Taking stock of quantum machine learning—a critical perspective

PennyLane’s very own Maria Schuld recently gave a talk at the inaugural QML Meetup, summarizing some critical quantum machine learning insights. Check out the video below to learn why variational quantum models have a scaling problem, why the way we encode data must become more than an incidental choice …

Contributing to Pennylane with Jack Ceroni

Interested in hearing more about what it’s like to develop PennyLane? On the latest Quantum Computing Now podcast, Ethan Hansen sits down with PennyLane developer Jack Ceroni to hear about his experiences getting started with quantum, how he got into quantum software development, and answer the question “what in …

QHack QML Challenge Walkthrough: Variational Quantum Eigensolver

QHack 2021, the quantum machine learning (QML) hackathon, ran earlier this year from 17-26 February. A big portion of the event was the QML Challenge Leaderboard, where hundreds of teams raced to solve QML programming problems in order to claim hardware credits to help with their Open Hackathon projects. Solutions …

IonQ’s trapped ion hardware now available via PennyLane

We are excited to announce that PennyLane now natively supports quantum computing devices provided by IonQ! 🎉🍾 IonQ is the leading provider of quantum computers based on trapped ions. With long coherence times and all-to-all connectivity, trapped ions make a great hardware substrate for testing complex quantum computing algorithms, like those …

PennyLane v0.15 released

We’re excited to announce PennyLane v0.15, which comes with many new and exciting features. These include a new hardware device integration, more flexible shot control, brand new operations, and new methods for working with more powerful quantum circuits.