Today I happened to across a new product from Google. It’s called quantum AI and it is based on a new architecture. Google’s quantum chip, called Sycamore. It has achieved several milestones that demonstrate its advancing capabilities. The chip operates using quantum bits, or qubits, which rely on quantum mechanics to perform computations far beyond the scope of classical computers.

Per Google, it is a significant development in the field of quantum computing. It was designed to perform quantum computations and is part of Google’s broader efforts in quantum research, particularly through its Quantum AI lab.

Here’s their promotional video on it –

https://youtu.be/W7ppd_RY-UE?si=ln_Ls8WjeilaTQ-F

One major breakthrough was Google’s ability to execute a computational task known as random circuit sampling (RCS), demonstrating “quantum supremacy.” This means the quantum computer solved a problem in seconds that would have taken classical supercomputers thousands of years to complete.

Sycamore is a superconducting qubit processor. It consists of 54 qubits, although only 53 were operational during Google’s demonstration of quantum supremacy.

Recent improvements have reduced the error rates of Sycamore’s qubits, allowing it to outperform classical systems in certain benchmarks while operating in a “weak noise phase,” a condition crucial for maintaining computational accuracy.

Error correction remains a key challenge in quantum computing, as qubits are highly prone to interference. Google is working on building logical qubits, which combine multiple physical qubits to reduce errors. This approach has shown progress; for example, scaling up the size of logical qubits has begun to lower error rates, but further refinement is needed before fully error-corrected quantum computers become practical.

The ultimate goal of quantum computing research, including Google’s efforts, is to create systems capable of solving real-world problems that classical computers cannot tackle. These could include advancements in materials science, cryptography, and optimization tasks.

Here are some key points about Willow:

Performance

– Exponential Speed: Willow can perform computations in under five minutes that would take the world’s fastest supercomputers 10 septillion years (a number so large it exceeds the estimated age of the universe).

Error Reduction: One of the major challenges in quantum computing is error rates, which increase with the number of qubits (quantum bits). Willow addresses this by reducing errors exponentially as more qubits are added.

Implications

Multiverse Theory: Google’s Quantum AI lead, Hartmut Neven, suggested that Willow’s performance might lend credence to the idea that quantum computation occurs in parallel universes, aligning with the multiverse theory.

Practical Uses: This breakthrough brings quantum computers closer to practical applications, potentially revolutionizing fields like cryptography, scientific research, and complex problem-solving. While Sycamore’s demonstration was primarily a proof of concept, the ultimate goal of quantum computing is to tackle complex problems in fields such as cryptography, materials science, drug discovery, and optimization that are currently intractable for classical computers.