The challenge of observing and controlling complex phases of matter has long intrigued researchers, particularly when it comes to non-equilibrium systems like time crystals.
Researchers successfully observed topological time-crystalline order using superconducting qubits on a programmable quantum processor.
Predicting the behavior of many interacting quantum particles is a complex task, but it’s essential for unlocking the potential of quantum computing in real-world applications. A team of researchers, led by EPFL, has developed a new method to compare quantum algorithms and identify the most challenging quantum problems to solve.
Quantum systems, from subatomic particles to complex molecules, hold the key to understanding the workings of the universe. However, modeling these systems quickly becomes overwhelming due to their immense complexity. It’s like trying to predict the behavior of a massive crowd where everyone constantly influences everyone else. When you replace the crowd with quantum particles, you encounter what’s known as the “quantum many-body problem.”
Quantum many-body problems involve predicting the behavior of numerous interacting quantum particles. Solving these problems could lead to major breakthroughs in fields like chemistry and materials science, and even accelerate the development of technologies like quantum computers.
Researchers have achieved a breakthrough in observing intrinsic magnetic structures in kagome lattices, which may significantly influence future quantum computing and superconductivity applications.
A research team led by Prof. Qingyou Lu from the Hefei Institutes of Physical Science at the Chinese Academy of Sciences, in collaboration with Prof. Yimin Xiong from Anhui University, has achieved a groundbreaking discovery. Using advanced techniques such as magnetic force microscopy (MFM), electron paramagnetic resonance spectroscopy, and micromagnetic simulations, they have made the first-ever observation of intrinsic magnetic structures within a kagome lattice.
These findings, published recently in Advanced Science, shed new light on the behavior of materials, which is largely determined by the interaction between their internal electrons and lattice structure. Kagome lattices, known for their unique properties like Dirac points and flat bands, display extraordinary phenomena such as topological magnetism and unconventional superconductivity. These lattices are of great interest because of their potential to unlock new insights into high-temperature superconductivity and quantum computing. Despite this, the intrinsic spin patterns that define these materials have remained elusive—until now.
NASA has temporarily halted operations of its quantum computer after it produced unexpected results. The computer, which is still under development, is designed to simulate complex systems such as those found in space. However, during a recent test, the computer-generated results that were inconsistent with known physical laws.
NASA scientists are currently investigating the cause of the anomaly. They are also working to develop safeguards to prevent similar incidents from happening in the future.
The shutdown of the quantum computer is a setback for NASA’s efforts to develop new technologies for space exploration. However, it is also an opportunity to learn more about the potential of quantum computing.
Residents on Chicago’s Southeast Side are urging city and state officials to slow down the development of a quantum computing campus.
What is consciousness, and is it really inherent only to humans? In this video, we explore whether consciousness is not only inherent in humans, but also in animals, artificial intelligence, and even the universe itself. We dive into the complex concepts of panpsychism and quantum consciousness, looking at Roger Penrose and Stuart Hameroff’s Orch-OR project, which claims that quantum processes in microtubules may underlie consciousness. We will analyze Giulio Tononi’s Integral Information Theory, which proposes to quantify the level of consciousness in any system.
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A team of Chinese researchers, led by Wang Chao from Shanghai University, has demonstrated that D-Wave’s quantum annealing computers can crack encryption methods that safeguard sensitive global data.
This breakthrough, published in the Chinese Journal of Computers, emphasizes that quantum machines are closer than expected to threatening widely used cryptographic systems, including RSA and Advanced Encryption Standard (AES).
The research team’s experiments focused on leveraging D-Wave’s quantum technology to solve cryptographic problems. In their paper, titled “Quantum Annealing Public Key Cryptographic Attack Algorithm Based on D-Wave Advantage,” the researchers explained how quantum annealing could transform cryptographic attacks into combinatorial optimization problems, making them more manageable for quantum systems.
How do we assess quantum advantage when exact classical solutions are not available?
A quantum advantage is a demonstration of a solution for a problem for which a quantum computer can provide a demonstrable improvement over any classical method and classical resources in terms of accuracy, runtime…
Today, algorithms designed to solve this problem mostly rely on what we call variational methods, which are algorithms guaranteed to output an energy for a target system which cannot be lower than the exact solution — or the deepest valley — up to statistical uncertainties. An ideal quality metric for the ground state problem would not only allow the user to benchmark different methods against the same problem, but also different target problems when tackled by the same method.
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A research team led by National Tsing Hua University Department of Physics and Center for Quantum Science and Technology professor Chuu Chih-sung (褚志崧) has developed Taiwan’s first and the world’s smallest quantum computer, using a single photon, the university said yesterday.
Chuu said in the…
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The prediction that twisted semiconductor bilayers can host so-called non-Abelian states without a magnetic field holds promise for fault-tolerant quantum computing.
