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Microsoft unveiled Majorana 1, the world’s first quantum computing chip powered by a topological core.

About Majorana 1

Majorana 1 is Microsoft’s quantum processing unit (QPU), designed to scale to one million qubits on a single chip.

It leverages topological qubits—a new type of quantum bit encoded using Majorana zero modes (MZMs)—quasiparticles theorized in 1937 by physicist Ettore Majorana—to enable more stable, error-resistant computing.

The chip uses a custom material called a "topoconductor" (a hybrid of indium arsenide and aluminum) to harness these particles.

Technology Behind Majorana 1

Topoconductor Material: The chip is built from indium arsenide (semiconductor) and aluminum (superconductor), atomically engineered to form nanowires. When cooled near absolute zero, these nanowires generate MZMs at their endpoints, enabling stable qubit operations.

Error-Resistant Qubits: Unlike superconducting qubits (used by Google/IBM), Majorana 1’s topological qubits encode data in the topological state of electrons, making them immune to minor environmental disturbances. 

• Early tests show 99% measurement fidelity and coherence times exceeding 1 millisecond—a dramatic improvement over conventional qubits.

Scalability: Microsoft claims Majorana 1 can scale to 1 million qubits on a single chip the size of a desktop CPU, avoiding the bulky infrastructure required by other quantum systems.

How Does It Works?

Majorana Fermions: These particles act as their own antiparticles, enabling "braiding" (a process to manipulate quantum states) for stable calculations.

Material Fabrication: Microsoft engineered the topoconductor by stacking indium arsenide (semiconductor) and aluminum (superconductor) atom by atom to create nanowires that generate Majorana zero modes (MZMs) at their ends.

Quantum Dots: These tiny electron traps help measure fermion parity (even/odd electron counts) with extreme precision, enabling reliable qubit control.

Majorana 1 could revolutionize fields like:

• Medicine: Simulate molecular interactions to design drugs for diseases like Alzheimer’s.
• Material Science: Develop self-repairing materials or ultra-efficient batteries.
• Climate Modeling: Optimize renewable energy systems and reduce pollution.
• AI: Accelerate machine learning and solve complex optimization problems.

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Source: 

HINDUSTAN TIMES