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AI researchers aim to achieve stability, speed, manipulability and a gain in operational height from for the robot by using machine learning and a 3D printed stick on the robot’s hind legs to allow quadruped transformers to become a humanoid biped robot and walk. Quantum researchers designed a machine learning-based method that shows how artificial controllers can discover non-intuitive pulse sequences that can rapidly cool a mechanical object from high to ultra cold temperatures, faster than other standard methods, which could be used to advance quantum computers. Researchers used deep reinforcement learning to arrange atoms into a lattice shape, which could be used to create new materials and nano devices, including a robot arm mate of atoms.

AI News Timestamps:
0:00 Transformers Robotics Tech.
2:39 Artificial Intelligence To Control Quantum Computer.
5:21 New Nano Scale Robot Arm.

#technology #tech #ai

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This story is a part of MIT Technology Review’s What’s Next series, where we look across industries, trends, and technologies to give you a first look at the future

In 2023, progress in quantum computing will be defined less by big hardware announcements than by researchers consolidating years of hard work, getting chips to talk to one another, and shifting away from trying to make do with noise as the field gets ever more international in scope.

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Scientists at Brookhaven National Laboratory have uncovered an entirely new kind of quantum entanglement, a phenomenon that causes particles to become weirdly linked, even across vast cosmic distances, reports a new study. The discovery allowed them to capture an unprecedented glimpse of the bizarre world inside atoms, the tiny building blocks of matter.

The mind-bending research resolves a longstanding mystery about the nuclei of atoms, which contain particles called protons and neutrons, and could help shed light on topics ranging from quantum computing to astrophysics.

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Quantum computers hold the promise of performing certain tasks that are intractable even on the world’s most powerful supercomputers. In the future, scientists anticipate using quantum computing to emulate materials systems, simulate quantum chemistry, and optimize hard tasks, with impacts potentially spanning finance to pharmaceuticals.

However, realizing this promise requires resilient and extensible hardware. One challenge in building a large-scale quantum computer is that researchers must find an effective way to interconnect quantum nodes—smaller-scale processing nodes separated across a computer chip. Because quantum computers are fundamentally different from classical computers, conventional techniques used to communicate electronic information do not directly translate to quantum devices. However, one requirement is certain: Whether via a classical or a quantum interconnect, the carried information must be transmitted and received.

To this end, MIT researchers have developed a quantum computing architecture that will enable extensible, high-fidelity communication between superconducting quantum processors. In work published in Nature Physics, MIT researchers demonstrate step one, the deterministic emission of single photons—information carriers—in a user-specified direction. Their method ensures quantum information flows in the correct direction more than 96 percent of the time.

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While multiphoton entangled states are the essential building blocks of quantum photonic technologies, large-scale production of such states has proven to be difficult. This study utilizes the unique structure of hole spins in quantum dot molecules to propose an approach that overcomes many of the existing obstacles in the deterministic generation of such states. With high fidelity and production rates that are unmatched among currently available protocols, this proposal seems quite promising as a basis for tomorrow’s optical quantum communication hardware.

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This past year, global attention has been focused on geo-strategic issues, such as the devastating war in Ukraine, which has dislocated many and caused immense suffering. Attention has also been focused on the recovery from the COVID pandemic, which was the overriding concern over the past three years. And finally, the economic destruction wrought by rapidly ramped interest rates which have targeted all sectors of the economy, particularly technology. But despite all this negativity, the business of building the future continues. There has been progress across major axes of computing, from visualization to AI and new types of processors (quantum).

With immense progress in technology, what might we look forward to in 2023?

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One potential application: Enhancing the sensitivity of atomic magnetometers used to measure the alpha waves emitted by the human brain.

Scientists are increasingly seeking to discover more about quantum entanglement, which occurs when two or more systems are created or interact in such a manner that the quantum states of some cannot be described independently of the quantum states of the others. The systems are correlated, even when they are separated by a large distance. Interest in studying this kind of phenomenon is due to the significant potential for applications in encryption, communications, and quantum computing.

Performing computation using quantum-mechanical phenomena such as superposition and entanglement.

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The way electrons interact with photons of light is a vital part of many modern technologies, from lasers to solar panels to LEDs. But the interaction is inherently weak because of a major mismatch in scale: the wavelength of visible light is about 1,000 times larger than an electron, so the way the two things affect each other is limited by that disparity.

Now, researchers at The University of Hong Kong (HKU), MIT and other universities say they have come up with an innovative way to make more robust interactions between photons and electrons possible, that produces a hundredfold increase in the emission of light from a phenomenon called Smith-Purcell radiation. The findings have potential ramifications for both and fundamental scientific research, although it will require more years of investigation to put into practice.

The findings are published in Nature by Dr. Yi Yang (Assistant Professor of the Department of Physics at HKU and a former postdoc at MIT), Dr. Charles Roques-carmes (Postdoctoral Associate at MIT) and Professors Marin Soljačić and John Joannopoulos (MIT professors). The research team also included Steven Kooi at MIT’s Institute for Soldier Nanotechnologies, Haoning Tang and Eric Mazur at Harvard University, Justin Beroz at MIT, and Ido Kaminer at Technion-Israel Institute of Technology.

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Nuclear physicists have found a new way to use the Relativistic Heavy Ion Collider (RHIC)—a particle collider at the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory—to see the shape and details inside atomic nuclei. The method relies on particles of light that surround gold ions as they speed around the collider and a new type of quantum entanglement that’s never been seen before.

Through a series of quantum fluctuations, the particles of light (a.k.a. photons) interact with gluons—gluelike particles that hold quarks together within the protons and neutrons of nuclei. Those interactions produce an intermediate particle that quickly decays into two differently charged “pions” (π). By measuring the velocity and angles at which these π+ and π- particles strike RHIC’s STAR detector, the scientists can backtrack to get crucial information about the photon—and use that to map out the arrangement of gluons within the nucleus with higher precision than ever before.

“This technique is similar to the way doctors use positron emission tomography (PET scans) to see what’s happening inside the brain and other body parts,” said former Brookhaven Lab physicist James Daniel Brandenburg, a member of the STAR collaboration who joined The Ohio State University as an assistant professor in January 2023. “But in this case, we’re talking about mapping out features on the scale of femtometers —quadrillionths of a meter—the size of an individual proton.”

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