diff --git a/Iterators and Closures.md b/Iterators and Closures.md
index e92a203..2ae8e6c 100644
--- a/Iterators and Closures.md	
+++ b/Iterators and Closures.md	
@@ -17,4 +17,15 @@ It will cover:
 
 We have already covered some other Rust freatures, such as pattern matchin and enums, that are also influenced by the functional style.
 
-Mastering closures and iterators is an improtant part of wiritng idiomatic, fast Rust code.
\ No newline at end of file
+Mastering closures and iterators is an improtant part of wiritng idiomatic, fast Rust code.
+
+
+## Summary
+
+Closures and iterators are Rust features inspired by functional programming language ideas.
+
+They contribute to the capability to express high-level ideas at low-level preformance.
+
+The implementations of closures and iterators are such that runtime performance is not affected.
+
+This is part of Rust's goal to strive to provide zero-cost abstractions.
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diff --git a/The preformance Closures and Iterators.md b/The preformance Closures and Iterators.md
index e69de29..b99c16d 100644
--- a/The preformance Closures and Iterators.md	
+++ b/The preformance Closures and Iterators.md	
@@ -0,0 +1,84 @@
+# Comparing Performance: Loops vs. Iterators
+
+To determince whether to use loops or iterators, you need to know which implementation is faster
+
+Is it the version with an explicit `for` loop?
+
+Is it the version with iterators?
+
+Here is a benchmark where we load the entire contnets of *The Adventures of Sherlock Holmes* by Sir Arthur Conan Doyle into a `String` and looking ofr the word *the* in the contents
+
+Here is the results of the benchmark on the version of `search` using the `for` loop and the version using iterators:
+```
+test bench_search_for  ... bench:  19,620,300 ns/iter (+/- 915,700)
+test bench_search_iter ... bench:  19,234,900 ns/iter (+/- 657,200)
+```
+The two have similar performace!
+
+We won't explain the benchmark code here, because the poin is not to prive that the two versions are equivalent but to get a general sense of how these two compare performance-wise.
+
+For a more comprehensive benchmark, you should check using various texts of various sizes as the `contents`, different words and words of different lenghts as the `query` and all kinds of other variations.
+
+The point is this, iterators, although a high-level abstraction, get compiled down to roughly the same code as if you wrote the lower-level code yourself.
+
+Iterators are one of Rust's *zero-cost abstractions`. This means using the abstraction imposes no addtional runtime overhead.
+
+This is analogous to how Bjarne Stroustrup, the original designer and implementor of C++ defines *zero-verhead* in "Fondations of C++" (2012)
+```
+In general, C++ implementations obey the zero-overhead principle: What you don’t use, you don’t pay for. And further: What you do use, you couldn’t hand code any better.
+```
+
+Here is another example, the code is taken from an audio decoder.
+
+The decoding algorithm uses the linear prediction mathematical operation to estimate future values based on a linear function of the previous samples.
+
+This code uses an iterator chain to do some math on three variables in scope:
+- a `buffer` slice of data
+- an array of `coefficients`
+- an amount ot which shift data in `qlp_shift`
+
+We declared the variables within this example but not given them any values.
+
+Even though this code doesnt have muc meaning outside of its context, it is still a concise, real-world example of how Rust tranlate high-level ideas to low-level code.
+```rust
+let buffer: &mut [i32];
+let coefficients: [i64; 12];
+let qlp_shift: i16;
+
+for i in 12..buffer.len() {
+    let prediction = coefficients.iter()
+                                 .zip(&buffer[i - 12..i])
+                                 .map(|(&c, &s)| c * s as i64)
+                                 .sum::<i64>() >> qlp_shift;
+    let delta = buffer[i];
+    buffer[i] = prediction as i32 + delta;
+}
+```
+To calcuate the value of `prediction`, the code iterates though each of he 12 values in `coefficients` and ses the `zip` method to pair the coefficient values with the previous 12 values in `buffer`
+
+For each pair then we multiply the values together, sum all the results and shift the bits in the sum `qlp_shift` bits to the right.
+
+Calculations in applications like audio decoders often prioritize perfomance.
+
+Here we are creating an iterator, using two adapters and then consuming the value.
+
+What assembly would this Rust code compile into.
+
+As of writing this in the book, it compiles down to the same assbly you would write by hand.
+
+There is no loop at all corresponding to the iteration over the values in `coefficients`.
+
+Rust knows that there are 12 iterations, so it "unrolls" the loop.
+
+*Unrolling* is an optimization that removes the overhead of the loop controlling code and instead generates repetitive code for each iteration fo the loop.
+
+All of the coefficients ge stored in registers which means accessing the values is very fast.
+
+There are no bounds checks on the array access at runtime.
+
+All of these optimizations that Rust is able to apply make the resulting code extremely efficient.
+
+Now you know that you can use iterators and closures without fear of performance hits.
+
+They make code seem like its highe level but again dont impose a performance hit.
+