What are the challenges of quantum computing?

There are several challenges in building a large-scale quantum computer – fabrication, verification, and architecture. The power of quantum computing comes from the ability to store a complex state in a single bit. This also what makes quantum systems difficult to build, verify, and design.

Which property of quantum systems allow for more efficient computation?

Quantum computing exploits the coherence and superposition properties of quantum systems to explore many possible computational paths in parallel. This provides a fundamentally more efficient route to solving some types of computational problems, including several of relevance to biological simulations.

Does quantum computing provide the promise of solving all the NP complete problems explain why or why not?

Contrary to myth, quantum computers are not known to be able to solve efficiently the very hard class called NP-complete problems.

How does a quantum computing algorithm work?

Quantum algorithms are usually described, in the commonly used circuit model of quantum computation, by a quantum circuit which acts on some input qubits and terminates with a measurement. The number of qubits has to be fixed because a changing number of qubits implies non-unitary evolution.

Why are quantum computers difficult?

Quantum computers are exceedingly difficult to engineer, build and program. As a result, they are crippled by errors in the form of noise, faults and loss of quantum coherence, which is crucial to their operation and yet falls apart before any nontrivial program has a chance to run to completion.

Are quantum computers reliable?

Hence, an arbitrarily long quantum computation can be performed reliably, provided that the average probability of error per quantum gate is less than a certain critical value, the accuracy threshold….Reliable Quantum Computers.

Can quantum computers do NP problems?

Quantum computers can solve NP-hard problems that classical computers are unable to solve. Currently, the two most important and notable complexity classes are “P” and “NP.” P represents problems that can be solved in polynomial time by a classical computer.

What does it mean for a problem to be in NP?

nondeterministic polynomial time
A problem is assigned to the NP (nondeterministic polynomial time) class if it is solvable in polynomial time by a nondeterministic Turing machine. A P-problem (whose solution time is bounded by a polynomial) is always also NP.

Are quantum computers really faster than conventional computers?

Sign up for Scientific American ’s free newsletters. Popular accounts often imply that quantum computers, because superposition and entanglement allow them to carry out multiple computations at the same time, are simply faster versions of conventional computers. Those accounts are misleading, Aaronson says.

How many possible solutions can a quantum computer have?

As we saw earlier, there were 8 possible solutions to this problem: With a regular computer, using 3 bits, we were able to represent only one of these solutions at a time — for example, 001. However, with a quantum computer, using 3 qubits, we can represent all 8 of these solutions at the same time.

Are quantum computers ready for the market?

By the time quantum computers are ready for the marketplace, they might lose potential customers—if, for example, classical computers become powerful enough to simulate the quantum systems that chemists and materials scientists “actually care about in real life,” Aaronson says.

How does a quantum computer store information?

A quantum computer does not use bits to store information. Instead, it uses something called qubits. Each qubit can not only be set to 1 or 0, but it can also be set to 1 and 0. But what does that mean exactly? Let me explain this with a simple example. This is going to be a somewhat artificial example.