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Table of Contents
List of Figures ................................................................................................................................ ivAbstract ........................................................................................................................................... vIntroduction ..................................................................................................................................... 1History of Modern Computing........................................................................................................ 1History of Quantum Computing ..................................................................................................... 4
Entanglement & Superposition ................................................................................................... 4Quantum Mechanics in Computing............................................................................................. 5
Comparison of Quantum Computing Methods ............................................................................... 5Ion Trap Method.......................................................................................................................... 5
Current Level of Development ................................................................................................ 5Relative Cost............................................................................................................................ 7Current Level of Development ................................................................................................ 8
Quantum Dot Method.................................................................................................................. 9Current Level of Development ................................................................................................ 9Relative Cost............................................................................................................................ 9Projected Development Cost ................................................................................................. 10
Conclusion .................................................................................................................................... 11References ..................................................................................................................................... 13Glossary ........................................................................................................................................ 14
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List of Figures
Figure 1 D-Waves commercial quantum computer....................................................................... 1Figure 2 Punch card computer input ............................................................................................... 2Figure 3 Room-sized vaccum-tube computer ................................................................................. 3Figure 4 Representation of Quantum Spins .................................................................................... 4Figure 5 Future registers in quantum computers may look like this ion trap. ................................ 6Figure 6 The various shapes and flaws in silicon carbide crystal structure. ................................... 8Figure 7 Map of Current Sources of Cadmium ............................................................................ 10Figure 8 2009 Projection of usage of Quantum Dots ................................................................... 10Figure 9 A working ion trap information processor, developed at the National Institute of
Standards and Technology. ........................................................................................................... 12
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Abstract
Modern computing has evolved incredibly quickly over the last several decades. From
programmable textile mills to vacuum-tube computers to modern transistor-based
microprocessors, computational power, speed, and flexibility have grown exponentially.
Unfortunately, modern computing is reaching its limit. If transistor density continues to increase
at its current rate, within a few decades the transistors will have to be the size of atoms. Our
current technology can no longer keep up with our expanding needs and capabilities.
Quantum computing is the science of using quantum properties of atoms as a basis for
computations. This exponentially increases the power of a computer. Quantum computers,
however, are not commercially viable and need further research and development. There are two
main methods of quantum computing: ion-trap and quantum dot. They use different sets of
quantum properties to function.
Based on analysis of cost, current development status, complexity, and time to production, itseems that ion-trap will be the most likely successor to modern computing. It is cheaper to build
and closer to a finished state of development. There are, however, still major problems to be
overcome before the quantum computers can become available to the public.
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Introduction
Over the last twenty years, computer technology has advanced greatly. Computers have gone
from the size of large rooms to the palm of our hands due to new developments in
superconducting Silicon. However, scientists have found that Silicon based computing has limits.
Moores Law states that every 18 months the maximum capabilities of computer processingspeed and memory will double. This law is based on the number of transistors that can be
feasibly placed on an integrated circuit. In a decade or two, following this trend, transistors will
be reduced to the atomic level and superconductors will have reached their limit. Thus, a new
and more powerful system of computing will be required, and it is most likely going to be
Quantum Computing.
However, there are several roadblocks that need to be overcome before quantum computing
becomes a practical approach to mainstream consumer computing. The first roadblock is an
obvious one: quantum systems are microscopic. The challenge is to gain exquisite levels of
control at the atomic scale, over thousands of atoms. To date, this has only been achieved on theorder of 14 atoms. The first group to solve these problems will most likely produce the first
quantum computer feasible for mainstream use.
As scientists continue to research and develop quantum computing different methods and
processes have arisen. Even now though, some scientists are extremely skeptical about quantum
computing and doubt that it will ever amount to
anything tangible. We intend to research the
different methods and practices that are currently
under development and determine which is most
feasible and therefore most likely to emerge on themarket first.
Vancouver-based D-Wave Systems claims to
actually have a commercially available quantum
computer on the market (see fig. 1). However, it is
contained in a ten square meter shielded room and
costs approximately ten million dollars (D-wave
Systems, 2011). Obviously there is more work to be
done before quantum computing becomes widely
available to the general public.
History of Modern Computing
The modern use of the word computer means a machine that can carry out computations. At
the root of what we consider a computer is something that can do automated calculations as well
as being programmable. The first instances of a device that could do automated calculation came
Figure 1
D-Waves commercial quantum computer
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to be hundreds of years agoin 1642 a mechanic calculator was invented that could add,
subtract, multiply, and divide on its own (Akera, 2002).
The first major programmable device was built in 1801, when Joseph Marie Jacquard built a
textile loom that could produce specific pattern automatically by reading a punched paper card
(Akera, 2002). Although this wasnt much in terms of flexibility, and could only read data, notrecord it, it was the first step on the way to programmability, and paper punch cards were used
for many years in the early stages of computer programming.
It took combining to ability to calculate and the ability to program to create the first machines
that we would consider computers. In 1837, Charles Babbage conceptualized and designed his
analytical engine, the first programmable computing machine (Akera, 2002). It wasnt
finished and successfully demonstrated until 1906, however.
Herman Hollerith was the first person to invent the ability to
record machine data. He chose punch cards, the same typethat Jacquard had used to program his loom (see fig. 2). He
used his technology for the 1890 US Census, and later it
became the core of IBM (Akera, 2002).
For the next few decades, analog computers became more
powerful and sophisticated. These computers used a different
model for each problem they had to solve, but they werent
truly programmable, instead having to be built for a specific
purpose.
In 1936 Alan Turing came up with the idea of algorithms and
computation for a digital computer. This enabled people to
start building truly programmable digital computers similar to
the type we use today. George Stibitz built the first computer
that used binary circuits in way modern computers use. His first computer could only perform
arithmetic, but later models became more powerful (Akera, 2002).
Figure 2
Punch card computer input
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Until the 1960s, computers based on vacuum
tubes as electronic elements were widely used.
These computers were extremely large (the size of
entire rooms) and limited in how quickly they
could process information (see fig. 3). By the
1960s, these computers were largely replaced by
transistor-based machines, the model which is in
use today. There are two types of transistors, both
of which conditionally allow a current to pass
them. This enables digital logic at the foundation
of all modern computers. These computers are
faster, smaller, cheaper, more reliable, and use
less power than the old vacuum-tube machines (Akera, 2002).
Since the invention of transistor-based technology, computers have continued to become morepowerful, smaller, and cheaper. In the 1970s the first microprocessor was invented using
integrated circuits. In the 1980s computers were small and cheap enough to be put in individual
homes. When the internet was invented, personal computers became a central part of life in the
Western world (Akera, 2002).
Since then, microprocessorsthe fundamental piece of a modern computerhave become better
and better, smaller and smaller. As mentioned in the introduction, transistor density has roughly
doubled every two years since their inception. We are, however, rapidly approaching the point
where this will no longer be possiblethey will simply be too small.
As we can see, computer technology has changed greatly over the years since its conception.
The first use of the word computer was in 1613, meaning a person who could do calculations
(Oxford, 2011). Obviously our understanding of what a computer is and what it can do has
changed several times throughout the history of computing. What we consider commonplace
now seemed completely impossible as little as forty or fifty years ago.
With the continuing progress in modern science, technology, and general understanding and
needs, modern computing will need to continue to evolve. Given the exponential increase in
compute power over the last few decades, it seems extremely unlikely that progress will be able
to continue as it has. Soon our ability to make smaller, cheaper, more powerful computers will
slow and eventually halt unless we find another way to make them, in the same way that
transistor-based computers revolutionized vacuum-tube machines.
Quantum computers are a likely successor to modern silicone transistor-based computers. They
continue to use the same fundamental concepts of automated calculation and programmability,
but they introduce another way to process and manage data. As our needs for computing power
Figure 3
Room-sized vaccum-tube computer
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and data storage continue to increase, quantum computing could be the next major revolution in
computing that makes it so those demands can be met.
History of Quantum Computing
The idea of quantum computing has been around for over fifty years. In 1959 Richard Feynman,the American physicist and Nobel laureate, theorized that as computers began to evolve farther
and farther into the microscopic area, they could harness the power of quantum mechanics and
become far more powerful than conventional computers. While it would seem that quantum
computing is a long time coming, until recently the progress has been extremely slow. This is
partially due to our lack of understanding of quantum mechanics but mainly to our inability to
control molecules and particles on the quantum scale. In the world of quantum mechanics,
objects do not have clearly defined states. Frankly, quantum mechanics is a complicated field
and behaviors such as superposition are unintuitive. Simply put though, this phenomenon means
that if we could properly control the states of objects on a quantum scale, we could make
combinations far greater than the current method of 0 and 1 (two states, ie on or off). Scientistfocus on controlling the objects in 3 states, what can be called a x,y, and z axis or plane.
A traditional computer uses 1s and 0s, known as Binary Digits in order to process information.
Because of only these two states, a computer with 4-bits can hold any one of 16 numbers (2^4)
represented in binary. Quantum computers can control objects in any number of states from 0 to
1, and as such will increase exponentially in computing power. For example, a 30 qubit quantum
computer would be capable of 10 trillion floating-point operations per second, or in other words,
would be as fast as the fastest supercomputers we have today.
Scientists are researching changing the very nature ofhow computers function, replacing the classic model of
binary 1s and 0s based on electrical charge (bits) with
photon spin states that can be any combination of 1s and
0s superimposed on top of each other (qubits) (see fig. 4).
As understanding of quantum mechanics increases,
strange behaviors of photons and other subatomic
particles are better understood and able to be harnessed.
Entanglement & Superposition
Quantum entanglement and superposition are harnessed by quantum computers to process large
amounts of data much more quickly than traditional computers can. Quantum entanglement is
the observed behavior of two particles that interact and then are separated and then still behave
similarly.
Quantum superposition states that a particle or system can be in all possible states at once and
will, upon observation, break down into a resulting state consistent with each of the previously
Figure 4
Representation of Quantum Spins
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superimposed states. For example, two particles that had undergone quantum entanglement and
were separated light-years apart would still behave the same (similar spin state, etc.). Such
behavior violates Einsteinian physics in that it allows particles to communicate faster than the
speed of light.
Quantum Mechanics in Computing
Quantum computing employs entanglement to manipulate qubits and superposition to have those
qubits essentially compute simultaneous superimposed inputs.
Scientists are researching changing the very nature of how computers function, replacing the
classic model of binary 1s and 0s based on electrical charge (bits) with photon spin states that
can be any combination of 1s and 0s superimposed on top of each other (qubits). As
understanding of quantum mechanics increases, strange behaviors of photons and other
subatomic particles are better understood and able to be harnessed.
Comparison of Quantum Computing Methods
Ion Trap Method
As current processors approach the physical limit of silicon-based hardware, technology
researchers have begun to explore how to harness the power of atomic particles for computing.
The trapped ion method of quantum has already been proven to be a theoretical solution for post-
silicon processors, but other factors such as its development cycle, cost, time to consumer
launch, and complexity of usage will determine if it will become the practical successor for the
next generation of computing hardware.
A trapped ion quantum computer is still a traditional computer in the sense that it reads the
binary states of its processing elements. However, instead of reading the flow of electrons in a
transistor as current processors do, trapped ion quantum computers use ions, or charged atomic
particles, which can be confined and suspended in free space using electromagnetic fields.
Qubits (the quantum equivalent of traditional bitsin other words, a system from which a 1 or a
0 can be read) are stored in stable electronic states of each ion, and quantum information can be
processed and transferred through the collective quantum motion of the ions in the trap. Lasers
are applied to induce coupling between the qubit states (for single qubit operations) or coupling
between the internal qubit states and the external motional states (for entanglement between
qubits).
Current Level of Development
Development of trapped ion computers is already well underway. The fundamental operations of
this method of quantum computing have been demonstrated experimentally with high accuracy
(or "high fidelity" in quantum computing language) in and a strategy has been developed for
scaling the system to numbers large enough for consumer computing needs. Just as the number
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of transistors determines the computing power of a traditional silicon processor, the number of
ion traps through which ions are shuttled determines the power of a quantum computer.
Recent advancements in the size of these trap arrays make the trapped ion quantum computer
system one of the most promising architectures for a scalable, universal, quantum computer. As
of May 2011, the largest number of particles to be controllably entangled is 14 trapped ions,
which was accomplished by a group of researchers in Austria (Monz, 2011). However,
computing on this scale doesnt even come close to the power of silicon processors currently
available. Ren Stock, a post-doctorate researcher of ion trap computing at the University of
Toronto, reported in May 2009 that Right now, classical computers are faster than [ion trap
computers]. The goal of quantum computing is to eventually speed up the time scale of solving
certain important problems, such as factoring and data search, so that quantum computing can
not only compete with, but far outperform, classical computing on large scale problems
(Marquit, 2009). He also noted that the development of ion trap computers has made a lot of
progress in the last ten years.
Figure 5
Future registers in quantum computers may look like this ion trap.
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Relative Cost
The cost of a quantum computer is somewhat difficult to determine as there are virtually none
being sold yet. The first commercial quantum computer was sold by D-Wave Systems to
Lockheed-Martin Corporation in May 2011, and while details of transaction were not disclosed,
D-Wave Systems did comment that the cost was consistent with large-scale, high-performancecomputing systems (Feldman, 2011). At that cost (in the millions of dollars), quantum
computing is still well out of reach of the mainstream consumer.
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Current Level of Development
However, a recent development in ion trap computing could lead to quantum computing being
nearly as affordable as currently available traditional processors. In late 2011, Researchers at
U.C. Santa Barbara demonstrated quantum coherencea necessary step to computingusing
imperfections contained in silicon carbide crystals. These crystals are used in todays traditionalprocessors, but while imperfections in these crystals are disadvantageous for computing with
electric current (as todays processors do), it is these same imperfections that allow the crystals
to be used as ion traps for quantum computing.
Figure 6
The various shapes and flaws in silicon carbide crystal structure.
As Dr. David Awschalom, senior author of the paper notes, We are looking for the beauty and
utility in imperfection, rather than struggling to bring about perfect order, and to use these
defects as the basis for a future quantum technology (Knapp, 2011).
The speed at which significant developments occur in the field of ion trap computing is
remarkable. Current indications suggest that by the end of this decade, sufficient advancements
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will have been made to make ion trap quantum computing a feasible consumer solution in terms
of cost, accessibility, and scalability.
Quantum Dot Method
With the benefits of a true Quantum Computer now clear, the scientific community has been
searching for the most efficient and feasible method to not only make true Quantum Computer,
but that will lead to the possibility of mass production. Since the idea of Quantum Computing
was first introduced in 1982 by Richard Feynman, there have been a great deal of advances in the
hardware, but not as much in the theory of how it works. This changed in 1997 when Daniel
Loss and David P. DiVincenzo introduced a new possible method to produce a Quantum
Computer. This eventually would be known as Quantum Dot Quantum Computing. Instead of
using large magnetic fields to trap ions in order to track their quantum movement, these
researchers proposed using tiny semiconductor islands, quantum dots, to confine single
electrons. These islands are no more than one to twenty nano-meters, in other words more than
1000 times thinner than a human hair. There are however obstacles to be overcome.
Current Level of Development
At the moment, there are no functioning quantum computers utilizing Quantum Dots. However,
the field of Quantum Dots has consistently grown over the last 15 years, closely following the
improvement of silicon based computer technology used to track the movement of the confined
electrons. There are many other uses for Quantum Dots including transistors, solar cells, LEDs,
and diode lasers.
Some of the major problems facing the future advancement of Quantum Dot computing is the
fact that the main metals being used to make them (namely Cadmium and Selenium) are rare,hard to isolate (extract from other metals), and prolonged exposure is toxic to most forms of life.
This leads to yet another problem. With all the Going Green movements, the isolation,
production, disposal and recycling of these heavy metals are expensive and require extensive
training to do.
Relative Cost
This is one area that has made it especially hard to progress in research, since Quantum Dots are
very expensive. Of course the exact cost depends on the materials used, but it can range from
$3,000 to $10,000 per gram, and that is not including the cost to use those dots to make the
matrix needed for Quantum Computing, thereby restricting their use to only a very few well
funded researchers. Of the few elements that can be used, Cadmium is the most popular for
various reasons. It is however 200,000 times less common than Silicon, only making up 0.1 parts
per million of the earths crust (Silicon makes up 27.7%). While it is found throughout the world,
China has risen to be by far the largest producer of Cadmium, as well as many other precious
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computer would still be in the range of 100,000-500,000 Dollars, far out of reach for most
consumers.
Part of any reformation of technology is the hype or the anticipation of the next big thing, and
this summer Quantum Computing took a large step forward in attainability. The University of
Southern California became the first institution to own an operational Quantum Computersystem, purchasing the D-Wave One from Canada based D-Wave Systems. Though this has
taken criticism lately on whether it really is a quantum computer or not, it is beginning to
introduce to the general population what a Quantum Computer is and what it can do. Even in this
day an age, the progress of Quantum Computing will still most likely require a good deal of trial
and error.
Conclusion
The need for a new alternative to the current method of silicon-based computer processing is not
a problem that will go away if ignored. Experts estimate that the physical limit of this type ofchip will be reached by 2017 (Overton, 2007), and theoretically, one of the two methods of
quantum computing discussed in this paper could be its successor. While both the ion trap
method and the quantum dot method of computing operate on the same basic principle of using
quantum states instead of silicon transistors, the other factors mentioned in this report such as
cost of production and current state of development could indicate which is more likely to be the
architecture of the next generation of mainstream computers. However, as the development of
quantum technology is still in such an early state, and game-changing advancements occur in this
field almost weekly, the conclusions drawn from this data could be obsolete in the near future.
This is simply the nature of a discipline that evolves as fast as computer science.
From what has been presented so far, the ion trap method appears to be the more likely successor
to silicon-based computing, based on its estimated time of market release, cost, and range of
applications.
In consumer technology, there is a great advantage in being first in the market. Ion trap has a big
advantage over quantum dot in this category because it could nearly be ready for consumer use
by the time the limit of silicon chips is reached (estimated to be 2017). The release of
mainstream hardware that uses quantum dot technology is still unknown. Major advancements
are still required in order for quantum dot technology to be manufactured, due to the prohibitive
cost and large requirement of rare materials.
As far as cost is concerned between the two options, we can only draw some general
conclusions. Hardware that utilizes these computing methods is not being sold or even widely
manufactured yet, so there is virtually no data to indicate which will be more affordable for
consumers. However, we can look at the cost of manufacturing materials. Ion trap technology
also has the advantage in this category because it potentially could use the same silicon crystals
that todays processors use, as mentioned in U.C. Santa Barbara report. Quantum dot technology,
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on the other hand, uses large amounts of expensive rare earths, including cadmium and selenium,
which are toxic, difficult to isolate, and difficult to recycle.
Finally, ion trap technology also has the advantage over quantum dot technology as far as range
of applications is concerned. The ion trap method has already been used in functional computing
experiments, whereas quantum dots have as of now only been used in non-computing capacities,such as in LEDs, transistors, and solar cells.
Figure 9
A working ion trap information processor, developed at the National Institute of Standards and Technology.
From the trends and developments seen so far, ion trap technology appears to be more likely than
quantum dot technology to become the architecture that powers the future of consumer
computing.
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References
Akera, A., & Nebeker, F. (Eds.). (2002). From 0 to 1: An authoritative history of modern
computing. New York, NY: Oxford University Press.
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D-Wave Systems, Inc. (2011). Retrieved November 17, 2011 from:
http://www.dwavesys.com/en/dw_homepage.html
D-Wave Systems, Inc. (2011). [Untitled rendering of D-wave One Computer]. Retrieved
November 17, 2011 from: http://www.dwavesys.com/en/products-services.html
Feldman, Michael (May 26, 2011). D-Wave Sells First Quantum Computer. HPCWire.com.
Retrieved November 10, 2011 from http://www.hpcwire.com/hpcwire/2011-05-26/d-
wave_sells_first_quantum_computer.html
Knapp, Alex (November 4, 2011). Cheap Quantum Computing at Room Temperatures.
Forbes.com. Retrieved November 9, 2011, from
http://www.forbes.com/sites/alexknapp/2011/11/04/cheap-quantum-computing-at-room-
temperatures/
Kuhn, S. (Photographer). (2003). Lochkarte_Tanzorgel [Photograph]. Retrieved November 17,
2011 from:http://en.wikipedia.org/wiki/File:Lochkarte_Tanzorgel.jpg
Marquit, Miranda (May 12, 2009). Ion Trap Quantum Computing. PhysOrg.com. Retrieved
November 10, 2011, from http://www.physorg.com/news161348276.html
Monz, Thomas (March 31, 2011). 14-Qubit Entanglement: Creation and Coherence. Physical
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http://adsabs.harvard.edu/abs/2011PhRvL.106m0506M
Osaka University Vacuum Tube Computer [Photograph]. Retrieved November 17, 2011 from:
http://www.eng.osaka-u.ac.jp/en/research/gallery_02.html
Overton, Rick. (August 2007). Molecular Electronics Will Change Everything. Wired.com.
Retrieved November 20, 2011 from
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Oxford English Dictionary (2011). Retrieved November 17, 2011 from:
http://www.oed.com/view/Entry/37975?redirectedFrom=computer#eid
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Glossary
Algorithms - an effective method expressed as a finite list of well-defined instructions for
calculating a function.
Computational power - A term used to define the amount of information a computer canprocess in a given amount of time.
Electromagnetic Field - A physical field created by the moving of electrically charged objects.
Can also be thought of as a mixture of an Electric and Magnetic field.
Integrated circuit - an electronic circuit manufactured by the patterned diffusion of trace
elements into the surface of a thin substrate of semiconductor material. Additional materials are
deposited and patterned to form interconnections between semiconductor devices.
Ions - An atom or molecule in which the number of electrons does not equal the number of
protons, thus giving it a positive or negative charge.
Laser - Light Amplification by Stimulated Emission of Radiation. Basically light concentrated
to a specific frequency and wavelength. These properties allow it to interact with atoms on such
a small level that they can assist the process needed for Quantum studies.
Microprocessors - It is a multipurpose, programmable device that accepts digital data as input,
processes it according to instructions stored in its memory, and provides results as output
Silicon - A very common metal that conducts electricity. Has become the basis for all computers
today.
Silicon Carbide Crystals - Also known as carborundum. While it rarely occurs in nature, it has
been mass produced since 1893 for use in ceramics and other purposes, often as an abrasive.
Superconducting - A phenomenon of exactly zero electrical resistance occurring in certain
materials below a characteristic temperature.
Transistor - is a semiconductor device used to amplify and switch electronic signals and power
Transistor density - The overall amount of integrated circuits in a given space.
Vacuum-tube - a device that relies on the flow of electric current through a vacuum. Vacuumtubes may be used for rectification, amplification, switching, or similar processing or creation of
electrical signals. Vacuum tubes rely on thermionic emission of electrons from a hot filament or
cathode, that then travel through a vacuum toward the anode (commonly called the plate), which
is held at a positive voltage relative to the cathode.