Tensor networks enable researchers to tackle quantum physics problems previously thought to be solvable only by quantum computers. Credit: Lucy Reading-Ikkanda/Simons Foundation By applying a 1980s ...

Microsoft's 2029 quantum supercomputer ambitions may have hit a roadblock, as critics claim the company's 2025 quantum ...

Independent Researcher, West Des Moines, IA, USA. Finally, we distinguish two operational stages of Chrono-Emergence. The first is the primordial generation of the time-density field—and hence ...

TeNPy (short for 'Tensor Network Python') is a Python library for the simulation of strongly correlated quantum systems with tensor networks. The philosophy of this library is to get a new balance of ...

Abstract: In the current NISQ (Noisy Intermediate-Scale Quantum) era, simulating and verifying noisy quantum circuits is crucial but faces challenges such as quantum state explosion and complex noise ...

The third quarter of 2025 was dominated by massive rounds for companies developing AI chips and quantum computers. Over $2.5 billion went to AI, with wafer-scale chip maker Cerebras leading the pack ...

Hybrid HPC-Quantum Systems: Enterprises are exploring hybrid setups that tightly couple Quantum Processing Units (QPUs) with classical accelerators (GPUs/TPUs) to combine their strengths. For example, ...

We introduce efficient tensor network models for sequence processing motivated by correspondence to probabilistic graphical models, interpretability and resource compression. Inductive bias is ...

Developers can now take advantage of NVIDIA NIM packages to deploy enterprise generative AI, said NVIDIA CEO Jensen Huang. NVIDIA’s newest GPU platform is the Blackwell (Figure A), which companies ...

Circuit design for quantum machine learning remains a formidable challenge. Inspired by the applications of tensor networks across different fields and their novel presence in the classical machine ...