Context: We often hear that Quantum computers efficiently solve problems that are very difficult to solve with a classical computer. But even if the hardware is available to build a quantum computer, exploiting its quantum features requires us to write smart algorithms.
What is Quantum computing?
- Quantum computing is a field of study focused on the development of computer-based technologies centred around the principles of quantum theory.
- Quantum theory, a subfield of physics, describes the nature of energy and matter on the quantum (atomic and subatomic) scale.
Principles of Quantum Computing:
- Superposition: A qubit can represent both 0 and 1 state simultaneously.
- Entanglement: States of qubits become interlinked allowing coordinated processing.
- Interference: Quantum states combine to amplify correct solutions and cancel out wrong ones.
- Tunnelling: Particles can pass through barriers aiding in optimisation tasks.
- Measurement: Extracts a result from a qubit collapsing its state to either 0 or 1.
- Quantum Gates: Operations that manipulate qubits, analogous to classical logic gates.
- No-Cloning: Qubits cannot be precisely copied.
- Decoherence: External influences can cause errors requiring error correction.
Application of Quantum computing
What is Classical Computing?
Classical computing refers to the traditional model of computing based on classical physics principles and the binary system.
- Bits: The fundamental unit of classical computing. A bit can be in one of two states: 0 or 1.
- Logic Gates: Operations that manipulate bits. Common gates include AND, OR, NOT, XOR, and others. These gates form the building blocks of digital circuits and processors.
- Binary System: Classical computers operate using the binary numeral system, where data and instructions are represented using combinations of 0s and 1s.
- Deterministic: Classical computers operate in a deterministic manner, meaning given the same input, they will always produce the same output.
- Stored-Program Concept: Modern classical computers follow this concept, where instructions (software) and data are stored in memory and processed by a central processing unit (CPU).
- Architecture: Classical computers typically have a CPU, memory (RAM), storage (hard drive or SSD), input/output devices, and other components interconnected by a system bus.
- Applications: Classical computing encompasses a wide range of devices, from simple calculators to supercomputers, and is used in virtually every industry and aspect of modern life.
- Limitations: There are problems that classical computers find challenging or time-consuming, such as factoring very large numbers or simulating quantum systems. This is where quantum computing may offer advantages.
Quantum computing vs Classical computing
| Feature/Aspect | Quantum Computing | Classical Computing |
| Basic Unit | Quantum bits (qubits) | Binary bits (0 or 1) |
| State Representation | 0, 1, or a superposition of both | Either 0 or 1 |
| Parallelism | Can process multiple possibilities simultaneously | Processes tasks sequentially or with limited parallelism |
| Entanglement | Qubits can be entangled | No equivalent phenomenon |
| Operations | Uses quantum gates | Uses logic gates (AND, OR, NOT, etc.) |
| Determinism | Probabilistic outcomes | Deterministic outcomes |
| Data Storage | Quantum states (fragile) | Electronic storage (RAM, SSDs, hard drives) |
| Error Correction | Requires quantum error correction | Uses classical error correction methods |
| Maturity & Applications | Early stages with specific potential applications | Mature, used in countless applications |
| Hardware | Specialised conditions (E.g., very low temperatures) | Operates at room temperature with semiconductor technology |
Benefits of Quantum Computing:
- Speed: Solve specific problems exponentially faster.
- Parallelism: Process vast information simultaneously.
- Optimisation: Efficiently tackle complex optimization tasks.
- Simulation: Directly simulate quantum systems for research.
- Cryptography: Enable ultra-secure quantum encryption.
- Machine Learning: Accelerate training and improve accuracy.
- Material Discovery: Efficiently find new materials with desired properties.
- Climate Modelling: Achieve more accurate environmental simulations.
- Enhanced Search: Quickly search through unsorted databases.
- Error Correction: Advanced techniques applicable beyond just quantum computing.
Limitations of Quantum Computing:
- Decoherence: Qubits are unstable and lose information over time.
- Error Rates: High error rates compromise computation reliability.
- Scalability: Difficult to build large-scale quantum systems.
- Quantum-to-Classical Transition: Information loss when translating quantum results into classical data.
- Selective Speedup: Not universally faster; speed benefits apply to specific problems.
- Algorithm Complexity: Quantum algorithms are intricate and hard to design.
- Hardware Demands: Requires extreme conditions (E.g., very low temperatures) to function.
- Error Correction: Needs many extra qubits, complicating the design.
- Immature Software: Lacks a robust software ecosystem.
- Cryptography Risks: Threatens current encryption methods.
- Practicality: Many quantum solutions have limited immediate real-world use.
