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Category: quantum physics – Page 662

Materials challenges and opportunities for quantum computing hardware

The potential of quantum computers to solve problems that are intractable for classical computers has driven advances in hardware fabrication. In practice, the main challenge in realizing quantum computers is that general, many-particle quantum states are highly sensitive to noise, which inevitably causes errors in quantum algorithms. Some noise sources are inherent to the current materials platforms. de Leon et al. review some of the materials challenges for five platforms for quantum computers and propose directions for their solution.

Science, this issue p. eabb2823.

Researchers Have Achieved Sustained Long-Distance Quantum Teleportation

In a way, entangled particles behave as if they are aware of how the other particle is behaving. Quantum particles, at any point, are in a quantum state of probabilities, where properties like position, momentum, and spin of the particle are not precisely determined until there is some measurement. For entangled particles, the quantum state of each depends on the quantum state of the other; if one particle is measured and changes state, for example, the other particle’s state will change accordingly.

The study aimed to teleport the state of quantum qubits, or “quantum bits,” which are the basic units of quantum computing. According to the study, the researchers set up what is basically a compact network with three nodes: Alice, Charlie, and Bob. In this experiment, Alice sends a qubit to Charlie. Bob has an entangled pair of qubits, and also sends one qubit to Charlie, where it interferes with Alice’s qubit. Charlie projects Alice’s qubit onto an entangled quantum Bell State that transfers the state of Alice’s original qubit to Bob’s remaining qubit.

The breakthrough is notable for a few reasons. Many previous demonstrations of quantum teleportation have proven to be unstable over long distances. For example, in 2016, researchers at the University of Calgary were able to perform quantum teleportation at a distance of six kilometers. This was the world record at the time and was seen as a major achievement.

What is VCSEL Laser (Vertical Cavity Surface Emitting Laser)?

The science behind “quantum dots”

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VCSEL stands for Vertical Cavity Surface Emitting Laser.

VCSEL emits light in a cylindrical beam vertically from the surface of a fabricated wafer, and offers significant advantages when compared to the conventional edge-emitting lasers currently used in the majority of fiber optic communications devices.

Now let’s take a comparison between conventional edge emitting laser and VCSEL laser.

Continue reading “What is VCSEL Laser (Vertical Cavity Surface Emitting Laser)?” | >

IBM Announces Quantum Computing Partnership With Quebec

IBM has just announced a partnership with the Government of Quebec to create the Quebec-IBM Discovery Accelerator in Bromont, Quebec. The accelerator will focus on using quantum computing, Artificial Intelligence (AI), and High-Performance Computing (HPC) to develop new projects, business/scientific/academia collaborations, and skills-building initiatives in research areas including energy, life sciences (genomics and drug discovery), new materials development, and sustainability. This is the fourth such center that IBM has announced. The three previously announced partnerships are with Cleveland Clinic, the University of Illinois Urbana-Champaign, and the UK’s Science and Technology Facilities Council Hartree Centre. IBM’s formal mission statement for these Discovery Accelerators is: “Accelerate scientific discovery and societal impact with a convergence of AI, quantum, and hybrid cloud in a community of discovery with research, academic, industry, startup, and government organizations working together.” IBM’s formal mission statement for these Discovery Accelerators is:

“Accelerate scientific discovery and societal impact with a convergence of AI, quantum, and hybrid cloud in a community of discovery with research, academic, industry, startup, and government organizations working together.”

In addition, the company has developed individual mission statements for each of the four Discovery Accelerators:

“Boson Clouds” Could Explain Dark Matter

The nature of dark matter continues to perplex astronomers. As the search for dark matter particles continues to turn up nothing, it’s tempting to throw out the dark matter model altogether, but indirect evidence for the stuff continues to be strong. So what is it? One team has an idea, and they’ve published the results of their first search.

The conditions of dark matter mean that it can’t be regular matter. Regular matter (atoms, molecules, and the like) easily absorbs and emits light. Even if dark matter were clouds of molecules so cold they emitted almost no light, they would still be visible by the light they absorb. They would appear like dark nebula commonly seen near the galactic plane. But there aren’t nearly enough of them to account for the effects of dark matter we observe. We’ve also ruled out neutrinos. They don’t interact strongly with light, but neutrinos are a form of “hot” dark matter since neutrinos move at nearly the speed of light. We know that most dark matter must be sluggish, and therefore “cold.” So if dark matter is out there, it must be something else.

In this latest work, the authors argue that dark matter could be made of particles known as scalar bosons. All known matter can be placed in two large categories known as fermions and bosons. Which category a particle is in depends on a quantum property known as spin. Fermions such as electrons and quarks have fractional spin such as 1/2 or 3/2. Bosons such as photons have an integer spin such as 1 or 0. Any particle with a spin of 0 is a scalar boson.

Top resources to learn quantum machine learning

Quantum computing and machine learning are two of the most exciting technologies that can transform businesses. We can only imagine how powerful it can be if we can combine the power of both of these technologies. When we can integrate quantum algorithms in programs based on machine learning, that is called quantum machine learning. This fascinating area has been a major area of tech firms, and they have brought out tools and platforms to deploy such algorithms effectively. Some of these include TensorFlow Quantum from Google, Quantum Machine Learning (QML) library from Microsoft, QC Ware Forge built on Amazon Braket, etc.

Students skilled in working with quantum machine learning algorithms can be in great demand due to the opportunities the field holds. Let us have a look at a few online courses one can use to learn quantum machine learning.

In this course, the students will start with quantum computing and quantum machine learning basics. The course will also cover topics on building Qnodes and Customised Templates. It also teaches students to calculate Autograd and Loss Function with quantum computing using Pennylane and to develop with the Pennylane.ai API. The students will also learn how to build their own Pennylane Plugin and turn Quantum Nodes into Tensorflow Keras Layers.

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