Advancements in machine learning have made it a crucial technology across many domains, from signal processing to healthcare. However, machine learning procedures suffer from gradient vanishing in high-dimensional parameter spaces and from quadratic sample sizes and training times for certain tasks. On the other hand, quantum computing offers exponential computational speedups for a family of problems. The combination of these two technologies, termed quantum machine learning, promises...

Holliday, Pugh, and Riggs proposed the idea that DNA methylation was palindromic, acted as an epigenetic mark, and that distinct enzymes were responsible for methylation of both modified and unmodified DNA already methylated on one strand. This idea was in response to Ohno et al. 1959; Lyon 1961, where X chromosome inactivation...

Entanglement renormalization is a numerical technique that locally reorganizes the Hilbert space of a quantum many-body system to reduce entanglement in its wave function. It addresses the computational challenges of real-space renormalization group RG methods, which struggle with the rapid growth of degrees of freedom during successive RG transformations. The key idea is...