Session page, including audio: https://schedule.sxsw.com/2018/events/PP79118
Jerry Chow, IBM
Bo Ewald, D-Wave systems
Andrew Fursman, 1Qbit
Antia Lamas-Linares, Texas Advanced Computing Center at
University of Texas
Antia: The first concept of quantum computing was detailed
by Prof. Feynman in 1981. The quantum
computer uses three principles of quantum mechanics:
- Superposition – a bit can be 0 and 1 simultaneously
- Entanglement
- Quantum tunneling
Quantum mechanics application is found in multiple areas –
quantum sensors, quantum communication, and quantum computing, which is the
focus of this discussion. There is a lot
of attention on quantum computing, due to its promise. The EU has created a $1B program to advance
quantum computing and China is spending $11B on the topic.
Quantum computers come in two architectures: Gate
architecture and annealing architecture.
Basically the two are different ways to represent a Qbit.
Quantum computers are good at finding the probability to the
best answer – they do not provide certainty.
So, they are good for optimization problems. For example, routing traffic; placing
satellites, some machine learning problems.
Jerry: Quantum computing has grown from a concept only
understood by physicists, to something that is more popular in the computing circles. As hardware has progressed, we are learning
what quantum processors can do.
IBM Launched IBM QX (Quantum eXperience), which is a 5 Qbit processor
that’s available online and accessible for the public. IBM also released an SDK and a Python API set
to help users write code more easily and experiment with the quantum processor
and simulators. There’s also a user’s
guide for beginners.
Andrew: There are still very complex problems that can’t be
solved in traditional computing methods, for which quantum computing is more
suited.
Anita: Where are we in terms of the hardware? Why do we see it in the news so much now?
Bo: Our technology now is probably at a similar stage to the
level regular computers were in the 50s – just as we transitioned from vacuum tubes
to transistors, and before the development of Fortran, the first computer
language that made computers somewhat accessible.
On the other hand, we are dealing with very advanced hardware,
and are progressing very quickly. Large
companies are buying ever bigger machines – Google bought a 500 Qbit machine,
and Lost Alamos and NASA bought 2000 Qbit machines. So the hardware is advanced, but the software
and application are 50s era.
Jerry: With circuit model, we need to have large numbers of
perfect Qbits to achieve meaningful usage, but the physics of the domain are
such that large numbers of Qbits increase the likelihood of errors in
calculations, in which case strong error correction is needed. Right now we can build tens or hundreds of
physical Qbits, but those would generate a lot of noise, and we’d need to find
the right applications for them.
Andrew: We need to think about what types of things are not
possible with classical computers and how we would build quantum computers to
solve these types of problems. Regular
computers and quantum computers are not in competition; they enhance each
other. It’ll likely have a model similar
to CPU and GPUs – the CPU farms out certain types of operations to a GPU, which
is better suited for them.
Jerry: Quantum chemistry is an example of a domain that’s best
tackled with quantum computers. It would
be too hard to have large scale simulations of quantum chemistry on traditional
computers.
Andrew: If you must use 30% of a supercomputer cluster for a
relatively simple chemical simulation, that’s a hint we’re not using the right
tool for the problem. We will be
building quantum computers to solve specific types of problem: a computer optimized
for matter manipulation, one optimized for quantum material science analysis,
and so on.
We need to increase the exposure and availability of quantum
computing to better expand and speed up potential development.
Jerry: We’re still not in the level of maturity that we
would have compilers, operating systems on Quantum computers. It’s still very early days here.
Bo: There are only about ten companies in the world who can
build quantum computers, and we need to get them into the hands of millions to accelerate
the field.
Anita: What are the drivers of quantum investment? Is it still mostly government and education
sector?
Andrew: Once we start seeing results the corporate sector
will enter the field. The government
should be encouraging businesses to invest in the field.
Jerry: We’re starting to see rapid development of technology
with academic advancement.
Bo: We’re still in the R&D phase, which makes the users
mostly big operators like governments.
The first killer app will change that.
Andrew: We need to ramp up the talent now, not when the
first killer app hits.
Jerry: In the past, we would be primarily hiring physicists,
because only they were able to understand the domain. But now we see more and more computer
scientists available.
Question: What should we be concerned about in terms of
security and what is overblown?
Jerry: Breaking encryption comes up a lot, but I wouldn’t be
worried about it – the technology to support this is still not available. It’s important to start thinking about transitioning
away from traditional encryption, but it’s not an immediate problem.
Bo: It’s probably another 10 years before Shor’s algorithm
can be used.
Anita: This is something we’re thinking about, but there’s also
quantum encryption – that will likely take replace the common encryption
algorithms we use today.
Question: What are consumer applications of Quantum
computing?
Andrew: Probably in the financial world, solving
optimization problems. For example, how
can I get the most X by investing the least Y. Other than that, it’s currently hard to tell
what types of usage there will be. The
field will innovate once access becomes more available and knowledge spreads
more.
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