Masako Yamada, a physicist at the University of Tokyo, recently participated in Physics World’s “Ask me anything” session, where she discussed the challenges of quantum problem-solving. Yamada is an expert in quantum computing and quantum information theory, and her research focuses on developing new algorithms and protocols for quantum computers.

During the session, Yamada explained that one of the biggest challenges in quantum problem-solving is the issue of noise. Quantum computers are extremely sensitive to their environment, and even small amounts of noise can cause errors in calculations. This is because quantum computers use qubits, which are the basic building blocks of quantum information. Unlike classical bits, which can only be in one of two states (0 or 1), qubits can exist in multiple states simultaneously. This property, known as superposition, allows quantum computers to perform certain calculations much faster than classical computers.

However, the downside of this sensitivity is that qubits are easily affected by their environment. Any interaction with the outside world can cause the qubit to lose its superposition and collapse into a single state. This is known as decoherence, and it is one of the biggest obstacles to building a practical quantum computer.

To overcome this challenge, Yamada and her colleagues are working on developing new error-correction techniques that can protect qubits from noise and decoherence. One approach is to use a technique called quantum error correction, which involves encoding information in multiple qubits and using redundancy to detect and correct errors.

Another challenge in quantum problem-solving is the issue of scalability. While quantum computers have shown great promise in solving certain types of problems, such as factoring large numbers and simulating quantum systems, they are still far from being able to solve real-world problems on a large scale. This is because current quantum computers have only a few dozen qubits, whereas many practical applications would require thousands or even millions of qubits.

To address this challenge, Yamada and her colleagues are working on developing new hardware and software architectures that can scale up quantum computers to larger sizes. One approach is to use a technique called quantum annealing, which involves using a special type of qubit called a “flux qubit” to solve optimization problems.

Overall, Yamada’s work highlights the exciting potential of quantum computing and the challenges that must be overcome to realize this potential. As she noted during the session, “Quantum computing is still in its infancy, but it has the potential to revolutionize many fields, from cryptography to drug discovery to materials science. We still have a long way to go, but I’m optimistic that we’ll get there.”

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