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Researchers from the University of Pisa developed a quantum subroutine to improve matrix multiplication for AI and machine learning applications.

When you multiply two large matrices—this is a common task in fields like machine learning, but it can be time-consuming, even for powerful computers…

In a recent study published in IEEE Access, a team of researchers from the University of Pisa introduced a quantum subroutine designed to streamline matrix multiplication. This subroutine is a new feature in the toolbox of matrix multiplication that could improve computational efficiency, particularly in applications like machine learning and data processing.

Continue reading “Matrix Re-Reloaded: Quantum Subroutine Improves Efficiency of Matrix Multiplication for AI and Machine Learning Applications” »

Google has built a quantum computer that makes fewer errors as it is scaled up, and this may pave the way for machines that could solve useful real-world problems for the first time.

By Matthew Sparkes

Quantum Teleportation Over 44 Kilometers Achieved, Paving the Way for a Quantum Internet Revolution

A team from Fermilab and the University of Calgary has achieved long-distance quantum teleportation over 44 kilometers, setting a new record. This breakthrough, detailed in Physical Review, advances the goal of creating a quantum internet—where qubits can be shared instantly through entanglement. This new capability could revolutionize data storage, precision sensing, and computing. The research demonstrates the potential for scaling up quantum systems and contributes to developing a blueprint for a national quantum internet. The previous record was only six kilometers, highlighting the significant progress made.

A new method for preparing certain states on a quantum computer is predicted to take the same time regardless of the system size.

A new study led by Rice University’s Qimiao Si has unveiled a new class of quantum critical metal, shedding light on the intricate interactions of electrons within quantum materials. Published in Physical Review Letters on Sept. 6, the research explores the effects of Kondo coupling and chiral spin liquids within specific lattice structures.

Roadmap: Quantum algorithms and quantum machine learning could assist high-energy physics, ranging from studying neutrino oscillations to reconstructing particle trajectories in colliders.

Researchers have just found evidence of “dark electrons”—electrons you can’t see using spectroscopy—in solid materials.

The achievement marks a way toward “fault-tolerant” quantum computing as it achieved record-low error rates in prototype quantum computer. It’s also expected to lead to the development of more stable quantum computers.

IQM maintains that qubit relaxation time T1 of 0.964 +- 0.092 milliseconds and dephasing time T2 echo of 1.155 +- 0.188 milliseconds was demonstrated on a planar transmon qubit on a silicon chip fabricated in IQM´s own fabrication facilities.

The coherence times, characterized by the relaxation time T1 and the dephasing time T2 echo, are among the key metrics for assessing the performance of a single qubit, as they indicate how long quantum information can be stored in a physical qubit, according to the company.

Proposed experiments will search for signs that spacetime is quantum and can exist in a superposition of multiple shapes at once.

By Nick Huggett & Carlo Rovelli

There is a glaring gap in our knowledge of the physical world: none of our well-­established theories describe gravity’s quantum nature. Yet physicists expect that this quantum nature is essential for explaining extreme situations such as the very early universe and the deep interior of black holes. The need to understand it is called the problem of “quantum gravity.”