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A new study in Physical Review Letters illuminates the intricacies of energy exchanges within bipartite quantum systems, offering profound insights into quantum coherence, pure dephasing effects, and the potential impact on future quantum technologies.

In quantum systems, the behavior of particles and are governed by probability distributions and wave functions, adding layers of complexity to the understanding of energy exchanges.

The exploration of energy exchanges in quantum systems inherently involves tackling the complexities arising from and the scales at which quantum systems operate, introducing sensitivity.

A study led by the University of Oxford has used the power of machine learning to overcome a key challenge affecting quantum devices. For the first time, the findings reveal a way to close the “reality gap”: the difference between predicted and observed behavior from quantum devices. The results have been published in Physical Review X.

Quantum computing could supercharge a wealth of applications, from climate modeling and financial forecasting to drug discovery and artificial intelligence. But this will require effective ways to scale and combine individual (also called qubits). A major barrier against this is inherent variability, where even apparently identical units exhibit different behaviors.

Functional variability is presumed to be caused by nanoscale imperfections in the materials from which quantum devices are made. Since there is no way to measure these directly, this internal disorder cannot be captured in simulations, leading to the gap in predicted and observed outcomes.

Although chaos theory can solve nearly anything that is unknown I basically think that in an infinite universe as made real from the infinite microchip that uses superfluid processing power is the real answer and we are off by factor of infinite parameters still.


When we look at scientific progress, especially in physics, it can seem like all the great discoveries lie behind us. Since the revolutions of Einstein’s theory of relativity and quantum mechanics, physicists have been struggling to find a way to make them fit together with little to no success. Tim Palmer argues that the answer to this stalemate lies in chaos theory.

Revisiting a book by John Horgan, science communicator and theoretical physicist Sabine Hossenfelder recently asked on her YouTube channel whether we are facing the end of science. It might seem like a rhetorical question — it’s not possible for science to really end — but she concludes that we are in dire need of some new paradigms in physics, and seemingly unable to arrive at them. We are yet to solve the deep ongoing mysteries of the dark universe and still haven’t convincingly synthesised quantum and gravitational physics. She suggests that ideas from chaos theory might hold some of the answers, and therefore the ability to rejuvenate science. I think she’s right.

Many physicists – perhaps most — might think this is surely a silly idea. After all, chaotic systems are describable by elementary classical Newtonian dynamics. The phenomenon of chaos can be illustrated by taking the simplest of dynamical systems, the pendulum, and simply adding a second pivot into its swinging arm. The motion of the tip of the pendulum arm is hard to predict, being sensitive to its exact starting conditions – the hallmark of chaos. Fascinating yes, but surely, if we have learned anything over the last 100 years it is this: we are not going to make progress in fundamental physics by going back to elementary classical dynamics.

The first functional semiconductor made from graphene has been created at the Georgia Institute of Technology. This could enable smaller and faster electronic devices and may have applications for quantum computing.

Credit: Georgia Institute of Technology.

Semiconductors, which are materials that conduct electricity under specific conditions, are foundational components of electronic devices like the chips in your computer, laptop, and smartphone. For many decades, their architecture has been getting smaller and more compact – a trend known as Moore’s Law. This has enabled gigantic leaps in a vast range of technologies, from general computing speeds and video game graphics, to the resolution of medical scans and the sensitivity of astronomical observatories.

For the first time, researchers have demonstrated the remarkable ability to perturb pairs of spatially separated yet interconnected quantum entangled particles without altering their shared properties.

The team includes researchers from the Structured Light Laboratory (School of Physics) at the University of the Witwatersrand in South Africa, led by Professor Andrew Forbes, in collaboration with string theorist Robert de Mello Koch from Huzhou University in China (previously from Wits University).

“We achieved this experimental milestone by entangling two identical photons and customizing their shared wave-function in such a way that their topology or structure becomes apparent only when the photons are treated as a unified entity,” explains lead author, Pedro Ornelas, an MSc student in the structured light laboratory.

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.