Episode 56: Apprehending Quantum Computation with Alba Cervera-Lierta

Timestamps

(1:55) Alba shared her background growing up interested in studying Physics and pivoting into quantum mechanics.(3:33) Alba went over her Bachelor’s in Fundamental Physics at The University of Barcelona.(4:54) Alba continued her education with an M.S. degree that specialized in Particle Physics and Gravitation.(6:40) Alba started her Ph.D. in Physics in 2015 and discussed her first publication, “Operational Approach to Bell Inequalities: Application to Qutrits.”(9:48) Alba also spent time as a visiting scholar at the University of Oxford and the University of Madrid during her Ph.D.(11:25) Alba explained her second paper to understand the connection between maximal entanglement and the fundamental symmetries of high-energy physics.(13:27) Alba dissected her next work titled “Multipartite Entanglement in Spin Chains and The Hyperdeterminant.”(18:56) Alba shared the origin of Quantic, a quantum computation joint effort between the University of Barcelona and the Barcelona Supercomputing Center.(22:27) Alba unpacked her article “Quantum Computation: Playing The Quantum Symphony,” making a metaphor between quantum computing and musical symphony.(27:47) Alba discussed the motivation and contribution of her paper “Exact Ising Model Simulation On A Quantum Computer.”(32:51) Alba recalled creating a tutorial that ended up winning the Teach Me QISKit challenge from IBM back in 2018.(35:01) Alba elaborated on her paper “Quantum Circuits For the Maximally Entangled States,” which designs a series of quantum circuits that generate absolute maximally entangled states to benchmark a quantum computer.(38:54) Alba dissected key ideas in her paper “Data Re-Uploading For a Universal Quantum Classifier.”(43:51) Alba explained how she leveled up her knowledge of classical neural networks.(47:40) Alba shared her experience as a Postdoctoral Fellow at The Matter Lab at the University of Toronto — working on quantum machine learning and variational quantum algorithms (checked out the Quantum Research Seminars Toronto that she has been organizing).(52:18) Alba explained her work on the Meta-Variational Quantum Eigensolver algorithm capable of learning the ground state energy profile of a parametrized Hamiltonian.(59:23) Alba went over Tequila, a development package for quantum algorithms in Python that her group created.(01:04:49) Alba presented a quantum calling for new algorithms, applications, architectures, quantum-classical interface, and more (as presented here).(01:08:59) Alba has been active in education and public outreach activities about encouraging scientific vocations for young minds, especially in Catalonia.(01:12:07) Closing segment.

Her Contact Info

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Her Recommended Resources

Ewin Tang (Ph.D. Student in Theoretical Computer Science at the University of Washington)Alán Aspuru-Guzik (Professor of Chemistry and Computer Science at the University of Toronto, Alba’s current supervisor)José Ignacio Latorre (Professor of Theoretical Physics at the University of Barcelona, Alba’s former supervisor)Quantum Computation and Quantum Information (by Michael Nielsen and Isaac Chuang)Quantum Field Theory and The Standard Model (by Matthew Schwarz)The Structure of Scientific Revolutions (by Thomas Kuhn)Against Method (by Paul Feyerabend)Quantum Computing Since Democritus (by Scott Aaronson)

About the show

Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe.

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