Researchers at Pacific Northwest National Laboratory have developed a new algorithm, Picasso, that reduces quantum data preparation time by 85%, addressing a key bottleneck in hybrid quantum-classical computing. The algorithm uses advanced graph analytics and clique partitioning to compress and organize massive datasets, making it feasible to prepare quantum inputs from problems 50 times larger than previous tools allowed. The PNNL team was able to lighten the computational load substantially by developing new graph analytics methods to group the Pauli operations, slashing the number of Pauli strings included in the calculation by about 85 percent. Altogether, the algorithm solved a problem with 2 million Pauli strings and a trillion-plus relationships in 15 minutes. Compared to other approaches, the team’s algorithm can process input from nearly 50 times as many Pauli strings, or vertices, and more than 2,400 times as many relationships, or edges. The scientists reduced the computational load through a technique known as clique partitioning. Instead of pulling along all the available data through each stage of computation, the team created a way to use a much smaller amount of the data to guide its calculations by sorting similar items into distinct groupings known as “cliques.” The goal is to sort all data into the smallest number of cliques possible and still enable accurate calculations. By combining sparsification techniques with AI-guided optimization, Picasso enables efficient scaling toward quantum systems with hundreds or thousands of qubits.
Scientists develop OS that allows quantum computers to connect with each other, paving the way for a quantum internet
Scientists have developed the world’s first operating system for quantum computers, QNodeOS. This system allows quantum computers to connect with each other, paving the way for a quantum internet. QNodeOS operates by combining a classical network processing unit (CNPU) with a quantum network processing unit (QNPU), which controls the quantum code. The QNodeOS connects to a separate quantum device called the QDevice, which is responsible for executing quantum operations. The QDriver is a key component of QNodeOS, enabling it to control different types of quantum computers. The QNodeOS was demonstrated by connecting different quantum computers together and running a test program. Further experimentation is required, including using more quantum computers of different types and increasing the distance between them. The architecture could be improved by having the CNPU and QNPU on a single system board to avoid millisecond delays in communication. A quantum computer operating system represents a major step forward in their development, with potential applications for distributed quantum computing and potentially laying the foundations for a quantum internet.
Fujitsu and RIKEN develop world-leading 256-qubit superconducting quantum computer for more complex challenges like implementing error correction algorithms and seamless collaboration between quantum and classical computers
Fujitsu Limited and RIKEN have developed a 256-qubit superconducting quantum computer, which will be integrated into their hybrid quantum computing platform starting in Q1 2025. The computer builds on the 64-qubit version, launched with the Japanese Ministry of Education, Culture, Sports, Science and Technology’s support in October 2023. The 256-qubit superconducting quantum computer will enable users to tackle complex challenges like analyzing larger molecules and implementing error correction algorithms. The platform will also enable seamless collaboration between quantum and classical computers, enabling efficient execution of hybrid quantum-classical algorithms. The computer overcomes technical challenges, including appropriate cooling within the dilution refrigerator. Scalable 3D connection structure: Enables efficient scaling of qubit count without requiring complex redesigns by arranging 4-qubit unit cells in a 3D configuration; The 256-qubit machine utilizes the same unit cell design established in its 64-qubit predecessor, effectively demonstrating the scalability of this architectural approach. Quadrupled implementation density within dilution refrigerator: Quadrupled implementation density achieved within the dilution refrigerator, allowing the 256-qubit machine to operate within the same cooling unit as the 64-qubit system; Highly optimized design that carefully balances heat generation from control circuits with the cooling capacity of the refrigerator, while maintaining the necessary ultra-high vacuum and extremely low temperatures