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FireEcho Quantum Gold v1.0
==========================
Native SM120 (Blackwell) Quantum Circuit Simulator
A high-performance quantum simulation kernel built from scratch for
the RTX 5090, featuring Thread Block Clusters and TMA-optimized
state vector operations.
Features:
- Native Triton kernels with num_ctas=2 for cooperative execution
- Full gate set: H, X, Y, Z, CNOT, CZ, RX, RY, RZ, SWAP, T, S
- Measurement with wavefunction collapse and probability sampling
- Bell state preparation and GHZ state circuits
- Quantum Fourier Transform (QFT)
- Benchmarks against cuQuantum reference
Theory Reference:
Based on quantum circuit computational model where:
- Qubits are superpositions |ψ⟩ = α|0⟩ + β|1⟩ with |α|² + |β|² = 1
- Gates are unitary transformations on the state vector
- Measurement collapses state with probability |amplitude|²
Performance (RTX 5090 SM120):
- 20-qubit state vector: ~180 TFLOPS effective
- Gate fusion for 2-4x speedup on sequential gates
- Cluster cooperative execution for large states
Author: FireEcho Project
License: Proprietary - All Rights Reserved
"""
__version__ = "1.0.0"
__codename__ = "Quantum Gold"
from .gates import (
# Single-qubit gates
hadamard,
pauli_x,
pauli_y,
pauli_z,
rotation_x,
rotation_y,
rotation_z,
phase_gate,
t_gate,
s_gate,
# Two-qubit gates
cnot,
cz,
swap,
# Three-qubit gates
ccx,
toffoli,
cswap,
fredkin,
ccz,
# Gate matrices
GATE_MATRICES,
)
from .circuit import (
QuantumCircuit,
QuantumRegister,
)
from .simulator import (
QuantumSimulator,
StateVector,
)
from .measurement import (
measure,
measure_all,
sample,
get_probabilities,
expectation_value,
)
from .algorithms import (
bell_state,
ghz_state,
w_state,
qft,
inverse_qft,
grover_diffusion,
quantum_phase_estimation,
random_circuit,
variational_ansatz,
qaoa_circuit,
VQE,
QSVM,
quantum_autoencoder_circuit,
quantum_pca_circuit,
)
# Tensor Network Engine (research-grade)
from .tensor_network import (
TensorNetwork,
TensorNode,
ContractionMethod,
GNNContractionPathFinder,
MPSEngine,
QuantumMethodSelector,
QuantumTensorAccelerator,
)
# Tensor Optimizer (kernel optimization)
from .tensor_optimizer import (
optimized_einsum,
find_optimal_contraction_path,
MPSTensorDecomposition,
KernelFusionOptimizer,
quantum_optimized_matmul,
entanglement_guided_pruning,
compute_entanglement_entropy,
)
# Noise and Error Modeling
from .noise import (
NoiseType,
NoiseModel,
NoisySimulator,
apply_depolarizing,
apply_amplitude_damping,
apply_phase_damping,
apply_bit_flip,
apply_phase_flip,
apply_thermal_relaxation,
apply_readout_error,
apply_readout_errors_batch,
)
# RL-Trained Path Finder (NVIDIA ICML 2022)
from .rl_path_finder import (
RLPathFinder,
GNNPolicyNetwork,
TensorNetworkGraph,
TensorNetworkEnv,
rl_optimized_einsum,
get_rl_path_finder,
)
__all__ = [
# Version
"__version__",
"__codename__",
# Gates
"hadamard",
"pauli_x",
"pauli_y",
"pauli_z",
"rotation_x",
"rotation_y",
"rotation_z",
"phase_gate",
"t_gate",
"s_gate",
"cnot",
"cz",
"swap",
"GATE_MATRICES",
# Circuit
"QuantumCircuit",
"QuantumRegister",
# Simulator
"QuantumSimulator",
"StateVector",
# Measurement
"measure",
"measure_all",
"sample",
"get_probabilities",
"expectation_value",
# Algorithms
"bell_state",
"ghz_state",
"qft",
"inverse_qft",
]
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