Theory

Quantum computing is based on a new type of computer that gets it's processing power from quantum effects. A normal computer is based on the model of a Universal Turing Machine. Richard P. Feynman once made an offhand remark that Turing machines, which are really supposed to be able to model everything that is an algorithm, ie. everything that can be modeled, can't seem to model quantum behavior decently, because they need a exponential amount of memory to do any calculation. (For instance, if you have a system with 5 quantum bits, and there are 4 interactions, you must use 5^5^5^5 bits in memory, = 7.18 * 10436.) This was clearly unpractical, and he suggested that if you based a computer on quantum effects, it is possible that then you could model these effects better.

Of course, hypothesizing a new type of computer and working out a realistic theory of it's operation are two completely separate things, and it took several years before the theoreticians had models for what quantum computing should look like. There were 2 main models, which have been shown to be equivalent, so that any problem solvable in one system is solvable on the other. Basically this means that any programs written on one machine are able to be written on the other, though actually porting them is not necessarily so trivial. The two types of logical quantum machines are implementable on the same quantum hardware. In addition to this, It has been shown that the set of operations that quantum computer can do includes the set of operation that any Turing machine can do. This means that any stardard computer function, and possibly more, can be done. It is clear that non-computable (ie. Non-algorithmic) computations cannot be done, but speed increases (in terms of theoretical maximum efficiency) seem very likely in a number of very practical areas.

Engineering

Several working models of very small scale quantum computers currently exist. Most of these, including the largest, a tiny 7-qubit machine owned by IBM, are based on the principle of Nuclear Magnetic Resonance. This is basically the method used to write data into the qubits. Its effective limit, however, as far as anyone can tell, is around 15 qubits, which is significantly smaller than would be truly useful for most applications.

Other types of Quantum computers are smaller, but have much higher theoretical limits to size. Several 3 and 4 qubit computers, owned by universities and research departments, are based on these models. There is a hope than at least one of these models will be able to be scaled up far enough to become practical.

Among the other types of quantum computers in the works, there are several that rely on complex chemical structures to bind (in one case) seven qbits as a unit, so that they can be manipulated en-masse. These would allow much larger quantum computers, using existing techniques for manipulating 3 and 4 qbit machines (such as linear ion arrays,) to produce machines 20 and 30 qbits large, a giant leap that could enable quantum computers to do the first practical work.

The biggest single practical obstacle in quantum computing, however, increases with size. When a quantum system is observed, the problem of decoherence interferes, literally. Quantum states rely on interference between particles in the system. This, however, is also an immense downside, because particles are not choosy about what they interfere with. After a time, the system interferes with the environment around it, and the system becomes incoherent, because the particles that you want to read are attached, via interference, with particles that are not part of the system. The Qbits that have interfered are now incorrect. This, however, has been shown to be correctable, but Quantum error correction algorithms, which must be vastly improved before large scale error correction can be made practical for partially observed quantum systems.

Possible Downside

Quantum Computers, however, are only disputably worthwhile. Many Computer Science theorists believe that while in limited cases the quantum computers will offer appreciable gains on classical turing machines, in most cases the gain will be limited to, at most, polynomial time, and in that case, quantum computers would have to reach the level of complexity and speed at least approaching that of classical computers, (gigahertz ranges) to be useful. However, other argue that since certain applications (factoring especially) allow a exponential decrease in algorithm time, it is useful. In addition, many avenues have only begun to be explored, and may prove to be the most useful aspects of all. Quantum communication seems to be a very interesting, if young field, as does quantum dense coding (which includes lossless image compression , and data transmissions with errors eliminated to arbitrary accuracy.) It is also very possible that certain classes of NP complete problems are either equivalent to the already investigated factoring problem, or are similarly much easier when working with quantum computation. In this case, it is immensely practical to develop these quantum computers.

In all, quantum computing is a field that is essentially still in formation. It is unclear whether it will be possible to build larger scale computers in the near future, of the size that will endanger RSA encryption. Whether it is or not, companies like HP and IBM, to forestall competition, as well as universities like MIT and Caltech, to forstall graduate students, will continue to do research into this exciting field.

Hardy, Yorick. Steeb, Willi Hans. "Introduction" Classical and Quantum Computing: With C++ and Java Simulations. Pg. ii-xxv.
Vazirani, Umesh. "Introduction to Special Section on Quantum Computation" SIAM Journal on Computing, Volume 26, Number 5, pg. 1409-1410. Nielsen, Michael A. "Rules for a Complex Quantum World" Scientific American, November 2002.
Bennett, Charles H. Bernstein, Ethan. Brassard, Gilles. and Vazirani, Umesh. "Strengths And Weaknesses of Quantum Computing" SIAM Journal on Computing Volume 26, Number 5 pg. 1410-1423.
Fortnow, Lance. "One complexity theorist's view of quantum computing" Theoretical Computer Science, Volume 292, Issue 3, Pg. 597-610.

I am considering
the quantum computer
because of an unread book
which is squashed

between two others
above me on the shelf
beside this old couch
I find myself quietly lying on

while the world spins
all around me.
There is a child
in the next room

with a hole but no door
to dampen the between of us.
It is late and he should
be off to bed

but despite the distraction
he causes by watching a film
while wearing headphones
and commentating

none the less throughout
I cannot raise myself
(in either sense)
to send him up

and into the darkness.
His mother
is already above us
tucked into a different bed

but also watching
a production originally designed
to be broadcast on television
but mostly consumed

in vast sessions
while supine
with laptop.
Which brings us

to quantum computers
and the necessary circle
of some connected sense.
The book is called

'A Short Cut In Time'
which seems to suggest
some chance of dodging
the dull bits of an evening

but would we really do so
if we could?
It might be a short life
and who would choose

or opt for that?
The fact of it
and it's a pleasing one
is that if we had the choice

of skimming the slow bits
the boring or annoying bits
the arguments or hunger
frustration and uncertainty

but then realized
if we did so
that what time remained
would go by too fast

we might instead resolve
to make all the moments
either have some value
or at least be observed

and appreciated
for their finer points.
I'm almost sure
Mister George Johnson

the book in question's author
explains just this
and it is a valuable
and pertinent thought

and one now I think of it
I need waste none
of this all too brief life
I am living by reading further.

 

 

{for FS - or at least with him in mind}

This girl, or that girl?
This career, or that career?
This book, or that book?
This shirt, or that shirt?

Do I solve the problem this way, or that way?
Do I design a circuit this way, or that way?

The blank canvas.
Where do I begin?
A light pencil sketch?
Rough out the composition?
Balance, form, symmetry, light and dark?
The first stroke causes misgivings.
I should have started there, rather than here.
It's best to suspend decision.

Mao said that
The march of ten thousand miles
Begins with the first step.
The converse is also true.
The first step
Leads to a march of ten thousand miles.

The horror of the blank canvas.
Too many possibilities.
The infinitude of possible passages,
A Borgesque labyrinth of paths,
Branches begetting branches,
As in quantum mechanics.
The Problem of Infinities.

The pencil hovers over the paper,
Reluctant to start.
Because starting begins the clock.
T = 0.
Cleaving time.
Before zero, and after zero.
Causing a beginning.
The first breath is the dual of the last breath.
The fear of starting the machinery.

Well. Here we go.
Now we've started, we've nowhere to go but forward,
To the inevitable heat death of the universe.
To completion.
Perhaps not completion, but the end.

Beginnings presuppose endings.
Endings aren't guaranteed to be clean.
There is no guarantee of completion.
There is no guarantee of a pretty, well-formed symmetric story.
The artist cannot be guaranteed to finish,
And to stand back and behold his work
And declare it good.

Thus the hover.
Thus the indecision.
The myriad ways this thing could go.
The tension just before the beginning.

Not yes. Not no.
Not this, nor that.
Both.
Together.
An undifferentiated, unbinaried wholeness of possibilities.
An AND, not an OR.
An uncollapsed wavefunction,
Entangled, all states equiprobable.

The truest poem
Is the one unfin




For friend D.W., muse, friend, inspiration.

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