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Quantum Systems Modeled Without Prior Assumptions

An improved algorithm for learning the static and dynamic properties of a quantum system could have applications in quantum computing, simulation, and sensing.

Quantum systems are notoriously hard to study, control, and simulate. One key reason is that their full characterization requires a vast amount of information. Fortunately, in the past decade, scientists have shown that many physical properties of a quantum system can be efficiently predicted using much less information [1, 2]. Moreover, researchers have built quantum sensors that can measure these properties with a much smaller uncertainty compared with the best classical sensors [3]. Nevertheless, it has been difficult to achieve both efficient predictions and precise measurements at the same time. Now, building on previous breakthroughs in the field, Hong-Ye Hu at Harvard University and his colleagues have demonstrated a new algorithm that characterizes quantum systems of any size with optimal efficiency and precision [4].

Quantum theory faces ‘cultural gaps’ as computational limits reshape entanglement understanding

Quantum researchers in the twenty-first century are part of an international network that requires a great deal of interaction and communication. Around one hundred publications on the topic are produced every day, often by authors who work in close collaboration with one another. New developments and discoveries are quickly integrated into the field, usually within a matter of just a few weeks. Researchers immediately proceed to build on these findings with innovative ideas. That is what the day-to-day life in the field of quantum theory looks like as it celebrates the one-hundredth anniversary of the initial development of quantum mechanics.

In honor of this milestone, UNESCO has declared 2025 the International Year of Quantum Science and Technology. One of the latest discoveries in this special year comes from an international research group led by quantum physicist Jens Eisert, professor at Freie Universität Berlin. The group’s surprising findings have made a significant contribution to scientists’ understanding of .

Their study, “Entanglement Theory with Limited Computational Resources,” was recently published in the journal Nature Physics. The article shows that, in practice, the established method used to measure correlations in quantum mechanics might not function exactly as was previously assumed.

Scientists Propose Quantum Network to Finally Detect Universe’s Mysterious Missing Substance

Researchers at Tohoku University have shown that linking quantum sensors in optimized networks can dramatically boost their sensitivity. Uncovering dark matter, the invisible substance thought to bind galaxies together, remains one of the greatest mysteries in physics. While it cannot be directly

Physicists Find Hidden “Quantum Mirrors” That Trap Light in 2D Materials

Under certain conditions, two-dimensional (2D) materials can exhibit remarkable quantum states, including superconductivity and unusual types of magnetism. Scientists and engineers have long sought to understand why these phases appear and how they might be controlled.

A new study published in Nature Physics has identified a previously unnoticed characteristic that may shed light on the origins of these mysterious quantum behaviors.

Quantum simulations that once needed supercomputers now run on laptops

UB physicists have upgraded an old quantum shortcut, allowing ordinary laptops to solve problems that once needed supercomputers. A team at the University at Buffalo has made it possible to simulate complex quantum systems without needing a supercomputer. By expanding the truncated Wigner approximation, they’ve created an accessible, efficient way to model real-world quantum behavior. Their method translates dense equations into a ready-to-use format that runs on ordinary computers. It could transform how physicists explore quantum phenomena.

Picture diving deep into the quantum realm, where unimaginably small particles can exist and interact in more than a trillion possible ways at the same time.

It’s as complex as it sounds. To understand these mind-bending systems and their countless configurations, physicists usually turn to powerful supercomputers or artificial intelligence for help.

Oxford Physicists Simulate Quantum “Light from Darkness” for the First Time

Scientists have created the first real-time 3D simulations of how lasers alter the quantum vacuum. Using cutting-edge computational modeling, scientists from the University of Oxford, in collaboration with the Instituto Superior Técnico at the University of Lisbon, have successfully produced the fi

Optical system achieves terabit-per-second capacity and integrates quantum cryptography for long-term security

The artificial intelligence (AI) boom has created unprecedented demand for data traffic. But the infrastructure needed to support it faces mounting challenges. AI data centers must deliver faster, more reliable communication than ever before, while also confronting their soaring electricity use and a looming quantum security threat, which could one day break today’s encryption methods.

To address these challenges, a recent study published in Advanced Photonics proposes a quantum-secured architecture that involves minimal digital signal processing (DSP) consumption and meets all the stringent requirements for AI-driven data center optical interconnect (AI–DCI) scenarios. This system enables data to move at terabit-per-second speeds with while defending against future quantum threats.

“Our work paves the way for the next generation of secure, scalable, and cost-efficient optical interconnects, protecting AI-driven data centers against quantum security threats while meeting the high demands of modern data-driven applications,” the researchers state in their paper.

The quantum door mystery: Electrons that can’t find the exit

What happens when electrons leave a solid material? This seemingly simple phenomenon has, until now, eluded accurate theoretical description. In a new study, researchers have found the missing piece of the puzzle.

Imagine a frog sitting inside a box. The box has a large opening at a certain height. Can the frog escape? That depends on how much energy it has: if it can jump high enough, it could in principle make it out. But whether it actually succeeds is another question. The height of the jump alone isn’t enough—the frog also needs to jump through the opening.

A similar situation arises with inside a solid. When given a bit of extra energy—for example, by bombarding the material with additional electrons—they may be able to escape from the material.

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