Quantum Computing

What is Quantum Computing?

Quantum computing is an area of research and development that focuses on how to use the unique properties of quantum mechanics to perform mathematical calculations faster and solve computational problems more efficiently than is currently possible with classical computers that use Boolean logic.

Quantum mechanics (also called quantum physics) is an area of research and development that seeks to provide a mathematical framework for explaining a wide range of unique phenomena that only occurs at the atomic and subatomic level.

How Quantum Computing Works

Quantum computers are faster than classical computers because they perform calculations in a fundamentally different way.

Classical computers perform mathematical operations by using step-by-step procedures called algorithms to manipulate binary bits represented by 0s or 1s. The results are deterministic, which means that given the same initial conditions, the same step-by-step procedures will always produce the same outcome.

In contrast, quantum computers perform mathematical operations by using algorithms to manipulate quantum bits (qubits). Qubits are also represented by 0s and 1s, but they can exist in a superposition of both states simultaneously. Given the same initial conditions, the same quantum algorithm will produce a probability distribution for the relative likelihoods of all possible outcomes instead of a single, deterministic value.

To resolve the probability distribution and determine a single value, a mathematical function called a “wave function” captures information about all the possible states the system can be in — and all the probabilities associated with each state. Repeated interactions with the system will cause the wave function to collapse and produce one specific outcome.

Schrödinger’s Cat

Schrödinger’s Cat is a famous thought experiment in quantum mechanics that illustrates the concept of superposition and wave function collapse. The thought experiment was proposed by the Austrian physicist Erwin Schrödinger in 1935 to explain the unique properties of quantum physics.

The experiment asks the participant to imagine that a cat has been placed inside a sealed box along with a vial of poison and a radioactive atom that may (or may not) decay.

If the radioactive atom decays, it will trigger the release of the poison and kill the cat. If the radioactive atom does not decay, the vial of poison will remain intact, and the cat will live.

According to the rules of quantum mechanics, the entire system – including the cat and the atom – can be described by a single wave function that represents all the various possible outcomes of the experiment.

In the context of this thought experiment, the wave function describes a superposition of two states: one state where the atom has decayed, released the poison, and killed the cat — and one state where the atom has not decayed, the poison vial has stayed intact, and the cat is alive.

Schrödinger explained that as long as the box remains closed, the cat will remain in a superposition of two states because the quantum state of the cat is entangled with the quantum state of the atom.

Once someone opens the box and observes the system, however, the wave function will collapse, and the probability distribution will resolve to one specific result that is calculated by using all the probabilities from its superposition state. When that happens, the cat will either be alive if it’s more likely the atom didn’t decay – or dead if it’s more likely the atom decayed.

Schrödinger’s thought experiment is often used to introduce people to the ideas that (1) Quantum systems can exist in multiple states simultaneously until an outside observation (also called a measurement) causes the wave function to collapse and (2) Measurements in the quantum world are inherently probabilistic.

Decoherence and the High Cost of Quantum Computing

Quantum computing is still extremely expensive and error-prone because when a quantum system interacts with its external environment, any type of entanglement can mimic the way a wave function collapses and make the quantum system behave more like a classical system. This phenomenon is known as decoherence.

To mitigate decoherence and ensure qubits can exist in multiple states simultaneously, quantum computing systems require highly-controlled and isolated environments that shield qubits from external disturbances such as temperature fluctuations and electromagnetic interference.

It requires sophisticated cryogenic systems that can cool qubits to extremely low temperatures (close to absolute zero) and advanced shielding techniques that can protect them from external influences.

Without effective ways to manage decoherence, the computational power of quantum systems is significantly reduced. Methods to mitigate decoherence, such as error correction codes and isolation techniques, are crucial concerns when it comes to making quantum computing practical and cost-effective.

How Is Quantum Computing Being Used Today?

While there’s a lot of excitement around the potential of quantum computing, it’s still in its early stages, and many practical applications of using quantum mechanics to improve upon classical computing are still in the early stages.

As the technology matures and quantum computers become more accessible, it’s expected that quantum computing will continue to impact a broad range of industry concerns, including:

Cryptography: Quantum computers could potentially break many of the cryptographic schemes currently in use, necessitating the development of new quantum-safe encryption techniques.

Pharmaceutical Research: Researchers are using quantum computing to help model complex molecular and chemical reactions, which can potentially lead to the discovery of new drugs and improve healthcare.

Optimization and Efficiency: Quantum-as-a-Service delivery models are being used for tasks such as traffic optimization, supply chain logistics, and financial modelling.

Artificial Intelligence and Machine Learning: Quantum computers are being used to speed up the execution of machine learning algorithms and make artificial intelligence outputs more accurate.

Climate Modeling: Modeling complex environmental systems, which currently demand significant computational power, could be revolutionized by quantum computing.

Materials Science: Quantum computing has the potential to revolutionize the field of materials science, including the discovery of new superconductors.

Financial Modeling: Quantum computers can be used to help optimize trading strategies, manage risk, and enhance the modelling of financial systems.

Agriculture: Quantum systems are already being used to optimize crop yields by analyzing DNA sequences in plants.

Risk Management: Quantum computers can be used to analyze vast and complex datasets to refine risk models and enable more accurate risk assessments.

Quantum Simulations: One of the primary strengths of quantum computing is its ability to simulate complex quantum systems that are difficult for classical computers to model accurately.