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A new quantum algorithm developed by University of Georgia statisticians addresses one of the most complex challenges in single-cell analysis, signaling significant impact in both the fields of computational biology and quantum computing.

The study, “Bisection Grover’s Search Algorithm and Its Application in Analyzing CITE-seq Data,” was published in the Journal of the American Statistical Association on Sept. 20.

While traditional approaches struggle to handle the immense amount of data generated from measuring both RNA and protein expression in individual cells, the new quantum algorithm enables analysis of data from a single-cell technology known as CITE-seq. It allows for selection of the most important markers from billions of possible combinations—a task that would be formidable using classical methods.

Leading by example is a core belief. I’ve always advocated for a leadership approach that empowers the team and fosters a culture of continuous learning. The focus on sustainability isn’t just about technology—it’s about cultivating an environment where innovation thrives and where every team member is aligned with the vision of creating a more energy-efficient future.

Operating on three core principles (empowerment, communication and accountability) drives success and ensures every decision made is in line with long-term goals of sustainability and growth. Empowering the team means trusting them to innovate and make decisions that move the company forward, while open communication ensures alignment as the organization scales.

Looking ahead, the future of data centers lies in sustainability and transparency. As the demand for computing power grows, so too will the need for solutions that minimize environmental impact.

The manipulation of mechanical strain in materials, also known as strain engineering, has allowed engineers to advance electronics over the past decades, for instance enhancing the mobility of charge carriers in devices. Over the past few years, some studies have tried to devise effective strategies to manipulate strain in two-dimensional (2D) semiconductors that are compatible with existing industrial processes.

Researchers at Stanford University recently introduced a CMOS-compatible approach to engineer the tensile strain (i.e., stretchiness) in monolayer semiconductor transistors.

This approach, outlined in a paper published in Nature Electronics, relies on the use of silicon nitride capping layers that can impart strain on monolayer molybdenum disulfide (MoS₂) transistors integrated on silicon substrates.

Researchers have developed a revolutionary method to produce entangled photon pairs using much thinner materials, drastically reducing the size of quantum computing components.

This breakthrough enables simpler, more compact setups for quantum technologies, potentially transforming fields from climate science to pharmaceuticals.

Breakthrough in Quantum Computing.

The classic strategy of continually shrinking transistors in silicon chips to create faster, more powerful computers is starting to fail us.

“Even though silicon works at these extremely small dimensions, the energy efficiency required to do one calculation has been going up, and this makes it highly unsustainable,” Deep Jariwala, an engineering professor at the University of Pennsylvania, told the Wall Street Journal in 2022. “Energy-wise it doesn’t make sense anymore.”

Continue reading “Silicon chips are no longer sustainable. Here’s what’s next” »

Researchers at the University of Chicago have developed a new method for enhancing quantum information systems by integrating trapped atom arrays with photonic devices.

This innovation allows for scalable quantum computing and networking by overcoming previous technological incompatibilities. The design features a semi-open chip that minimizes interference and enhances atom connectivity, promising significant advances in computational speed and interconnectivity for larger quantum systems.

Merging technologies for enhanced quantum computing.

A team of engineers at the University of Science and Technology of China has developed a new way to code data onto a diamond with higher density than prior methods. In their paper published in the journal Nature Photonics, the group notes that such optical discs could hold data safely at room temperature for millions of years.

Prior research has shown that it is possible to code data onto a diamond, allowing for much longer data storage than any other known method. But such efforts have produced low-density storage. In this new effort, the research team developed a new method for etching data onto a diamond that allows for much denser data storage, and thus for storing more information onto a single diamond.

In their work, the researchers used diamond pieces just a few millimeters in length—they were pursuing a proof of concept, not a true storage medium. Future versions, they note, could be the size of a Blu-ray disc. The new method involved the use of a laser to remove single carbon atoms from the surface of the diamond, leaving a tiny cavity. The cavity, the researchers note, exhibits a certain level of brightness when another laser is shone on it.

We present a DNA self-assembly based molecular data writing strategy to enable parallel movable-type printing for scalable DNA storage.

Researchers have managed to coax a quantum computer to pulse with a rhythm unlike any before—a rhythm that defies conventional physics. For the first time, scientists have transformed a quantum processor into a robust time crystal, a bizarre state of matter that ticks endlessly without external energy.

This achievement, the work of physicists from China and the United States, could mark a turning point for quantum computing. By stabilizing the delicate systems that underpin this cutting-edge technology, the experiment hints at a path toward practical quantum computers capable of solving problems far beyond the reach of traditional machines.

Unlike conventional phases, such as solids or liquids, time crystals exist in a state of perpetual motion. Let me explain.