Encryption systems rely on “random” numbers, but conventional computers can’t generate them perfectly. New research shows that quantum physics can. By Alexander Nazaryan Researchers in Switzerland ...

Statistical models based on Gaussian random variables occupy a central position in modern data analysis, offering a mathematically tractable framework for inference, prediction and dimensionality ...

Conformist and anticonformist biases in acquiring cultural variants have been documented in humans and several nonhuman species. We introduce a framework for quantifying these biases when cultural ...

Fault-tolerant quantum computing architecture using hybrid qubits / Fault-tolerant quantum computing architecture based on hybrid qubits that utilize both DV and CV qubits simultaneously. It utilizes ...

u = pv.to_pseudo_obs(discrete_obs) controls = pv.FitControlsBicop(family_set=[pv.BicopFamily.gaussian]) copula = pv.Bicop(data=u, controls=controls,var_types = ['d ...

Quantum annealing (QA) is a cutting-edge algorithm that leverages the unique properties of quantum computing to tackle complex combinatorial optimization problems (a class of mathematical problems ...

Roll a die and ask students to identify the random variable. Since a die can only take on values of 1, 2, 3, 4, 5, or 6, this is a discrete random variable. Repeat ...

Fig 1. (Top) Generative model of Neural Continuous-Discrete State Space Model. (Bottom) Amortized inference for auxiliary variables and continuous-discrete Bayesian inference for states. This ...

Continuous-variable quantum key distribution offers simple, stable and easy-to-implement key distribution systems. The discrete modulation scheme further reduces the technical difficulty. The main ...