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Category: quantum physics – Page 605

Although we are currently in an era of quantum computers with tens of noisy qubits, it is likely that a decisive, practical quantum advantage can only be achieved with a scalable, fault-tolerant, error-corrected quantum computer. Therefore, development of quantum error correction is one of the central themes of the next five to ten years. Our article “Topological and subsystem codes on low-degree graphs with flag qubits” [1], published in Physical Review X, takes a bottom-up approach to quantum error correcting codes that are adapted to a heavy-hexagon lattice – a topology that all our new premium quantum processors use, including IBM Quantum Falcon (d=3) and Hummingbird (d=5).

Many in the quantum error correction community pursue a top-down computer science approach, i.e., designing the best codes from an abstract perspective to achieve the smallest logical error rate with minimal resource. Along this path, the surface code is the most famous candidate for near-term demonstrations (as well as mid- to long-term applications) on a two-dimensional quantum computer chip. The surface code naturally requires a two-dimensional square lattice of qubits, where each qubit is coupled to four neighbors.

We started with the surface code architecture on our superconducting devices and demonstrated an error detection protocol as a building block of the surface code around 2015 [2]. While the experimental team at IBM made steady progress with cross-resonance (CR) gates, achieving gate fidelities near 99%, an experimental obstacle appeared along the path of scaling up the surface code architecture. The specific way to operate the CR gates requires the control qubit frequency to be detuned from all its neighboring target qubits, such that the CNOT gates between any pair of control and target can be individually addressed.

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When probing the subtle effects of quantum mechanics, all the parameters in the system and its measurements need to be finely tuned to observe the result you are hoping for. So what happens when you gear everything towards detecting what you least expect? Researchers at MIT and Purdue University in the U.S. took just this approach and found they could amplify quantum signals by a factor of 30 while conditionally changing the relative phase of a photon from π/80 to π/2. The results could provide the missing link that nudges a number of quantum network technologies closer to practical use.

Quantum technology protocols generally aim to maximize interaction strengths, but preparing these entangled systems can be very difficult. “We asked the question, can we turn weak interactions into very strong interactions somehow?” explains Vladan Vuletic, Wolf Professor of Physics at MIT. “You can, and the price is, they don’t happen often.”

The effects Vuletic and colleagues observe hinge on the factors that feed into the “expectation values” of quantum experiments. Expectation values describe the average outcome of a quantum scenario and equate to the product of each possible value and its probability. Vuletic and his collaborators focused their studies on scenarios where the average is dominated by , like a lottery where everyone wins a small amount on average, although in fact, just a few people win huge amounts. In quantum mechanics, light also sometimes takes the path less traveled, and as the researchers show, this really can make all the difference.

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The emergence of artificial intelligence and machine learning techniques is changing the world dramatically with novel applications such as internet of things, autonomous vehicles, real-time imaging processing and big data analytics in healthcare. In 2020, the global data volume is estimated to reach 44 Zettabytes, and it will continue to grow beyond the current capacity of computing and storage devices. At the same time, the related electricity consumption will increase 15 times by 2030, swallowing 8% of the global energy demand. Therefore, reducing energy consumption and increasing speed of information storage technology is in urgent need.

Berkeley researchers led by HKU President Professor Xiang Zhang when he was in Berkeley, in collaboration with Professor Aaron Lindenberg’s team at Stanford University, invented a new data storage method: They make odd numbered layers slide relative to even-number layers in tungsten ditelluride, which is only 3nm thick. The arrangement of these atomic layers represents 0 and 1 for data storage. These researchers creatively make use of quantum geometry: Berry curvature, to read information out. Therefore, this material platform works ideally for memory, with independent ‘write’ and ‘read’ operation. The using this novel data storage method can be over 100 times less than the traditional method.

This work is a conceptual innovation for non-volatile storage types and can potentially bring technological revolution. For the first time, the researchers prove that two-dimensional semi-metals, going beyond traditional silicon material, can be used for information storage and reading. This work was published in the latest issue of the journal Nature Physics. Compared with the existing non-volatile (NVW) memory, this new material platform is expected to increase speed by two orders and decrease energy cost by three orders, and it can greatly facilitate the realization of emerging in-memory computing and neural network computing.

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The technology behind the quantum computers of the future is fast developing, with several different approaches in progress. Many of the strategies, or “blueprints,” for quantum computers rely on atoms or artificial atom-like electrical circuits. In a new theoretical study in the journal Physical Review X, a group of physicists at Caltech demonstrates the benefits of a lesser-studied approach that relies not on atoms but molecules.

“In the quantum world, we have several blueprints on the table and we are simultaneously improving all of them,” says lead author Victor Albert, the Lee A. DuBridge Postdoctoral Scholar in Theoretical Physics. “People have been thinking about using molecules to encode information since 2001, but now we are showing how molecules, which are more complex than atoms, could lead to fewer errors in quantum computing.”

At the heart of quantum computers are what are known as qubits. These are similar to the bits in classical computers, but unlike classical bits they can experience a bizarre phenomenon known as superposition in which they exist in two states or more at once. Like the famous Schrödinger’s cat thought experiment, which describes a cat that is both dead and alive at the same time, particles can exist in multiple states at once. The phenomenon of superposition is at the heart of quantum computing: the fact that qubits can take on many forms simultaneously means that they have exponentially more computing power than classical bits.

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