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HPQC Research Institution
From the smallest fluctuations to the limits of prediction.
We aim to investigate how microscopic quantum uncertainty relates to classical macroscopic unpredictability. Turbulence offers a demanding setting for that question, bringing fundamental physics, high-performance computing and careful measurement into the same conversation.
01 / The question
Where does a small uncertainty become consequential?
The ambition is to trace how uncertainty enters a physical system, how its dynamics transform that uncertainty, and what remains predictable at a larger scale. We want to identify the conditions under which a microscopic quantum contribution could matter for a specified macroscopic observable.
This is a proposed research programme. It does not establish that quantum uncertainty sets a universal forecast horizon, or that every unpredictable classical system needs a quantum explanation.
We aim to establish whether a physically justified connection can be measured between microscopic quantum fluctuations and macroscopic prediction limits.
02 / Two descriptions
A scale of dissipation. A relation between observables.
Classical turbulenceA continuum dissipation scale
Quantum stateA bound on position and momentum spread
Different physical descriptions. These relations do not define a shared length or a universal quantum–classical crossover.
The Kolmogorov length
In classical turbulence, η is a characteristic small scale where viscosity becomes important. Here ν is kinematic viscosity and ε is the mean rate of kinetic-energy dissipation per unit mass. The relation belongs to a continuum description, under the assumptions of Kolmogorov scaling. Its value depends on the flow.
For position and its conjugate momentum, σx and σp describe the statistical spreads in a quantum state; ℏ is the reduced Planck constant. This relation constrains their product. It does not supply a single length at which classical turbulence becomes quantum.
Three questions to ask of an uncertain prediction.
Quantum uncertainty
What distribution is specified by the quantum state, and which observable is measured? Any link to a larger-scale flow needs an explicit account of preparation, coupling and observation.
Chaotic sensitivity
How strongly do nearby initial states separate under the dynamics? A deterministic classical model can amplify small differences without invoking quantum randomness. Lorenz, 1963.
Measurement and model uncertainty
What is uncertain because observations are incomplete, instruments are imperfect, or a model omits relevant physics? Numerical resolution and approximation error must also be tested before attributing an effect to fundamental physics.
04 / A programme to test
Make the connection measurable.
Proposed directions, not reported findings.
Quantum turbulence provides a concrete comparison: superfluids and atomic condensates exhibit quantized vortices, with similarities to and differences from turbulence in ordinary fluids. Those systems call for models appropriate to their material and scale. They do not turn an ordinary atmospheric flow into a quantum fluid. Barenghi, Skrbek & Sreenivasan, 2014.
Specify the system. Choose a physical regime, observable and timescale. State which classical or quantum description applies and where its assumptions fail.
Track the contributions. Compare controlled initial perturbations, measurement error and model error. Introduce a quantum contribution only through a justified physical model.
Test what survives. Check convergence, conservation and uncertainty estimates against independent references. Report null results and the conditions under which an effect disappears.
High-performance and quantum computing are tools to investigate these questions. Their usefulness must be measured against strong classical methods with matched information, accuracy and resource accounting.
Edward N. Lorenz. Journal of the Atmospheric Sciences 20, 130–141 (1963). DOI: 10.1175/1520-0469(1963)020<0130:DNF>2.0.CO;2. A foundational study of sensitivity in a deterministic model.
Carlo F. Barenghi, Ladislav Skrbek & Katepalli R. Sreenivasan. PNAS 111, 4647–4652 (2014). DOI: 10.1073/pnas.1400033111. A review of quantum-fluid regimes and their classical comparisons.
Explore the work
A question becomes useful when it can be tested.
The workbench and research notes show how we approach bounded problems. The weather interface uses synthetic data; it is an exploration of a proposed workflow.
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