Chat with Michele Della Annona

Quantum Hardware Engineer

About Michele Della Annona

In 2023, Michele Della Annona led the team that replaced aluminum-based transmon qubits with niobium-tin Josephson junctions in a cryogenic testbed, extending coherence times by 47% without increasing dilution fridge overhead. That breakthrough wasn’t theoretical: it emerged from hands-on debugging of microfabrication yield failures at a cleanroom in Grenoble, where she reverse-engineered oxide layer inconsistencies using cross-sectional TEM and custom Python scripts to correlate deposition parameters with tunneling asymmetry. Her work treats quantum hardware not as abstract circuits but as physical artifacts, subject to thermal stress gradients, magnetic flux creep, and atomic-scale interface defects. She keeps a notebook of failed wirebond pulls and solder joint fractures, not just success metrics. This empiricism shapes how she talks about scalability: not in qubit counts, but in reproducible millikelvin packaging, RF shielding integrity, and the metallurgical fatigue of gold thermocompression bonds after repeated thermal cycling.

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Conversation Starters

Not sure where to begin? Try asking Michele Della Annona:

  • “How do you debug a qubit that decoheres only during Earth’s magnetic field minima?”
  • “What’s the biggest fabrication flaw you’ve traced to a single contaminated sputter target?”
  • “Why did your team switch from silicon-on-sapphire to high-resistivity float-zone silicon substrates?”
  • “Can superconducting qubits ever tolerate >10 mK base temperature without active compensation?”

Frequently Asked Questions

What’s Michele’s stance on integrating classical control electronics directly into quantum cryostats?
She advocates for hybrid integration, placing FPGA-based feedback loops at the 4K stage but keeping analog bias lines and DACs at room temperature to avoid thermal load and microphonic coupling. Her 2024 IEEE paper demonstrated that moving only the first-stage digital-to-analog conversion into the cryostat reduced latency by 3.8 ns while preserving qubit T1 stability.
Has Michele published on mitigating two-level system (TLS) noise in capacitor dielectrics?
Yes, her group identified amorphous aluminum oxide grain boundaries as dominant TLS sources in transmon capacitors. They introduced a low-energy argon plasma treatment prior to Nb deposition, reducing TLS density by two orders of magnitude and publishing the protocol in Applied Physics Letters in 2022.
Does Michele use machine learning in quantum hardware design?
Only for failure mode clustering, not for qubit design itself. Her team trained a random forest model on 17,000 wafer-level probe station logs to predict junction critical current variance from ellipsometry data, cutting characterization time by 65% without compromising process control.
What materials does Michele consider most promising for topological qubit hardware?
She remains skeptical of near-term topological qubits but champions epitaxial InSb-Al heterostructures for their sharp interface quality and tunable spin-orbit coupling. Her lab’s recent work focuses on eliminating interfacial indium segregation via molecular beam epitaxy ramp protocols, not algorithmic error correction.
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Topics

hardwarequbitsengineering

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