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Category: quantum physics – Page 167

Scientists around the world work hard to rinse quantum systems for noise, which may disturb the function of tomorrow’s powerful quantum computers. Researchers from the Niels Bohr Institute (NBI) have found a way to use noise to process quantum information. This raises the performance of the quantum computing unit, the qubit.

An international collaboration led by scientists at the Niels Bohr Institute (NBI), University of Copenhagen, has demonstrated an alternative approach. Their method allows to use noise to process quantum information. As a result, the performance of the fundamental quantum computing unit of information, the qubit, is increased by 700 percent.

The results were published recently in the journal Nature Communications.

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The owner of Novo Nordisk, the drugmaker that gave the world Ozempic and Wegovy, is funding a new supercomputer powered by Nvidia’s artificial intelligence technology with a key aim of discovering new medicines and treatments.

The Novo Nordisk Foundation has awarded France’s Eviden a contract to build what the computing company says will be one of the world’s most powerful supercomputers, able to process vast amounts of data using AI.

It should provide “unprecedented potential to accelerate groundbreaking scientific discoveries in areas such as drug discovery, disease diagnosis and treatment,” Cédric Bourrasset, Eviden’s head of quantum computing, said in a statement.

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Researchers at Osaka University’s Institute of Scientific and Industrial Research (SANKEN) used the shortcuts to the adiabaticity (STA) method to greatly speed-up the adiabatic evolution of spin qubits. The spin flip fidelity after pulse optimization can be as high as 97.8% in GaAs quantum dots. This work may be applicable to other adiabatic passage and will be useful for fast and high-fidelity quantum control.

A quantum computer uses the superposition of “0” and “1” states to perform information processing, which is completely different from classical computing, thus allowing for the solution of certain problems at a much faster rate.

High-fidelity quantum state operation in large enough programmable qubit spaces is required to achieve the “quantum advantage.” The conventional method for changing quantum states uses pulse control, which is sensitive to noises and control errors.

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The 3 MLCT-excited [Ru(bpz)3]2+ and the spin-flip excited states of [Cr(dqp)2]3+ underwent photoinduced electron-transfer reactions with 12 amine-based electron donors similarly well, but provided cage escape quantum yields differing by up to an order of magnitude. In three exemplary benchmark photoredox reactions performed with different electron donors, the differences in the reaction rates observed when using either [Ru(bpz)3]2+ or [Cr(dqp)2]3+ as photocatalyst correlated with the magnitude of the cage escape quantum yields. These correlations indicate that the cage escape quantum yields play a decisive role in the reaction rates and quantum efficiencies of the photoredox reactions, and also illustrate that luminescence quenching experiments are insufficient for obtaining quantitative insights into photoredox reactivity.

From a purely physical chemistry perspective, these findings are not a priori surprising as the rate of photoproduct formation in an overall reaction comprising several consecutive elementary steps can be expressed as the product of the quantum yields of the individual elementary steps45,46. A recent report on solvent-dependent cage escape and photoredox studies suggested that the correlations between photoredox product formation rates and cage escape quantum yields might be observable11, but we are unaware of previous reports that have been able to demonstrate that the rate of product formation in several batch-type photoreactions correlates with the cage escape quantum yields determined from laser experiments. Synthetic photochemistry and mechanistic investigations are often conducted under substantially different conditions, which can lead to controversial discrepancies47,48,49, whereas here their mutual agreement seems remarkable, particularly given the complexity of the overall reactions.

The available data and the presented analysis suggest that the different cage escape behaviours of [Ru(bpz)3]2+ and [Cr(dqp)2]3+ originate in the fact that for any given electron donor, in-cage reverse electron transfer is ~0.3 eV more exergonic for the RuII complex than for the CrIII complex. Thermal reverse electron transfer between caged radical pairs therefore occurs more deeply in the Marcus inverted region with [Ru(bpz)3]2+ than with [Cr(dqp)2]3+, decelerating in-cage charge recombination in the RuII complex and increasing the cage escape quantum yields compared with the CrIII complex (Fig. 3D).

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Amidst rapid technological advancements, Tiny AI is emerging as a silent powerhouse. Imagine algorithms compressed to fit microchips yet capable of recognizing faces, translating languages, and predicting market trends. Tiny AI operates discreetly within our devices, orchestrating smart homes and propelling advancements in personalized medicine.

Tiny AI excels in efficiency, adaptability, and impact by utilizing compact neural networks, streamlined algorithms, and edge computing capabilities. It represents a form of artificial intelligence that is lightweight, efficient, and positioned to revolutionize various aspects of our daily lives.

Looking into the future, quantum computing and neuromorphic chips are new technologies taking us into unexplored areas. Quantum computing works differently than regular computers, allowing for faster problem-solving, realistic simulation of molecular interactions, and quicker decryption of codes. It is not just a sci-fi idea anymore; it’s becoming a real possibility.

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This paper introduces a novel theoretical framework for understanding consciousness, proposing a paradigm shift from traditional biological-centric views to a broader, universal perspective grounded in thermodynamics and systems theory. We posit that consciousness is not an exclusive attribute of biological entities but a fundamental feature of all systems exhibiting a particular form of intelligence. This intelligence is defined as the capacity of a system to efficiently utilize energy to reduce internal entropy, thereby fostering increased order and complexity. Supported by a robust mathematical model, the theory suggests that subjective experience, or what is often referred to as qualia, emerges from the intricate interplay of energy, entropy, and information within a system. This redefinition of consciousness and intelligence challenges existing paradigms and extends the potential for understanding and developing Artificial General Intelligence (AGI). The implications of this theory are vast, bridging gaps between cognitive science, artificial intelligence, philosophy, and physics, and providing a new lens through which to view the nature of consciousness itself.

Consciousness, traditionally viewed through the lens of biology and neurology, has long been a subject shrouded in mystery and debate. Philosophers, scientists, and thinkers have pondered over what consciousness is, how it arises, and why it appears to be a unique trait of certain biological organisms. The “hard problem” of consciousness, a term coined by philosopher David Chalmers, encapsulates the difficulty in explaining why and how physical processes in the brain give rise to subjective experiences.

Current research in cognitive science, neuroscience, and artificial intelligence offers various theories of consciousness, ranging from neural correlates of consciousness (NCCs) to quantum theories. However, these theories often face limitations in fully explaining the emergence and universality of consciousness.

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