Assembly Theory Meets SETI: A Universal Biosignature

Series: Technosignatures | Part: 5 of 9

In 1976, Viking 1 landed on Mars carrying four experiments designed to detect life. One measured metabolic activity. Another looked for organic molecules. The problem? Every experiment assumed Martian life would resemble Earth biochemistry. When results came back ambiguous, we had no framework to interpret them. Forty years later, we still don't know if Viking detected life or not.

Lee Cronin, a chemist at the University of Glasgow, thinks this entire approach is backwards. We've been searching for life by looking for specific molecular signatures—DNA, amino acids, phospholipids—when we should be searching for something far more fundamental: complexity that requires selection.

This is assembly theory, and it might finally give us a universal biosignature that works regardless of substrate, chemistry, or evolutionary pathway. It's a framework that doesn't ask "does this look like Earth life?" but rather "could this thing exist without evolution?"

The implications for SETI are profound. Assembly theory provides a quantitative threshold for detecting life-like processes anywhere in the universe—on exoplanet atmospheres, in returned samples, in radio signals, even in non-carbon-based systems we haven't imagined yet.

The Assembly Index: Measuring Evolutionary Necessity

At its core, assembly theory makes one deceptively simple claim: complex objects that require many assembly steps to construct cannot arise from random processes alone. They require memory, selection, and iteration—in other words, they require evolution.

Cronin's team quantifies this with the assembly index (MA), which measures the minimum number of joining operations needed to construct an object from elementary building blocks. A simple molecule like methane (CH₄) has an assembly index of 1—you just stick carbon and hydrogen together once. But a protein with 150 amino acids in a specific sequence? That has an assembly index in the hundreds.

The key insight is that there's a threshold. Below MA ≈ 15, molecules can plausibly arise from random chemistry. Above that threshold, the combinatorial space becomes so vast that random assembly becomes statistically impossible on cosmological timescales. High assembly index implies evolutionary selection.

This gives us something SETI has desperately needed: a quantitative, substrate-independent marker for life-like processes. You don't need to know anything about an alien's biochemistry. You just need to measure complexity that can't exist without selection pressure over time.

Why Substrate Independence Matters for Alien Detection

Traditional biosignatures are hopelessly Earth-centric. Oxygen in an atmosphere might indicate photosynthesis—or it might indicate photochemistry. Phosphine might indicate life—or it might indicate volcanism. Methane, amino acids, even chirality—all of these have abiotic pathways.

Worse, they assume life elsewhere will use the same chemistry. What if alien life uses silicon polymers instead of carbon chains? What if it operates in liquid methane instead of water? What if it doesn't use DNA at all?

Assembly theory sidesteps this entirely. It doesn't care about chemical composition. It cares about copy number and assembly complexity. If you find many copies of a high-MA object, that object almost certainly required evolution to produce. The chemistry doesn't matter. The substrate doesn't matter. The physics of information processing through selection does.

This is what Cronin calls "life detection without a theory of life." You don't need to know what life is. You just need to know what life does: it produces high-complexity objects through iterative selection, and those objects appear in abundance because evolution discovered a replicable pathway.

From Molecules to Megastructures: Assembly Across Scales

The beauty of assembly theory is that it scales. The principle works whether you're analyzing:

• Molecules in a mass spectrometer → Detecting biosignatures in returned samples or atmospheric spectra
• Radio signal patterns → Identifying communication protocols with high algorithmic complexity
• Material structures → Recognizing engineered objects versus natural formations
• Orbital configurations → Distinguishing megastructures from asteroid belts

Cronin's lab has already demonstrated this works for terrestrial biochemistry. They analyzed samples from Earth, Mars, and meteorites. Earth samples consistently showed molecules with MA > 15. Mars and meteorites showed only low-MA molecules. The boundary was clean.

But the real test came when they analyzed non-biological complex systems. Crystals, despite their ordered structure, have low assembly indices because they form through repetitive lattice rules, not evolutionary selection. Polymers produced by random chemistry also stay below the threshold. Only systems with evolutionary memory breach MA ≈ 15 consistently.

This means assembly index could work on technosignatures too. A Dyson swarm doesn't just have high complexity—it has high assembly complexity. The configuration of orbits, energy collectors, and structural elements requires intentional design iteration. Random orbital debris doesn't look like that.

The Markov Blanket Connection: Assembly Requires Boundaries

There's a deep connection between assembly theory and the free energy principle that's worth making explicit. In Karl Friston's framework, life is defined by Markov blankets—statistical boundaries that separate internal states from external states while allowing conditional dependencies.

Assembly theory implicitly requires Markov blankets. You can't have evolutionary selection without something that persists across generations—a membrane, a replicator, a structure that maintains its organization while interacting with its environment. High assembly index signals the presence of such boundaries.

This is why assembly theory works as a biosignature: complexity that requires selection necessarily implies boundaries that define what gets selected. You can't evolve proteins without cells. You can't evolve megastructures without civilizations. The assembly index doesn't just measure complexity—it measures the persistence of organized systems under selection pressure.

In AToM terms, high assembly index indicates coherence over time (M = C/T). An object with MA > 15 demonstrates that something maintained sufficient internal coherence to survive iterative selection across many assembly steps. Random processes don't do that. Evolution does.

Atmospheric Assembly: Detecting Life on Exoplanets

One of the most exciting applications is exoplanet atmospheres. Current biosignature approaches look for disequilibrium gases—oxygen with methane, for example—but these have false positive problems. Assembly theory offers an alternative.

Instead of asking "is this gas biologically produced?", you ask: "does this atmosphere contain molecules with high assembly index?" If JWST or future telescopes detect molecules with MA > 15 in an exoplanet atmosphere, that's strong evidence for life, regardless of whether the molecules resemble anything on Earth.

This is particularly powerful for ruling out false positives. Abiotic processes can produce complex mixtures, but they don't produce high-MA molecules in abundance. Volcanism might release hundreds of chemical species, but nearly all will have MA < 10. A biosphere will produce a smaller set of molecules, but some will have MA > 20, and they'll appear in high copy numbers.

The signature isn't the presence of any one molecule. It's the distribution of assembly indices across the molecular population. Life produces a distinct pattern: a few high-MA molecules in great abundance, reflecting evolutionary optimization.

Radio SETI and Algorithmic Assembly

Assembly theory isn't limited to molecules. The same principle applies to information. A radio signal can have an assembly index based on its algorithmic complexity—how many operations are needed to generate the observed pattern?

Random noise has near-zero assembly index. Natural astrophysical signals (pulsars, masers) have low assembly index because they arise from simple physical processes. But a communication protocol? That has high assembly index. The structure of frames, error correction, modulation schemes—all of these require intentional design iteration.

This gives traditional radio SETI a new tool. Instead of just looking for narrow-band carriers or specific mathematical sequences, you can analyze the assembly complexity of candidate signals. A signal with high algorithmic assembly index didn't arise from natural processes. It required selection—either biological evolution or technological design, which is itself an evolutionary process.

The threshold is the same: below MA ≈ 15, natural explanations remain plausible. Above MA ≈ 15, you're looking at something that required memory and iteration to produce.

The Assembly Threshold as Existential Filter

There's a darker implication worth considering. If assembly theory is correct, then high-MA objects are vanishingly rare in the universe not just because evolution is rare, but because evolution capable of producing MA > 100 objects is exceptionally fragile.

Every extinction event resets the assembly clock. Every civilizational collapse destroys high-MA artifacts faster than they can be rebuilt. The Great Filter might not be about reaching technological sophistication—it might be about maintaining the institutional coherence necessary to produce ultra-high-MA systems.

Consider: a smartphone has an assembly index in the thousands. It requires global supply chains, semiconductor fabs, materials science, software engineering—all of which depend on stable institutional structures spanning decades. If civilization fragments, those structures collapse, and the assembly index of manufactured objects plummets.

This suggests that SETI signals might not just be rare because intelligence is rare, but because intelligence capable of sustained high-MA production is unstable on cosmic timescales. We might be searching for a phenomenon that only exists in brief windows before systems collapse back below the threshold.

In cliodynamic terms, high-MA technosignatures may only be detectable during integrative phases of secular cycles. During disintegrative phases, complexity collapses too rapidly for megastructures or interstellar communication to persist.

Practical Applications: What We Can Search For Now

Assembly theory provides several concrete search strategies for current and near-future SETI efforts:

For atmospheric characterization:

• Prioritize exoplanets where JWST can perform molecular spectroscopy
• Calculate assembly indices for detected molecules
• Look for distributions skewed toward a few high-MA molecules in abundance
• Rule out targets with only low-MA chemistry regardless of disequilibrium

For sample return missions:

• Design mass spectrometry protocols optimized for assembly index measurement
• Establish MA thresholds for declaring biosignature detection
• Test against Earth samples to calibrate the boundary
• Avoid reliance on Earth-specific molecular markers

For radio SETI:

• Develop algorithmic assembly metrics for candidate signals
• Filter out low-MA naturalistic explanations automatically
• Focus compute resources on high-MA candidates for deeper analysis
• Cross-reference with temporal persistence (high-MA signals should recur)

For optical SETI:

• Look for high-MA structural features in resolved imaging of stellar environments
• Analyze light curve complexity for non-random assembly signatures
• Search for infrared excess with high-MA orbital configurations
• Distinguish engineered patterns from natural clustering

The Ontological Question: What Counts as "Assembly"?

There's a philosophical wrinkle here that assembly theory doesn't fully resolve. How do we define the elementary building blocks from which assembly index is measured?

For molecules, it's relatively clear: atoms are elementary, and you count how many joining operations it takes to build the molecule. But for radio signals? For megastructures? For social institutions?

The choice of "elementary units" is arbitrary. You could measure the assembly index of a radio signal using bits, symbols, packets, or protocols, and you'd get different numbers. This doesn't invalidate the approach—it just means assembly index is scale-dependent.

What remains invariant is the threshold. Regardless of how you define elementary units, random processes produce low assembly index, and selection processes produce high assembly index. The specific number might shift, but the boundary persists.

This is actually encouraging for SETI. It means assembly theory is robust against our ignorance about alien systems. We don't need to correctly identify their fundamental units. We just need to measure complexity relative to some reasonable decomposition, and the life-versus-random distinction will emerge.

Beyond Detection: Assembly as Communication Protocol

Here's a speculative application: what if we intentionally design METI (Messaging Extraterrestrial Intelligence) signals to have maximal assembly index?

Instead of sending prime numbers or mathematical constants—which might have low algorithmic assembly—we could send information-dense packages with high assembly complexity. The signal itself would function as a biosignature, demonstrating that the sender possesses evolutionary selection processes (either biological or technological).

This flips the traditional METI approach. Instead of making signals easy to detect, you make them difficult to mistake for anything natural. High-MA signals can't arise from astrophysical processes, so any detection would immediately warrant follow-up.

The challenge is bandwidth. High assembly index requires specificity, and specificity requires data. A simple tone has low MA. A complex modulation scheme has higher MA but requires more transmission power and longer integration time. There's a trade-off between detectability and assembly complexity.

But the principle holds: if we want to be noticed, we should maximize the assembly index of our transmission. That's the universal biosignature strategy in reverse.

Where Assembly Theory Meets Coherence Geometry

In the AToM framework, assembly index is a direct measure of temporal coherence under constraint. Objects with high MA are objects that maintained their organizational integrity across many selection steps. They didn't dissolve into thermodynamic equilibrium. They didn't fragment under perturbation. They persisted.

This is coherence in the technical sense: the system's trajectory remained within a narrow region of state space despite environmental noise. High assembly index implies low entropy production relative to the constraints the system operates under. It implies a Markov blanket successfully insulated internal states from external chaos.

The assembly threshold MA ≈ 15 corresponds to a curvature threshold in coherence geometry. Below the threshold, systems explore state space randomly—high curvature, unstable trajectories, no persistent organization. Above the threshold, systems follow constrained trajectories shaped by selection—low curvature, stable attractors, coherent persistence.

Life isn't just complexity. Life is complexity that curvature can't erase. Assembly theory quantifies exactly that property.

Synthesis: A Universal Biosignature for the Technosignature Era

Assembly theory provides what SETI has lacked since its inception: a detection criterion that doesn't assume alien life resembles Earth life. It shifts the question from "what molecules should we look for?" to "what complexity patterns can only arise from selection?"

The assembly index isn't perfect. It's scale-dependent, threshold-sensitive, and computationally expensive to calculate for complex systems. But it's substrate-independent, quantitative, and testable. That makes it the most promising biosignature framework we've developed.

More importantly, it extends naturally to technosignatures. If intelligence is just evolution continuing by other means—cultural selection, technological iteration, institutional memory—then all products of intelligence should have high assembly index. Megastructures, communication protocols, atmospheric pollution, even orbital mechanics all carry the signature of selection.

We've been searching for aliens by looking for things that look like us. Assembly theory lets us search for things that look like evolution, regardless of substrate. That's the difference between asking "do you use DNA?" and asking "did you have to evolve to exist?"

The answer to the second question is observable. And it might be visible in atmospheric spectra, radio signals, and orbital configurations across the galaxy, if we learn to measure it correctly.

The next time we analyze a Mars sample, an exoplanet atmosphere, or a candidate SETI signal, we shouldn't just ask "is this biology?" We should ask: "what's the assembly index?" If it's above threshold, we're looking at something that required time, memory, and selection to produce.

And that, substrate-independent and universal, is as close to a definition of life as we're likely to get.

This is Part 5 of the Technosignatures series, exploring the scientific search for evidence of alien technology.

Previous: The Lurker Hypothesis: Could Something Already Be Here?
Next: Gravitational Wave Technosignatures: A New Search Channel

Further Reading

• Cronin, L., et al. (2023). "Assembly Theory Explains and Quantifies Selection and Evolution." Nature, 622, 321-328.
• Marshall, S. M., et al. (2021). "Identifying Molecules as Biosignatures with Assembly Theory and Mass Spectrometry." Nature Communications, 12, 3033.
• Walker, S. I., & Cronin, L. (2022). "The Algorithmic Origins of Life." Journal of the Royal Society Interface, 19, 20220152.
• Friston, K. (2013). "Life as We Know It." Journal of the Royal Society Interface, 10, 20130475.
• Turchin, P. (2016). Ages of Discord: A Structural-Demographic Analysis of American History. Beresta Books.