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In quantum physics, the enigmatic dance between interactions and disorder unfolds in the intricate phenomenon known as many-body localization.

Quantum many-body systems may not thermalize due to the phenomenon of many-body localisation. Its theoretical underpinning is given by observables, the l-bits, which could not as of now be probed by experiments. The authors define experimentally relevant quantities to retrieve spatially resolved entanglement information, allowing to probe the l-bits.

Quantum computing is becoming more accessible for performing calculations. However, research indicates that there are inherent limitations, particularly related to the quality of the clock utilized.

There are different ideas about how quantum computers could be built. But they all have one thing in common: you use a quantum physical system – for example, individual atoms – and change their state by exposing them to very specific forces for a specific time. However, this means that in order to be able to rely on the quantum computing operation delivering the correct result, you need a clock that is as precise as possible.

But here you run into problems: perfect time measurement is impossible. Every clock has two fundamental properties: a certain precision and a certain time resolution. The time resolution indicates how small the time intervals are that can be measured – i.e. how quickly the clock ticks. Precision tells you how much inaccuracy you have to expect with every single tick.

Over the past twenty years, many companies, including Google, Microsoft, and IBM, have invested in quantum computing development. Investors have contributed over $5 billion to this cause. The aim is to use quantum physics properties to process information in ways that traditional computers cannot. Quantum computing could impact various fields, including drug discovery, cryptography, finance, and supply-chain logistics. However, the excitement around this technology has led to a mix of claims, making it hard to gauge the actual progress.

The main challenge in developing quantum computers is managing the ‘noise’ that can interfere with these sensitive systems. Quantum systems can be disrupted by disturbances like stray photons from heat, random signals from nearby electronics, or physical vibrations. This noise can cause errors or stop a quantum computation. Regardless of the processor size or the technology’s potential uses, a quantum computer will not surpass a classical computer unless the noise is controlled.

For a while, researchers thought they might have to tolerate some noise in their quantum systems, at least temporarily. They looked for applications that could still work effectively with this constraint. However, recent theoretical and experimental advances suggest that the noise issue might soon be resolved. A mix of hardware and software strategies is showing potential for reducing and correcting quantum errors. Earl Campbell, vice president of quantum science at Riverlane, a UK-based quantum computing company, believes there is growing evidence to be hopeful about quantum computing’s future.

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The third-generation superconducting quantum computer, “Origin Wukong,” was launched on January 6 at Origin Quantum Computing Technology in Hefei, according to Chinese-based media outlet, The Global Times, as reported by the Pakistan Today.

According to the news outlets, the “Origin Wukong” is powered by a 72-qubit superconducting quantum chip, known as the “Wukong chip.” This development marks a new milestone in China’s quantum computing journey as it’s the most advanced programmable and deliverable superconducting quantum computer in China, as per a joint statement from the Anhui Quantum Computing Engineering Research Center and the Anhui Provincial Key Laboratory of Quantum Computing Chips, shared with the Global Times.

Superconducting quantum computers, such as the “Origin Wukong,” rely on a approach being investigated by several other quantum computer makers, including IBM and Google quantum devices.

Einstein dreamed of a unified theory of nature’s laws. String theory has long promised to deliver it: a mathematically elegant description that some have called a “theory of everything.” Join one of the most influential groups of theorists ever assembled on a single stage to evaluate the current state of this most ambitious of theories.\
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Scientific knowledge can progress rapidly, yet its social, economic, and political impacts often unfold at a painstakingly slow pace. The medicine of the 21st century draws upon genetic and embryological breakthroughs of the 19th century. Our current technology is firmly grounded in quantum physics, which was formulated a century ago. And the topic of the day, artificial intelligence (AI), traces its origins to the secret weapons research during World War II.

‌In 1935, the brilliant British mathematician, Alan Turing, envisioned a conceptual computer. His genius would later lead him to crack the Enigma code used by German submarines for secret communications during the war. Turing’s contributions extended beyond cryptography, as he introduced fundamental concepts of AI, including the training of artificial neural networks. Benedict Cumberbatch portrayed Turing in the 2014 film The Imitation Game, which earned a screenplay Oscar that year. All this historical context brings us to the heart of the current AI revolution.

‌AI uses neural networks, also known as artificial neural networks, which are comprised of multiple layers of artificial neurons. Each neuron receives numerous inputs from the lower layer and produces a single output to the upper layer, similar to the dendrites and axon of natural neurons. As information progresses through each layer, it gradually becomes more abstract, resembling the process that occurs in the visual cortex of our brains.

Ever think you’d see a single atom without staring down the barrel of a powerful microscope? Oxford University physicist David Nadlinger has won the top prize in the fifth annual Engineering and Physical Sciences Research Council’s (EPSRC) national science photography competition for his image ‘Single Atom in an Ion Trap’, which does something incredible: makes a single atom visible to the human eye.

Click image to zoom. Photo: David Nadlinger/EPSRC

Captured on an ordinary digital camera, the image shows an atom of strontium suspended by electric fields emanating from the metal electrodes of an ion trap—those electrodes are about 2mm apart. Nadlinger shot the photo through the window of the ultra-high vacuum chamber that houses the ion trap, which is used to explore the potential of laser-cooled atomic ions in new applications such as highly accurate atomic clocks and sensors, and quantum computing.

One of the greatest challenges of modern physics is to find a coherent method for describing phenomena, on the cosmic and microscale. For over a hundred years, to describe reality on a cosmic scale we have been using general relativity theory, which has successfully undergone repeated attempts at falsification.

Albert Einstein curved space-time to describe gravity, and despite still-open questions about dark matter or dark energy, it seems, today, to be the best method of analyzing the past and future of the universe.

To describe phenomena on the scale of atoms, we use the second great theory: quantum mechanics, which differs from general relativity in basically everything. It uses flat space-time and a completely different mathematical apparatus, and most importantly, perceives reality radically differently.