Author Archives: Gabriel Abrahams

Revealing Nature’s Quantum Compass – Kickoff Day

Yesterday marked the kickoff for the BBSRC’s funded Strategic Longer and Larger (sLoLa) scheme “Revealing Nature’s Quantum Compass”1. The sLoLa grants are a laudable endeavor by the UK government to fund “ambitious research projects that will deepen our understanding of life’s most fundamental processes”. It is wonderful to see the UK government taking seriously the importance of blue sky basic research, appreciating that asking deep questions is what drives scientific progress, often leading to unexpected breakthroughs with application down the line.

At the kickoff event, principal investigators presented on what their research can bring to the table. Much like entering a bakery2 where everything smells delicious and it seems impossible to choose, an overwhelming range of experimental and computational techniques were presented, each bringing to bear their own unique approach to tackling the outstanding problem: mechanistically, how is that birds (and other animals) can navigate distances up to thousands of kilometers using the Earth’s magnetic field. Alongside this, my own group is interested in how we can develop biotechnologies that take advantage of magnetic field sensitive biochemistry, which has a host of applications near and long term.

The challenge of linking the biochemistry of a single protein known to be magnetic field sensitive to a behavioral phenotype will require a highly interdisciplinary approach, and excitingly for this community, machine learning is being involved from the start. Prof. Degiacomi, a member of the core team, presented how his lab is developing ML techniques to reduce the computational burden of linking experimental results to protein dynamics informed by molecular dynamics simulation. On the flip-side, I hope such techniques will develop into methods we can use for design. Similar to enzymes, the proteins we are interested have a function depending on mechanisms far more complex than only structure and binding (not to trivialize either of these!). Magnetic field sensing in this context depends on creating an environment in which quantum entanglement can exist, and being able to transduce the state of this quantum entanglement into into a biological signal – thus far this second step in particular has remained highly elusive.

Ultimately, the day concluded with much enthusiasm and excitement for all that is to come. Watch this space!

  1. https://www.ox.ac.uk/news/2025-11-19-new-project-aims-reveal-nature-s-quantum-compass ↩︎
  2. Yes, I just returned from a symposium in Germany ↩︎

Creating scientific figures in Inkscape

As a rule in scientific education, at some point between starting undergraduate and doing professional research it would seem we are expected to simply start knowing how to do things, without necessarily any formal training. One example in my degree was writing code, but another, as it turns out, is drawing figures for papers. Today, I would like to assist with the latter!

Inkscape https://inkscape.org/ is free and very powerful. Paired with python plotting and the textext plugin https://github.com/textext/textext it can really handle a lot, from abstract concepts to technical diagrams to artistic illustrations. Here I’ll just describe the workflow for including LaTeX and plots generated in Matplotlib, the rest (the artsy bit) is more about playing around with the different tools to find an ideal workflow.

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GUI Slop

Previously, I wrote about writing GUI’s for controlling and monitoring experiments. For ML this might be useful for tracking model learning (e.g. the popular weights and biases platform), while in the wet-lab it is great for making experiments simpler and more reliable to run, monitor and record.

And as it turns out, AI is quite good at this!

I have been using VSCode CoPilot in agent mode with Gemini 2.5 Pro to create simple GUIs that can control my experiments, which has proved pretty effective. Although there is clearly a concern when interfacing AI generated code with real hardware (especially if you “vibe code”, that is, just run whatever it generates) in practice it has allowed me to quickly generate tools for testing purposes, cutting the time required for getting a project started from hours to minutes.

As an example, I recently needed to hook up a Helmholtz coil to some custom electronics, centred around a Teensy micro-controller and designed to output a precisely controlled current.

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GUI Science

There comes a point in every software-inclined lab based grad student’s life, where they think: now is the time to write a GUI for my software, to make it fast, easy to use, generalised so that others will use it too, the new paradigm for how to do research, etc. etc.

Of course such delusions of grandeur are rarely indulged, but when executed they certainly can produce useful outputs, as a well designed (or even, designed) GUI can improve an experimentalist’s life profoundly by simplifying, automating and standardising data acquisition, and by reducing the time to see results, allowing for shorter iteration cycles (this is known in engineering as “Design, Build, Test, Learn” cycle, in software it’s called “Coding”).

Having written a few GUIs in my time, I thought it might be helpful to share some experience I have, though it is by no means broad.

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Happily hallucinating (for humans)

Many of us in academia face worries about an uncertain future. As an undergraduate, exams, assignments, exchanging information via auditory and visual cues with other members of the species1, then as one moves through the pipeline there’s funding, publications, the expectation that you know something about something, what will I be when I eventually grow up2, and I haven’t even mentioned the perennial question that is, what am I going to cook tonight?!

I have faced all of these worries and more, and will no doubt continue to, but through talking to my peers, mentors and family, I’ve learnt a few lessons that have proved invaluable for me, and perhaps will be for you as well.

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In defence of chaos

I commend you on your skepticism, but even the skeptical mind must be prepared to accept the unacceptable when there is no alternative. If it looks like a duck, and quacks like a duck, we have at least to consider the possibility that we have a small aquatic bird of the family Anatidæ on our hands.

Douglas Adams

It’s not every day that someone recommends a new whizzbang note-taking software. It’s every second day, or third if you’re lucky. They all have their bells and whistles: Obsidian turns your notes into a funky graph that pulses with information, the web of complexity of your stored knowledge entrapping your attention as you dazzle in its splendour while also the little circles jostle and bounce in decadent harmony. Notion’s aesthetic simplicity belies its comprehensive capabilities, from writing your notes so you don’t need to, to exporting to the web so that the rest of us can read what you didn’t write because you didn’t need to. To pronounce Microsoft OneNote requires only five syllables, efficiently cramming in two extra words while only being one bit slower to say than the mysterious rock competitor. Apple notes can be shared with all the other Apple people who live their happy Apple lives in happy Apple land – and sometimes this even works!

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