Quantum Computing is NOT hard. (2024)

FAQs

What is the biggest problem with quantum computing? ›

Compared with standard computers, quantum computers are extremely susceptible to noise. The quantum state of qubits is extremely fragile and any disturbance, such as a slight vibration or a change in temperature, can uncontrollably affect the computer, causing information stored to be lost.

The abrupt shutdown of NASA's quantum computing project was triggered by an unforeseen incident during a routine test. During the analysis of a complex simulation, the quantum computer demonstrated unprecedented computational power, solving a previously intractable problem.

Building quantum computers is incredibly difficult. Many candidate qubit systems exist on the scale of single atoms, and the physicists, engineers, and materials scientists who are trying to execute quantum operations on these systems constantly deal with two competing requirements.

Unfortunately, the technology of quantum computing isn't fully operational yet. One major challenge lies in translating quantum algorithms from abstract mathematical concepts into concrete code that can run on a quantum computer.

The delicate nature of quantum systems makes them extremely vulnerable to the slightest disturbance, whether that's a stray photon created by heat, a random signal from the surrounding electronics, or a physical vibration. This noise wreaks havoc, generating errors or even stopping a quantum computation in its tracks.

The current field of quantum computers isn't quite ready for prime time: McKinsey has estimated that 5,000 quantum computers will be operational by 2030 but that the hardware and software necessary for handling the most complex problems won't be available until 2035 or later.

Google said the quantum system offered a combination of fewer errors and better performance than its previous systems. But the company also found out that it had to sacrifice a lot of quantum performance in order to bring stability to the system. Google's Sycamore quantum computer. Rocco Ceselin/Google.

In 1994, American mathematician Peter Shor developed quantum algorithms to factor integers and solve the discrete logarithm problem. When run on a big enough quantum computer, these algorithms will be able to crack all the public key crypto systems we rely on today for privacy.

Quantum specialists have yet to achieve anything truly useful that could not be done using classical computers.

Qubits (or anything from the quantum realm) are extremely small, so even the smallest perturbation or vibration can cause them to behave chaotically. Not to mention that in a large system with many qubits, such as a quantum computer, there are bound to be a few errors in the state of the qubits.

Why is quantum difficult? ›

The probabilistic nature of quantum mechanics thus stems from the act of measurement. This is one of the most difficult aspects of quantum systems to understand.

Self-learning quantum computing is not simple, but it is possible. What helps learning is that there is no need to understand the details because it is difficult to understand.

Quantum computers are being manufactured and used. But they cannot yet make the large-scale calculations that are expected to be possible in the future.

Can You Buy a Quantum Computer? Yes, it's possible to buy a quantum computer in 2023. However, quantum computers are not yet widely available to the general public and are currently very expensive and extremely difficult to manufacture.

NASA's QuAIL team has extensive and experience utilizing near-term quantum computing hardware to evaluate the potential impact of quantum computing.

Standard quantum mechanics accounts for what happens when you measure a quantum system: essentially, the measurement causes the system's multiple possible states to randomly “collapse” into one definite state. But this accounting doesn't define what constitutes a measurement—hence, the measurement problem.

What is a current concern regarding the advancement of quantum computing? Existing cryptography may be easily cracked. Computers will replace humans in all decision - making tasks. Algorithmic trading may cause stock market instability.