Scientists Come One Step Further in Creating Quantum Computers

New Delhi: The world of technology has got one step closer to creating quantum computers. Dutch scientists have recently created a 2-qubit (quantum bit) processor running on a silicon chip.

While standard computers work with bits of information that can have only two states, 0 or 1, quantum processors are based on the fact that bits can exist in both states at the same time. As a result, they have tremendous computing power and can do things that no classical computer can do. Quantum computers can be used for solving complex problems and can manage much larger number of calculations at once.

Scientists explain that they are still in the early stages of developing a real quantum processor. Hardware manufacturer IBM has already built a 50-qubit computer, but with superconductive materials that need extreme cooling. Putting a quantum processor on a silicon chip, which is already used in the computer industry, may be the first step toward mass production.

In such quantum processors, electrons can be in many states at once. This is called superposition. In the lab, scientists have managed to keep electrons between both positions at the same time, however, such electrons are not stable and quickly fall apart. By linking these electrons together on a silicon chip qubit hardware manufacturers could produce quantum processors for commercial use.

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The Quantum Advantage

Quantum computers operate on principles fundamentally different from those of classical computers. While traditional computers use bits as the smallest unit of data, which can be either 0 or 1, quantum computers use quantum bits, or qubits. Qubits can exist in a state of 0, 1, or both simultaneously, thanks to the phenomenon known as superposition. Additionally, qubits can be entangled, meaning the state of one qubit is directly related to the state of another, even if they are physically separated.

These unique properties allow quantum computers to perform multiple calculations at once, vastly increasing their processing power. This capability, known as quantum parallelism, is what makes quantum computers potentially far superior to classical computers for certain tasks, particularly those involving complex simulations and large datasets.

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Recent Breakthroughs

One of the most significant recent advancements in quantum computing is the improvement in qubit coherence time. Coherence time refers to the length of time that a qubit can maintain its quantum state before it decoheres and loses its information. Longer coherence times are essential for performing accurate and complex quantum computations.

Researchers at several leading institutions, including IBM, Google, and various academic laboratories, have reported significant increases in coherence times. These improvements have been achieved through better qubit design, error-correction techniques, and advancements in quantum algorithms.

Another milestone in quantum computing is the development of more robust error correction methods. Quantum computers are highly susceptible to errors due to their sensitivity to external disturbances. Error correction is a crucial aspect of making quantum computers reliable and scalable. Scientists are making strides in creating error-correcting codes that can detect and fix errors without significantly slowing down computations.

Real-World Applications

The potential applications of quantum computing are vast and varied. In cryptography, quantum computers could break current encryption methods, but they could also create new, unbreakable encryption techniques. In healthcare, quantum computers could accelerate drug discovery by simulating molecular interactions at unprecedented speeds. In finance, they could optimize portfolios and risk management strategies with far greater accuracy than classical computers.

One of the most promising applications is in solving complex optimization problems. Quantum computers could revolutionize industries such as logistics, energy, and materials science by finding optimal solutions to problems that are currently too complex for classical computers to handle efficiently.

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