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A groundbreaking theoretical proof reveals that using a technique called overparametrization enhances performance in quantum machine learning.

Machine learning is a subset of artificial intelligence (AI) that deals with the development of algorithms and statistical models that enable computers to learn from data and make predictions or decisions without being explicitly programmed to do so. Machine learning is used to identify patterns in data, classify data into different categories, or make predictions about future events. It can be categorized into three main types of learning: supervised, unsupervised and reinforcement learning.

Scientists at University College Cork have uncovered a unique superconducting state in Uranium Ditelluride, which could pave the way for more stable and efficient quantum computers. This groundbreaking discovery offers a potential solution to one of quantum computing.

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

Classical thermodynamics has only a handful of laws, of which the most fundamental are the first and second. The first says that energy is always conserved; the second law says that heat always flows from hot to cold. More commonly this is expressed in terms of entropy, which must increase overall in any process of change. Entropy is loosely equated with disorder, but the Austrian physicist Ludwig Boltzmann formulated it more rigorously as a quantity related to the total number of microstates a system has: how many equivalent ways its particles can be arranged.

The second law appears to show why change happens in the first place. At the level of individual particles, the classical laws of motion can be reversed in time. But the second law implies that change must happen in a way that increases entropy. This directionality is widely considered to impose an arrow of time. In this view, time seems to flow from past to future because the universe began — for reasons not fully understood or agreed on — in a low-entropy state and is heading toward one of ever higher entropy. The implication is that eventually heat will be spread completely uniformly and there will be no driving force for further change — a depressing prospect that scientists of the mid-19th century called the heat death of the universe.

Boltzmann’s microscopic description of entropy seems to explain this directionality. Many-particle systems that are more disordered and have higher entropy vastly outnumber ordered, lower-entropy states, so molecular interactions are much more likely to end up producing them. The second law seems then to be just about statistics: It’s a law of large numbers. In this view, there’s no fundamental reason why entropy can’t decrease — why, for example, all the air molecules in your room can’t congregate by chance in one corner. It’s just extremely unlikely.

A potentially game-changing theoretical approach to quantum computing hardware avoids much of the problematic complexity found in current quantum computers. The strategy implements an algorithm in natural quantum interactions to process a variety of real-world problems faster than classical computers or conventional gate-based quantum computers can.

“Our finding eliminates many challenging requirements for quantum hardware,” said Nikolai Sinitsyn, a at Los Alamos National Laboratory. He is co-author of a paper on the approach in the journal Physical Review A. “Natural systems, such as the electronic spins of defects in diamond, have precisely the type of interactions needed for our process.”

Sinitsyn said the team hopes to collaborate with experimental physicists also at Los Alamos to demonstrate their approach using ultracold atoms. Modern technologies in are sufficiently advanced to demonstrate such computations with about 40 to 60 qubits, he said, which is enough to solve many problems not currently accessible by classical, or binary, computation. A is the basic unit of quantum information, analogous to a bit in familiar classical computing.

The protons and neutrons making up atomic nuclei are made up of a trio of even smaller fundamental particles known as quarks.

A new study has now mapped out in unprecedented detail the distribution of the different kinds of quark inside a proton, expanding on our understanding of this all-important part of an atom.

Although the quantum landscape within protons is a seething mess of quarks and their opposing antiquarks popping in and out of existence, there is a general dominance of two ‘flavors’ over the others; two up-flavor quarks and a single down-flavor quark.

Sabine Hossenfelder, Rupert Sheldrake and Bjorn Ekeberg go head to head on consciousness, panpsychism, physics and dard matter.

Watch more fiery contenet at https://iai.tv?utm_source=YouTube&utm_medium=description&utm…e-universe.

“Not only is the universe stranger than we think. It is stranger than we can think.” So argued Niels Bohr, one of the founders of quantum theory. We imagine our theories uncover how things are but, from quantum particles to dark matter, at fundamental levels the closer we get to what we imagine to be reality the stranger and more incomprehensible it appears to become.

Might science, and philosophy one day stretch to meet the universe’s strangeness? Or is the universe not so strange after all? Or should we give up the idea that we can uncover the essential character of the world, and with Bohr conclude that the strangeness of the universe and the quantum world transcend the limits of the human mind?

😗😁 2021


After appearing for decades in science fiction, then moving into an actual theory, a new patent for an updated warp drive was published last year to no fanfare. Like many other false starts in cutting-edge research, the patent may represent the next step in the expanding theory, or it could mean the practical, real-world design of a functioning warp drive is on the horizon.

Background: How to Bend Space-Time with A Warp Drive