Measurement

1.3 Measurement
Measurement is a critical part of quantum programming, and QASM256 simplifies it with flexible syntax.

Syntax:


MEASURE [QUBIT(S)] TO [CLASSICAL REGISTER];  
[QUBIT(S)]: The qubit(s) to measure.
[CLASSICAL REGISTER]: The classical register to store the measurement result.
Examples:

Measure a single qubit:

MEASURE Q[1] TO CLASSICAL[C1];  
Measure an entire register:

MEASURE Q[1 TO 5] TO CLASSICAL[C[1 TO 5]];  
Conditional Operations Based on Measurement:
QASM256 allows conditional logic based on measurement outcomes.


IF CLASSICAL[C1] == 1 THEN APPLY X ON Q[2];  
2. Advanced Syntax Features
2.1 Modularity
Modularity is one of the core innovations of QASM256, allowing developers to define reusable blocks of quantum logic.

Syntax:


MODULE [MODULE_NAME] {  
    [QUANTUM OPERATIONS];  
}  
Example:
Define a module for creating a Bell state:


MODULE CreateBellPair {  
    APPLY H ON Q[1];  
    APPLY CNOT Q[1], Q[2];  
}  
APPLY CreateBellPair ON Q[1, 2];  
2.2 Auto-Generative Functions
QASM256 introduces automation features for generating quantum circuits dynamically.

Syntax:


AUTO_GENERATE [PARAMETERS];  
Examples:

Auto-generate an entangled register:


AUTO_GENERATE QUBITS[1 TO 10] AS ENTANGLED;  
Automatically apply a variational algorithm:

AUTO_EXECUTE VQE FOR HAMILTONIAN[H];  
2.3 Error Correction
Error correction is built into QASM256 with syntax to simplify the application of standard protocols like Shor’s and Surface Codes.

Syntax:


APPLY [ERROR_CORRECTION_SCHEME] ON [QUBITS];  
Examples:

Apply Shor’s code:

APPLY SHOR_CORRECTION Q[1 TO 9];  
Apply a custom error correction module:


MODULE MyErrorCorrection {  
    APPLY ENCODED_GATE ON Q[1 TO 3];  
}  
APPLY MyErrorCorrection ON Q[1 TO 3];  
2.4 Hybrid Integration
QASM256 is designed for hybrid quantum-classical workflows, allowing real-time interaction between classical and quantum resources.

Syntax:


VARIATIONAL_ALGO [ALGO_NAME] USING CLASSICAL[RESOURCE];  
Examples:

Run a Variational Quantum Eigensolver (VQE):

VARIATIONAL_ALGO VQE[H] USING CLASSICAL[OPTIMIZER];  
Perform hybrid AI training:

APPLY TRAIN_MODEL [QUBITS] USING CLASSICAL[AI_FRAMEWORK];