Posts by Jonathon Riddell
Just a near 1000x1000 tight binding simulation with an impurity in the middle.
#quantum #physics #condensedmatter
Things I think should be simpler and have a lower barrier to entry:
- scientific computing
- high performance computing
- domain specific methods and solutions in numerical computing & modelling
- quantum computing
- expressing ideas in code while taking advantage of any of the above
#quantum
I haven't been posting YouTube videos for a while. And there is a good reason for this. I got frustrated enough doing scientific / high performance computing day to day for quantum many body research, I decided to do something about it:
youtu.be/kn4CgpDj_Gk
#quantum #science
Nothing like a good rant after a referee report
youtu.be/yTDqVgaEN0U
@dulwichquantum.bsky.social
My recent preprint: arxiv.org/abs/2503.05698
#quantum
Ouch!
"These findings substantially shift the quantum advantage frontier and underscore that classical variational techniques, which are not fundamentally constrained by entanglement growth, remain competitive at larger system sizes than previously anticipated."
If you want to learn more I will be at APS March meeting talking about this work!
#quantum #physics #quantumcomputing
@bbrunetto.bsky.social
This behavior also appears to be stable: shifting the model away from the DU point, we still observe faster state design preparation, but the story is more complicated than being characterized only by entangling power.
The rate of approaching Haar statistics is governed by the entangling power of the static 2-local gates. Even modest entangling power is enough to be faster than circuits made up of 2-local Haar random gates.
We do this with two strategies: random driving only on the boundary, or random driving each qubit for each layer of the curcuit. Remarkably, at the dual unitary point this prepares state designs significantly faster than circuits built entirely from random unitaries.
In the past, studies have focused on the case where circuits are made up entirely of local random unitaries. Instead we approach the problem with fixed two-local gates, and restrict ourselves to inserting driving with one qubit random gates.
New preprint!
Here we demonstrate an optimal strategy to prepare approximate Haar random statistics with a quantum circuit.
arxiv.org/abs/2503.05698
#quantum #physics #science
I've always been passionate about this, and I recently had the opportunity to do another podcast: youtu.be/xtnFRWCvo9E?...
Scientific communication is a key task for scientists. It can come in all shapes and sizes. From attending undergraduate recruitment events, to writing clear and concise research articles and of course engaging with a wider audience. This is an ongoing task that should be prioritized.
AND of course signatures of more generic dynamics than traditional integrable models. The answer is yes! But with lots of open questions to push this truly to a spatially extended locally interacting Hamiltonian. #quantum #physics
With dual unitary models, and random circuit models showing us that it is possible to write down minimal models for quantum chaos and generic dynamics we asked the question: is it possible to construct a model for continuous (energy preserving) dynamics, which has analytically tractable properties?
🚀 Exciting insights from @unibirmingham! Quantum research is pushing boundaries and proving to be classically hard. Dive into the latest advancements and challenges in the field. #QuantumComputing #Research #Innovation @jonathon-riddell.bsky.social blog.bham.ac.uk/bear/2025/02... ^AKG
The best indicator of how close we are to quantum utility is that researchers who should be first or second wave adopters of the technology typically can't tell you what they'd do with it. #quantum
Agreed I feel like we are saying the same thing. I'm advocating / wishing more scientists would pick up c/c++.
Agreed! The problem is numpy and other libraries fairly often don't fit the workload you want or need for a given problem.
I agree python is a lovely front end when the tool you need exists.
Of course this is more nuanced than "python slow, c++ fast". In a lot of cases folks are building complex solutions in python with tools that aren't designed for their workload or problem, this is the edge case I care about. If a compiled library in python meets what you need, I'm all for it!
Am I wrong in thinking if c/c++ or other compiled languages just had good build and dependency tools, more people would adopt them in science as their default tool? Or is this wishful thinking? I like python a lot. I wouldn’t put python on the compute cluster I have access to.
#quantum #physics
Oo I'm tempted! How do you get involved?