Lifeboat Foundation

Today, one of the biggest paradoxes in the universe threatens to unravel modern science: the black hole information paradox. Every object in the universe is composed of particles with unique quantum properties and even if an object is destroyed, its quantum information is never permanently deleted. But what happens to that information when an object enters a black hole? Fabio Pacucci investigates. [Directed by Artrake Studio, narrated by Addison Anderson, music by WORKPLAYWORK / Cem Misirlioglu].

Photons, particles that represent a quantum of light, have shown great potential for the development of new quantum technologies. More specifically, physicists have been exploring the possibility of creating photonic qubits (quantum units of information) that can be transmitted over long distances using photons.

Despite some promising results, several obstacles still need to be overcome before photonic qubits can be successfully implemented on a large-scale. For instance, photons are known to be susceptible to propagation loss (i.e., a loss of energy, radiation, or signals as it travels from one point to another) and do not interact with one another.

Researchers at University of Copenhagen in Denmark, Instituto de Física Fundamental IFF-CSIC in Spain, and Ruhr-Universität Bochum in Germany have recently devised a strategy that could help to overcome one of these challenges, namely the lack of photon-photon interactions. Their method, presented in a paper published in Nature Physics, could eventually aid the development of more sophisticated quantum devices.

Intel Corp.’s two primary research organizations, Intel Labs and Components Research, announced today that they’re making big progress as they work toward large-scale production of quantum computing processors.

At the 2022 Silicon Quantum Electronics Workshop in Orford, Quebec, Intel’s researchers said that they’ve been able to demonstrate the highest reported yield and uniformity rate when manufacturing “silicon spin qubit devices” at the company’s transistor research and development facility. The research is believed to be a key milestone for Intel as it moves toward being able to fabricate quantum computing chips on its existing transistor manufacturing processes.

Intel is a key player in the race to build quantum computers, which are more advanced machines that encode data as “qubits,” as opposed to the conventional bits used in traditional computers. The advantage of qubits is they’re not restricted to states of 1 or 0. They can also exist as both states at the same time, a characteristic that’s known as superposition.

Richard Gott, co author with Neil De Grasse Tyson of “Welcome to The Universe” argues the key to understanding the origin of the universe may be the concept of closed time like curves. These are solutions to Einstein’s theory that may allow time travel into the past. in this film, Richard Gott of Princeton University explains the model he developed with LIxin Li. Gott explores the possibility of a closed time like curve forming in the early universe and how this might lead to the amazing property of the universe being able to create itself. Gott is one of the leading experts in time travel solution to Einstein’s equations and is author of the book “Time Travel In Einstein’s Universe”.
This film is part of a series of films exploring competing models of th early universe with the creators of those models. We have interviewed Stephen Hawking, Roger Penrose, Alan Guth and many other leaders of the field. To see other episodes, click on the link below:
https://www.youtube.com/playlist?list=PLJ4zAUPI-qqqj2D8eSk7yoa4hnojoCR4m.

We would like to thank the following who helped us are this movie:
Animations:
Morn 1415
David Yates.
NASA
ESA
M Buser, E Kajari, and WP Schleich.
Storyblocks.
Nina McCurdy, Anthony Aguirre, Joel Primack, Nancy Abrams.
Pixabay.
Ziri Younsi.

Continue reading “Before the Big Bang 6: Can the Universe Create Itself?” »

A team of researchers with the University of New South Wales (UNSW) in Sydney has achieved a breakthrough in spin qubit coherence times (opens in new tab). The research took advantage of the team’s previous work on so-called “dressed” qubits — qubits constantly under the effect of an electromagnetic field shielding them from interference. In addition, the researchers leveraged a newly-designed protocol, SMART, (opens in new tab) which leverages the increased coherence times to allow individual qubits to be safely coaxed to perform the required computations.

The improvements allowed the researchers to register coherence times of up to two milliseconds — over a hundred times higher than similar control methods in the past, but still a ways from the amount of time your eyelids take to blink.

The even-denominator state appears in a 2D quasiparticle system, but researchers still can’t explain its origin.

Tiny particles are interconnected despite sometimes being thousands of kilometers apart—Albert Einstein called this “spooky action at a distance.” Something that would be inexplicable by the laws of classical physics is a fundamental part of quantum physics. Entanglement like this can occur between multiple quantum particles, meaning that certain properties of the particles are intimately linked with each other.

Entangled systems containing multiple quantum particles offer significant benefits in implementing quantum algorithms, which have the potential to be used in communications, data security or quantum computing. Researchers from Paderborn University have been working with colleagues from Ulm University to develop the first programmable optical quantum memory. The study was published as an “Editor’s suggestion” in the Physical Review Letters journal.

Quantum computing and communication often rely on the entanglement of several photons together. But obtaining these multiphoton states is a bit like playing the lottery, as generating entanglement between photons only succeeds a small fraction of the time. A new experiment shows how to improve one’s odds in this quantum game of chance. The method works like an entanglement assembly line, in which entangled pairs of photons are created in successive order and combined with stored photons.

The traditional method for obtaining multiphoton entanglement requires a large set of photon sources. Each source simultaneously generates an entangled photon pair, and those photons are subsequently interfered with each other. The process is probabilistic in that each step only succeeds in producing pair entanglement, say, once in every 20 tries. The odds become exponentially worse as entanglement of more and more photons is attempted.

Christine Silberhorn from Paderborn University, Germany, and her colleagues have developed a new method that offers a relatively high success rate [1]. They use a single source that generates pairs of polarization-entangled photons in succession. After the first pair is created, one of these photons is stored in an optical loop. When the source creates a new pair (which can take several tries), one of these photons is interfered with the stored photon. If successful, this interference creates a four-photon entangled state. The process can continue—with new pairs being generated and one photon being stored—until the desired multiphoton state is reached.

The rise of quantum computing and its implications for current encryption standards are well known. But why exactly should quantum computers be especially adept at breaking encryption? The answer is a nifty bit of mathematical juggling called Shor’s algorithm. The question that still leaves is: What is it that this algorithm does that causes quantum computers to be so much better at cracking encryption? In this video, YouTuber minutephysics explains it in his traditional whiteboard cartoon style.

“Quantum computation has the potential to make it super, super easy to access encrypted data — like having a lightsaber you can use to cut through any lock or barrier, no matter how strong,” minutephysics says. “Shor’s algorithm is that lightsaber.”

Continue reading “How Quantum Physics Leads to Decrypting Common Algorithms” »