quantrs2-core 0.1.3

// WebGPU shaders for specialized quantum gate operations
// Cross-platform high-performance implementation for holonomic, post-quantum crypto, and quantum ML gates

// Workgroup size constants
const WORKGROUP_SIZE: u32 = 256u;
const MAX_QUBITS: u32 = 16u;
const TENSOR_SIZE: u32 = 16u;

// Complex number structure
struct Complex {
    real: f32,
    imag: f32,
}

// Helper functions for complex arithmetic
fn complex_add(a: Complex, b: Complex) -> Complex {
    return Complex(a.real + b.real, a.imag + b.imag);
}

fn complex_mul(a: Complex, b: Complex) -> Complex {
    return Complex(
        a.real * b.real - a.imag * b.imag,
        a.real * b.imag + a.imag * b.real
    );
}

fn complex_conj(a: Complex) -> Complex {
    return Complex(a.real, -a.imag);
}

fn complex_abs_squared(a: Complex) -> f32 {
    return a.real * a.real + a.imag * a.imag;
}

fn complex_normalize(a: Complex) -> Complex {
    let norm = sqrt(complex_abs_squared(a));
    if (norm > 1e-10) {
        return Complex(a.real / norm, a.imag / norm);
    } else {
        return Complex(0.0, 0.0);
    }
}

// ============= Holonomic Gate Shader =============

// Buffer bindings for holonomic gate
@group(0) @binding(0) var<storage, read_write> state: array<Complex>;
@group(0) @binding(1) var<storage, read> holonomy_matrix: array<Complex>;
@group(0) @binding(2) var<storage, read> target_qubits: array<u32>;
@group(0) @binding(3) var<uniform> params: HolonomicParams;

struct HolonomicParams {
    state_size: u32,
    num_qubits: u32,
    matrix_size: u32,
    work_per_thread: u32,
}

@compute @workgroup_size(WORKGROUP_SIZE)
fn holonomic_gate_main(@builtin(global_invocation_id) global_id: vec3<u32>) {
    let thread_id = global_id.x;
    let total_work_items = params.state_size / params.work_per_thread;
    
    if (thread_id >= total_work_items) {
        return;
    }
    
    // Calculate qubit mask for target qubits
    var qubit_mask: u32 = 0u;
    for (var i: u32 = 0u; i < params.num_qubits; i++) {
        qubit_mask |= (1u << target_qubits[i]);
    }
    
    // Calculate base state index for this thread
    var base_idx: u32 = 0u;
    var temp_id = thread_id;
    
    for (var i: u32 = 0u; i < 32u; i++) {
        if ((qubit_mask & (1u << i)) == 0u) {
            if ((temp_id & 1u) != 0u) {
                base_idx |= (1u << i);
            }
            temp_id >>= 1u;
        }
    }
    
    // Local storage for state amplitudes
    var temp_state: array<Complex, 32>;
    
    // Load relevant state amplitudes
    for (var i: u32 = 0u; i < params.work_per_thread && i < 32u; i++) {
        let state_idx = base_idx | (i << firstTrailingBit(qubit_mask));
        temp_state[i] = state[state_idx];
    }
    
    // Apply holonomic transformation using matrix multiplication
    for (var i: u32 = 0u; i < params.work_per_thread && i < 32u; i++) {
        var result = Complex(0.0, 0.0);
        
        for (var j: u32 = 0u; j < params.work_per_thread && j < 32u; j++) {
            let matrix_idx = i * params.work_per_thread + j;
            result = complex_add(result, complex_mul(holonomy_matrix[matrix_idx], temp_state[j]));
        }
        
        let state_idx = base_idx | (i << firstTrailingBit(qubit_mask));
        state[state_idx] = result;
    }
}

// ============= Post-Quantum Hash Gate Shader =============

@group(0) @binding(0) var<storage, read_write> hash_state: array<Complex>;
@group(0) @binding(1) var<storage, read> hash_circuit: array<Complex>;
@group(0) @binding(2) var<uniform> hash_params: PostQuantumParams;

struct PostQuantumParams {
    state_size: u32,
    rate: u32,
    capacity: u32,
    num_rounds: u32,
}

// Shared memory for sponge construction
var<workgroup> sponge_state: array<Complex, WORKGROUP_SIZE>;
var<workgroup> round_matrix: array<Complex, WORKGROUP_SIZE>;

@compute @workgroup_size(WORKGROUP_SIZE)
fn post_quantum_hash_main(@builtin(global_invocation_id) global_id: vec3<u32>,
                          @builtin(local_invocation_id) local_id: vec3<u32>) {
    let thread_id = global_id.x;
    let local_thread_id = local_id.x;
    
    if (thread_id >= hash_params.state_size) {
        return;
    }
    
    // Load state into shared memory for rate portion
    if (local_thread_id < hash_params.rate && local_thread_id < WORKGROUP_SIZE) {
        sponge_state[local_thread_id] = hash_state[thread_id];
    }
    
    workgroupBarrier();
    
    // Apply quantum sponge rounds
    for (var round: u32 = 0u; round < hash_params.num_rounds; round++) {
        // Absorption phase - XOR input with rate portion
        if (local_thread_id < hash_params.rate) {
            let circuit_idx = round * hash_params.rate + local_thread_id;
            sponge_state[local_thread_id] = complex_add(
                sponge_state[local_thread_id], 
                hash_circuit[circuit_idx]
            );
        }
        
        workgroupBarrier();
        
        // Permutation phase - apply quantum permutation
        var temp = Complex(0.0, 0.0);
        if (local_thread_id < hash_params.rate) {
            for (var i: u32 = 0u; i < hash_params.rate; i++) {
                let perm_idx = round * hash_params.rate * hash_params.rate + 
                              local_thread_id * hash_params.rate + i;
                temp = complex_add(temp, complex_mul(
                    hash_circuit[perm_idx], 
                    sponge_state[i]
                ));
            }
            sponge_state[local_thread_id] = temp;
        }
        
        workgroupBarrier();
    }
    
    // Write back to global memory
    if (local_thread_id < hash_params.rate && thread_id < hash_params.state_size) {
        hash_state[thread_id] = sponge_state[local_thread_id];
    }
}

// ============= Quantum ML Attention Shader =============

@group(0) @binding(0) var<storage, read_write> attention_state: array<Complex>;
@group(0) @binding(1) var<storage, read> query_params: array<Complex>;
@group(0) @binding(2) var<storage, read> key_params: array<Complex>;
@group(0) @binding(3) var<storage, read> value_params: array<Complex>;
@group(0) @binding(4) var<uniform> attention_params: AttentionParams;

struct AttentionParams {
    state_size: u32,
    num_heads: u32,
    head_dim: u32,
    seq_length: u32,
}

// Shared memory for attention computation
var<workgroup> attention_scores: array<Complex, WORKGROUP_SIZE>;
var<workgroup> query_cache: array<Complex, WORKGROUP_SIZE>;
var<workgroup> key_cache: array<Complex, WORKGROUP_SIZE>;
var<workgroup> value_cache: array<Complex, WORKGROUP_SIZE>;

@compute @workgroup_size(WORKGROUP_SIZE)
fn quantum_ml_attention_main(@builtin(global_invocation_id) global_id: vec3<u32>,
                             @builtin(local_invocation_id) local_id: vec3<u32>,
                             @builtin(workgroup_id) workgroup_id: vec3<u32>) {
    let thread_id = local_id.x;
    let head_id = workgroup_id.x % attention_params.num_heads;
    let seq_id = workgroup_id.x / attention_params.num_heads;
    
    if (seq_id >= attention_params.seq_length) {
        return;
    }
    
    let head_offset = head_id * attention_params.head_dim;
    let seq_offset = seq_id * attention_params.head_dim;
    
    // Load query, key, value for this head into shared memory
    if (thread_id < attention_params.head_dim) {
        query_cache[thread_id] = query_params[head_offset + thread_id];
        key_cache[thread_id] = key_params[head_offset + thread_id];
        value_cache[thread_id] = value_params[head_offset + thread_id];
    }
    
    workgroupBarrier();
    
    // Compute attention scores using quantum interference
    if (thread_id < attention_params.head_dim) {
        let query_val = query_cache[thread_id];
        var attention_sum = Complex(0.0, 0.0);
        
        // Compute attention weights through quantum inner product
        for (var k: u32 = 0u; k < attention_params.head_dim; k++) {
            let key_val = key_cache[k];
            let score = complex_mul(complex_conj(query_val), key_val);
            attention_sum = complex_add(attention_sum, score);
        }
        
        // Apply quantum normalization (softmax-like)
        attention_scores[thread_id] = complex_normalize(attention_sum);
    }
    
    workgroupBarrier();
    
    // Apply attention to values
    if (thread_id < attention_params.head_dim) {
        var output = Complex(0.0, 0.0);
        
        for (var v: u32 = 0u; v < attention_params.head_dim; v++) {
            output = complex_add(output, complex_mul(attention_scores[v], value_cache[v]));
        }
        
        // Update state with attention output
        let state_idx = seq_id * attention_params.num_heads * attention_params.head_dim + 
                       head_offset + thread_id;
        if (state_idx < attention_params.state_size) {
            attention_state[state_idx] = output;
        }
    }
}

// ============= Fused Rotation Sequence Shader =============

@group(0) @binding(0) var<storage, read_write> rotation_state: array<Complex>;
@group(0) @binding(1) var<storage, read> rotation_angles: array<f32>;
@group(0) @binding(2) var<storage, read> rotation_axes: array<u32>; // 0=X, 1=Y, 2=Z
@group(0) @binding(3) var<storage, read> rotation_targets: array<u32>;
@group(0) @binding(4) var<uniform> rotation_params: RotationParams;

struct RotationParams {
    state_size: u32,
    num_rotations: u32,
    num_qubits: u32,
}

@compute @workgroup_size(WORKGROUP_SIZE)
fn fused_rotation_main(@builtin(global_invocation_id) global_id: vec3<u32>) {
    let thread_id = global_id.x;
    
    if (thread_id >= rotation_params.state_size) {
        return;
    }
    
    var current_amplitude = rotation_state[thread_id];
    
    // Apply each rotation in the sequence
    for (var rot: u32 = 0u; rot < rotation_params.num_rotations; rot++) {
        let angle = rotation_angles[rot];
        let axis = rotation_axes[rot];
        let target_qubit = rotation_targets[rot];
        
        let qubit_state = (thread_id >> target_qubit) & 1u;
        let paired_idx = thread_id ^ (1u << target_qubit);
        
        let cos_half = cos(angle / 2.0);
        let sin_half = sin(angle / 2.0);
        
        var paired_amplitude = Complex(0.0, 0.0);
        if (paired_idx < rotation_params.state_size) {
            paired_amplitude = rotation_state[paired_idx];
        }
        
        var new_amplitude: Complex;
        
        switch (axis) {
            case 0u: { // X rotation
                if (qubit_state == 0u) {
                    new_amplitude = complex_add(
                        complex_mul(Complex(cos_half, 0.0), current_amplitude),
                        complex_mul(Complex(0.0, -sin_half), paired_amplitude)
                    );
                } else {
                    new_amplitude = complex_add(
                        complex_mul(Complex(cos_half, 0.0), current_amplitude),
                        complex_mul(Complex(0.0, -sin_half), paired_amplitude)
                    );
                }
            }
            case 1u: { // Y rotation
                if (qubit_state == 0u) {
                    new_amplitude = complex_add(
                        complex_mul(Complex(cos_half, 0.0), current_amplitude),
                        complex_mul(Complex(-sin_half, 0.0), paired_amplitude)
                    );
                } else {
                    new_amplitude = complex_add(
                        complex_mul(Complex(sin_half, 0.0), paired_amplitude),
                        complex_mul(Complex(cos_half, 0.0), current_amplitude)
                    );
                }
            }
            case 2u: { // Z rotation
                if (qubit_state == 0u) {
                    new_amplitude = complex_mul(Complex(cos_half, -sin_half), current_amplitude);
                } else {
                    new_amplitude = complex_mul(Complex(cos_half, sin_half), current_amplitude);
                }
            }
            default: {
                new_amplitude = current_amplitude;
            }
        }
        
        current_amplitude = new_amplitude;
    }
    
    // Write final result
    rotation_state[thread_id] = current_amplitude;
}

// ============= Tensor Network Contraction Shader =============

@group(0) @binding(0) var<storage, read_write> tensor_data: array<Complex>;
@group(0) @binding(1) var<storage, read> contraction_indices: array<u32>;
@group(0) @binding(2) var<uniform> tensor_params: TensorParams;

struct TensorParams {
    tensor_size: u32,
    contraction_pairs: u32,
    bond_dimension: u32,
}

// Shared memory for tensor operations
var<workgroup> tensor_cache: array<Complex, WORKGROUP_SIZE>;

@compute @workgroup_size(WORKGROUP_SIZE)
fn tensor_contraction_main(@builtin(global_invocation_id) global_id: vec3<u32>,
                          @builtin(local_invocation_id) local_id: vec3<u32>) {
    let thread_id = global_id.x;
    let local_thread_id = local_id.x;
    
    if (thread_id >= tensor_params.tensor_size) {
        return;
    }
    
    // Load tensor data into shared memory
    if (local_thread_id < WORKGROUP_SIZE && thread_id < tensor_params.tensor_size) {
        tensor_cache[local_thread_id] = tensor_data[thread_id];
    }
    
    workgroupBarrier();
    
    // Perform tensor contraction
    var result = Complex(0.0, 0.0);
    
    for (var pair: u32 = 0u; pair < tensor_params.contraction_pairs; pair++) {
        let idx1 = contraction_indices[pair * 2u];
        let idx2 = contraction_indices[pair * 2u + 1u];
        
        if (idx1 < WORKGROUP_SIZE && idx2 < WORKGROUP_SIZE) {
            result = complex_add(result, complex_mul(tensor_cache[idx1], tensor_cache[idx2]));
        }
    }
    
    workgroupBarrier();
    
    // Write result back to global memory
    tensor_data[thread_id] = result;
}

// ============= Gate Fusion Optimization Shader =============

@group(0) @binding(0) var<storage, read_write> fusion_state: array<Complex>;
@group(0) @binding(1) var<storage, read> fusion_matrices: array<Complex>;
@group(0) @binding(2) var<storage, read> fusion_targets: array<u32>;
@group(0) @binding(3) var<uniform> fusion_params: FusionParams;

struct FusionParams {
    state_size: u32,
    num_fused_gates: u32,
    matrix_stride: u32,
}

@compute @workgroup_size(WORKGROUP_SIZE)
fn gate_fusion_main(@builtin(global_invocation_id) global_id: vec3<u32>) {
    let thread_id = global_id.x;
    
    if (thread_id >= fusion_params.state_size) {
        return;
    }
    
    var current_amplitude = fusion_state[thread_id];
    
    // Apply fused gate sequence
    for (var gate: u32 = 0u; gate < fusion_params.num_fused_gates; gate++) {
        let target_qubit = fusion_targets[gate];
        let matrix_offset = gate * fusion_params.matrix_stride;
        
        let qubit_state = (thread_id >> target_qubit) & 1u;
        let paired_idx = thread_id ^ (1u << target_qubit);
        
        var paired_amplitude = Complex(0.0, 0.0);
        if (paired_idx < fusion_params.state_size) {
            paired_amplitude = fusion_state[paired_idx];
        }
        
        // Apply 2x2 gate matrix
        let m00 = fusion_matrices[matrix_offset + 0u];
        let m01 = fusion_matrices[matrix_offset + 1u];
        let m10 = fusion_matrices[matrix_offset + 2u];
        let m11 = fusion_matrices[matrix_offset + 3u];
        
        var new_amplitude: Complex;
        if (qubit_state == 0u) {
            new_amplitude = complex_add(
                complex_mul(m00, current_amplitude),
                complex_mul(m01, paired_amplitude)
            );
        } else {
            new_amplitude = complex_add(
                complex_mul(m10, paired_amplitude),
                complex_mul(m11, current_amplitude)
            );
        }
        
        current_amplitude = new_amplitude;
    }
    
    // Write final result
    fusion_state[thread_id] = current_amplitude;
}