- Quantum computing is a new way of processing information.
It's quite different when compared
with how computers work today.
To really grasp the nature of quantum,
it's valuable to understand just how significant
the difference is.
To achieve this, let's look at how today's computing,
something we call classical or binary computing,
works at a very basic level.
At the heart of today's computing
is the essential role of electricity.
Electricity is energy and is powered by electrons.
Tiny particles that orbit around atoms.
Electrons can remain tied to a particular atom,
which we call static electricity,
or they can be made to move from atom to atom
which is called current electricity.
Electrons need material called conductors to move.
Materials that stop electrons flowing
are called insulators.
An ability to both conduct and be an insulator
under certain conditions is
a property called semi-conducting.
Silicone, for example, is a semi conductor.
Let's look at a familiar example of current electricity.
To turn a light on, electricity must flow
through conducting material from a switch to a bulb.
Copper wire is an excellent conductor.
When the switch is on electrons flow
and power the light bulb.
When the circuit, the name for the system, is broken,
that is the switch is in the off position,
no electrons flow and the light bulb powers off.
This concept of a switch which enables or disables
the flow of electricity is almost everything
you need to know to understand
how classical computing works.
In computing, we call these switches transistors.
Let's explore this further.
A switch that is on or off represents just two states.
This is called binary.
Let's say that a switch that is on is a one
and an off switch is a zero.
By controlling the flow of electricity
between on and off, we can get a series of ones and zeros.
These are called binary bits.
A unique series of these ones and zeros
can each equate to say, the letters of the alphabet.
For example, the computer science community agreed,
a long time ago, that the following series of bits,
01000111 is the letter G.
A single switch is interesting itself
but when we combine switches,
we can begin to do cool things like mathematics.
This is achieved because with at least two switches
there are multiple combinations
that can instruct electricity to flow in certain directions.
For example, if both switches are open,
we can direct electricity flow in a specific direction.
If one is closed and the other is open,
we can direct it elsewhere.
By defining these conditions, called logic gates,
we achieve a variety of outputs.
If we combine many switches together,
hundreds, thousands, or more,
the binary output communicates complex instructions.
Today high end microchips contain billions
of transistors, yes, billions.
Take a look at one of those coins
that I asked you to have on hand during the introduction.
That's roughly the size of a microchip.
And some chips are much smaller than this one.
Those billions of transistors must be tiny.
Innovation over the past few decades
has enabled us to further miniaturize the technology,
enabling more and more transistors
on the same small microchip real estate.
These transistors equate to faster processors.
Basically this results in more instructions
being processed in less time.
What is striking about this architecture
is that it's fundamental construction is simple.
Each discreet transaction is just one of two states.
A one, or a zero, but this has enabled
the most powerful machines humans have ever created.
Our coins are a good metaphor for binary states.
Place your two coins on the table.
Even though there are two sides to each,
we can only read one side from both of them.
Today's computing handles this well.
In coin parlance, a bit can only be a heads
or tales at any given moment.
We've had a good run with miniaturization.
After all the processing capability today
in our small smartphones is remarkable.
There are enough transistors in them
to provide for a long period of usefulness.
With really complex scientific problems,
we use much larger computers
because they need many more processors.
Big, wicked calculations can take hours,
and sometimes days to compute,
even with the best of today's computing capabilities.
We are gradually approaching
at least two limiting dimensions.
First, we are closing in on the physical constraints
of how small a transistor can be and still function
and secondly the next era of processing needs
for a wide range of human aspirations
will take far too long using current computing technology.
To solve these challenges, we're going to need
a new computing paradigm.
Quantum may hold the answer.