# Quantum Computing: A glimpse

From the start of computing history, the power of our CPU’s is growing exponentially. Henceforth allowing the computer systems to be smaller and more powerful, but this joy ride is about to come to an end. To understand why, first we need to understand the greatest prediction of the 20th century which held on for more than 50 years. Yes, I am talking about the Moore Law, which is named after the Gordon Moore cofounder of Fairchild Semiconductors and CEO of the Intel.
According to his observations in 1965, he postulated that

The number of transistors in a dense integrated circuit, double about every two years, though the cost of the system is halved.

Gordon Moore

However today the doubling of installed transistors on silicon chips occurs close to every 18 months. The Moore law holds greatly for nearly more than 50 years.

. . . . . BUT . . . . .

This doubling of transistors comes with some physical limits and the computers or the CPUs, to be more precise will reach that point of limit at around 2020.

#### These physical limits will be

• HIGH TEMPERATURE:

The high temperature of transistors will make it impossible to create smaller circuits. This is because cooling down the transistors takes more energy than the amount of energy that already passe through the transistors.

• SMALL SIZE OF TRANSISTORS:

Lets first understand what a transistor is, and how does it work.

Transistors are tiny switches that can be triggered by electric signals. They are the basic building blocks of microchips. A traditional mechanical switch either enables or disables the flow of electricity by physically connecting (or disconnecting) two ends of the wire.

In a transistor, a signal tells the device to either conduct or insulate, thereby enabling or disabling the flow of electricity. Hence providing us with the 0’s or the 1’s which are the basis of Computers.

Currently, the smallest transistor is of 1nano meter in size and a typical transistor size around 14 NanoMeter. To understand the Prefix “Nano” means one-billionth or 10−9 . Hence one nanometer is one-billionth of a meter.

To help you imagine how small it is, a sheet of paper is 100,000 nm thick. Even a strand of our DNA is 2.5nm in diameter. Hence with the transistors getting smaller day by day, Quantum Physics is making things tricky.

Today a typical transistor scale is 14 nm which is 8 times smaller than the HIV virus scaling at 120 nm and 500 times smaller than an RBC (Red Blood Cell). Now with the transistors shrinking to the size of few atoms, electrons can transfer themselves to another side of blocked passage by the QUANTUM TUNNELING.

Quantum tunneling or tunneling is the quantum mechanical phenomenon where a subatomic particle passes through a potential barrier. Quantum tunneling is not predicted by the laws of classical mechanics where surmounting a potential barrier requires enough potential energy. “
In the quantum realm, physics works quite differently and in an unpredictable way hence traditional computing doesn’t make any sense.
Hence mankind reaching a real physical barrier for technological progress.

To avoid this the scientists are trying to use these quantum properties to their advantages by building quantum computers.

#### SO WHAT IS QUANTUM COMPUTING?

Today’s computing is limited to having a single value of either 0 or 1 for each bit, quantum computing uses quantum bits (qubits) that are simultaneously in both states (0 and 1) at the same time. This phenomenon is called as the SUPERPOSITION.
The consequence of this superposition is that quantum computers are able to test every solution to a problem at once. Further, because of this exponential relationship, such computers should be able to double their quantum computing power with each additional qubit.

The question arise is What are these QuBits?

QuBits 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, these two are aspects of Quantum Mechanics used by the quantum computers.

What is superposition?

Qubits can represent numerous possible combinations of 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” to either or 0

What is entanglement?

Researchers can generate pairs of qubits that are “entangled,” 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. It even baffled Einstein, who famously described it as “spooky action at a distance.” But it’s key 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 to work their magic. The machines’ ability to speed up calculations using specially designed quantum algorithms is why there’s so much buzz about their potential.

That’s the good news. The bad news is that quantum machines are way more error-prone than classical computers because of decoherence.

What is 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 will sap a lot of a quantum computer’s computational capacity.

And there’s the rub: so far, researchers haven’t been able to generate more than 128 standard qubits (see our qubit counter here). So we’re still many years away from getting quantum computers that will be broadly useful.

That hasn’t dented pioneers’ hopes of being the first to demonstrate “quantum supremacy.”

What is quantum supremacy?

It’s 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.

### Qubit Control

Computer scientists control the microscopic particles that act as qubits in quantum computers by using control devices.

• Ion traps use optical or magnetic fields (or a combination of both) to trap ions.
• Optical traps use light waves to trap and control particles.
• Quantum dots are made of semiconductor material and are used to contain and manipulate electrons.
• Semiconductor impurities contain electrons by using “unwanted” atoms found in semiconductor material.
• Superconducting circuits allow electrons to flow with almost no resistance at very low temperatures.

### Types of Quantum Computers and Their Applications

There are three types of quantum computers that are considered to be possible by IBM. Shown in the above infographic, they range from a quantum annealer to a universal quantum.

The quantum annealer has been successfully developed by D-Wave, but it is difficult to tell whether it actually has any real “quantumness” thus far. Google added credibility to this notion in December 2015, when it revealed tests showing that its D-Wave quantum computer was 3,600 times faster than a supercomputer at solving specific, complex problems.

The holy grail of quantum computing is the universal quantum, which could allow for exponentially faster calculations with more generality.

However, building such a device ends up posing a number of important technical challenges. Quantum particles turn out to be quite fickle, and the smallest interference from light or sound can create errors in the computing process.

Doing calculations at exponential speeds is not very useful when those calculations are incorrect.

### Usages of Quantum Computers

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 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 the machines could be used to accelerate artificial intelligence.

The field which will be greatly benefitted from the Quantum computers is the field of Artificial Intelligence. With the help of Quantum Computation, we can solve problems that were considered forever unsolvable using Classical Computers. This class of problems is called NP-Complete Problem.

Still the dream of building a Universal Quantum Computer is at the horizon, even with all the technology giants trying their best.

Who are we to be considered as humans, so fragile so insecure yet so stubborn to unravel the profound knowledge of everything around us which might be beyond the might of lifetimes.

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