diff --git a/numerical_methods/lu_decompose.cpp b/numerical_methods/lu_decompose.cpp
index a0a2d00ab..2ce5fb653 100644
--- a/numerical_methods/lu_decompose.cpp
+++ b/numerical_methods/lu_decompose.cpp
@@ -7,73 +7,15 @@
 #include <ctime>
 #include <iomanip>
 #include <iostream>
-#include <vector>
-#ifdef _OPENMP
-#include <omp.h>
-#endif
 
-/** Perform LU decomposition on matrix
- * \param[in] A matrix to decompose
- * \param[out] L output L matrix
- * \param[out] U output U matrix
- * \returns 0 if no errors
- * \returns negative if error occurred
- */
-int lu_decomposition(const std::vector<std::vector<double>> &A,
-                     std::vector<std::vector<double>> *L,
-                     std::vector<std::vector<double>> *U) {
-    int row, col, j;
-    int mat_size = A.size();
-
-    if (mat_size != A[0].size()) {
-        // check matrix is a square matrix
-        std::cerr << "Not a square matrix!\n";
-        return -1;
-    }
-
-    // regularize each row
-    for (row = 0; row < mat_size; row++) {
-        // Upper triangular matrix
-#ifdef _OPENMP
-#pragma omp for
-#endif
-        for (col = row; col < mat_size; col++) {
-            // Summation of L[i,j] * U[j,k]
-            double lu_sum = 0.;
-            for (j = 0; j < row; j++) lu_sum += L[0][row][j] * U[0][j][col];
-
-            // Evaluate U[i,k]
-            U[0][row][col] = A[row][col] - lu_sum;
-        }
-
-        // Lower triangular matrix
-#ifdef _OPENMP
-#pragma omp for
-#endif
-        for (col = row; col < mat_size; col++) {
-            if (row == col) {
-                L[0][row][col] = 1.;
-                continue;
-            }
-
-            // Summation of L[i,j] * U[j,k]
-            double lu_sum = 0.;
-            for (j = 0; j < row; j++) lu_sum += L[0][col][j] * U[0][j][row];
-
-            // Evaluate U[i,k]
-            L[0][col][row] = (A[col][row] - lu_sum) / U[0][row][row];
-        }
-    }
-
-    return 0;
-}
+#include "./lu_decomposition.h"
 
 /**
  * operator to print a matrix
  */
 template <typename T>
 std::ostream &operator<<(std::ostream &out,
-                         std::vector<std::vector<T>> const &v) {
+                         std::vector<std::valarray<T>> const &v) {
     const int width = 10;
     const char separator = ' ';
 
@@ -99,14 +41,14 @@ int main(int argc, char **argv) {
     std::srand(std::time(NULL));  // random number initializer
 
     /* Create a square matrix with random values */
-    std::vector<std::vector<double>> A(mat_size);
-    std::vector<std::vector<double>> L(mat_size);  // output
-    std::vector<std::vector<double>> U(mat_size);  // output
+    std::vector<std::valarray<double>> A(mat_size,
+                                         std::valarray<double>(mat_size));
+    std::vector<std::valarray<double>> L(
+        mat_size, std::valarray<double>(mat_size));  // output
+    std::vector<std::valarray<double>> U(
+        mat_size, std::valarray<double>(mat_size));  // output
     for (int i = 0; i < mat_size; i++) {
         // calloc so that all valeus are '0' by default
-        A[i] = std::vector<double>(mat_size);
-        L[i] = std::vector<double>(mat_size);
-        U[i] = std::vector<double>(mat_size);
         for (int j = 0; j < mat_size; j++)
             /* create random values in the limits [-range2, range-1] */
             A[i][j] = static_cast<double>(std::rand() % range - range2);
diff --git a/numerical_methods/lu_decomposition.h b/numerical_methods/lu_decomposition.h
new file mode 100644
index 000000000..9cb881ba9
--- /dev/null
+++ b/numerical_methods/lu_decomposition.h
@@ -0,0 +1,65 @@
+#pragma once
+
+#include <iostream>
+#include <valarray>
+#include <vector>
+#ifdef _OPENMP
+#include <omp.h>
+#endif
+
+/** Perform LU decomposition on matrix
+ * \param[in] A matrix to decompose
+ * \param[out] L output L matrix
+ * \param[out] U output U matrix
+ * \returns 0 if no errors
+ * \returns negative if error occurred
+ */
+template <typename T>
+int lu_decomposition(const std::vector<std::valarray<T>> &A,
+                     std::vector<std::valarray<double>> *L,
+                     std::vector<std::valarray<double>> *U) {
+    int row, col, j;
+    int mat_size = A.size();
+
+    if (mat_size != A[0].size()) {
+        // check matrix is a square matrix
+        std::cerr << "Not a square matrix!\n";
+        return -1;
+    }
+
+    // regularize each row
+    for (row = 0; row < mat_size; row++) {
+        // Upper triangular matrix
+#ifdef _OPENMP
+#pragma omp for
+#endif
+        for (col = row; col < mat_size; col++) {
+            // Summation of L[i,j] * U[j,k]
+            double lu_sum = 0.;
+            for (j = 0; j < row; j++) lu_sum += L[0][row][j] * U[0][j][col];
+
+            // Evaluate U[i,k]
+            U[0][row][col] = A[row][col] - lu_sum;
+        }
+
+        // Lower triangular matrix
+#ifdef _OPENMP
+#pragma omp for
+#endif
+        for (col = row; col < mat_size; col++) {
+            if (row == col) {
+                L[0][row][col] = 1.;
+                continue;
+            }
+
+            // Summation of L[i,j] * U[j,k]
+            double lu_sum = 0.;
+            for (j = 0; j < row; j++) lu_sum += L[0][col][j] * U[0][j][row];
+
+            // Evaluate U[i,k]
+            L[0][col][row] = (A[col][row] - lu_sum) / U[0][row][row];
+        }
+    }
+
+    return 0;
+}