DLTER (Dimension-Labeled Theory of Emergent Reality) is built around one idea:
reality becomes usable when information is organized, stabilized, and updated around an observer.
In its full technical form, DLTER is a quantum-information framework that explores how spacetime, matter, and forces could
emerge from deeper informational structure (a “theory-of-everything” style attempt).
In NeuForm, we use a human-scale translation—DLTER Reality Types—to map how you tend to
process information, adapt to change, and maintain identity over time.
It’s not a label for who you are. It’s a model of your default settings when life requires an update.
Optional reading · skimmable by design · go as deep as you want. You can take the quiz without reading this page.
This exists for context, clarity, and the “show me the logic” crowd.
The three axes
DLTER Reality Types come from three independent (orthogonal) axes.
Think of them as three dials your system tends to return to—especially when things feel uncertain,
fast-moving, stressful, or high-stakes.
In plain language, the three axes describe:
how you route information (Perception),
how you create stability (Emergence),
and how you update identity (Identity Dynamics).
Perception Axis
IN ↔ EXWhere clarity tends to come from first
Perception describes your default input route under change:
do you form coherence by fitting information into an internal model first,
or by using external feedback first?
Everyone does both—DLTER is about which route you instinctively trust when you’re moving fast.
IN — Internal Reality Framer
You tend to pause, interpret, and “make it make sense” internally before committing.
You often want the why and the framework. Strength: depth and coherence. Watch-out: overthinking can delay action.
EX — External Reality Absorber
You tend to gain clarity through interaction—doing, testing, talking, iterating, getting feedback.
Strength: momentum and learning-by-contact. Watch-out: without feedback loops, you can feel scattered.
Emergence Axis
ST ↔ FLHow you create stability when life shifts
Emergence describes your stability strategy:
do you stabilize through structure (repeatable patterns),
or through adaptive flow (flexible reconfiguration)?
Neither is “better.” They solve different problems.
ST — Structured Stabilizer
You prefer consistent systems: routines, repeatable schedules, clear rules, and predictable progressions.
Strength: reliability and compounding. Watch-out: too much disruption can feel draining—or trigger rigidity.
FL — Fluid Transmuter
You prefer flexible systems: options, improvisation, rapid adaptation, and learning as you go.
Strength: resilience and responsiveness. Watch-out: without anchors, “flexible” can slide into inconsistent.
Identity Dynamics Axis
FX ↔ TRHow your self-model tends to update
Identity Dynamics describes how your sense of self stays coherent over time:
do you update through refinement, or through phases and deeper reorganizations?
This axis matters a lot for long-term change—because behavior tends to follow identity.
FX — Fixed Pattern Holder
You tend to keep a stable identity core and improve by upgrading the system around it.
Strength: consistency and commitment. Watch-out: if the current identity story can’t fit the next chapter, you may resist needed change.
TR — Transformational Observer
You tend to update identity through meaningful shifts, seasons, and reinvention phases.
Strength: ability to evolve and re-author the self. Watch-out: “reset energy” can become a loop if you don’t keep anchors.
Middle scores are not a flaw. They often signal blend capacity—you can operate near the center without collapsing into one extreme.
DLTER includes dedicated “liminal” types specifically to represent common, stable midpoint patterns.
The geometry model
DLTER is easiest to understand as a coordinate system.
You’re not being “typed” from one trait—you’re being mapped by a pattern across three independent dimensions.
Your result is an “identity geometry” profile: a readable snapshot of how your system tends to stay coherent under change.
1) Axis scores are continuous
You’re not a binary label. You can be strongly ST, lightly ST, or right down the middle.
Near-center scores often mean you can switch strategies depending on context.
2) Types are prototypes
A Reality Type is a stable “best-fit” configuration—useful as a reference point for decisions and self-coaching.
It’s less “this is who you are” and more “this is your default settings menu.”
3) Liminal types exist on purpose
Some people are genuinely stable near key midpoints (for example, ST/FL blend).
DLTER includes prototypes for those patterns instead of forcing everyone into extremes.
Your quiz result also shows a match strength. If it’s “Exploratory,” treat your top type as a starting point
and pay attention to your “neighbor” (secondary resonance) type—both can explain you.
Why 12 types (not 8) and what “liminal” actually means
If you only used extremes, you’d get 8 “corner” configurations (one for each IN/EX × ST/FL × FX/TR combination).
DLTER adds 4 additional prototypes to represent common boundary patterns that many people live in consistently:
Axis Synthesizer and Resonant Fieldholder represent a stable ST/FL blend on the Emergence axis.
Dimensional Anchor and Horizon Breaker represent a stable IN/EX blend on the Perception axis.
Translation: “liminal” doesn’t mean unclear. It means you can stabilize near the midpoint on a key dimension—
which is a real operating mode with real strengths.
The 12 type prototypes (coordinate shorthand used under the hood)
If you like clean structure, here’s the compact way the prototypes are represented internally.
Think of the prototypes as directional anchors, not a judgment.
Midpoint (“liminal”) prototypes sit at 0 on the blended axis.
DLTER type codes and their prototype vectors in [Perception, Emergence, Identity Dynamics] format.
Type
Code
Prototype vector [P,E,I]
1 · Inner Frameworker
IN–ST–FX
[-1, -1, -1]
2 · Internal Alchemist
IN–FL–TR
[-1, +1, +1]
3 · Dimensional Flowweaver
EX–FL–TR
[+1, +1, +1]
4 · External Catalyst
EX–FL–FX
[+1, +1, -1]
5 · Reality Architect
EX–ST–FX
[+1, -1, -1]
6 · Structured Empathic Lens
IN–ST–TR
[-1, -1, +1]
7 · Analytical Evolver
EX–ST–TR
[+1, -1, +1]
8 · Fluxbound Weaver
IN–FL–FX
[-1, +1, -1]
9 · Axis Synthesizer
IN–(ST/FL)–TR
[-1, 0, +1]
10 · Resonant Fieldholder
EX–(ST/FL)–TR
[+1, 0, +1]
11 · Dimensional Anchor
(IN/EX)–ST–FX
[0, -1, -1]
12 · Horizon Breaker
(IN/EX)–FL–TR
[0, +1, +1]
Practical tip: if you’re near the midpoint on an axis, adjacent types can behave like “neighbors.”
Your best-fit type is still useful, but nearby patterns often explain your flexibility.
Why the quiz works
The quiz works because it measures the same thing DLTER is modeling at the human scale:
your default response tendencies under change across three independent axes.
No single question “decides” your type. Your result comes from the pattern across repeated signals.
1) Axis separation
Items are written to reflect one axis at a time (Perception, Emergence, Identity Dynamics),
so your result isn’t one blended “personality soup.”
2) Redundancy beats noise
Multiple questions per axis reduce randomness. The tendency that repeats across contexts is usually the meaningful one.
3) Stable prototypes
Types are stable prototypes of common configurations. Your result is simply the best-fit match to the configuration your answers describe most consistently.
How to answer for accuracy: respond as “what you default to when life is changing,” not what you wish you did.
If you’ve changed recently, answer for your last 6–12 months, not your best day.
Under the hood
Here’s the deeper layer: what DLTER itself is trying to model—and why the Reality Types map cleanly onto it.
DLTER started as a physics framework: a quantum-information approach exploring how spacetime geometry,
matter, and forces could emerge from an underlying informational substrate.
Whether or not the physics layer ultimately succeeds as a “theory of everything,” the core idea is useful:
systems become coherent through labeled information + stabilization rules + update rules.
The Reality Types are a human-scale interface for those same processes—without requiring you to care about physics at all.
Important: NeuForm does not use DLTER as metaphysics, identity dogma, or “ultimate truth.”
We use it as a practical framework for behavior: how do you route information, stabilize under change, and update identity over time?
DLTER’s core model (plain language, not philosophy)
DLTER uses “information,” “emergence,” and “geometry” as modeling language for how complex systems become coherent.
In simple terms, it’s describing a loop most stable systems share:
Input + labeling: what gets noticed, how it’s categorized, and what gets ignored.
Stabilization: how patterns become repeatable—through structure (rules/routines) or flow (adaptive reconfiguration).
Update rules: how the system stays itself over time—refinement within a stable core or phase-based reorganization.
Coherence under constraint: the system has limited attention/energy, so it compresses complexity into a workable model.
That compression shapes “what feels real” and “what feels doable.”
Reality Types are just the readable interface for that loop.
They translate deep system behavior into a simple, practical map you can apply in real life.
What “dimension-labeled” means (without equations)
“Dimension-labeled” means the system doesn’t just process raw data—it processes labeled channels.
Labels are the categories that tell the system what a signal means and what it’s allowed to influence.
Labels create consistency
When you consistently label something as “important,” “threat,” “safe,” “mine,” or “worth it,” you route attention and energy accordingly.
Over time, those labels become the rails your habits and identity run on.
Labels shape what can emerge
What you can’t reliably label is harder to stabilize.
If the system can’t categorize a pattern, it can’t repeat it, track it, or build a plan around it.
Human-scale translation
In Reality Types language, the axis poles behave like preferred processing labels:
IN/EX (input route),
ST/FL (stability strategy),
FX/TR (update rule).
Applied to training
NeuForm change is often a labeling shift:
“training = punishment” becomes “training = skill,”
“diet = restriction” becomes “nutrition = strategy,”
“I’m inconsistent” becomes “my system needs different inputs.”
DLTER helps you pick labels and structures that your system can actually hold.
Why DLTER uses “geometry” language
“Geometry” here is not a claim about literal shapes floating in space.
It’s a modeling shortcut: in complex systems, the pattern of relationships behaves like a geometry.
Some things become “close” (easy to activate together), others become “far” (high friction), and clusters form (stable routines, identity stories).
In a mind: concepts feel close when they connect easily; identity feels stable when core meanings stay linked.
In behavior: routines are stable geometry; adaptation is reconfigurable geometry.
In training: the goal isn’t just discipline—it’s reducing friction by making the “right actions” closer to your default identity.
This is why NeuForm talks about “identity geometry”:
real change is often a re-wiring of what feels natural, what feels possible, and what feels like “me.”
How the three axes map to DLTER’s deeper layer
The Reality Types layer compresses the deeper theory into three human-readable system behaviors:
input routing, stability mechanics, and self-model updating.
That’s intentional: it’s the minimum model that still predicts where friction usually shows up.
Perception → input routing
Do you form coherence by building an internal map first (IN),
or by pulling feedback from the environment first (EX)?
Emergence → stability mechanics
Do you stabilize by keeping structure consistent (ST),
or by staying adaptive and reshaping continuously (FL)?
Identity Dynamics → update rule
Do you preserve a stable identity core and refine it (FX),
or do you update identity through phases and transformations (TR)?
If you only remember one thing: the types describe how your system stays coherent while reality demands updates.
What DLTER is careful not to claim
Not destiny: DLTER describes defaults, not limits. You can train flexibility, structure, and identity skills.
Not a diagnosis: it doesn’t assess disorders or mental health. If you need clinical support, DLTER is not the tool.
Not “ultimate truth”: DLTER is a model with a language layer. The fitness application is pragmatic—use what helps.
Not a claim that humans are “quantum gravity”: the Reality Types are inspired by the same system logic (information → stability → update),
not a literal physics statement about your brain.
Not a substitute for evidence: if a lens doesn’t improve decisions or adherence, you don’t force it.
What DLTER is not
Not a diagnostic tool. It does not assess mental health, disorders, or pathology.
Not a moral ranking. There are no “better” types—only different defaults with different tradeoffs.
Not astrology. It’s not based on birth data, mysticism, or fate narratives.
Not a typical personality test. DLTER isn’t trying to capture your entire personality; it focuses on how you respond to change.
Not a box. You can grow across all axes while still having a recognizable baseline configuration.
Not an excuse. “That’s my type” is not a reason to stay stuck; it’s a starting point for better strategies.
Not absolute truth. It’s designed for usefulness: clarity you can apply, not identity dogma.
Why this shows up inside NeuForm Fitness
NeuForm is built around one principle: the best plan is the one you can execute.
Most people don’t fail because they “don’t want it.” They fail because the plan fights their default stability strategy,
their information style, or their identity update pattern.
DLTER helps us coach and design programs that match how you naturally stabilize and adapt—so the fundamentals
(training, nutrition, recovery, habits) become less friction, more consistency, and better outcomes.
Training structure
ST often thrives with repeating templates, predictable progressions, and clear tracking.
FL often thrives with modular plans, smart variation, and options that preserve momentum when life gets messy.
Adherence loops
IN often adheres better when the “why” clicks: rationale, clarity, and internal buy-in before action.
EX often adheres better with feedback loops: action first, accountability, environment design, and visible metrics.
Long-term change
FX often changes via refinement: building systems that reinforce a stable identity (“this is just what I do”).
TR often changes via phases: structured “chapters,” resets, and identity shifts that create real momentum.
DLTER doesn’t replace fundamentals—it helps you apply fundamentals in a way that matches how you actually function.
And once you know your defaults, you can train the opposite skills on purpose when life demands it.
Ready to see your Reality Type?
24 questions · ~4–6 minutes · instant result (with match strength + axis breakdown)
You don’t need to memorize anything here. Use your type as a starting point: reduce friction, build consistency,
and make the identity you want easier to live.
