Oxford Scientists Claim to Have Achieved Teleportation Using a Quantum Supercomputer

Scientists at the University of Oxford have successfully demonstrated quantum teleportation using a scalable quantum supercomputer. This breakthrough involves Tele porting logical gates (the fundamental components of quantum algorithms) across a network link, rather than just transferring quantum states.

 

Dougal Main and Beth Nichol working on the distributed quantum computer. Image credit: John Cairns.

This achievement addresses the scalability problem in quantum computing, potentially paving the way for a future quantum internet that could offer ultra-secure communication and computation. It's a significant step towards making quantum computing practical on a large scale.

According to the study lead, Dougal Main, this is a significant advancement because previous demonstrations of quantum teleportation focused on transferring quantum states between physically separated systems while this study achieved the teleportation of logical gates (the fundamental components of quantum algorithms) across a network link.

Quantum teleportation is a fascinating process but is different from Science Fiction Teleportation. Science Fiction Teleportation is often depicted as the instantaneous transport of a person or object from one location to another. While Quantum Teleportation involves transferring quantum information from one location to another without physically moving the particles involved. 

It's important to note that quantum teleportation doesn't involve the physical transportation of particles themselves, just the transfer of their quantum state. Also, classical information must be sent alongside the quantum process, so it doesn't violate the speed of light limit.

In this study published in Nature, the team used quantum teleportation to create interactions between distant systems, allowing them to perform logical quantum gates between qubits housed in separate quantum computers. This effectively "wires together" distinct quantum processors into a single, fully-connected quantum computer.

The researchers developed a scalable architecture based on modules containing a small number of trapped-ion qubits (atomic-scale carriers of quantum information). These modules are linked together using optical fibers and photonic links (light-based data transmission) rather than electrical signals.

The photonic links enable qubits in separate modules to be entangled, allowing quantum logic to be performed across the modules using quantum teleportation. This means that logical operations can be executed between qubits housed in different quantum computers.

By linking multiple quantum processors, the researchers effectively created a distributed quantum computer. This approach addresses the scalability problem by allowing computations to be distributed across the network, potentially enabling the connection of millions of qubits.

The breakthrough could lay the groundwork for a future quantum internet, where distant processors form an ultra-secure network for communication, computation, and sensing.

Professor David Lucas, principal investigator of the research team and lead scientist for the UK Quantum Computing and Simulation Hub, led from the Department of Physics, said:

Our experiment demonstrates that network-distributed quantum information processing is feasible with current technology.

Scaling up quantum computers remains a formidable challenge that will likely require new physics insights and intensive engineering efforts over the coming years said professor Lucas. 

The researchers believe this breakthrough could lay the groundwork for a future quantum internet, which would offer an ultra-secure network for communications, computation, and sensing. The scalable architecture they developed uses modules containing a small number of trapped-ion qubits linked together via optical fibers. This modular approach could potentially overcome the scalability challenges faced by quantum computing.

It's an exciting development that brings us closer to realizing the full potential of quantum computing on a practical scale.

Samsung to Acquire Oxford Varsity Professors' Founded AI Startup

Samsung Electronics has signed an agreement to acquire Oxford Semantic Technologies, a UK-based startup specializing in knowledge graph technology. Notably, the knowledge graph technology facilitates a deeper understanding of data, making it valuable for applications across domains.

Founded in 2017 by three Oxford University professors — Ian Horrocks, Boris Motik, and Bernardo Cuenca Grau — Oxford Semantic Technologies excels in knowledge representation and semantic reasoning. 

Oxford Semantic's AI-centric engine, RDFox®, collaborates with organizations across Europe and North America in finance, manufacturing, and e-commerce.

The acquisition will enhance Samsung's on-device AI capabilities, providing ultra-personalized experiences across products like mobile devices, televisions, and home appliances.

Samsung did not disclose the value of the deal.

Combined with on-device AI technology, such as that on Samsung’s Galaxy S24 series, personal knowledge graph technology facilitates hyper-personalized user experiences while ensuring sensitive personal data remains secure on the device. It will be applicable across all of Samsung’s products, extending beyond just mobile devices to televisions and home appliances.

Samsung's VC arm, Samsung Ventures, is an investor in Oxford Semantic and Samsung Electronics has been collaborating with Oxford Semantic on various projects since 2018.

Knowledge graph technology is challenging to implement due to the complex computations used in the process of converting dynamic and extensive real-world data into knowledge graphs and utilizing them. However, Oxford Semantic Technologies has developed and successfully commercialized knowledge graph technology that optimizes data processing and enables advanced reasoning, in the cloud and on-device.

For an uninitiated, Knowledge graph technology is a powerful approach to organizing and representing information. It creates a structured network of interconnected data points, where entities (such as people, places, or concepts) are nodes, and relationships between them are edges. Knowledge graphs use a graph-based model, which allows for flexible and rich representations. Unlike traditional databases, where data is stored in tables, knowledge graphs emphasize relationships.

Oxford Semantic's flagship product, RDFox®, stands out as a rules-based reasoning engine. Unlike traditional databases, RDFox® reasons like a human, deducing new knowledge based on existing facts. It's all about accuracy, truth, and explainability.

RDFox operates in-memory, consistently outperforming other graph technologies by orders of magnitude in benchmark tests. It handles massive knowledge and data stores efficiently. Remarkably efficient and optimized, RDFox can be embedded on edge and mobile devices. It's the brain behind AI applications, ensuring privacy and enabling the next-gen Internet of Things.

Knowledge graphs capture not only the data itself but also the context and semantics. This enables more nuanced understanding and reasoning about the information. Knowledge graphs often incorporate linked data principles, connecting information from various sources (such as databases, APIs, and the web) into a coherent whole.

Google's Knowledge Graph powers search results by understanding entities and their relationships. Netflix, for example, uses knowledge graphs to recommend personalized content.

Knowledge graphs enhance NLP tasks by providing context and disambiguation. Knowledge graphs enable AI systems to infer new facts based on existing ones.

Even in healthcare, the Knowledge Graph finds applications as it help organize medical data, patient records, and drug interactions.

“We are delighted to be working with Samsung,” said Peter Crocker, CEO of Oxford Semantic Technologies. “By integrating Samsung’s expertise in user experience and data with our advanced knowledge graph and reasoning technology, we will provide Samsung’s customers with even more sophisticated personalization. In addition, developing RDFox with Samsung, and being part of the larger group, will provide all of our clients with an even better product, service and support.”

The Oxford Semantic team started working on RDFox® in 2011 at the Computer Science Department of the University of Oxford with the conviction that flexible and high-performance reasoning was a possibility for data-intensive applications without jeopardising the correctness of the results. RDFox is the first market-ready knowledge graph designed from the ground up with reasoning in mind.