| --- |
| license: other |
| license_name: brsx-open-license |
| license_link: https://brsxlabs.gt.tc/brsxlicense.html |
| pipeline_tag: zero-shot-classification |
| tags: |
| - Ising |
| - quantum |
| - phy |
| - physics |
| --- |
| |
| # IsingBreaker |
|
|
| ## Overview |
|
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| IsingBreaker is an experimental symbolic sequence classification model developed by BRSX-Labs. |
|
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| The model analyzes sequences composed of four symbolic tokens: |
|
|
| ```text |
| U D + - |
| ``` |
|
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| and estimates the degree of structural order present within the sequence. |
|
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| The goal is not language modeling, but pattern recognition, periodicity detection, and symbolic structure analysis. |
|
|
| --- |
|
|
| ## Classification Labels |
|
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| ### Absolute |
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| Perfect repeating motifs and highly ordered structures. |
|
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| Examples: |
|
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| ```text |
| UDUDUDUDUDUDUDUD... |
| UD+-UD+-UD+-UD+... |
| UU++DD--UU++DD--... |
| ``` |
|
|
| --- |
|
|
| ### Maybe |
|
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| Mostly ordered structures containing small local perturbations. |
|
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| Examples: |
|
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| ```text |
| UDUDUDUDUDDDUDUD... |
| UD+-UD++UD+-UD+-... |
| UU++DD--UU+DDD--... |
| ``` |
|
|
| --- |
|
|
| ### NoN |
|
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| Chaotic or non-periodic structures. |
|
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| Examples: |
|
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| ```text |
| U+D--DU+U-+D++UD... |
| +-U-++UU+D+-DDUU... |
| ``` |
|
|
| --- |
|
|
| ## Architecture |
|
|
| IsingBreaker uses a hybrid Mixture-of-Experts architecture composed of four independent expert branches: |
|
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| ### CNN Expert |
|
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| Captures local motifs and short-range symbolic structures. |
|
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| Specialized for: |
|
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| * Local repetition |
| * Motif detection |
| * Symbol blocks |
|
|
| --- |
|
|
| ### GRU Expert |
|
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| Captures sequential dependencies and order-sensitive patterns. |
|
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| Specialized for: |
|
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| * Temporal relationships |
| * Sequence continuity |
| * Ordered transitions |
|
|
| --- |
|
|
| ### Transformer Expert |
|
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| Captures long-range interactions between distant symbols. |
|
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| Specialized for: |
|
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| * Global structure |
| * Long-distance dependencies |
| * Pattern consistency |
|
|
| --- |
|
|
| ### Mamba Expert |
|
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| Provides efficient state-space sequence modeling. |
|
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| Specialized for: |
|
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| * Long-context symbolic reasoning |
| * Efficient memory retention |
| * Sequence compression |
|
|
| --- |
|
|
| ## Expert Fusion |
|
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| Outputs from all four experts are combined through a learned gating mechanism. |
|
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| The model dynamically allocates attention between experts depending on the structure of the input sequence. |
|
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| Example expert activity: |
|
|
| ```text |
| CNN 0.28 |
| GRU 0.24 |
| Transformer 0.22 |
| Mamba 0.26 |
| ``` |
|
|
| --- |
|
|
| ## Model Information |
|
|
| * Architecture: GenoLiteHybrid |
| * Parameters: ~88 Million |
| * Context Length: 64 |
| * Vocabulary Size: 4 |
| * Classes: 3 |
|
|
| --- |
|
|
| ## Dataset |
|
|
| Training dataset: |
|
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| * 1,500 Absolute samples |
| * 1,500 Maybe samples |
| * 1,500 NoN samples |
|
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| Total: |
|
|
| ```text |
| 4,500 unique samples |
| ``` |
|
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| All samples are unique and shuffled before training. |
|
|
| --- |
|
|
| ## Performance |
|
|
| Benchmark Accuracy: |
|
|
| ```text |
| 93%+ |
| ``` |
|
|
| The model demonstrates reliable separation between: |
|
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| * Fully ordered structures |
| * Partially corrupted structures |
| * Chaotic structures |
|
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| while generalizing to unseen motif combinations. |
|
|
| --- |
|
|
| ## Example |
|
|
| Input: |
|
|
| ```text |
| UDUD-UDUD+UDUD-UDUD+UDUD-UDUD+ |
| ``` |
|
|
| Prediction: |
|
|
| ```text |
| Absolute |
| ``` |
|
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| Confidence: |
|
|
| ```text |
| 0.94+ |
| ``` |
|
|
| --- |
|
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| ## License |
|
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| brsx-open-license |
|
|
| --- |
|
|
| ## Author |
|
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| BRSX-Labs |
|
|
