Quantum computers are a term which has been
gaining popularity recently especially with
a large amount of revenue dedicated to its
research each year.
While the general populous is aware of the
fact that research is being done in this field
but not many are truly aware of the complexities
and working principles behind it.
This article aims to provide a basic overview
of the principals involved, issues faced,
and solutions to tackle them.
Basically, Quantum computing is the use of
quantum-mechanical phenomena such as superposition
and entanglement to perform computation.
The field of quantum computing is actually
a sub-field of quantum information science,
which includes quantum cryptography and quantum
communication.
Quantum Computing was started in the early
1980s when Richard Feynman and Yuri Manin
expressed the idea that a quantum computer
had the potential to simulate things that
a classical computer could not.
In 1994, Peter Shor published an algorithm
that is able to efficiently solve some problems
that are used in asymmetric cryptography that
are considered hard for classical computers.
There are currently two main approaches to
physically implementing a quantum computer:
analog and digital.
Analog approaches are further divided into
quantum simulation, quantum annealing, and
adiabatic quantum computation.
Digital quantum computers use quantum logic
gates to do computation.
Both approaches use quantum bits or qubits.
Qubits are fundamental to quantum computing
and are somewhat analogous to bits in a classical
computer.
Qubits can be in a 1 or 0 quantum state.
But they can also be in a superposition of
the 1 and 0 states.
However, when qubits are measured the result
is always either a 0 or a 1; the probabilities
of the two outcomes depends on the quantum
state they were in.
Today’s physical quantum computers are very
noisy and quantum error correction is a burgeoning
field of research.
Unfortunately, existing hardware is so noisy
that fault-tolerant quantum computing is still
a rather distant dream.
As of April 2019, no large scalable quantum
hardware has been demonstrated, nor have commercially
useful algorithms been published for today’s
small, noisy quantum computers.
There is an increasing amount of investment
in quantum computing by governments, established
companies, and start-ups.
Both applications of near-term intermediate-scale
device and the demonstration of quantum supremacy
are actively pursued in academic and industrial
research.
A quantum computer harnesses some of the almost-mystical
phenomena of quantum mechanics to deliver
huge leaps forward in processing power.
Quantum machines promise to outstrip even
the most capable of today’s — and tomorrow’s
— supercomputers.
They won’t wipe out conventional computers,
though.
Using a classical machine will still be the
easiest and most economical solution for tackling
most problems.
But quantum computers promise to power exciting
advances in various fields, from materials
science to pharmaceuticals research.
Companies are already experimenting with them
to develop things like lighter and more powerful
batteries for electric cars, and to help create
novel drugs.
Qubits
Today’s computers use bits — a stream
of electrical or optical pulses representing
1s or 0s.
Everything from your music, games, videos,
etc., are essentially long strings of these
binary digits.
Quantum computers, on the other hand, use
qubits, which are typically subatomic particles
such as electrons or photons.
Generating and managing qubits is a scientific
and engineering challenge.
Some companies, such as IBM, Google, and Rigetti
Computing, use superconducting circuits cooled
to temperatures colder than deep space.
Others, like IonQ, trap individual atoms in
electromagnetic fields on a silicon chip in
ultra-high-vacuum chambers.
In both cases, the goal is to isolate the
qubits in a controlled quantum state.
Qubits have some quirky quantum properties
that mean a connected group of them can provide
way more processing power than the same number
of binary bits.
One of those properties is known as superposition
and another is called entanglement.
Qubit Superposition
Qubits can represent numerous possible combinations
of 1 and 0 at the same time.
This ability to simultaneously be in multiple
states is called superposition.
To put qubits into superposition, researchers
manipulate them using precision lasers or
microwave beams.
Thanks to this counterintuitive phenomenon,
a quantum computer with several qubits in
superposition can crunch through a vast number
of potential outcomes simultaneously.
The final result of a calculation emerges
only once the qubits are measured, which immediately
causes their quantum state to collapse and
revert to either 1 or 0.
Qubit Entanglement
Researchers can generate pairs of qubits with
quantum entanglement which means the two members
of a pair exist in a single quantum state.
Changing the state of one of the qubits will
instantaneously change the state of the other
one in a predictable way.
This happens even if they are separated by
very long distances.
Nobody really knows quite how or why entanglement
works.
This phenomenon also baffled Einstein, who
famously described it as “spooky action
at a distance.”
But this is inherently necessary to the power
of quantum computers.
In a conventional computer, doubling the number
of bits doubles its processing power.
But thanks to entanglement, adding extra qubits
to a quantum machine produces an exponential
increase in its number-crunching ability.
Quantum computers harness entangled qubits
in a kind of quantum daisy chain in order
to perform computational tasks.
The machines ability to speed up calculations
using specially designed quantum algorithms
is key to unlocking its potential.
While the advantages of a quantum computers
are clear to see, however, the bad news is
that quantum machines are way more error-prone
than classical computers because of decoherence.
Decoherence
The interaction of qubits with their environment
in ways that cause their quantum behavior
to decay and ultimately disappear is called
decoherence.
Their quantum state is extremely fragile.
The slightest vibration or change in temperature
— disturbances known as “noise” in quantum-speak
— can cause them to tumble out of superposition
before their job has been properly done.
That’s why researchers do their best to
protect qubits from the outside world in those
supercooled fridges and vacuum chambers.
But despite their efforts, noise still causes
lots of errors to creep into calculations.
Smart quantum algorithms can compensate for
some of these, and adding more qubits also
helps.
However, it will likely take thousands of
standard qubits to create a single, highly
reliable one, known as a logical qubit.
This, in turn, drains a lot of a quantum computer’s
computational capacity.
And so far, researchers haven’t been able
to generate more than 128 standard logical
qubits which is far from the amount necessary
to perform and complex tasks.
So, we’re still many years away from getting
quantum computers that will be broadly useful.
Quantum supremacy
Despite the drawbacks of decoherence, the
aim of all companies and researchers working
on quantum computers is to achieve quantum
supremacy.
This is the point at which a quantum computer
can complete a mathematical calculation that
is demonstrably beyond the reach of even the
most powerful supercomputer.
It’s still unclear exactly how many qubits
will be needed to achieve this because researchers
keep finding new algorithms to boost the performance
of classical machines, and supercomputing
hardware keeps getting better.
But researchers and companies are working
hard to claim the title, running tests against
some of the world’s most powerful supercomputers.
There’s plenty of debate in the research
world about just how significant achieving
this milestone will be.
Rather than wait for supremacy to be declared,
companies are already starting to experiment
with quantum computers made by companies like
IBM, Rigetti, and D-Wave, Alibaba, etc.
Some businesses are even buying current large
and bulky quantum computers, while most others
are using ones made available through cloud
computing services.
Current uses of quantum computing
One of the most promising applications of
quantum computers is for simulating the behavior
of matter down to the molecular level.
Auto manufacturers like Volkswagen and Daimler
are using quantum computers to simulate the
chemical composition of electrical-vehicle
batteries to help find new ways to improve
their performance.
And pharmaceutical companies are leveraging
them to analyze and compare compounds that
could lead to the creation of new drugs.
The machines are also great for optimization
problems because they can crunch through vast
numbers of potential solutions extremely fast.
Airbus, for instance, is using them to help
calculate the most fuel-efficient ascent and
descent paths for aircraft.
And Volkswagen has unveiled a service that
calculates the optimal routes for buses and
taxis in cities in order to minimize congestion.
Some researchers also think that quantum computers
could be used to accelerate developments in
artificial intelligence.
It could take quite a few years for quantum
computers to achieve their full potential.
Universities and businesses working on them
are facing a shortage of skilled researchers
in the field — and a lack of suppliers of
some key components.
However, recent promising developments such
as nanofridges could provide potential cooling
solutions to the quantum circuits and possibly
reduce decoherence.
But any real-world applications of this, for
potential consumer grade quantum computers,
is still 10 to 15 years away at least.
If these exotic new computing machines live
up to their promise and expectations, they
could usher in an age of innovation and possibly
change entire industries.
