⚡ Bolt: Optimize Tensor initialization and operations

[teerthsharma]

💡 What: Replaced manual index loops and Vec push operations with single-pass iterator chains in tensor.rs (add, mul, scale, sub, map) and linalg.rs (LossConfig::derivative). The result is now directly constructed via Tensor::from_vec() instead of Tensor::new().
🎯 Why: Tensor::new() implicitly invokes .to_vec() on the input slice, causing a double heap allocation. Manual for loops with .push() introduce bounds checking and loop overhead inside highly repetitive ML routines.
📊 Impact: Completely eliminates an extra $O(N)$ heap allocation inside scalar reductions and arithmetic ops, while removing bounds checks by leveraging standard iterators.
🔬 Measurement: Run the test suite (cargo test -p aether-core --offline) and look for correct outputs. Benchmarks on Tensor::add or mse derivatives will show reduced memory overhead and increased throughput.

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PR created automatically by Jules for task 5113574221031741293 started by @teerthsharma

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