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Quantum Simulation Engine: Domain-Driven Design - Strategic Design

Version: 0.1 Date: 2026-02-06 Status: Draft

Domain Vision

The Quantum Simulation Engine provides on-device quantum algorithm experimentation within ruVector's always-on, agentic environment. It enables hybrid classical-quantum research on edge devices, allowing agents to leverage quantum algorithms (VQE, Grover, QAOA, QEC) without cloud services.

This is not a cloud quantum API. The engine answers: "What does this quantum circuit produce?" entirely on the local device, using classical state-vector simulation with SIMD acceleration.

The engine follows ruVector's event-driven model: inert when idle, activated on demand, resources released immediately. A 20-qubit simulation allocates 16 MiB of state vector on activation and frees it the moment the circuit completes. No background threads, no persistent memory, no warm pools.

The Universal Simulation Object

The power lies in a single underlying state-vector engine inside ruqu-sim. Once the linear algebra is fixed, everything else becomes interpretation:

Domain Qubits Become Gates Become Measurement Becomes Circuit Becomes
Chemistry Molecular orbitals Fermionic operators Energy estimates VQE ansatz
Optimization Decision variables Mixing/cost ops Cut values QAOA circuit
Search Database indices Oracle + diffusion Found element Grover iterations
Error Correction Data + ancilla qubits Stabilizer checks Syndrome bits QEC cycle
Cryptography Key register bits Quantum Fourier transform Period estimate Shor subroutine
Machine Learning Feature dimensions Parameterized rotations Classification Quantum kernel

Same linear algebra, different interpretations. Same state vector = superposition. Same measurement = probabilistic collapse with Born rule.

Strategic Design

Core Domain

Quantum State Simulation - The heart of the system, managing quantum state vectors, applying unitary gate operations, and performing projective measurements. This is where the primary complexity and innovation reside. Most circuits run in a single fast pass; only large entangled states or iterative variational loops require sustained computation.

Supporting Domains

  1. Circuit Construction - Building, validating, and optimizing quantum circuits
  2. State Management - State vector lifecycle, entanglement tracking, memory gating
  3. Measurement & Observation - Projective measurement, expectation values, syndrome extraction
  4. Algorithm Execution - High-level quantum algorithm implementations (VQE, Grover, QAOA, QEC)
  5. Optimization & Backend - SIMD acceleration, gate fusion, tensor network backends
  6. Deployment & Integration - WASM compilation, agent bridge, coherence bridge to ruQu

Generic Domains

  1. Linear Algebra - Complex number math, matrix-vector products, Kronecker products (via ruvector-math)
  2. Random Sampling - Measurement outcome sampling, noise injection (via rand crate)
  3. Logging/Tracing - Event recording, performance metrics (via tracing crate + ruvector-metrics)

Application Evolution

Timeline Capabilities Key Value
Phase 1 (Now) State vector sim, basic gates, VQE/Grover/QAOA Local quantum experimentation without cloud
Phase 2 (6mo) Tensor networks, noise models, surface code cycles Error correction research on edge devices
Phase 3 (12mo) GPU acceleration, OpenQASM 3.0 import, 30+ qubits Production-grade quantum algorithm research
Phase 4 (24mo) Quantum hardware bridge, hybrid cloud-local execution Real quantum device integration

Edge-First Quantum: The system eventually enables agents to reason about quantum algorithms without any network dependency.

Ecosystem Integration Map

+---------------------------------------------------------------------------+
|                        QUANTUM SIMULATION ENGINE                          |
|                                                                           |
|  +-------------------------------------------------------------------+   |
|  |                  CIRCUIT CONSTRUCTION DOMAIN                       |   |
|  |  QuantumCircuit | Gate | GateSchedule | CircuitOptimizer          |   |
|  |  Parameterized templates (VQE ansatz, QAOA mixer, Grover oracle)  |   |
|  +-------------------------------------------------------------------+   |
|                              |                                            |
|                              v                                            |
|  +-----------------------------+  +-----------------------------+        |
|  | CORE: QUANTUM STATE         |  | STATE MANAGEMENT            |        |
|  | SIMULATION                  |<-| DOMAIN                      |        |
|  |                             |  |                             |        |
|  | * State vector engine       |  | * Allocation / deallocation |        |
|  | * Gate application (SIMD)   |  | * Entanglement tracking     |        |
|  | * Unitary evolution         |  | * Memory gating (zero-idle) |        |
|  | * Tensor contraction        |  | * State checkpointing       |        |
|  +-----------------------------+  +-----------------------------+        |
|           |            |                      |                           |
|           v            v                      v                           |
|  +-----------------------------+  +-----------------------------+        |
|  | MEASUREMENT &               |  | ALGORITHM EXECUTION         |        |
|  | OBSERVATION DOMAIN          |  | DOMAIN                      |        |
|  |                             |  |                             |        |
|  | * Projective measurement    |  | * VQE + classical optimizer |        |
|  | * Expectation values        |  | * Grover auto-iteration     |        |
|  | * Shot-based sampling       |  | * QAOA graph-based circuits |        |
|  | * Syndrome extraction       |  | * Surface code + decoder    |        |
|  +-----------------------------+  +-----------------------------+        |
|                                            |                              |
|                                            v                              |
|  +-----------------------------+  +-----------------------------+        |
|  | OPTIMIZATION &              |  | DEPLOYMENT &                |        |
|  | BACKEND DOMAIN              |  | INTEGRATION DOMAIN          |        |
|  |                             |  |                             |        |
|  | * SIMD dispatch             |  | * WASM bindings (ruqu-wasm) |        |
|  | * Gate fusion               |  | * Agent bridge (activation) |        |
|  | * Tensor network backend    |  | * Observability / metrics   |        |
|  | * Cache-local strategies    |  | * Coherence bridge (ruQu)   |        |
|  +-----------------------------+  +-----------------------------+        |
|                                                                           |
+---------------------------------------------------------------------------+
                              |
         +--------------------+---------------------+
         |                    |                      |
         v                    v                      v
  +--------------+   +-----------------+   +------------------+
  | ruvector-    |   | ruvector-       |   | ruQu             |
  | math (SIMD)  |   | metrics         |   | (decoder bridge) |
  +--------------+   +-----------------+   +------------------+
         |                                          |
         v                                          v
  +--------------+   +-----------------+   +------------------+
  | ruvector-    |   | ruvector-       |   | cognitum-gate-   |
  | graph        |   | nervous-system  |   | kernel (tiles)   |
  +--------------+   +-----------------+   +------------------+
         |                    |
         v                    v
  +--------------+   +-----------------+
  | ruvector-    |   | sona (adaptive  |
  | mincut       |   |  learning)      |
  +--------------+   +-----------------+

Crate-to-Context Mapping

Bounded Context Primary Crate Supporting Crates
Circuit Construction ruqu-sim (new) -
Quantum State Simulation (Core) ruqu-sim (new) ruvector-math
State Management ruqu-sim (new) -
Measurement & Observation ruqu-sim (new) rand
Algorithm Execution ruqu-sim (new) ruvector-graph (QAOA)
Optimization & Backend ruqu-sim (new) ruvector-math (SIMD)
Deployment & Integration ruqu-wasm (new) ruqu, ruvector-metrics, ruvector-nervous-system

Context Map

+-----------------------------------------------------------------------+
|                     QUANTUM ENGINE CONTEXT MAP                         |
|                                                                        |
|                     [Published Language]                                |
|                     OpenQASM 3.0 format                                |
|                            |                                           |
|                            v                                           |
|   +------------------+         +------------------+                    |
|   |                  | Shared  |                  |                    |
|   |  CIRCUIT         | Kernel  |  STATE           |                    |
|   |  CONSTRUCTION    |<------->|  MANAGEMENT      |                    |
|   |                  | (Gate,  |                  |                    |
|   |  Builds circuits | QubitIdx|  Allocates and   |                    |
|   |  Validates gates |  types) |  tracks state    |                    |
|   +--------+---------+         +--------+---------+                    |
|            |                            |                              |
|            | Customer                   | Customer                     |
|            | Supplier                   | Supplier                     |
|            v                            v                              |
|   +------------------+         +------------------+                    |
|   |                  |         |                  |                    |
|   |  MEASUREMENT &   |-------->|  ALGORITHM       |                    |
|   |  OBSERVATION     |Supplier |  EXECUTION       |                    |
|   |                  |Customer |                  |                    |
|   |  Measures states |         |  Runs VQE/QAOA/  |                    |
|   |  Extracts syndr. |         |  Grover/QEC      |                    |
|   +--------+---------+         +--------+---------+                    |
|            |                            |                              |
|            +------------+---------------+                              |
|                         |                                              |
|                         v                                              |
|            +------------------+         +------------------+           |
|            |                  |         |                  |           |
|            |  OPTIMIZATION &  |         |  DEPLOYMENT &    |           |
|            |  BACKEND         |         |  INTEGRATION     |           |
|            |                  |         |                  |           |
|            |  SIMD, fusion,   |         |  WASM, agents,   |           |
|            |  tensor networks |         |  ruQu bridge     |           |
|            +------------------+         +--------+---------+           |
|                                                  |                     |
|                                    Conformist    | Anti-Corruption     |
|                                    (ruVector     | Layer               |
|                                     APIs)        | (ruQu decoder)     |
|                                                  |                     |
+--------------------------------------------------+---------------------+
                                                   |
                                                   v
                                     [Existing ruVector Ecosystem]

Context Relationships:
  <-------> Shared Kernel (shared types across boundary)
  -------> Customer-Supplier (downstream depends on upstream)
  Conformist: Deployment conforms to existing ruVector APIs
  ACL: CoherenceBridge wraps ruQu decoder behind anti-corruption layer
  Published Language: OpenQASM 3.0 for circuit interchange
  Open Host Service: ruqu-wasm exposes JS API

Relationship Summary

Upstream Downstream Pattern Shared Types
Circuit Construction State Management Shared Kernel Gate, QubitIndex, GateMatrix
Measurement & Observation Algorithm Execution Customer-Supplier MeasurementOutcome, ExpectationValue
State Management Algorithm Execution Customer-Supplier QuantumState, StateCheckpoint
State Management Measurement & Observation Customer-Supplier QuantumState, Amplitude
Optimization & Backend Core Simulation Partnership FusedGateMatrix, OptimizationHint
Existing ruVector APIs Deployment & Integration Conformist ruVector event types, metric types
ruQu decoder API Deployment & Integration Anti-Corruption Layer Isolated behind CoherenceBridge
Circuit Construction External tools Published Language OpenQASM 3.0 circuit format
Deployment & Integration JS consumers Open Host Service ruqu-wasm JS API

Ubiquitous Language

Quantum Fundamentals

Term Definition
Qubit Fundamental unit of quantum information existing in superposition of
Amplitude Complex number representing probability amplitude of a basis state; measurement probability is its squared modulus
State Vector Array of 2^n complex amplitudes representing the full quantum state of an n-qubit register
Basis State One of 2^n classical bit-string configurations; each has an associated amplitude
Superposition State where multiple basis states have nonzero amplitude
Entanglement Quantum correlation preventing independent per-qubit factorization of the joint state
Born Rule Measurement probability equals squared modulus of amplitude: P(x) =

Circuit Model

Term Definition
Gate Unitary matrix operation acting on 1 or 2 qubits; transforms state via matrix-vector multiply
Circuit Ordered sequence of gates applied to a qubit register; the program of a quantum computation
Gate Matrix Unitary matrix defining gate action; must satisfy U * U_dagger = I
Qubit Index Zero-based integer identifying a qubit; determines which amplitude pairs a gate addresses
Circuit Depth Maximum sequential gate layers; primary determinant of simulation time
Parameterized Gate Gate whose matrix depends on continuous real parameters (e.g., Ry(theta))
Gate Fusion Combining adjacent gates on same qubits into a single matrix multiply
Gate Schedule Topologically sorted gate-to-timestep assignment respecting qubit-sharing constraints

Measurement & Algorithms

Term Definition
Measurement Projective observation collapsing superposition to a basis state per the Born rule
Mid-Circuit Measurement Measurement during (not only at end of) circuit execution
Shot Single circuit execution + measurement; repeated shots build statistics
Expectation Value Observable average over quantum state: <psi
Pauli String Tensor product of per-qubit Pauli operators (I/X/Y/Z) with coefficient
Hamiltonian Hermitian operator (weighted sum of Pauli strings) representing total energy
Syndrome Classical bits from ancilla measurements indicating error presence and location
Ansatz Parameterized circuit template encoding the variational search space
VQE Variational Quantum Eigensolver; iteratively minimizes Hamiltonian expectation
QAOA Quantum Approximate Optimization Algorithm; alternating cost/mixer unitaries
Grover Search Amplitude amplification finding marked items in O(sqrt(N)) queries
Oracle Black-box gate marking target states by phase flip
Surface Code 2D topological QEC code with stabilizer checks on lattice faces/vertices
Logical Error Rate Undetected logical error probability per QEC cycle
Decoder Classical algorithm mapping syndromes to corrections; bridge to ruQu

Simulation Infrastructure

Term Definition
State Allocator On-demand allocation/deallocation enforcing zero-idle policy
Memory Estimate Predicted bytes: 2^n * 16; gating threshold for allocation
Entanglement Tracker Tracks qubit correlations enabling subsystem splitting
State Checkpoint Serialized state snapshot for mid-circuit save/restore
Tensor Network Alternative representation via contracted tensor factors; efficient for low entanglement
Contraction Path Tensor contraction order minimizing total FLOPs

Bounded Context Details

Context 1: Circuit Construction Domain

Purpose: Language for expressing quantum computations. Validation, scheduling, optimization, OpenQASM interchange.

Entity / Value Object Type Responsibility
QuantumCircuit Aggregate Root Ordered gate collection with register metadata
Gate Entity Single unitary with target qubits and optional parameters
GateSchedule Entity Time-step assignment for parallel execution analysis
CircuitOptimizer Domain Service Fusion, cancellation, and commutation rules
GateId, QubitIndex, GateMatrix, ParameterBinding, GateType Value Objects Immutable circuit building blocks

Events: CircuitCreated, GateAppended, CircuitOptimized, CircuitValidated, ParametersBound

Invariants: (1) Gate unitarity. (2) Qubit indices within bounds. (3) No duplicate targets per gate. (4) All parameters bound before execution.

Context 2: State Management Domain

Purpose: State vector lifecycle following zero-idle model. Entanglement tracking. Memory gating.

Entity / Value Object Type Responsibility
QuantumState Aggregate Root Owns the 2^n complex amplitude array
EntanglementTracker Entity Bipartite entanglement graph for subsystem analysis
StateAllocator Domain Service On-demand allocation, immediate deallocation
Amplitude, QubitCount, MemoryEstimate, StateCheckpoint Value Objects State representation primitives

Events: StateAllocated, StateDeallocated, EntanglementDetected, SubsystemSplit, CheckpointCreated, MemoryLimitExceeded

Invariants: (1) Normalization preserved. (2) Zero-idle: no state persists beyond execution. (3) Allocation gated by device capacity. (4) Checkpoint restore reproduces exact amplitudes.

Context 3: Measurement & Observation Domain

Purpose: Projective measurement with collapse. Analytical expectation values. Syndrome extraction for QEC.

Entity / Value Object Type Responsibility
MeasurementEngine Aggregate Root Born-rule sampling and state collapse
ExpectationCalculator Entity Analytical <psi
SyndromeExtractor Entity Ancilla measurement and classical bit extraction
MeasurementOutcome, PauliString, Hamiltonian, SyndromeBits, ShotResult Value Objects Measurement data types

Events: MeasurementPerformed, ExpectationComputed, SyndromeExtracted, ShotsCompleted

Invariants: (1) Born rule: probabilities sum to 1.0. (2) Post-measurement collapse to definite state. (3) Hamiltonian Hermiticity. (4) Syndrome bit count matches code.

Context 4: Algorithm Execution Domain

Purpose: High-level quantum algorithms as orchestrated loops over circuits, states, and measurements.

Entity / Value Object Type Responsibility
VQERunner Entity Iterative ansatz parameter optimization to minimize energy
GroverSearch Entity Oracle + diffusion with auto-computed iteration count
QAOASolver Entity Graph-based cost/mixer circuit construction and angle optimization
SurfaceCodeSimulator Entity Stabilizer cycles, syndrome extraction, decoder invocation
AlgorithmResult, OptimizationTrace, CutValue, LogicalErrorRate, ConvergenceCriteria Value Objects Algorithm output types

Events: VQEIterationCompleted, VQEConverged, GroverSearchCompleted, QAOARoundCompleted, SurfaceCodeCycleCompleted, LogicalErrorDetected

Invariants: (1) Grover iteration count = floor(pi/4 * sqrt(N/M)). (2) VQE energy is upper bound on ground state. (3) QAOA cost/mixer alternate with correct parameter count. (4) Surface code distance matches lattice.

Context 5: Optimization & Backend Domain

Purpose: Performance backends that accelerate simulation without altering semantics. SIMD, fusion, tensor networks.

Entity / Value Object Type Responsibility
SimulationBackend Aggregate Root Selects optimal execution strategy
GateFuser Entity Combines compatible gate sequences into single operations
TensorContractor Entity Tensor network decomposition for low-entanglement states
SIMDDispatcher Entity Platform detection and optimized kernel dispatch
OptimizationHint, ContractionPath, FusedGateMatrix, PlatformCapabilities Value Objects Backend selection metadata

Events: BackendSelected, GatesFused, TensorNetworkContracted, SIMDKernelDispatched

Invariants: (1) Fused gates produce identical results to sequential. (2) Tensor contraction matches state-vector. (3) SIMD falls back to scalar if unavailable. (4) Intermediates stay within memory budget.

Context 6: Deployment & Integration Domain

Purpose: WASM compilation, agent activation bridge, ruQu decoder anti-corruption layer, observability.

Entity / Value Object Type Responsibility
WASMBindings Entity Open Host Service via wasm-bindgen JS API
AgentBridge Entity ruvector-nervous-system integration for context-triggered activation
MetricsReporter Entity Publishes SimulationMetrics to ruvector-metrics
CoherenceBridge Entity ACL translating syndromes to ruQu's DetectorBitmap/SyndromeRound
PlatformCapabilities, QubitLimit, SimulationMetrics, DecoderResult Value Objects Integration data types

Events: SimulationRequested, SimulationCompleted, ResourcesReleased, DecoderInvoked, MetricsPublished

Integration Patterns:

  • Anti-Corruption Layer: CoherenceBridge isolates engine from ruQu's internal DDD model
  • Conformist: Deployment conforms to existing ruVector event types and metric schemas
  • Open Host Service: ruqu-wasm exposes clean JS/TS API for browser experimentation
  • Published Language: OpenQASM 3.0 for circuit interchange with external tools

Cross-Cutting Concerns

Zero-Idle Resource Model

IDLE (0 bytes) --> ACTIVATE (allocate 2^n * 16 bytes) --> COMPUTE --> RELEASE (0 bytes)

No warm pools, no pre-allocated buffers, no background threads.

Memory Gating

Qubits State Vector Size Decision
10 16 KiB Always permit
15 512 KiB Always permit
20 16 MiB Permit on most devices
25 512 MiB Gate: check available RAM
30 16 GiB Gate: likely refuse on edge
35+ 512 GiB+ Always refuse (state vector); consider tensor network

Error Model

Context Error Severity Recovery
Circuit Construction Non-unitary gate Fatal Reject circuit
State Management Memory limit exceeded Recoverable Try tensor network or refuse
State Management Normalization drift Warning Renormalize
Measurement Zero-probability outcome Warning Return uniform
Algorithm Execution VQE non-convergence Recoverable Return best-so-far
Deployment WASM memory limit Fatal Report to agent
Deployment ruQu decoder unavailable Recoverable Skip correction, log

Observability

All simulation runs produce SimulationMetrics (circuit name, qubit count, gate count, depth, shots, backend type, wall time, peak memory, SIMD utilization) flowing through ruvector-metrics for unified dashboard integration.

Security

Concern Mitigation
Timing side channels in measurement Constant-time sampling via rejection method
Memory contents after deallocation Zero-fill on deallocation (SecureAllocator mode)
Denial-of-service via large qubit counts Memory gating with hard upper bound per request
Untrusted OpenQASM input Parser validates unitarity and qubit bounds before execution
WASM sandbox escape No file I/O, no network; pure computation within WASM sandbox

Module Structure

crates/ruqu-sim/src/
+-- lib.rs                     # Public API
+-- circuit/                   # Circuit Construction context
|   +-- quantum_circuit.rs     # QuantumCircuit aggregate
|   +-- gate.rs                # Gate entity, GateType enum
|   +-- schedule.rs            # GateSchedule
|   +-- optimizer.rs           # CircuitOptimizer (fusion, cancel)
|   +-- openqasm.rs            # OpenQASM 3.0 import/export
+-- state/                     # State Management context
|   +-- quantum_state.rs       # QuantumState aggregate
|   +-- allocator.rs           # StateAllocator (zero-idle)
|   +-- entanglement.rs        # EntanglementTracker
|   +-- checkpoint.rs          # StateCheckpoint
+-- measurement/               # Measurement & Observation context
|   +-- engine.rs              # MeasurementEngine
|   +-- expectation.rs         # ExpectationCalculator
|   +-- syndrome.rs            # SyndromeExtractor
+-- algorithms/                # Algorithm Execution context
|   +-- vqe.rs, grover.rs      # VQERunner, GroverSearch
|   +-- qaoa.rs                # QAOASolver
|   +-- surface_code.rs        # SurfaceCodeSimulator
+-- backend/                   # Optimization & Backend context
|   +-- simulation_backend.rs  # SimulationBackend
|   +-- gate_fuser.rs          # GateFuser
|   +-- tensor_network.rs      # TensorContractor
|   +-- simd_dispatch.rs       # SIMDDispatcher
|   +-- kernels/               # avx2.rs, avx512.rs, neon.rs, wasm_simd.rs, scalar.rs
+-- types.rs, events.rs, error.rs

crates/ruqu-wasm/src/
+-- lib.rs                     # wasm-bindgen entry
+-- js_api.rs                  # JS-facing API
+-- agent_bridge.rs            # ruvector-nervous-system integration
+-- coherence_bridge.rs        # ACL for ruQu decoder
+-- metrics.rs                 # ruvector-metrics export

Dependency Graph

ruqu-sim
+-- ruvector-math           (SIMD kernels, complex math)
+-- rand                    (measurement sampling)
+-- ruvector-graph          (QAOA graph input)

ruqu-wasm
+-- ruqu-sim                (core simulation)
+-- ruqu                    (coherence bridge ACL)
+-- ruvector-metrics        (observability)
+-- ruvector-nervous-system (agent activation)
+-- wasm-bindgen            (JS bindings)

Performance Targets

Metric Target
Single-gate (1q, 20-qubit register) < 50 us
Full circuit (100 gates, 15 qubits) < 10 ms
Hamiltonian expectation (10q, 50 terms) < 1 ms
SIMD speedup over scalar > 3x (AVX2), > 6x (AVX-512)
Grover (20 qubits, 1 target) < 500 ms
VQE convergence (H2, 4 qubits) < 5s, < 100 iterations
State allocation/deallocation < 10 us / < 1 us
WASM circuit (10 qubits, 50 gates) < 50 ms

References

  1. Evans, E. (2003). "Domain-Driven Design: Tackling Complexity in the Heart of Software."
  2. Vernon, V. (2013). "Implementing Domain-Driven Design."
  3. Nielsen, M. A. & Chuang, I. L. (2010). "Quantum Computation and Quantum Information."
  4. Peruzzo, A. et al. (2014). "A variational eigenvalue solver on a photonic quantum processor."
  5. Farhi, E. et al. (2014). "A Quantum Approximate Optimization Algorithm."
  6. Fowler, A. G. et al. (2012). "Surface codes: Towards practical large-scale quantum computation."
  7. ruQu crate: Existing coherence assessment and syndrome processing in ruVector.
  8. Coherence Engine DDD: /docs/architecture/coherence-engine-ddd.md
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