Lifeboat Foundation

The concept of ‘anti-realism’ is widely seen as a fact of life for many physicists studying the mysterious effects of quantum mechanics. However, it also seems to contradict the assumptions of many other fields of research. In his research, Dr William Sulis at McMaster University in Canada explores the issue from a new perspective, by using a novel mathematical toolset named the ‘process algebra model’. In suggesting that reality itself is generated by interacting processes more fundamental than quantum particles, his theories could improve researchers’ understanding of fundamental processes in a wide variety of fields.

The concept of ‘locality’ states that objects and processes can only be influenced by other objects and processes in their immediate surroundings. It is a fundamental aspect of many fields of research and underpins all of the most complex systems we observe in nature, including living organisms. “Biologists and psychologists have known for centuries that the physical world is dominated by processes which are characterized by factors including transformation, interdependence, and information”, Dr Sulis explains. “Organisms are born, develop, continually exchange physical components and information with their environment, and eventually die.”

Beyond biology, the principle of locality also extends to Einstein’s theory of special relativity. Since the speed of light sets a fundamental speed limit on all processes in the universe, the theory states that no process can occur if it has not been triggered by another event in its past, at a close enough distance for light to travel between them within the time separating them. In general, these theories are unified by a concept which physicists call ‘realism’. Yet despite this seemingly intuitive rule, physicists have increasingly come to accept the idea that it doesn’t present a full description of how all processes unfold.

Researchers at Tohoku University, the University of Messina, and the University of California, Santa Barbara (UCSB) have developed a scaled-up version of a probabilistic computer (p-computer) with stochastic spintronic devices that is suitable for hard computational problems like combinatorial optimization and machine learning.

Moore’s law predicts that computers get faster every two years because of the evolution of semiconductor chips. While this is what has historically happened, the continued evolution is starting to lag. The revolutions in machine learning and artificial intelligence means much higher computational ability is required. Quantum computing is one way of meeting these challenges, but significant hurdles to the practical realization of scalable quantum computers remain.

A p-computer harnesses naturally stochastic building blocks called probabilistic bits (p-bits). Unlike bits in traditional computers, p-bits oscillate between states. A p-computer can operate at room-temperature and acts as a domain-specific computer for a wide variety of applications in machine learning and artificial intelligence. Just like quantum computers try to solve inherently quantum problems in quantum chemistry, p-computers attempt to tackle probabilistic algorithms, widely used for complicated computational problems in combinatorial optimization and sampling.

Researchers have used a quantum processor to make microwave photons uncharacteristically sticky. They coaxed them to clump together into bound states, then found that these photon clusters survived in a regime where they were expected to dissolve into their usual, solitary states. The discovery was first made on a quantum processor, marking the growing role that these platforms are playing in studying quantum dynamics.

Photons—quantum packets of electromagnetic radiation like light or microwaves—typically don’t interact with one another. Two crossed flashlight beams, for example, pass through one another undisturbed. But in an array of superconducting qubits, microwave photons can be made to interact.

In “Formation of robust bound states of interacting photons,” published today in Nature, researchers at Google Quantum AI describe how they engineered this unusual situation. They studied a ring of 24 superconducting qubits that could host microwave photons. By applying quantum gates to pairs of neighboring qubits, photons could travel around by hopping between neighboring sites and interacting with nearby photons.

A quantum approach to data analysis that relies on the study of shapes will likely remain an example of a quantum advantage — albeit for increasingly unlikely scenarios.

The merged computing power can give rise to faster and more accurate machine learning applications.

Last month, LUMI, the fastest supercomputer in Europe, was connected to HELMI, Finland’s first quantum computer, a five-qubit system operational since 2021. This makes Finland the first country in Europe to have created such a hybrid system — it is one of the few countries worldwide to have done the same.

LUMI is famous — the supercomputer ranks third in the latest Top 500 list of the world’s fastest supercomputer and can carry out 309 petaflops. LUMI, too became operational in 2021.

Continue reading “Europe’s fastest supercomputer just connected to a quantum computer in Finland — here’s why” »

Dark matter makes up about 27% of the matter and energy budget in the universe, but scientists do not know much about it. They do know that it is cold, meaning that the particles that make up dark matter are slow-moving. It is also difficult to detect dark matter directly because it does not interact with light. However, scientists at the U.S. Department of Energy’s Fermi National Accelerator Laboratory (Fermilab) have discovered a way to use quantum computers to look for dark matter.

Aaron Chou, a senior scientist at Fermilab, works on detecting dark matter through quantum science. As part of DOE’s Office of High Energy Physics QuantISED program, he has developed a way to use qubits, the main component of quantum computing.

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

Bernardo Kastrup, Carlo Rovelli and Patricia Churchland lock horns over the New Science of Consciousness.

00:00 Intro.
01:20 Patricia Churchland | On scientific evidence.
02:50 Bernardo Kastrup | On material idealism.
04:47 Carlo Rovelli | There is no hard problem of consciousness.
07:00 Robert Lawrence Kuhn | Will we ever be able to provide data explaining consciousness?

Continue reading “Can science crack the mystery of consciousness? | Bernardo Kastrup, Carlo Rovelli, and more” »

https://www.youtube.com/watch?v=EFILtb2E5ss

Universe to go through a cosmic Poincare Recurrence? In other words, can the universe repeats itself? Will the same history happen again at some distant future? If the universe is closed and isolated, which indicates that it’s probably qualified for experiencing a Poincare Recurrence in cosmic scale, will the entire history of our universe happen for an infinite number of times? If cosmic Poincare Recurrence can take place, does it mean that the entropy of the entire universe will decrease at some point? Isn’t that the violation of the second law of thermodynamics?

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Sources:
(K. Ropotenko) The Poincar´e recurrence time for the de Sitter space with dynamical chaos.
https://arxiv.org/abs/0712.

Continue reading “Post Eternity Part 1: The Universe Repeats Itself” »

The hunt for a theory of quantum gravity suggests that spacetimes might emerge more easily than anyone imagined.