diff --git a/src/main/java/org/flag4j/operations/sparse/coo/real_complex/RealComplexCooTensorOperations.java b/src/main/java/org/flag4j/operations/sparse/coo/real_complex/RealComplexCooTensorOperations.java
index b02c28b54..88912037a 100644
--- a/src/main/java/org/flag4j/operations/sparse/coo/real_complex/RealComplexCooTensorOperations.java
+++ b/src/main/java/org/flag4j/operations/sparse/coo/real_complex/RealComplexCooTensorOperations.java
@@ -261,76 +261,4 @@ public static CooCTensor elemMult(CooTensor src1, CooCTensor src2) {
         // Truncate arrays if necessary.
         return new CooCTensor(src1.shape, Arrays.copyOf(productEntries, count), Arrays.copyOf(productIndices, count));
     }
-
-
-    /**
-     * <p>Computes the element-wise division between two sparse COO tensors.</p>
-     *
-     * <p>Assumes indices of both tensors are sorted lexicographically.</p>
-     *
-     * @param src1 First tensor in the element-wise division.
-     * @param src2 Second tensor in the element-wise division.
-     * @return The element-wise quotient of {@code src1} and {@code src2}.
-     */
-    public static CooCTensor elemdiv(CooCTensor src1, CooTensor src2) {
-        ParameterChecks.assertEqualShape(src1.shape, src2.shape);
-
-        CNumber[] productEntries = new CNumber[Math.min(src1.nnz, src2.nnz)];
-        int[][] productIndices = new int[Math.min(src1.nnz, src2.nnz)][src1.indices[0].length];
-        int count = 0;
-
-        int src2Idx = 0;
-        for(int i = 0; i < src1.nnz && src2Idx < src2.nnz; i++) {
-            int cmp = -1;
-
-            while(src2Idx < src2.nnz && (cmp = Arrays.compare(src2.indices[src2Idx], src1.indices[i])) < 0) {
-                src2Idx++;
-            }
-
-            if(src2Idx < src2.nnz && cmp == 0) {
-                productEntries[count] = src1.entries[i].div(src2.entries[src2Idx]);
-                productIndices[count] = src1.indices[i];
-                count++;
-            }
-        }
-
-        // Truncate arrays if necessary.
-        return new CooCTensor(src1.shape, Arrays.copyOf(productEntries, count), Arrays.copyOf(productIndices, count));
-    }
-
-
-    /**
-     * <p>Computes the element-wise division between two sparse COO tensors.</p>
-     *
-     * <p>Assumes indices of both tensors are sorted lexicographically.</p>
-     *
-     * @param src1 First tensor in the element-wise division.
-     * @param src2 Second tensor in the element-wise division.
-     * @return The element-wise quotient of {@code src1} and {@code src2}.
-     */
-    public static CooCTensor elemdiv(CooTensor src1, CooCTensor src2) {
-        ParameterChecks.assertEqualShape(src1.shape, src2.shape);
-
-        CNumber[] productEntries = new CNumber[Math.min(src1.nnz, src2.nnz)];
-        int[][] productIndices = new int[Math.min(src1.nnz, src2.nnz)][src1.indices[0].length];
-        int count = 0;
-
-        int src2Idx = 0;
-        for(int i = 0; i < src1.nnz && src2Idx < src2.nnz; i++) {
-            int cmp = -1;
-
-            while(src2Idx < src2.nnz && (cmp = Arrays.compare(src2.indices[src2Idx], src1.indices[i])) < 0) {
-                src2Idx++;
-            }
-
-            if(src2Idx < src2.nnz && cmp == 0) {
-                productEntries[count] = new CNumber(src1.entries[i]).div(src2.entries[src2Idx]);
-                productIndices[count] = src1.indices[i];
-                count++;
-            }
-        }
-
-        // Truncate arrays if necessary.
-        return new CooCTensor(src1.shape, Arrays.copyOf(productEntries, count), Arrays.copyOf(productIndices, count));
-    }
 }