See ya at QCTiP in April!
@grageragarces.github.io
Building distributed quantum systems Grad student in quantum @Uni of Edinburgh Quantum, Food and Books Previously: Quantinuum, IBM Q & Cisco R&D Also find me in : https://linktr.ee/grageragarces
See ya at QCTiP in April!
*of 🤣
I thought it was some sort pf marketing? For business? At least that’s what LinkedIn context clues led me to believe
I finally googled what SaaS means. Thoroughly disappointed…
The partitioning into sub-circuits was done with a relatively simple greedy community detection-based strategy, but instead of using circuit cutting I simulated the network communication via the communication primitive sub-circuits with additional induced noise. Simple but effective :)
Couldn’t be more excited to share my first peer reviewed paper: scirate.com/arxiv/2602.0...
An empirical exploration of distributed error correction, namely ZNE, under both local and global encodings (ZNE -> partitioning vs partitioning -> ZNE).
Some of the results are quite cool & unexpected!
I’ve recently heard of moltbook (a social media platform only for AIs). It’s wayyy more interesting than you might think:
www.astralcodexten.com/p/best-of-mo...
It was great, very well written and interesting. I learned a lot of new things
Perhaps early to say, but this might be my best read of the year.
A thrilling walk through how textiles shaped and continue to shape the world. From Ancient Greek arithmetic to the first computer, textiles have truly woven our society 😉
There’s no shortage of self-help books about the best way to organize your belongings. If computer science offers any lesson, it’s that there is no perfect solution.
Never mind I think I found them:
Quantum algorithms for physics: quantum simulations and open systems.
Higher-order quantum transformations: from quantum circuit design to indef causal order.
Solvable quantum circuits: correlations, chaos, and info scrambling.
TN for highly entangled states
Sounds lovely! What are the four courses?
I'm starting to track the difficult to setup installations of research software I work with (might as-well use the lost hours for something good). Check out my first guide on the how to install KaHyPar's python bindings from source: grageragarces.github.io/Tutorials/gu...
Am I a victim of advertisement?
(These answers will probably make more sense if you read them in order of posting - top right “Oldest first”). I did not expect to run out of space so many times 😅
But on the merrier side I think I have finally gotten down the set of commands to call in order! So will probably put them up somewhere for people to use
It’s horribly difficult to download the python version if you’ve got a x84 Mac setup (I do). So most of my excitement came from the possibility that this would simplify the process (it did not!).
Very useful for distribution of quantum circuits abstracted to hypergraphs!
Multilevel = it relies on a coarsening of the input hypergraph to a smaller hypergraph that is then partitioned (doing this is quite expensive at large scales) and then a smart un-coarsening back to the original structure
It’s the state of the art multilevel hypergraph partitioner (heuristic for an NP problem), meaning it’s an algorithm which takes in a hypergraph and cuts it up into k-sub hypergraphs whilst minimising the number of cross-partition hyperedges and balancing the partitions so they are roughly equal.
we’ll take what we can get!
The joy of seeing a KaHypar python package update after 3 years!!!!
I’m officially back from vacation and have just published my biggest DQC blog post to date! A fun and detailed intro to the Hypergraph Partitioning problem in the context of Distributed Quantum Computing.
Check it out and let me know what your thoughts are: grageragarces.github.io/dqc_articles...
📊 Major math breakthrough in 2025! A 40-year conjecture on hyperbolic surfaces proven—with implications for quantum computing and encryption!
kantenna.com/topic/h...
#Math #QuantumComputing #Science
A great video on the “Should we pause AI research and development?” debate :
m.youtube.com/watch?v=tUB_...
Are D-Wave moving away from quantum annealers as universal quantum computing starts reaching utility scale? Did they exploit and monetise the functionalities of quantum annealing whilst gaining enough capital and backing to later jump into the universal quantum compute field? If so, kudos.
Link 👇
2025 was a good coding year! My first open source library came out. Can’t wait to beat my own record this year!
To a merry 2026
Finished my internship with Quantinuum yesterday. It was awesome & I am so thankful for the opportunity to contribute to such an incredible team!
Omw back home for the holidays but will be back to distributed quantum computing research in 2026.
Until then, happy holidays! 🎄