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, a Canadian firm.
Chinese firms like Alibaba are also offering access to quantum machines.
Some businesses are buying quantum computers, while others are using ones made available through cloud computing services.
Where is a quantum computer likely to be most useful first?.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 the machines could be used to accelerate artificial intelligence.
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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.
But if these exotic new computing machines live up to their promise, they could transform entire industries and turbocharge global innovation.
Keep up with the latest in AI chips at EmTech Digital.
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