Sonia Lopez Alarcon
Rochester Institute of Technology, NY·Computer Science
Quantum computers promise speedups for problems like drug design and financial modeling, but there is a mundane bottleneck in the way. On real hardware, qubits — the quantum bits that store information — can only interact with their immediate neighbors, so a program that needs two distant qubits to talk requires extra operations to shuttle their states together.
- Fields
Computer Science
Physics
Engineering
- Topics
quantum computing
quantum compilation
qubit routing
- Grants
- 1 known grant, through Sep 2027
What they work on
- Train machine learning models to identify and synthesize qubit routing algorithms tailored to a specific quantum device and objective, including selection of optimal parameters and optimization functions.
- Explore alternative quantum circuit representations, including hypergraph circuit descriptions and ZX-calculus diagrammatic rewriting, to handle the scalability of the routing problem.
- Address the joint problem of routing among physical qubits and composing logical qubits under quantum error correction and in Noisy Intermediate-Scale Quantum regimes, targeting improved fault tolerance and large-scale entanglement.
More about the research
This is the qubit routing problem, and because every extra operation adds noise, poor routing can destroy a computation. This project develops compilation techniques that make routing more scalable and more reliable.
Why it matters
Routing overhead is one of the practical limits on what today's noisy quantum machines can run, since each added operation introduces error. Compilers that adapt their routing strategy to a specific device could let existing and near-term hardware execute larger entangled computations reliably, benefiting anyone relying on quantum algorithms, and could ease the transition toward error-corrected machines.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Todd Brun
University of Southern California, CA·Physics
Develop weakly fault-tolerant quantum computing using error-detecting codes that store n–2 logical qubits in n physical qubits, detecting single faults and discarding runs that show errors, for use on near-term processors.
Steven Girvin
Yale University, CT·Physics
Design and deploy superconducting quantum hardware in which each logical qubit is one microwave photon shared between two long-lived resonators. This 'dual-rail' encoding turns photon loss into a detectable, flagged erasure error.
Milad Marvian
University of New Mexico, NM·Physics·Early-career
Develop mathematical models describing how errors propagate through quantum circuits, and use them to construct resource-efficient fault-tolerant computing subroutines.
The school
Rochester Institute of Technology: 9 labs on PI Pages, $78M a year on research, 65 research doctorates a year.
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