atoms,
we can increase the
power of computation
of storing the memory.
Again with having
like 50 or 60 atoms,
we can have a memory which
is comparable to whatever
all the memory of the
universe we can build on now
and if it had like, maybe
a few hundred qubits using
like a few hundred atoms,
where we can either
use the [INAUDIBLE] states,
or some energy states,
we can build much more
powerful computers.
And of course there
are different systems.
Some of the systems
which nowadays
consider to be very
prominent is the ion traps.
And recently there was
publication in nature,
where there actually
people use a few ion
traps to build a universal
kind of, quantum computer,
or programmable
quantum computer.
They can program not just
a single algorithm, which
was possible only before
you really build a quantum
computer which consoles is
a good algorithm problem,
but people show that
they can use to solve--
they can program this quantum
computer on a five beats,
that the can see what state
interior problems could
be in the future, if they want
to really try to coherency
control the whole devices.
There was also big
advances in them,
in a script based
quantum computers
where they use the current
kind of degree of freedom
when they have
either current which
goes from left to right,
or from right to left.
That would be inherited qubit.
On the using the
small schemes, people
try to use the quantum dots.
Try to use atom floating
on the surfaces.
Again, I'm trying to use
neutron as a quantum device.
Maybe it's some of the ideas
not really of use for now,
it's not clear how
you can expand them.
But still there could
be some properties,
not on just building
quantum computer itself,
but also like creating
new devices, which
will be much more robust
against the noise,
and much more sensitive.
So you can study forces
of nature which we
wouldn't be able to do before.
Thanks for that, Dmitry.
And just a quick
follow up, tell us
what the current
state of the art is?
I mean for example,
a number of qubits?
Like where are we, at
the moment, what's the,
I mean, do we have something
today that we can point to
and say, yes, this is
a quantum computer,
and we've used it to solve
such and such problem?
Dmitry, where do we
stand at the moment?
So there is few, of course,
debatable questions.
But let's say, what most
people believe that we have
just like 15 qubits systems.
Maybe a bit more,
maybe a bit less,
which are fully controllable.
Which you can have a
neural stable interactions,
so you can control
the phases of each.
Either it would be this
[INAUDIBLE] or the ion,
or some other properties atoms.
OK, thanks.
And we've got some questions
that are already coming in,
online but just before I go to
them I'll ask Steve and Ramis.
Did you want to pick up
on anything that Dmitry
has been saying there?
Or do any of you have a
question for each other
before we go to our
audience questions?
Well I might have one
more comment, which
is that, so a metric that
gets talked a lot about I
think, especially in the
press, is number of qubits.
And there is also another metric
which I think is important.
Maybe even more important, which
is basically the precision,
the coherence times.
And there's been
a lot of progress
over the last few years about
making the qubits last longer,
and being more resilient
against errors,
and I think this
is going to be one
of the key things going
forward in scaling up
quantum computers.
And that's the thing to
really pay attention to.
In particular,
there is a threshold
which says that once you get
your error per operation, down
below a certain level, maybe
a tenth of a percentage
or something, then in principle
you can use active error
correction to correct
errors as you go along,
and then perform arbitrarily
long quantum computations.
And so that's like
a, I would say,
a very significant milestone.
In theory, people
have now demonstrated,
say single qubits or two
qubits very carefully isolated,
that nominally are below these
fault tolerance thresholds.
It's not quite the
finish line yet,
because you need to be well
below these thresholds.
Otherwise the size of
the error correcting
codes you need to use is just
too large, and not practical.
But I think that was a
key milestone anyway,
that was one of the
things that triggered
this recent wave of interest
from industry giants
like Microsoft and Google.
OK, thanks.
And I'm just looking
at our questions that
are coming in online, and we've
got a fair number already.
Some are well what I would
say, are quite technical,
and some are a little
more lay-person oriented.
So with my own
bias towards things
that I myself, can
sort of understand,
I'm going to take a question
to the audience that
is fairly straight forward.
And the question
is, how do you think
quantum computers could aid
NASA in designing or executing
space missions?
So would one of you like
to address that question?
Or if not, we can go
to another question.
I mean, we can think of the
like exchange of information.
Sometimes you need
to encrypt something.
This is going to be for example,
encryption key transfer.
And these technologies
already exist.
People try to
actually communicate
with the satellites
using quantum information
for their cryptography or
their information exchange.
And of course,
like maybe at NASA
trying to talk about
some devices which
they need to measure.
I don't know, like
there's a lot of ideas
to try to put some quantum
devices on the space station
and do a lot of
measurements, even
for the fundamental physics.
To study gravity, you really
need to know, for example,
big G to the quite
high precision,
to tenth to the minus six level,
to really kind of understand
better, better world.
And there's another
question, quite related
to that first one
which is, can you
comment on the Chinese quantum
communication satellite?
I know this was in
the news recently.
Dmitry, can you say a
word or two about that?
Maybe I'll pass.
OK.
All right, let's
go to the next--
Well, I mean, what they're
demonstrating I think,
is quantum key distribution.
It's a way of transmitting data
that cannot be eavesdropped
upon.
The usual way of doing
this is over fiber optics,
but it's limited in
its range to maybe,
a couple of hundred kilometers.
A different way is to transmit
the photons through free space
using telescopes
basically, and bouncing
the signals off of satellites.
And in principle this
might be able to achieve
somewhat longer range than
the fiber-based systems.
It's pretty expensive though.
OK.
I mean, it's--
I'm going to go to another
question that there is I think,
fairly answerable I
think, or at least it
should be easy to have
an opinion about it.
The person asking the
question-- oh I'm sorry,
I thought I should maybe
credit you know, someone named,
John C. And sorry for not
crediting the first two
questioners.
John says, I'd love to hear a
quick answer from each, will
government, academia,
or industry,
drive the most
innovation in this field?
So government,
academia, or industry?
Where do you think
the innovations
are going to be coming from?
Well, I could say maybe
a couple of words?
Please.
So right now, everybody
is active on it.
Certainly universities, as you
can see, one of our panelists
is working in the university.
And Stephen is at the
National Institute,
and I am with a
private company idea.
So there certainly
are quite a bit.
There's quite a bit of
activity in various sectors.
Of the industry right
now, there seems
to be a good push
from companies that
have quite a bit of resources.
So Google, IBM certainly
recently launched this five,
some of the cleanest qubits.
So there's a lot of push.
Government, from what we know,
has a good push, but maybe
Stephen they can say more.
And they may be
doing more things
that we don't know about.
And certainly
there are a lot of,
both theoretical and
experimental activity,
at universities.
Some universities have
embraced quantum information
and computation
more than others.
So in academia it's not, it's
a very interdisciplinary field.
So it doesn't have
a natural home.
You cannot necessarily place it
exactly mathematics, physics,
or computer science.
It's a little bit of both.
So it's had a harder time,
at least for theorists.
I guess experimentalists, they
would have a natural home,
in physics or perhaps
electrical engineering.
But as far as the
theorists are concerned,
not every institution has
embraced quantum information
as well, but it's
certainly picking up.
And we see more and more
hires and initiatives
from the academia, as well.
Did any of the other two
panelists want to weigh in?
I can add something.
Maybe it will quote,
[INAUDIBLE] on a saying.
Like it's really our
curiosity of understand
the world, pretty much
driving us to study
a lof of new phenomenons.
We live in that era of,
I guess I would say,
a new revolution of
the quantum control.
So we understood
quantum mechanics,
and now we try to harness it,
to use it in a everyday life.
And maybe that will
be quantum computers,
maybe it would be
just quantum sensor.
And then that could be
some way of program of I
don't know, some maybe
combining some particles,
designing new drugs.
And I mean, you can see
it, there is a conglomerate
already, that the
university is merging
with some national labs,
like Joint Quantum Institute.
It's a national
lab and university
trying to be specifically
based, on a kind of quantum
information quantum mechanics,
bringing people together
to study that.
There is of course, a lot of
interest in the government.
Let's say maybe military.
And of course, in academia too,
because again, maybe they're
curious.
Thanks.
And before, I'll go back to the
audience questions in a moment,
I want to just--
you know, there's a
famous quote from,
this will sound familiar to
you guys, but back in 1943,
you know the chairman
of IBM, actually I
should fact check this quote,
because maybe it's you know.
But he said, only five
people in the world
are going to need a computer.
Now, of course it
turned out that a lot
more than five people
need a computer.
What can we say at
this stage, and I
know it's tricky because quantum
information, quantum computing,
is in its infancy, but are
we talking about something
that you know,
everybody is ultimately,
you know, all our lives are
going to be affected by?
Or are we talking about,
sort of niche applications,
and for the most
part, regular folks
can just get by with
classical computing the way
we've been doing up until now?
Whichever one of you might
like to have a thought on that.
I think at the very
advanced stage,
if we one day we do
have a quantum computer,
and it's fairly powerful,
it will affect our lives
in so many different ways that
everybody will be either direct
or indirect affected by it.
To give you one simple
example right now,
where somebody spoke of NASA.
So people have very little
trouble sending space ships
to distant places using
various slingshots,
or having a little probe sit
on a comet of with a length
scale two kilometer rock,
basically an empty space.
So this takes a lot of
control understanding,
and a lot of accuracy
in simulating
these classical systems.
But once it comes
to quantum matter,
even to simulate you know,
like 100 spins, or 200 spins,
it takes a tremendous
amount of resources.
And we can't really
do it exactly.
But if one day we do
have a quantum computer,
we can do that very naturally.
And that has various
ramifications.
One of which is that as we
understand quantum matter
better.
And understanding quantum matter
better would, in principle,
can revolutionize, not
only our electronics,
but perhaps biology and
chemistry, certainly chemistry.
And you know, so it's
impact on our lives
is going to be tremendous.
Now whether there is a
particular use for a quantum
laptop that everybody
should have,
so there's certainly search
algorithms that are faster.
There is demo mention,
there is also communication
that they can do faster
using quantum computers.
But the field of
quantum algorithms,
and coming up with uses
for quantum computer,
is very much active and alive.
So it could very well
be that we have new,
it's actually difficult
field, coming up
with useful algorithms
is very hard,
but it is not out
of the question
that we'll have more and more
uses for quantum computer.
And that could change
the usability of it,
and the widespread
usability of it.
Yeah.
Just my two cents.
One thing I might
add, is that I think
it's useful to keep
two distinct questions.
One is whether computers
will be something
we'll have on our desk or carry
in our pockets or whatever,
something we will
physically possess,
versus whether it's something
that we'll use on a day
to day basis over the cloud.
So like the Google cluster.
It's not something
we carry around,
and it's really quite
different from the computers
that we have on our
desk, in some sense.
Although not as
different as a computer.
But it's something that we
access every day and interact
with every day.
And so I could see quantum
computers being like that,
even if we don't really have
them physically with us.
OK.
Thanks for that.
I know again, and this
is a tricky space,
you know, Yogi Berra said,
predictions are difficult,
especially about the future.
And I know this is
so tricky trying
to imagine the future of a
field that's just beginning.
I'm going to go back to
our audience questions.
And it's just a fairly
straightforward question
about the state of the
art of quantum computers,
from Larry Smith
in Austin, Texas.
And he's asking,
when do you think
we will have a quantum
computer that can factor
an integer faster than a PC?
All right, so that seems
like a fairly straightforward
question.
Can one of you -- or by the
way, has it already been done?
If it has, please tell us.
My guess is not at
least until the 2030s.
I think that there is a
few programs which really
are kind of funding their
idea of building a quantum
computer with 100
beats, and like I
think IBM is one part of it.
There's a few projects to try
to do something like that,
and would be like a 10
year project, or 20 maybe?
And also you probably know.
So I'm talking to the person
who asked the question,
so factoring has been done for
small integers like 15 or 21.
So we do have quantum computers
that do drop a lot of money on
and they can factorize 21 to
3 times 7 probabilistically.
So that is nice because we
do have proof of principle,
but so I think the
person actually
articulated the question well.
To say that, can we factor
a number at least as fast
as the classical computer?
So one is the speed of course,
the costs going into it.
The second is that, does the
probabilistic answers you
get from a quantum computer, so
that's a negative thing, right?
Compared to a
classical computer.
But at some point, if you
can do it large enough
that it outweighs the fact that
you get probabilistic answers,
is yet another thing
that should be weighted
in to the in comparison.
Just to clarify for
listeners who may not
be familiar with this idea, when
you say a probabilistic answer,
this is when the computer does
the computation, but then says,
oh I might be wrong, here's
the probability that I'm right.
Is that what we mean by this?
Right, so you basically,
so the key difference
between quantum mechanics
and classical physics
is that the laws of
quantum mechanics
are not deterministic.
So at best, you can predict, you
can predict the probabilities
with certainty.
You cannot predict the
particular outcome with
certainty, but the
probability with certainty.
And the quantum
circuits that you know,
that you give an input
into a superposition,
that superposition
is a statement
about that probabilistic
nature, then you
put a circuit that
implements the algorithm,
then it gives you an answer.
And the answer is
based on interference,
I think it was
mentioned earlier.
So the interference will say,
well with a high probability
you will get what
you want if you
have a good algorithm, or
experimentally a good circuit,
and with a low probability
you'll get garbage.
Now at every given instance
that you run the algorithm, well
you might get garbage, but
with lower probability.
But the good thing is that
the useful quantum algorithms
are just so much
faster, that compared
to the classical simulation, you
know even if you get garbage,
it's fine.
Because you can run it 10,000
times on the same task.
You can run it 100,000
times on the same task,
it'll take less
time, much less time,
than your classical computer.
And you can easily tell, that
with the probability that you
expect, for example
say even two-third.
Two-third of the time you
get that particular answer,
so that must be
the right answer.
So the answers
are probabilistic,
but for good algorithms.
They're outweighed by the
fact that the algorithm
runs very fast.
[INAUDIBLE]
One thing I would add, is that
I would expect that factoring
will not be the first thing
that quantum computers out
perform classical computers at.
What I think will happen first
is, we'll see quantum computers
out perform classical computers
at some kind of made up
problem, that nobody
intrinsically cares about,
but which is just
kind of cherry picked
to be easy for quantum
computers and hard
for classical computers.
And this will be done as
kind of a demonstration.
People refer to this
as a quantum supremacy
demonstration.
And I think that will be first.
I think that actually
is likely to happen even
within the next five years.
I think the next thing that
will happen after that is maybe
quantum computers out
performing classical computers
at some kind of simulation
test relating to chemistry
or material science.
And out performing classical
computers at factoring
will happen a number of years
after that, because as far
as we can tell it takes a fairly
large quantum computer to run
these factoring algorithms.
We're down to about
six or seven minutes,
and I want to try to squeeze
in another audience question.
But there's also
something that I
want to ask the
panelists just because it
has been in the press a lot.
As you folks know, there is a
Canadian company called D-Wave
that, you know, allegedly has
built a 512 qubit computer.
And they've actually
sold quantum computers
to NASA and to Lockheed Martin.
And according to Time
magazine, they sold one
to a US intelligence
agency, but the magazine
wouldn't say which agency it
was that bought the computer.
So 512 qubits, wow.
That sounds like a lot.
Can one of you comment, do we
know what sort of a machine
has D-Wave actually built?
They've obviously
built something.
Is it a quantum computer?
Well it's a special
purpose device.
It's not the kind
of quantum computer
that could ever do
factoring, for example.
Or even necessarily simulation.
It's really a special
purpose device
just for optimization problems.
And it's not exactly
a digital machine,
it's sort of more like
an analog machine.
And I think D-Wave
has demonstrated
fairly convincingly,
that this machine does
solve optimization problems.
There's much debate about
how quantum it really is,
and other debates
about how scalable
it is, how useful it is, etc.
But I say the basic
point is, it's
intended to be kind of a special
purpose quantum computer.
Oh I lost your audio.
Yeah, I lost your audio, Dan.
That's my fault, I
muted my microphone
and forgot to unmute it.
But that's okay, I wasn't
saying anything important.
I'll try to just squeeze in
this last question from again,
this person is in Austin, Texas.
So I guess they
like us in Texas.
It's McHale from
Austin, who says
that he's worked on fusion.
Which is another field
that has a lot of promise,
but is also sort of, in a
certain sense, struggling.
And he says that he was
always, it was always difficult
securing funding.
And he wants to know what
the funding landscape is
like in the research that
you people are doing.
is it you know, you just send
out the grant applications,
and the money comes in?
Or is it a bit of a struggle?
Tell us how much
confidence there
is in the work you're doing
from the people who actually
fund it.
My sense is that
it's, we have it
better than a lot of other
neighboring fields right now.
Yeah, I think so too.
I mean, there's a lot of big
push on the quantum devices,
quantum materials,
and which also
involve quantum computation.
There is still funding,
and people, I mean,
okay let's say
this for example, I
don't like apply for many funds.
Just particular in my
particular research,
because I was trying to
build specific device.
But I know people get funds,
and the funding is not bad.
OK.
I'll turn to, I think we're
getting close to the end here,
but let me just try to take this
last question from Jessica Lam,
who graduated from MIT in 2008.
And she wants to know,
sorry I have to lean forward
to read the small
print here, but how
can artificial
intelligence and machine
learning help increase
the development of quantum
computers, e.g.
Increased precision of
time or coherence of atoms,
and are there currently
places working on this?
So in other words,
I guess, you know
A.I. which is another field
that has been in the news a lot.
Can A.I help, in some
respect, with the work
that you people are doing?
So there has been
some discussion
about optimizing architecture of
quantum computers using machine
learning tasks.
Where you know, the
circuitry or the wiring,
which I'm not so familiar with
but that a experimentalist
would be, perhaps good
benefit from machine learning.
From machine learning
now, maybe other people
can comment more
about, there certainly
be some activity
about quantum machine
learning, a quantum
artificial intelligence.
But that's a different angle
than Jessica's question.
Maybe I can comment
in a sense, like we
do, trying to do the quantum
machine learning to search
for the different algorithms.
And one of the major
problems, and I
guess one of the
leading parts is really
to have a coherent control.
And if we scale too many
qubits, it's of course,
you will need to have a
more options, more devices,
I don't know, a better
control environment.
Because you still scale
control, and I mean,
with the quantum machine
learning, and in case
we come up with ideas how to
do the better control system.
If it would be useful, of
course it will get pickable.
OK, Dmitry, thanks.
And at this point, I
will wrap things up.
So a big thank you
to Dmitri, Stephen,
and to Ramis, and to our
audience following this online.
On behalf of the
Alumni Association,
thank you for tuning,
into this faculty forum
online alumni edition.
Thanks again, to our alumni
panelists from Waterloo,
from NIST, and from IBM.
We didn't get to all
the questions submitted,
but rest assured that our
panelists will see them all.
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chat using the #MITbetterworld,
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