If your code is timing out and only successfully processing the first test case, it suggests that the solution is not efficient enough to handle larger inputs within the given time limit. To address this issue, you need to optimize your code to improve its performance. Here are a few suggestions:

Avoid unnecessary calculations: Review your code to ensure that you're not performing any redundant or unnecessary calculations. Simplify the logic and eliminate any unnecessary computations.

Precompute values: If there are any repetitive calculations or values that can be precomputed, do so outside the loop to avoid recomputation in each iteration.

Analyze the problem constraints: Understand the constraints of the problem and look for any patterns or formulas that can help optimize the solution. There might be a mathematical or algorithmic approach to solve the problem more efficiently.

Optimize loops: If there are nested loops or loops with a large number of iterations, consider ways to optimize or eliminate them. Look for alternative algorithms or mathematical techniques that can solve the problem more efficiently.

Use efficient data structures: Evaluate the data structures used in your code. Consider if there are more efficient alternatives that can improve performance. For example, using arrays instead of vectors or optimizing memory usage.

Test with larger inputs: Ensure that your code works correctly with larger inputs by testing it against such cases. This will help identify any potential issues or bugs that might not be apparent with smaller inputs.

Remember, optimizing code for efficiency can be a complex task, and the specific optimizations required depend on the problem at hand. Take a careful look at your code, analyze the problem constraints, and apply appropriate techniques to improve its performance.