QuantumCT’s ‘Chai & Quantum’ series begins with Yale’s Steven Girvin

Steven Girvin, Sterling Professor of Physics at Yale University, will begin a new community engagement initiative, offering direct access to expertise in quantum science. QuantumCT designed the series to increase public awareness and encourage connections within the quantum community, launching it alongside the opening of its new home at 101 College Street in New Haven’s innovation district, the company says.

QuantumCT states the series aims to increase awareness of quantum innovation through informal conversations, expert insights, and open dialogue. This event builds momentum toward qiskit fall fest connecticut 2026, signaling a long-term commitment to advancing quantum technologies in Connecticut.

QuantumCT Launches “Chai & Quantum” Community Engagement Series

The inaugural event also celebrates QuantumCT’s relocation to 101 College Street in New Haven, a deliberate location within Connecticut’s growing innovation district. This new space is intended to facilitate collaboration between researchers, entrepreneurs, and policymakers focused on advancing quantum technologies. The program’s launch signifies a commitment to making quantum science more accessible, and the new location reflects the increasing momentum within Connecticut’s tech sector.

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Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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