QuantRS2-Circuit: Advanced Quantum Circuit Framework

QuantRS2-Circuit is the comprehensive quantum circuit construction and optimization engine of the QuantRS2 quantum computing framework, providing advanced circuit representation, analysis, optimization, and compilation capabilities for quantum computing applications.

Version 0.1.2

This release leverages SciRS2 v0.1.2 integration with refined patterns for enhanced performance in:

• Graph-based circuit optimization algorithms
• Parallel circuit analysis and transformation
• Memory-efficient circuit representations
• Hardware-aware compilation optimizations

Core Features

Circuit Construction & Representation

• Fluent Builder API: Intuitive, chainable interface for quantum circuit construction
• Type-Safe Operations: Compile-time verification of qubit counts and gate operations
• DAG Representation: Directed acyclic graph representation for advanced circuit analysis
• Classical Control: Support for classical control flow, measurements, and feed-forward
• Mid-Circuit Measurements: Real-time measurement with conditional operations

Advanced Optimization Framework

• Multi-Pass Optimization: Configurable optimization pipeline with cost-aware scheduling
• Hardware-Aware Compilation: Device-specific optimization with noise models and constraints
• Gate Fusion: Intelligent gate merging for reduced circuit depth and gate count
• Template Matching: Pattern recognition for efficient gate sequence replacement
• Noise-Aware Optimization: Circuit optimization considering realistic device characteristics

Quantum Circuit Analysis

• Commutation Analysis: Automatic detection of commuting operations for reordering
• Circuit Equivalence: Verification of circuit equivalence using multiple methods
• Topological Analysis: Circuit connectivity and entanglement structure analysis
• Resource Estimation: Accurate resource counting and complexity analysis
• Performance Profiling: Detailed metrics for circuit optimization and execution

Hardware Integration

• Device Routing: SABRE and lookahead algorithms for qubit mapping and SWAP insertion
• Pulse-Level Control: Translation to pulse sequences for direct hardware control
• Crosstalk Mitigation: Scheduling algorithms to minimize gate crosstalk effects
• Calibration Integration: Real-time device calibration data incorporation
• Multi-Architecture Support: Superconducting, trapped ion, photonic, and topological systems

Usage Examples

Basic Circuit Construction

use quantrs2_circuit::prelude::*;

fn basic_circuit_example() -> Result<(), Box<dyn std::error::Error>> {
    // Create a circuit with compile-time qubit count verification
    let mut circuit = Circuit::<4>::new();
    
    // Build a quantum Fourier transform circuit
    circuit.h(0)?
           .controlled_phase(0, 1, std::f64::consts::PI / 2.0)?
           .controlled_phase(0, 2, std::f64::consts::PI / 4.0)?
           .controlled_phase(0, 3, std::f64::consts::PI / 8.0)?
           .h(1)?
           .controlled_phase(1, 2, std::f64::consts::PI / 2.0)?
           .controlled_phase(1, 3, std::f64::consts::PI / 4.0)?
           .h(2)?
           .controlled_phase(2, 3, std::f64::consts::PI / 2.0)?
           .h(3)?;
    
    // Convert to DAG for analysis
    let dag = circuit_to_dag(&circuit);
    println!("Circuit depth: {}, Gate count: {}", dag.depth(), dag.gate_count());
    
    Ok(())
}

Advanced Optimization Pipeline

use quantrs2_circuit::prelude::*;

fn optimization_example() -> Result<(), Box<dyn std::error::Error>> {
    let mut circuit = Circuit::<8>::new();
    
    // Create a complex circuit with optimization opportunities
    for i in 0..8 {
        circuit.h(i)?;
    }
    for i in 0..7 {
        circuit.cnot(i, i + 1)?;
    }
    for i in 0..8 {
        circuit.rz(i, 0.1)?;
    }
    
    // Configure optimization pipeline
    let mut pass_manager = PassManager::new();
    pass_manager.add_pass(OptimizationPass::GateCancellation)?
                .add_pass(OptimizationPass::RotationMerging)?
                .add_pass(OptimizationPass::CommutationOptimization)?
                .add_pass(OptimizationPass::TemplateMatching)?;
    
    // Apply optimizations
    let optimized_circuit = pass_manager.run(&circuit)?;
    let report = pass_manager.get_report();
    
    println!("Original gates: {}, Optimized gates: {}, Reduction: {:.1}%",
             report.original_gates, report.final_gates, report.reduction_percentage());
    
    Ok(())
}

Hardware-Aware Compilation

use quantrs2_circuit::prelude::*;

fn hardware_compilation_example() -> Result<(), Box<dyn std::error::Error>> {
    // Define device topology (e.g., Google Sycamore)
    let coupling_map = CouplingMap::from_adjacency_list(&[
        (0, 1), (1, 2), (2, 3), (3, 4),
        (5, 6), (6, 7), (7, 8), (8, 9),
        (0, 5), (1, 6), (2, 7), (3, 8), (4, 9),
    ]);
    
    // Create logical circuit
    let mut logical_circuit = Circuit::<10>::new();
    logical_circuit.h(0)?
                   .cnot(0, 5)?  // This requires routing
                   .cnot(5, 9)?
                   .cnot(9, 4)?;
    
    // Configure router with device constraints
    let router_config = SabreConfig {
        max_iterations: 100,
        decay: 0.001,
        lookahead_depth: 3,
    };
    
    let mut router = SabreRouter::new(coupling_map, router_config);
    let routed_result = router.route(&logical_circuit)?;
    
    println!("Added {} SWAP gates for routing", routed_result.swap_count);
    println!("Final circuit depth: {}", routed_result.circuit.depth());
    
    Ok(())
}

Circuit Analysis and Verification

use quantrs2_circuit::prelude::*;

fn circuit_analysis_example() -> Result<(), Box<dyn std::error::Error>> {
    // Create two allegedly equivalent circuits
    let mut circuit1 = Circuit::<2>::new();
    circuit1.h(0)?.cnot(0, 1)?;
    
    let mut circuit2 = Circuit::<2>::new();
    circuit2.cnot(0, 1)?.h(0)?.cnot(0, 1)?.x(1)?.cnot(0, 1)?;
    
    // Verify equivalence using multiple methods
    let equivalence_checker = EquivalenceChecker::new();
    let result = equivalence_checker.check_equivalence(&circuit1, &circuit2)?;
    
    match result.equivalence_type {
        EquivalenceType::Unitary => println!("Circuits are unitarily equivalent"),
        EquivalenceType::Structural => println!("Circuits are structurally identical"),
        EquivalenceType::None => println!("Circuits are not equivalent"),
    }
    
    // Perform detailed circuit analysis
    let analyzer = CircuitAnalyzer::new();
    let metrics = analyzer.analyze(&circuit1)?;
    
    println!("Circuit metrics:");
    println!("  Depth: {}", metrics.depth);
    println!("  Gate count: {}", metrics.gate_count);
    println!("  Two-qubit gates: {}", metrics.two_qubit_gate_count);
    println!("  Entanglement measure: {:.3}", metrics.entanglement_measure);
    
    Ok(())
}

Classical Control and Measurement

use quantrs2_circuit::prelude::*;

fn classical_control_example() -> Result<(), Box<dyn std::error::Error>> {
    // Create measurement circuit with classical control
    let mut measurement_circuit = MeasurementCircuitBuilder::new(3, 3);
    
    // Prepare a superposition state
    measurement_circuit.h(0)?
                       .cnot(0, 1)?
                       .cnot(1, 2)?;
    
    // Mid-circuit measurement with feed-forward
    measurement_circuit.measure(0, 0)?;  // Measure qubit 0 to classical bit 0
    
    // Conditional operations based on measurement result
    let condition = ClassicalCondition::equals(0, ClassicalValue::One);
    measurement_circuit.conditional_x(1, condition)?;
    
    // Final measurements
    measurement_circuit.measure(1, 1)?
                       .measure(2, 2)?;
    
    // Execute with conditional logic
    let execution_result = measurement_circuit.execute_with_simulation(1000)?;
    println!("Classical outcomes: {:?}", execution_result.classical_outcomes);
    
    Ok(())
}

Fault-Tolerant Circuit Compilation

use quantrs2_circuit::prelude::*;

fn fault_tolerant_example() -> Result<(), Box<dyn std::error::Error>> {
    // Define a surface code for error correction
    let qec_code = QECCode::surface_code(3, 3)?;  // 3x3 surface code
    
    // Create logical circuit
    let mut logical_circuit = Circuit::<1>::new();
    logical_circuit.h(0)?
                   .s(0)?
                   .h(0)?;
    
    // Compile to fault-tolerant version
    let ft_compiler = FaultTolerantCompiler::new(qec_code);
    let ft_circuit = ft_compiler.compile(&logical_circuit)?;
    
    println!("Logical circuit gates: {}", logical_circuit.gate_count());
    println!("Fault-tolerant gates: {}", ft_circuit.physical_circuit.gate_count());
    println!("Resource overhead: {}x", ft_circuit.resource_overhead.total_overhead());
    
    // Analyze magic state requirements
    println!("Magic states required: {}", ft_circuit.resource_overhead.magic_states);
    
    Ok(())
}

QASM Import/Export

use quantrs2_circuit::prelude::*;

fn qasm_interoperability_example() -> Result<(), Box<dyn std::error::Error>> {
    // Parse QASM circuit
    let qasm_code = r#"
        OPENQASM 3.0;
        include "stdgates.inc";
        
        qubit[2] q;
        bit[2] c;
        
        h q[0];
        cnot q[0], q[1];
        c = measure q;
    "#;
    
    let qasm_parser = QasmParser::new();
    let parsed_program = qasm_parser.parse(qasm_code)?;
    
    // Convert to QuantRS2 circuit
    let circuit = parsed_program.to_quantrs2_circuit()?;
    
    // Optimize the circuit
    let optimizer = CircuitOptimizer::new();
    let optimized_circuit = optimizer.optimize(&circuit, OptimizationLevel::Aggressive)?;
    
    // Export back to QASM
    let export_options = ExportOptions {
        include_measurements: true,
        use_custom_gates: false,
        optimization_level: Some(OptimizationLevel::Basic),
    };
    
    let qasm_exporter = QasmExporter::new();
    let exported_qasm = qasm_exporter.export(&optimized_circuit, &export_options)?;
    
    println!("Exported QASM:\n{}", exported_qasm);
    
    Ok(())
}

Comprehensive Module Structure

Core Circuit Framework

• builder.rs: Fluent circuit builder API with type-safe operations
• dag.rs: Directed acyclic graph representation for circuit analysis
• classical.rs: Classical control flow, conditional operations, and measurements
• measurement.rs: Mid-circuit measurements and feed-forward control

Optimization & Analysis

• optimization/: Comprehensive optimization framework
  • pass_manager.rs: Configurable optimization pipeline management
  • passes.rs: Individual optimization passes (gate cancellation, fusion, etc.)
  • cost_model.rs: Hardware-aware cost models for optimization decisions
  • analysis.rs: Circuit analysis and metric computation
  • gate_properties.rs: Gate property analysis for optimization
• optimizer.rs: High-level circuit optimization interface
• graph_optimizer.rs: Graph-based optimization algorithms
• commutation.rs: Gate commutation analysis and reordering
• equivalence.rs: Circuit equivalence verification using multiple methods

Hardware Integration & Compilation

• routing/: Quantum circuit routing and layout algorithms
  • sabre.rs: SABRE routing algorithm
  • lookahead.rs: Lookahead routing for enhanced performance
  • coupling_map.rs: Device topology representation and analysis
  • swap_network.rs: SWAP gate insertion and optimization
• pulse.rs: Pulse-level control and waveform generation
• crosstalk.rs: Crosstalk analysis and mitigation scheduling
• topology.rs: Circuit topology analysis and optimization

Advanced Circuit Types

• fault_tolerant.rs: Fault-tolerant circuit compilation with error correction
• photonic.rs: Photonic quantum circuit representation and operations
• topological.rs: Topological quantum circuit compilation with anyons

Circuit Transformation & Synthesis

• synthesis.rs: Unitary synthesis and gate decomposition
• tensor_network.rs: Tensor network representation and compression
• zx_calculus.rs: ZX-diagram optimization and circuit extraction
• slicing.rs: Circuit slicing for parallel execution

Import/Export & Interoperability

• qasm/: QASM 2.0/3.0 support
  • parser.rs: QASM parsing with full language support
  • exporter.rs: Circuit export to QASM format
  • ast.rs: Abstract syntax tree representation
  • validator.rs: QASM validation and error checking
• simulator_interface.rs: Integration with various simulator backends

Machine Learning & Advanced Algorithms

• ml_optimization.rs: Machine learning-based circuit optimization
• scirs2_integration.rs: SciRS2 integration for graph algorithms and optimization
  • Leverages scirs2_core::parallel_ops for parallel circuit transformations
  • Uses SciRS2 graph algorithms for optimized circuit routing
  • Integrates SciRS2 memory management for large circuit handling

API Overview

Core Types

• Circuit<N>: Quantum circuit with const generic for qubit count
• Simulator: Trait for backends that can run quantum circuits

Macros

• circuit!: Creates a new circuit with the specified number of qubits
• qubits!: Creates a set of qubits for operations
• quantum!: DSL for quantum circuit construction (in development)

Technical Details

• The circuit builder uses a fluent API for method chaining
• Gate operations are type-checked at compile time where possible
• The framework supports custom gates through the GateOp trait
• Circuit operations return QuantRS2Result for error handling

Future Plans

See TODO.md for planned features.

Integration with Other QuantRS2 Modules

This module is designed to work seamlessly with:

• quantrs2-core: Uses core types and gates for circuit construction
• quantrs2-sim: Circuits can be executed on simulators
• quantrs2-device: Circuits can be transpiled and run on real hardware

License

This project is licensed under either:

• Apache License, Version 2.0
• MIT License

at your option.