pktron 2.0.2

PKTron - Pakistan's 1st Quantum AI Powered Simulation Framework

PKTron AI Quantum Lab

AI-Powered Quantum Simulation for Every Scientist — From Circuits to Cosmology in One Interactive Lab, Pakistan's 1st Quantum AI Powered Simulation Framework.

PKTron AI Quantum Lab is a comprehensive, AI-assisted quantum computing platform built entirely in Python. Whether you are a student, researcher, or engineer, PKTron gives you everything you need to build, simulate, analyse, and understand quantum systems — no real quantum hardware required.

From simple 2-qubit circuits to 100 Qubit fault-tolerant surface codes, quantum finance models, molecular chemistry simulations, and an AI assistant that explains every step — PKTron is the one platform that covers it all.

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Install

pip install pktron

Optional Extras

pip install pktron[gpu]   # GPU acceleration via CuPy
pip install pktron[ml]    # Quantum ML via PyTorch
pip install pktron[full]  # Everything

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Quick Start

from pktron import QuantumCircuit

qc = QuantumCircuit(2)
qc.h(0)
qc.cnot(0, 1)
print(qc.get_state())

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Why PKTron AI Quantum Lab?

Feature	PKTron
AI Quantum Assistant	Yes — explains circuits step by step
Fault-Tolerant Codes	Repetition, Steane, Surface Code
Quantum Finance	Portfolio, Risk, Fraud, QKD
Scientific Domains	Physics, Chemistry, Biology, Cosmology
Noise + Mitigation	ZNE, PEC, REM fully integrated
Algorithms	15+ including Shor, HHL, Grover, VQE
Memory Safe	Runs on free Google Colab (12 GB)
GPU Support	Optional via CuPy

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What PKTron AI Quantum Lab Can Do

AI-Powered Features

• AI Quantum Assistant — explains what every gate and circuit does in plain English
• Step-by-step simulation engine — watch your circuit execute one gate at a time
• Quantum Debugger — find and fix errors in your circuits interactively
• Auto Backend Optimiser — automatically picks the best simulator for your circuit

Core Simulation

• Statevector simulator (memory-safe, up to 22 qubits on standard hardware)
• Density matrix simulator with full Kraus noise support
• MPS tensor network simulator with adaptive bond dimensions
• Fast statevector engine with sparse zero-skipping
• GPU acceleration via CuPy (optional)

Noise and Error Handling

• Depolarising, bit-flip, phase-flip, and readout noise models
• Zero-Noise Extrapolation (ZNE) error mitigation
• Probabilistic Error Cancellation (PEC)
• Readout Error Mitigation (REM)

Fault-Tolerant Quantum Computing

• Repetition Code
• Steane [[7,1,3]] Code
• Surface Code with full syndrome measurement and correction
• Logical qubit wrapper

Quantum Algorithms (15+)

• VQE — Variational Quantum Eigensolver
• QAOA — Quantum Approximate Optimisation
• Grover's search algorithm
• Shor's factoring algorithm (full implementation)
• HHL quantum linear system solver
• Deutsch-Jozsa algorithm
• Bernstein-Vazirani algorithm
• Simon's algorithm
• Quantum Counting
• Quantum Walks (discrete and continuous-time)
• Quantum Principal Component Analysis (qPCA)
• Quantum GAN (QGAN)
• Quantum SVM (QSVM)
• Quantum Neural Networks (QNN)
• Advanced Algorithms Extension Module

Quantum Finance

• VQE portfolio optimisation
• Quantum Monte Carlo risk analysis
• VQC fraud detection
• Grover anomaly search
• BB84 Quantum Key Distribution (QKD)
• Unified QuantumFinance API

Scientific Domains

• Physics: quantum harmonic oscillator, spin chains, Ising model
• Chemistry: molecular VQE, bond dissociation, quantum phase estimation
• Biology: protein folding optimisation, DNA sequence alignment
• Cosmology: dark matter simulation, cosmic inflation modelling
• Scientific Algorithms: quantum annealing, adiabatic evolution

Autonomous Quantum Experimentation (AQEF)

• Adaptive Quantum Execution Engine with feedback loop
• Noise Intelligence Module — detects error-heavy qubits automatically
• Experiment Manager with full logging and history
• Backend Abstraction Layer
• Quantum Strategy Engine
• Real-time visualisation dashboard
• GHZ Scaling Engine
• Reproducibility and snapshot system

Developer Tools

• Circuit transpiler with full PassManager
• Performance profiler
• Circuit animation engine
• Hardware emulator
• Qiskit compatibility layer
• Plugin system
• Quantum Cryptography Suite

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Example: AI Assistant Explaining a Circuit

from pktron import QuantumCircuit, AIQuantumAssistant

qc = QuantumCircuit(2)
qc.h(0)
qc.cnot(0, 1)

ai = AIQuantumAssistant()
ai.explain(qc)
# Output:
# Step 1: H gate on qubit 0 — puts qubit into superposition (50% |0>, 50% |1>)
# Step 2: CNOT gate — entangles qubit 0 and qubit 1, creating a Bell state
# Final state: (|00> + |11>) / sqrt(2)

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Example: VQE for H2 Molecule

from pktron import QuantumCircuit
from pktron.quantum_info_v2 import Pauli, Statevector
import numpy as np

def ansatz(thetas):
    qc = QuantumCircuit(2)
    qc.ry(thetas[0], 0)
    qc.ry(thetas[1], 1)
    qc.cnot(0, 1)
    return qc

thetas = np.array([0.1, 0.2])
sv = Statevector(ansatz(thetas).get_state())
energy = float(np.real(Pauli('ZZ').expectation_value(sv)))
print(f"H2 Ground State Energy: {energy:.4f}")

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Example: Surface Code Error Correction

from pktron.fault_tolerant import SurfaceCode

sc = SurfaceCode(distance=3)
state = sc.encode_logical_zero()
state = sc.add_error(state, error_qubit=2, error_type='X')
syndrome = sc.measure_syndrome(state)
print(f"Syndrome detected: {syndrome}")

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Example: Quantum Finance

from pktron.finance import QuantumFinance

qf = QuantumFinance()
portfolio = qf.optimise_portfolio(returns=[0.1, 0.2, 0.15], risk=0.05)
print(portfolio)

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Example: Quantum Cosmology

from pktron.cosmology import CosmologySimulator

sim = CosmologySimulator()
result = sim.dark_matter_simulation(n_qubits=4, steps=10)
print(result.summary())

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License

MIT License — free to use, modify, and distribute.

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PKTron AI Quantum Lab — Making quantum computing accessible to every scientist, student, and researcher on the planet.