Researchers have succeeded in developing a technique to quickly search for the optimal quantum gate sequence for a quantum computer using a probabilistic method.
Superfast levitating trains, long-range lossless power transmission, faster MRI machines—all these fantastical technological advances could be in our grasp if we could just make a material that transmits electricity without resistance—or “superconducts”—at around room temperature.
By analyzing images made of colored dots created by quantum simulators, ETH researchers have studied a special kind of magnetism. In the future this method could also be used to solve other physics puzzles, for instance in superconductivity.
Since superfluid light exists in computers I think frankly we may already solve the theory of everything because the missing piece is infinity in all things which solves all future problems.
Thinking of spacetime as a liquid may be a helpful analogy. We often picture space and time as fundamental backdrops to the universe. But what if they are not fundamental, and built instead of smaller ingredients that exist on a deeper layer of reality that we cannot sense? If that were the case, spacetime’s properties would “emerge” from the underlying physics of its constituents, just as water’s properties emerge from the particles that comprise it. “Water is made of discrete, individual molecules, which interact with each other according to the laws of quantum mechanics, but liquid water appears continuous and flowing and transparent and refracting,” explains Ted Jacobson, a physicist at the University of Maryland, College Park. “These are all ‘emergent’ properties that cannot be found in the individual molecules, even though they ultimately derive from the properties of those molecules.”
Physicists have been considering this possibility since the 1990s in an attempt to reconcile the dominant theory of gravity on a large scale — general relativity — with the theory governing the very smallest bits of the universe—quantum mechanics. Both theories appear to work perfectly within their respective domains, but conflict with one another in situations that combine the large and small, such as black holes (extremely large mass, extremely small volume). Many physicists have tried to solve the problem by ‘quantizing’ gravity — dividing it into smaller bits, just as quantum mechanics breaks down many quantities, such as particles’ energy levels, into discrete packets. “There are many attempts to quantize gravity—string theory and loop quantum gravity are alternative approaches that can both claim to have gone a good leg forward,” says Stefano Liberati, a physicist at the International School for Advanced Studies (SISSA) in Trieste, Italy.
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The spin of the electron is nature’s perfect quantum bit, capable of extending the range of information storage beyond “one” or “zero.” Exploiting the electron’s spin degree of freedom (possible spin states) is a central goal of quantum information science.
Not all magnets are the same. When we think of magnetism, we often think of magnets that stick to a refrigerator’s door. For these types of magnets, the electronic interactions that give rise to magnetism have been understood for around a century, since the early days of quantum mechanics. But there are many different forms of magnetism in nature, and scientists are still discovering the mechanisms that drive them.
Now, physicists from Princeton University have made a major advance in understanding a form of magnetism known as kinetic magnetism, using ultracold atoms bound in an artificial laser-built lattice. Their experiments, chronicled in a paper published in the journal Nature (“Directly imaging spin polarons in a kinetically frustrated Hubbard system”), allowed the researchers to directly image the microscopic object responsible for this magnetism, an unusual type of polaron, or quasiparticle that emerges in an interacting quantum system.
Researchers at Princeton have directly imaged the microscopic origins of a novel type of magnetism. (Image: Max Prichard, Waseem Bakr group at Princeton University)
A quantum bit inspired by Schrödinger’s cat can resist making errors for an unprecedentedly long time, which makes it a candidate for building less error-prone quantum computers.
A powerful new idea about how the laws of physics work could bring breakthroughs on everything from quantum gravity to consciousness, says researcher Chiara Marletto
Researchers succeeded in conducting an almost perfect quantum teleportation despite the presence of noise that usually disrupts the transfer of quantum state.
In teleportation, the state of a quantum particle, or qubit, is transferred from one location to another without sending the particle itself. This transfer requires quantum resources, such as entanglement between an additional pair of qubits. In an ideal case, the transfer and teleportation of the qubit state can be done perfectly. However, real-world systems are vulnerable to noise and disturbances — and this reduces and limits the quality of the teleportation.
Advancements in Noise-Resilient Teleportation.
Researchers have made a significant advancement in quantum computing by adapting a microwave circulator to precisely control the nonreciprocity between a qubit and a resonant cavity. This innovation not only enhances the control within quantum computers but also simplifies the theoretical models for future research.
Scientists led by the University of Massachusetts Amherst have adapted a device called a microwave circulator for use in quantum computers, allowing them for the first time to precisely tune the exact degree of nonreciprocity between a qubit, the fundamental unit of quantum computing, and a microwave-resonant cavity. The ability to precisely tune the degree of nonreciprocity is an important tool to have in quantum information processing.
In doing so, the team, including collaborators from the University of Chicago, derived a general and widely applicable theory that simplifies and expands upon older understandings of nonreciprocity so that future work on similar topics can take advantage of the team’s model, even when using different components and platforms. The research was published recently in Science Advances.
