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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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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.


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.

BGS. (June 2007). Retrieved November 07, 2011 from:http://www.bgs.ac.uk/mineralsuk/commodity/world/home.html

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

Review Letters (American Physical Society). Retrieved November 9, 2011, from

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

http://www.wired.com/wired/archive/8.07/moletronics_pr.html

Oxford English Dictionary (2011). Retrieved November 17, 2011 from:

http://www.oed.com/view/Entry/37975?redirectedFrom=computer#eid
http://en.wikipedia.org/wiki/File:Lochkarte_Tanzorgel.jpghttp://en.wikipedia.org/wiki/File:Lochkarte_Tanzorgel.jpghttp://en.wikipedia.org/wiki/File:Lochkarte_Tanzorgel.jpghttp://www.oed.com/view/Entry/37975?redirectedFrom=computer#eidhttp://www.oed.com/view/Entry/37975?redirectedFrom=computer#eidhttp://www.oed.com/view/Entry/37975?redirectedFrom=computer#eidhttp://en.wikipedia.org/wiki/File:Lochkarte_Tanzorgel.jpg


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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.

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