How far is quantum computing from reality?

In summary, quantum computers are currently only capable of performing limited tasks, such as decryption. Building a full-scale quantum computer is still a long-term goal, but quantum technology can still be used in other forms, such as quantum cryptography and simulations. While there are challenges and limitations, the potential benefits in fields like physics and chemistry make it worth pursuing the development of quantum computers.
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When will quantum computers become useful? For example, cracking some real-world encryption, simulating quantum behaviour of molecules, or enhancing web search engines?
I somehow have the impression that this is a field of physics where theorists keep dreaming and experimentalists keep playing with toy systems.
 
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Is it possible to achieve realistic quantum computing by successively scaling up current systems and gaining experience along the way, or are we facing major hurdles and need a revolution in technology to do it?
 
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I wouldn't hold my breath. Currently quantum computers are hip, but fusion power or healing cancer or aids has also been hip some time ago. And we know how far that went.

Also, even if such machines existed, they would only really be useful for a very limited set of problems (decryption being one of them). The reason for this is the quantum "no cloning" theorem, which people tend to ignore when speaking about quantum computers. Most algorithms we know from computer science would be impossible to implement on a quantum computer.

There is one "quantum computing" paper which used the technique to calcualte a H2 molecule:
http://www.sciencemag.org/cgi/content/abstract/309/5741/1704
It was once described as the most expensive 2x2 matrix diagonalization in history :)
 
  • #4
A full scale quantum computer (QC) is still very far away (decades most likely) but quantum technology in a broader sense can be used much sooner than a full scale QC. For example, quantum cryptography, which is already working in commercial forms.

It's also the case that even though running a full useful quantum algorithm requires a lot more qubits then are currently possible (new recent record from innsbruck ion trap QC is 14 entangled qubits), it will be possible to use QC's much sooner in the form of quantum simulations. A recent paper for example described how the Dirac equation can be simulated with a reasonable amount of qubits.

It's also important to state that the reason so many are interested in building a QC is that there are actually very many problems in physics and chemistry that is and forever will be impossible to calculate without one. Good examples include calculations of complex molecules for producing medicines. Because it's the only way to ever simulate many things, it is worth putting money into the effort of building one, even if it's a long term goal. There is also a bonus you get along the way towards a QC, in the form of general understanding of a quantum phenomena. Very soon, if not already, even classical computers are going to contain components that are so small that they will require full understand of the quantum phenomena in order to function properly.
 
  • #5
petergreat said:
When will quantum computers become useful? For example, cracking some real-world encryption, simulating quantum behaviour of molecules, or enhancing web search engines?

Done and done, though admittedly there is plenty of scope to increase the complexity of the molecule.

http://www.msnbc.msn.com/id/35187725/ns/technology_and_science-innovation/

petergreat said:
I somehow have the impression that this is a field of physics where theorists keep dreaming and experimentalists keep playing with toy systems.

You may be suprised just how quickly "impossible" turns to "realisable" in experimental physics, particularly in a fast-moving field such as this :).

Claude.
 
  • #6
Claude Bile said:
Done and done, though admittedly there is plenty of scope to increase the complexity of the molecule.

http://www.msnbc.msn.com/id/35187725/ns/technology_and_science-innovation/

I will be impressed if someone manages to calculate the properties of a molecule to the same precision but with a lower cost than using classical computers, or simulate a molecule that is simply intractable by classical computers. As far as I'm aware of, neither of above was the case regarding the experiment you quoted. So that doesn't satisfy my definition of being "useful". Though I don't deny the possibility that the technology may improve in future.
 

1. How does quantum computing differ from classical computing?

Quantum computing utilizes the principles of quantum mechanics to process and store information, while classical computing uses classical physics. This allows quantum computers to perform complex calculations at a much faster rate.

2. What makes quantum computing difficult to achieve?

The main challenge in developing quantum computers is maintaining the delicate quantum states of information, known as qubits. These qubits are highly sensitive to external disturbances, making it difficult to control and manipulate them.

3. Is quantum computing currently being used in practical applications?

While there have been some demonstrations of quantum computing's potential, it is still in its early stages and not yet being used in practical applications. However, many researchers and companies are actively working towards developing quantum computers for practical use.

4. How far away are we from achieving quantum computing?

It is difficult to predict an exact timeline, but many experts believe that we are still several years away from achieving fully functional quantum computers. However, there have been significant advancements in recent years, and the technology is rapidly progressing.

5. What are the potential benefits of quantum computing?

Quantum computing has the potential to greatly accelerate the speed and efficiency of solving complex problems in various fields, such as cryptography, drug discovery, and financial modeling. It could also lead to the development of new technologies and advancements in fields like artificial intelligence and machine learning.

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