Quantum Like Benchmark Context Sensitive Memory

---
name: quantum-like-benchmark-context-sensitive-memory
description: Quantum-like benchmark framework for context-sensitive associative memory with adaptive plasticity. Provides controlled methodology for comparing quantum-like vs classical associative memory models under weak structural support, order-sensitive recall, and staged task conditions.
version: 1.0
created: 2026-06-12
arxiv_id: 2606.12449
authors: Yashine H. Goolam Hossen, Lea Gassab, Travis J. A. Craddock
paper_title: A quantum-like benchmark for context-sensitive associative memory with adaptive plasticity
doi: 10.48550/arXiv.2606.12449
activation_keywords:
  - quantum-like memory
  - associative memory benchmark
  - context-sensitive memory
  - adaptive plasticity
  - order-sensitive recall
  - staged recall
  - homeostatic stabilization
  - weak structural support
  - temporal organization
  - memory dynamics
related_domains:
  - quantum cognition
  - associative memory
  - computational neuroscience
  - memory models
  - neural plasticity
---

# Quantum-like Benchmark for Context-Sensitive Associative Memory

## Core Insight

**No universal quantum-like advantage** — model classes distinguished by multi-objective profile (recall, temporal organization, context sensitivity) rather than single recall score. Quantum-like models preserve order sensitivity better; classical Markov-rate models achieve stronger raw recall.

## Key Methodology

### Order-Sensitive Adaptive-Plasticity Benchmark
1. **Staged Associative Recall**: Sequential task presentation testing memory across phases
2. **Weak Structural Support Screening**: Identify narrow non-monotonic useful regime
3. **Factorial Comparison**: Quantum-like vs matched real-valued no-phase vs Markov-rate controls
4. **Conservative Operating Point**: Fixed settings for fair comparison

### Model Classes Compared
- **Quantum-like**: Complex-valued associative memory with phase information
- **No-phase (real-valued)**: Same architecture without complex phase
- **Markov-rate**: Classical probabilistic model matched for comparison

### Plasticity Mechanisms Tested
- **Adaptive plasticity**: Dynamic weight updates during learning
- **Homeostatic stabilization**: Self-regulating synaptic strength
- **No-plasticity ablation**: Control condition to isolate structural support effects

## Key Findings

1. **Weak Structural Support Regime**:
   - Useful regime is **narrow and non-monotonic**
   - Weak structure alone **does not rescue recall** without plasticity

2. **Plasticity Contributions**:
   - Most useful recall gains from **adaptive plasticity**
   - **Homeostatic stabilization** particularly important
   - Plasticity more impactful than background structure

3. **Model Comparison Profile**:
   - **Markov-rate**: Stronger raw recall scores
   - **Quantum-like**: Better order sensitivity preservation
   - **Quantum-like**: More consistent stage-dependent organization

4. **Multi-Objective Evaluation**:
   - Single recall score insufficient for model comparison
   - Need: recall + temporal organization + context sensitivity profile

## Benchmark Framework

### Task Design
```
Stage 1: Initial encoding phase
Stage 2: Perturbation/interference
Stage 3: Retrieval with context changes
Stage 4: Order-sensitive recall test
```

### Evaluation Metrics
- **Raw recall strength**: Percentage correct retrieval
- **Order sensitivity**: Preservation of item sequence
- **Temporal organization**: Time-structure fidelity
- **Context sensitivity**: Adaptation to context shifts

### Controlled Variables
- Same task schedule across models
- Same perturbation profiles
- Same weak-support conditions
- Same plasticity settings

## Applications

### Memory Model Evaluation
- Benchmark new associative memory architectures
- Compare quantum-inspired vs classical approaches
- Test plasticity mechanisms under controlled conditions

### Memory System Design
- Identify optimal plasticity mechanisms
- Determine useful structural support levels
- Balance recall strength vs temporal fidelity

### Computational Memory Research
- Provide controlled comparison framework
- Establish multi-objective evaluation standards
- Guide quantum-like memory model development

## Implementation Notes

### Quantum-like Model Features
- Complex-valued representations (phase information)
- NOT biological quantum computation claim
- Phase encodes temporal/context information
- Enables interference patterns for organization

### Classical Control Features
- Real-valued representations
- Standard Hebbian or probabilistic dynamics
- Matched architecture for fair comparison
- No phase information

### Homeostatic Stabilization
- Self-regulating synaptic strength
- Prevents runaway excitation/inhibition
- Maintains network stability during learning
- Key for sustained memory performance

## Critical Insights

### Why No Quantum-like Advantage?
1. **Task design**: Benchmark explicitly tests context sensitivity, not just raw capacity
2. **Matched controls**: Fair comparison with equivalent classical models
3. **Multi-objective**: Different models excel on different metrics
4. **Weak support**: Regime where structural help is minimal, plasticity dominates

### What Distinguishes Models
- **Markov-rate**: Optimizes for immediate recall strength
- **Quantum-like**: Preserves relational structure (order, context)
- **Selection depends on application**: Choose based on which objective matters more

## Limitations

1. **"Quantum-like" formalism only**: Not claiming biological quantum computation
2. **Specific task schedule**: May not generalize to all memory paradigms
3. **Weak support regime**: Different regimes might show different patterns
4. **Model architecture specific**: Results may depend on implementation details

## Future Directions

1. Test with different task schedules
2. Explore moderate structural support regimes
3. Compare additional model architectures
4. Apply to experimental neural data
5. Investigate other quantum-like formalisms

## References

- arXiv:2606.12449 - Quantum-like benchmark for context-sensitive memory (primary)
- Quantum cognition literature
- Associative memory benchmark papers
- Homeostatic plasticity studies
- Temporal memory organization research