©2019 by Michael Clarke-Whittet, all views expressed here are my own.

Michael Clarke-Whittet

PhD student in quantum biology tackling molecular noise and quantum decoherence.
I like playing music, hiking, and the rule of three in lists.

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  • Michael Clarke-Whittet

Quantum Biology, Quantum Computing, Bathtubs and Accordions.

A scientist might be interested in the way a particle acts, but to really understand it we need to contextualise it. Is the particle out in space, floating far away from planets and stars and black holes? Is it in a vacuum, in a lead-lined laboratory underground somewhere? Maybe it’s in a crystalline ocean on a far flung planet, or maybe it’s bobbing around in your blood or in a cell.

Physics tries to build generalised models of, say, a particle in an infinite box à la Schrodinger equation. But this tends to only be an idealized picture of a particle – even floating out in space the particle will still interact with gravity and cross paths with other objects out there. Even space isn’t as empty as we tend to think. Quantum mechanics have a measurement problem – when something interacts with quantum mechanics, you can alter the outcome. All of this can happen even in the emptiest regions of the universe. This is why mathematical modelling is useful in quantum physics, something which I am incidentally really bad at because empiricism works in much of life science.


So if interactions can change outcomes in quantum mechanics, the environment matters. First thing is first: yes, you could model a particle in a perfect vacuum, completely devoid of gravity and other forces as well as without any other particles or boundary effects. But that doesn’t exist. Even in the hard vacuum of space there are atoms, light, gravity, neutrinos, radiation etcetera and our best vacuum chambers on earth are more crowded still.

This is starting to feel quite complicated. How are we meant to predict how when things are going to come near our particle and how do we know if it will even change anything anyway? It’s so random, complicated, and unpredictable.


This is why we have the bath of harmonic oscillators. A harmonic oscillator is an approximation of another thing in the environment. They are describable by the sort of model that would describe the motion of the pendulum in a grandfather clock or an accordion in a hipster folk band – a periodic function. Meaning it swings or contracts and relaxes as time goes on.


Mathematically constructing a universe full of grandfather clocks or accordions is better than a completely empty universe but, as you might have noticed, our universe isn’t a box full of contracting and expanding accordions. For one thing we have unequal distributions in reality, as well as different types of oscillators, and uneven forces acting on each. Some accordions are bigger than others, and are being played more forcefully, bumping into each other, sharing the same tune or droning each other out. It's starting to sound like how I imagine 01:30 at a Bavarian Oktoberfest.

A better bath still has to choose a location because of the same problem – an ocean may be better represented by a bath of harmonic oscillators than space for example. Not to mention highly diverse environments, such as a cell. This is really the nub of the issue about bath models. Cells are heterogeneous environments. In fact, they are so crowded and hot that often decoherence (the transition from quantum mechanics to classical mechanics) is predicted to accelerate in life.

To model quantum mechanics inside cells we must use a relevant bath or model of the environment. Just like in real bathtubs, water is popular and is better than nothing. The good thing about using water is that a lot of important biological chemistry depends on water. The polar distribution of electrons between the big, electronegative oxygen and the small, relatively electropositive, hydrogens in H2O for many transient, fleeting interactions as well as crucial molecular shapes.


Clathrin (1XI4), a protein which forms important geometric cage-like structures

But just as cells aren’t full of grandfather clocks, they aren’t just bags of water either. They are completely swamped in big, complex molecules. Ambitious many-molecule simulations still tend to describe a protein as a sphere with a simple charge but proteins can be strikingly beautiful and geometric structures, with sophisticated biophysical and dynamic properties. Modelling one protein like this is a challenge, nevermind tens of millions of them, rolling, flexing, and rearranging in a single cell.



Human apoptosome (3J2T). A complex protein which carries out programmed cell death. These proteins are static so look stiff and rigid, but in reality they are... bendy and stretchy.

It’s a simulation problem, the supercomputers of the world could probably not achieve this in a realistic time. Encapsulating all of the important parameters of each molecule in a cell adds a layer of difficulty to the simulation. But all of these are important because these dynamics can interact and could regulate quantum mechanics.

To understand something we need to understand the forces acting on it.

The Room Temperature Effect is the observation that quantum mechanics can persist for a surprisingly long time in some experimental set-ups, hundreds of degrees hotter than the near-zero many physics experimentalists prefer.

At room-temperature, in fact, 300 Kelvin or thereabout – a temperature that is firmly in the land of the living. Most living creatures persist around 260 to 330 Kelvin (-13 to +57°C), an interesting observation to say the least for Quantum Biology.


So, in terms of baths and simulations, we are caught between a rock and a hard place. Baths tend to simplify and generalise the systems we are interested in. Our systems, especially such diverse and random ones, defy simulation. The solution to this for now is to walk the difficult path of choosing the aspects of our systems that are relevant and which ones can be ignored (if that is possible at all). In the future, quantum computing will be able to chug through these problems with relative ease, making it possible to effectively simulate a whole cell, a true renaissance for science.

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