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Updated: September 2025
I am a theoretical physicist working at the intersection of quantum and classical systems. My research often gravitates toward the complex systems community, where I apply methods of statistical physics to explore nanoscale devices and emergent phenomena in complex systems. I am also interested in quantum computing and the fundaments of thermodynamics.
I was a staff member of the T4 group at LANL (Condensed matter and Complex Systems), where I am however still a guest scientist. I held the JRO fellowship position at Los Alamos National Laboratory (CNLS). Before, between 2014 and 2017, I was a scientist at Invenia Labs, and before that at UCL, and Oxford in reverse order. PhD from University of Waterloo/Perimeter Institute, and MSc and Bachelor from University of Pisa. Between January and May 2019 I taught a course on statistical mechanics at UMass Boston. You can find here my detailed research interests.
I am part of the Advanced Network Science Initiative (ANSI), and did work and collaborate with Invenia Labs (Cambridge, UK). I was a postdoctoral researcher at the London Institute for Mathematical Sciences, University College London, and OCIAM, Oxford, in reverse order. I am currently also a guest scientist at the University of Pisa.
Spectral Methods in Complex Systems.
Spectral Methods in Complex Systems.
See the last version (pdf) here: Spectral Methods in Complex Systems (v1)
You can buy the book on Amazon if you want the hardcover or paperback version.
The hardcover is cheaper as it is in black and white. The price covers basically printing costs plus a coffee and a croissant.
Work highlights:
Solf-Organizing Memristive Networks perspective:
https://arxiv.org/abs/2509.00747
Classical Criticality via Quantum Annealing:
https://arxiv.org/abs/2505.13625
Thermodynamic cost of computing machines
https://arxiv.org/abs/2411.16088v1
DARPA report on quantum computing applications:
https://arxiv.org/abs/2406.06625
Uncontrolled learning with neuromorphic hardware: https://advanced.onlinelibrary.wiley.com/doi/full/10.1002/aisy.202400739
Centrality measures via Cavity: https://www.pnas.org/doi/10.1073/pnas.2403682121
Lack of ergodicity in spin ice:
https://www.nature.com/articles/s41467-023-41235-4
Deep physical reservoir computing with spin ice:
https://www.nature.com/articles/s41467-024-50633-1
Glass transitions in spin ice:
https://www.nature.com/articles/s41567-022-01538-7
Reservoir computing with artificial vortex ice:
https://www.nature.com/articles/s41565-022-01091-7
Rumbling transitions in memristive networks:
https://www.science.org/doi/10.1126/sciadv.abh1542
Rank-1 approximation to matrix inverses and centrality:
https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.5.033123
Production networks and ecology:
https://www.pnas.org/doi/10.1073/pnas.2106031118
Topological Order in Artificial Spin Ice:
https://www.nature.com/articles/s41567-018-0077-0
Memristive networks exact equations: https://journals.aps.org/pre/abstract/10.1103/PhysRevE.95.022140
Local potential approximation in quantum gravity:
Tools:
Here, you can find a description of Evolving Networks, the software we use for simulating graphs with memory.
Here you can find the link to the AMICI tool page.
A Matlab function for evaluating the transfer entropy of binary time series, and one for evaluating the path complexity of a graph
The page of the Nonlinear Time Series Analysis Toolbox to make predictions for chaotic time series. It is a collection of codes into a single GUI in Matlab. It uses State Space Reconstruction.
Here you can find the code for the memristive optimizer for QUBOs and here the script to use it. Here is a blog post about it, and the Julia implementation
A couple of fun facts about me.
A couple of hobbies.
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