By Rich Ptak (Commentary updated - 5/01/2018)
 |
| IBM Q at Thomas J. Watson Research Center
Photo by RLP
|
We’ve previously
discussed IBM efforts and contributions to Quantum Computing[1]. These range from fundamental
research to developing quantum computing science to providing services that
will speed the transition from a theoretical science to a technology for problem
solving. We described their efforts with partners to build a large, broad
constituency of interested user/researchers connected via the IBM Q Network[2]. IBM Q Network allow participants
to make collaborative arrangements that will speed the evolution of Quantum
Computing technology. We recommend reading those articles.
In IBM’s view, technological advance occurs in stages. Starting with
a theory, a technological explanation is developed, and research done to define
a technology. This leads to development of an engineering understanding of how it
might be applied. Next, the focus shifts to spreading the knowledge of the technology
and growing developmental tools as potential users learn how and where to apply
it.
Quantum computing is nearly
there today. Research labs and engineering efforts continue at IBM and by others
to address issues involving the operating environment, data input/output, qubit
stability and reliability. They need now to attract and develop potential
users.
Achieving a commercially
viable quantum technology requires quantum knowledgeable users able to identify
and articulate problems, as well as create programs/algorithms. This is a task
for educators, interested users, commercially-focused engineers, enterprises,
and researchers. Therefore, efforts to increase quantum knowledge in a much
wider, commercially savvy community have been expanded, e.g. the efforts
mentioned above and described below.
IBM is taking a leading
role to address these and other issues. This includes addressing such issues as:
How will quantum computers and classical computers work together? What types of
problems are uniquely quantum friendly? Even identifying the right questions to
ask remains an important open issue.
With such issues in mind, we accepted an invitation to visit
with members of IBM’s Quantum Computing team at IBM’s Thomas J Watson Research
Center in Yorktown Heights, NY.
Here is what we took away from the visit.
Delivering public access to quantum computing
A major step to broaden quantum knowledge occurred in May 2016,
when IBM provided free public access to the first implementation of wide-scale,
cloud-based 5-qubit quantum computing. In March 2017, IBM Q Experience[3]
upped the game with access to actual universal (general use) quantum computers.
Two years on, 83,000+ people have moved far beyond that
initial Q-experience. A large constituency has access to not just 5-qubit, but also
16-qubit quantum devices. IBM Q Network clients have access to a commercial
20-qubit system. In late 2017, IBM stated that a break-through 50-qubit system is under development. To date, users have created and run nearly 4 million experiments; a strong indication that quantum computing has left the esoteric
realm of pure science and
theoretical physicists’ dreams.
Quantum
computing has started down the path to become a commercially applicable
compute technology. Early applications range from building molecular models that
aid the mapping of quantum circuits to apps that analyze very large
unstructured data sets (used for financial planning) to apps able to factor
complex equations.
IBM Q Network[4] is designed to facilitate the
creation of a global network of quantum computing interested industries aimed
at applying quantum technology to problem solving. Currently, only Q Network
clients have access to the 20-qubit devices. They can also access the 5- and
16-qubit devices of the IBM Q Experience. The community is in the early stages
of understanding what kinds of problems can be solved, as well as how to
formulate the “question” to be answered. Participants include F500[5]
and start-up companies to research labs and universities[6].
More details are available in the paper mentioned earlier.
Today, the IBM Q Experience allows users free use of both real 5-qubit and 16-qubit computers and 32-qubit quantum simulators to write
programs with familiar development tools,including loading and accessing data using classical systems, e.g. GUI- Quantum Composer[7],
QISKit[8]-GitHub. IBM Q Network clients also have access to commercial 20-qubit systems and resources to explore practical applications in their industries.
On-site IBM researchers use Power Systems linked to IBM Q quantum computers. IBM Q Experience users, as well as IBM Q Network clients access the quantum systems and quantum simulators thru a Power System-based cloud.
Combining classical computing with quantum allows dramatic extension to computing capabilities. It will eventually lead to posing and solving completely unique problem sets – including rapid evaluation of incredibly large data spaces to optimize financial trading, create new drugs and materials or optimize energy production.
On-site IBM researchers use Power Systems linked to IBM Q quantum computers. IBM Q Experience users, as well as IBM Q Network clients access the quantum systems and quantum simulators thru a Power System-based cloud.
Combining classical computing with quantum allows dramatic extension to computing capabilities. It will eventually lead to posing and solving completely unique problem sets – including rapid evaluation of incredibly large data spaces to optimize financial trading, create new drugs and materials or optimize energy production.
Quantum computing and classical computing
Posing classical versus
quantum computing is not the issue; it is determining how to most effectively exploit
each architecture. Successful efforts working with real quantum machines lead
to the conclusion that for
the foreseeable future, quantum computers leveraged in tandem with and
complementary to classical computers is the most promising way forward. Classical
computing executing with its logic gates; quantum computing using quantum
theory to manipulate “bits” and logic.
Tests have been run comparing
the problem-solving speed of quantum algorithms (on quantum devices) against
classical algorithms (run on classical machines). The results show that quantum
devices don’t consistently complete more quickly or offer better solutions. Or,
not enough to justify the additional effort required to do so. Thereby confirming
the continuing value of classical computing, as well as the need for both
approaches. Today, the challenge lies in identifying the exact problems or
parts of a problem can best be addressed via a quantum computing device.
Interestingly, doing those
tests also helped to reveal ways to improve some algorithms to run even faster
on classical computers.
Theory and logical quantum computer simulations provide some
insight into problem formulation. However, the gap between what can be done
with a logical qubit versus a real, live qubit is enormous. As an example, a
logical qubit can hold its states forever and be examined at leisure. In real
life, the qubit has an accessible, informational life of microseconds, meaning
only samples of output can be taken. They are also error prone. Algorithms are
run repeatedly to correct for these errors. Research continues to identify ways
to extend the life and stability of qubits.
Decades of classical computing solving all kinds of problems
has given great insight into their operation. They use binary logic and mathematical
concepts tied to the physical world. Physical models allowed logical processes
to be replicated. The expected results could be predicted and checked. This
made problem formulation, execution and answer checking relatively
straightforward. The same level of knowledge doesn’t exist for quantum
computing. And, given the actual physics of the quantum computer, it is extremely
difficult to acquire.
Quantum should be best at solving problems involving large
data arrays or having many complex options. But, the quantum world operates at
the limits of our measurable knowledge and abilities of observation. So,
identifying the specific details of quantum friendly problems remains an
on-going challenge. These include determining the best way to articulate problems,
and even deciding what problem or pieces of a problem to run on a quantum computer.
Much remains to be learned about composing algorithms and verifying solutions.
What is different about quantum computing?
Quantum computing is superficially similar to, but fundamentally different from classical computing. Both quantum and classical computers use algorithms to solve problems. The actual algorithms are different because of unique execution techniques. Both are programmed with gates and transforms. But, quantum computing manipulates objects at a molecular level. The laws of molecular physics that apply to quantum operations are quite different as are the conditions at which it works. IBM Q requires near absolute zero, -273C, temperatures. That is colder than what exists in space. (Although this may change.) It operates in ways not fully observable, or currently even directly measurable.
Qubits
are casually like bits. But, bits hold only one of two states (0 or 1). Qubits
hold a state of 0, 1 or any combination in-between (e.g. 20% - 0, 80% - 1). The
amount of data a qubit holds accounts for its great potential. They are shorter-lived,
sensitive (collapsing to bits if touched by minimal external energy),
error-prone, etc. These are gradually being resolved.
 |
| Figure 1 Entanglement ©HowStuffWorks |
What is entanglement? Two particles (photon,
qubit, etc.) interact and retain a relationship that is neither a physical nor
a controllable exchange of any sort. In figure 1, particle (A) is entangled with
particle (B). Once entangled, any changes made in the superposition state of
one of the pair will correlate with changes in the superposition state of the other
particle.
The change in the state of (B) is
predictable but opposite (complementary) to the change in the state of (A). Entanglement
simply (or not) means that the superpositions of two entangled particles will
change in an observable, complementary way with no physical contact or
connection. Thus, the change state is “correlated”, not “causal”. The results
of stimulating (A) are detectable by comparing states afterwards. The change is
the result of random movement in both particles – but only the overall outcome is
observable.
Entanglement of particle superpositions is
unique to quantum computing. Neither classical computing nor classical physics
have anything like it. It is the basis of a lot of the power and promise of
quantum computing.
Decades long IBM efforts have led to major contributions to
quantum computing science. More recently, they concentrated on moving quantum computing
from a science to a technology for experiments in application. They support
widespread education in quantum. They recognize that progress to
commercialization occurs as a series of step-ups in knowledge and capability,
not a leapfrog.
Classical
computing is based on well-understood models of logic and mathematics. It is
how we think and analyze. Experience and detailed models allow us to predict
outcomes and measure results against expectations. We know how to articulate
problems and structure algorithms with precision. Not so for quantum; where we
are just learning how to do all that in quantum terms.
It is
critical to begin engaging with this new evolution in computing technology. Not
to become experts in the theoretical aspects, but to understand the change in
thinking about how things operate to discover how it might be useful. Operating
in a quantum environment requires a unique, almost philosophical view of
problems. There is no doubt that it has the potential to radically alter how
problems are viewed, articulated and solved.
Quantum
computing will have a major impact. It will require effort to learn quantum. To
learn how to think, communicate and frame questions and, then to comprehend
answers in quantum terms. IBM Q Experience participants include 1,500 universities, and 300 US high school and the
international equivalent students. We expect that will spread.
It
would be a mistake to ignore quantum computing today. Understanding this, IBM is
working to advance public awareness and competency.
We found the Yorktown meeting to be very worthwhile. It was informative,
challenging and rewarding. We left with a lot to think about. Our major
takeaways are as follows:
1)
For the foreseeable future, quantum and classical
computers will operate side-by-side.
2)
Classical computing and its techniques remain
relevant.
3)
Classical systems are not going to be obsolete
any time soon.
4)
Quantum computers are not poised to
replace/enhance smart phones.
5)
Quantum computing will radically change how we
view and think about problems.
6)
Very new and different types of problems will be
identified and solved by quantum computing.
Once
harnessed, quantum computing’s ability to analyze massive amounts of data in
reasonable time to provide accurate, actionable insights can benefit many
areas. It will improve forecasting and allow ‘what-if’ analysis of incredible
variety and complexity. The impact will be felt in shaping and developing strategies
for everything from financial trading to inventory management. It will benefit research
to improve energy discovery and use. It will drive innovations in metallurgy,
medicine, forecasting, machine learning, traffic control, and much more.
[1]
See
“IBM Research on the road to commercial Quantum Computing“ at https://ptakassociates.blogspot.com/2017/09/ibm-research-on-road-to-commercial.html
[2]
See “IBM
Q Network – moving Quantum Computing from science to problem solver” at
https://ptakassociates.blogspot.com/2017/12/
[6] Keio University, Oak Ridge National
Lab, University of Oxford, University of Melbourne.
[7] https://quantumexperience.ng.bluemix.net/proxy/tutorial/full-user-guide/001-The_IBM_Quantum_Experience/004-The_Quantum_Composer.htmlhttps://quantumexperience.ng.bluemix.net/proxy/tutorial/full-user-guide/001-The_IBM_Quantum_Experience/004-The_Quantum_Composer.html
No comments:
Post a Comment