Computers today work by converting information to a series of binary
digits, or bits, and operating on these bits using integrated circuits (ICs)
containing billions of transistors. Each bit has only two possible values,
0 or 1. Through manipulations of these so-called binary representations,
computers process text documents and spreadsheets, create amazing
visual worlds in games and movies, and provide the Web-based services
on which many have come to depend.
A quantum computer also represents information as a series of bits,
called quantum bits, or qubits. Like a normal bit, a qubit can be either 0
or 1, but unlike a normal bit, which can only be 0 or 1, a qubit can also
be in a state where it is both at the same time. When extended to systems
of many qubits, this ability to be in all possible binary states at the same
time gives rise to the potential computational power of quantum comput-
ing. However, the rules that govern quantum systems also make it dif-
ficult to take advantage of this power. How best to make use of quantum
properties—and the nature of the improvements these properties make
possible—is neither trivial nor obvious.
TYPES OF QUANTUM COMPUTERS
Adiabatic(aka annearler):aAdiabatic quantum
computers, a special case of quantum
annealers, use a result known as the adiabatic
theorem2 to perform calculations. They are
best suited for solving optimization problems,
which are ubiquitous across industries and
resources to solve by classical computing
methods. There are also opportunities to
apply adiabatic quantum computing methods
to sampling and machine learning problems.
Gate model(aka circuit model or standard model): Technically challenging to build
because they are extremely hardware specific,
gate model quantum computers perform
calculations by manipulating quantum states
via application of gates—a basic quantum
circuit operating on a number of individual
qubits. These quantum gates form building
blocks of quantum circuits in a manner similar
to how classical logic gates form the building
blocks of conventional digital circuits. When
quantum computers were first proposed, gate
model quantum computers were what was
envisioned.
Opportunity for quantum computing applications by industry
1.Financial services
Portfolio risk optimization and fraud detection: Quantum
computing shows promise in helping to determine attractive
portfolios given thousands of assets with interconnecting
dependencies. Additionally, quantum computing techniques
could be used to more effectively identify key fraud indicators.
2.Helthcare
Protein folding and drug discovery: Simulated annealing is
an algorithm currently used for the prediction of the effects
of potential therapeutic approaches while optimizing for
non-adverse effects. Quantum computing can replace some
of these techniques, and may be able to show improvements
at scale in the next few years such as advancing drug design
to the point of providing personalized prescription drugs for
individual patients.
3.Manufacturing
Supply chain and purchasing: Supply chain optimization
problems come in many different forms, such as
procurement, production and distribution. As quantum
computing improves, it will evolve from being able to solve
one-time scenarios like plan-o-grams or truck loads, to large
system-wide scenarios like store floor, regional distributions
and eventually global supply chains.
5.Media and Technology
Advertising scheduling and ad revenue maximization
systems are often tailored on a per-customer basis. These
systems collect hundreds of attributes about a consumer’s
preferences, which then need to be mapped to product
affinities and represented as a graph. Ultimately, the decision
on which ad to show a customer is an optimization of this
graph, a task that a quantum computer is well-suited to tackle.
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