Silicon spin qubits are promising for the realisation of scalable quantum computing platforms but their coherence times in natural silicon are limited by the non-zero nuclear spin of the 29Si isotope. Here, enriched 28 Si down to 2.3 ppm residual 29Si is obtained by focused ion beam implantation.
An international collaboration of researchers, led by Philip Walther at University of Vienna, have achieved a significant breakthrough in quantum technology, with the successful demonstration of quantum interference among several single photons using a novel resource-efficient platform. The work published in the journal Science Advances represents a notable advancement in optical quantum computing that paves the way for more scalable quantum technologies.
Interference among photons, a fundamental phenomenon in quantum optics, serves as a cornerstone of optical quantum computing.
It involves harnessing the properties of light, such as its wave-particle duality, to induce interference patterns, enabling the encoding and processing of quantum information.
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When Roger Penrose originally came out with the idea that the human brain uses quantum effects in microtubules and that was the origin of consciousness, many thought the idea was a little crazy. According to a new study, it turns out that Penrose was actually right… about the microtubules anyways. Let’s have a look.
Continue reading “Brain Really Uses Quantum Effects, New Study Finds” »
In a recent study merging the fields of quantum physics and computer science, Dr. Jun-Jie Zhang and Prof. Deyu Meng have explored the vulnerabilities of neural networks through the lens of the uncertainty principle in physics. Their work, published in the National Science Review, draws a parallel between the susceptibility of neural networks to targeted attacks and the limitations imposed by the uncertainty principle—a well-established theory in quantum physics that highlights the challenges of measuring certain pairs of properties simultaneously.
The researchers’ quantum-inspired analysis of neural network vulnerabilities suggests that adversarial attacks leverage the trade-off between the precision of input features and their computed gradients. “When considering the architecture of deep neural networks, which involve a loss function for learning, we can always define a conjugate variable for the inputs by determining the gradient of the loss function with respect to those inputs,” stated in the paper by Dr. Jun-Jie Zhang, whose expertise lies in mathematical physics.
This research is hopeful to prompt a reevaluation of the assumed robustness of neural networks and encourage a deeper comprehension of their limitations. By subjecting a neural network model to adversarial attacks, Dr. Zhang and Prof. Meng observed a compromise between the model’s accuracy and its resilience.
BASEL, Switzerland — A reliable and ultra-powerful quantum computer could finally be on the horizon. Researchers from the University of Basel and the NCCR SPIN in Switzerland have made an exciting advancement in the world of quantum computing, achieving the first controllable interaction between two “hole spin qubits” inside a standard silicon transistor. This leap forward could eventually allow quantum computer chips to carry millions of qubits — a feat that would drastically scale up their processing power and potentially replace the modern computer.
First, we need to explain some of the high-tech terms involved in the new study published in Nature Physics. A qubit is the quantum equivalent of a bit, the fundamental building block of data in conventional computing. While a standard bit can be either a 0 or a 1, qubits can be both simultaneously, thanks to the principles of quantum mechanics. This allows quantum computers to handle complex calculations at speeds today’s standard computers will never achieve.
The concept of hole spin qubits might sound even more abstract. In simple terms, in the materials used for making computer chips, electrons (tiny particles with negative charge) move around, and sometimes they leave behind empty spaces or “holes.”
The nuclear reactions that power the stars and forge the elements emerge from the interactions of the quantum mechanical particles, protons and neutrons. Explaining these processes is one of the most challenging unsolved problems in computational physics. As the mass of the colliding nuclei grows, the resources required to model them outpace even the most powerful conventional computers. Quantum computers could perform the necessary computations. However, they currently fall short of the required number of reliable and long-lived quantum bits. This research combined conventional computers and quantum computers to significantly accelerate the prospects of solving this problem.
The Impact
The researchers successfully used the hybrid computing scheme to simulate the scattering of two neutrons. This opens a path to computing nuclear reaction rates that are difficult or impossible to measure in a laboratory. These include reaction rates that play a role in astrophysics and national security. The hybrid scheme will also aid in simulating the properties of other quantum mechanical systems. For example, it could help researchers study the scattering of electrons with quantized atomic vibrations known as phonons, a process that underlies superconductivity.
Nice.
A novel quantum algorithm, which exploits the relation between the Lindblad master equation, stochastic differential equations, and Hamiltonian simulations, is proposed to simulate open quantum systems on a quantum computer.
The Quantum Insider (TQI) is the leading online resource dedicated exclusively to Quantum Computing.
The Quantum Insider (TQI) is the leading online resource dedicated exclusively to Quantum Computing.
