FairSpin Lab | Applied Spintronics & Quantum Computing Research
Spin Coherence: Stable

Manipulating the
Quantum Spin.

FairSpin Lab (fairspinlab.com) is an advanced physics research facility dedicated to Spintronics—the study of intrinsic electron spin and its associated magnetic moment for next-generation solid-state devices.

Core Research Vectors

Our experimental methodologies focus on overcoming quantum decoherence at room temperature using topological insulators.

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Spin-Orbit Torque (SOT)

Investigating the magnetization switching induced by in-plane currents via the spin Hall effect. This provides a pathway for ultra-fast, non-volatile magnetic memory architectures.

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Magnonics

Analyzing spin waves (magnons) in ferromagnetic nanostructures. Magnonics allows for data processing with Joule heating reduced by orders of magnitude compared to traditional CMOS.

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Qubit Decoherence

Tracking the exact parameters that cause a superposition state to collapse. Our FairSpin protocol measures environmental noise and its impact on electron spin coherence times.

Material Lattice Spin Relaxation Time (T1) Dephasing Time (T2*) Operating Temp
Silicon Isotope (28Si) ~10 seconds ~30 milliseconds 1.2 Kelvin
Monolayer Graphene ~5 nanoseconds ~2 nanoseconds 300 Kelvin (Room Temp)
Nitrogen-Vacancy Center (Diamond) ~5 milliseconds ~1.5 milliseconds 300 Kelvin (Room Temp)
Gallium Arsenide (GaAs) ~100 picoseconds ~10 picoseconds 4.2 Kelvin

Quantum Circuit Simulation

The FairSpin Lab relies heavily on open-source quantum frameworks to model electron spin dynamics before physical fabrication.

Below is an excerpt from our Qiskit simulation script, initializing a Bell state to demonstrate spin entanglement between two distinct qubits.

# FairSpin Lab: Entanglement Simulation
from qiskit import QuantumCircuit, Aer, execute

# Initialize a 2-qubit quantum circuit
qc = QuantumCircuit(2, 2)

# Apply Hadamard gate to place Qubit 0 in superposition
qc.h(0)

# Apply CNOT gate to entangle Qubit 0 and Qubit 1
# This correlates their spin states
qc.cx(0, 1)

# Measure the spin states
qc.measure([0,1], [0,1])

simulator = Aer.get_backend('qasm_simulator')
result = execute(qc, simulator, shots=1000).result()
print(result.get_counts(qc))