diff --git a/nalgebra-sparse/src/factorization/cholesky.rs b/nalgebra-sparse/src/factorization/cholesky.rs
index 86a95767..1f653278 100644
--- a/nalgebra-sparse/src/factorization/cholesky.rs
+++ b/nalgebra-sparse/src/factorization/cholesky.rs
@@ -3,7 +3,7 @@ use crate::ops::serial::spsolve_csc_lower_triangular;
 use crate::ops::Op;
 use crate::pattern::SparsityPattern;
 use core::{iter, mem};
-use nalgebra::{DMatrix, DMatrixSlice, DMatrixSliceMut, RealField, Scalar};
+use nalgebra::{DMatrix, DMatrixSlice, DMatrixSliceMut, RealField};
 use std::fmt::{Display, Formatter};
 
 /// A symbolic sparse Cholesky factorization of a CSC matrix.
@@ -209,15 +209,16 @@ impl<T: RealField> CscCholesky<T> {
                     let irow = *self.m_pattern.minor_indices().get_unchecked(p);
 
                     if irow >= k {
-                        *self.work_x.get_unchecked_mut(irow) = *values.get_unchecked(p);
+                        *self.work_x.get_unchecked_mut(irow) = values.get_unchecked(p).clone();
                     }
                 }
 
                 for &j in self.u_pattern.lane(k) {
-                    let factor = -*self
+                    let factor = -self
                         .l_factor
                         .values()
-                        .get_unchecked(*self.work_c.get_unchecked(j));
+                        .get_unchecked(*self.work_c.get_unchecked(j))
+                        .clone();
                     *self.work_c.get_unchecked_mut(j) += 1;
 
                     if j < k {
@@ -225,27 +226,27 @@ impl<T: RealField> CscCholesky<T> {
                         let col_j_entries = col_j.row_indices().iter().zip(col_j.values());
                         for (&z, val) in col_j_entries {
                             if z >= k {
-                                *self.work_x.get_unchecked_mut(z) += val.clone() * factor;
+                                *self.work_x.get_unchecked_mut(z) += val.clone() * factor.clone();
                             }
                         }
                     }
                 }
 
-                let diag = *self.work_x.get_unchecked(k);
+                let diag = self.work_x.get_unchecked(k).clone();
 
                 if diag > T::zero() {
                     let denom = diag.sqrt();
 
                     {
                         let (offsets, _, values) = self.l_factor.csc_data_mut();
-                        *values.get_unchecked_mut(*offsets.get_unchecked(k)) = denom;
+                        *values.get_unchecked_mut(*offsets.get_unchecked(k)) = denom.clone();
                     }
 
                     let mut col_k = self.l_factor.col_mut(k);
                     let (col_k_rows, col_k_values) = col_k.rows_and_values_mut();
                     let col_k_entries = col_k_rows.iter().zip(col_k_values);
                     for (&p, val) in col_k_entries {
-                        *val = *self.work_x.get_unchecked(p) / denom;
+                        *val = self.work_x.get_unchecked(p).clone() / denom.clone();
                         *self.work_x.get_unchecked_mut(p) = T::zero();
                     }
                 } else {
diff --git a/nalgebra-sparse/src/ops/serial/csc.rs b/nalgebra-sparse/src/ops/serial/csc.rs
index 70e61523..e5c9ae4e 100644
--- a/nalgebra-sparse/src/ops/serial/csc.rs
+++ b/nalgebra-sparse/src/ops/serial/csc.rs
@@ -165,13 +165,13 @@ fn spsolve_csc_lower_triangular_no_transpose<T: RealField>(
             // a severe penalty)
             let diag_csc_index = l_col_k.row_indices().iter().position(|&i| i == k);
             if let Some(diag_csc_index) = diag_csc_index {
-                let l_kk = l_col_k.values()[diag_csc_index];
+                let l_kk = l_col_k.values()[diag_csc_index].clone();
 
                 if l_kk != T::zero() {
                     // Update entry associated with diagonal
                     x_col_j[k] /= l_kk;
                     // Copy value after updating (so we don't run into the borrow checker)
-                    let x_kj = x_col_j[k];
+                    let x_kj = x_col_j[k].clone();
 
                     let row_indices = &l_col_k.row_indices()[(diag_csc_index + 1)..];
                     let l_values = &l_col_k.values()[(diag_csc_index + 1)..];
@@ -179,7 +179,7 @@ fn spsolve_csc_lower_triangular_no_transpose<T: RealField>(
                     // Note: The remaining entries are below the diagonal
                     for (&i, l_ik) in row_indices.iter().zip(l_values) {
                         let x_ij = &mut x_col_j[i];
-                        *x_ij -= l_ik.clone() * x_kj;
+                        *x_ij -= l_ik.clone() * x_kj.clone();
                     }
 
                     x_col_j[k] = x_kj;
@@ -223,22 +223,22 @@ fn spsolve_csc_lower_triangular_transpose<T: RealField>(
             // TODO: Can use exponential search here to quickly skip entries
             let diag_csc_index = l_col_i.row_indices().iter().position(|&k| i == k);
             if let Some(diag_csc_index) = diag_csc_index {
-                let l_ii = l_col_i.values()[diag_csc_index];
+                let l_ii = l_col_i.values()[diag_csc_index].clone();
 
                 if l_ii != T::zero() {
                     // // Update entry associated with diagonal
                     // x_col_j[k] /= a_kk;
 
                     // Copy value after updating (so we don't run into the borrow checker)
-                    let mut x_ii = x_col_j[i];
+                    let mut x_ii = x_col_j[i].clone();
 
                     let row_indices = &l_col_i.row_indices()[(diag_csc_index + 1)..];
                     let a_values = &l_col_i.values()[(diag_csc_index + 1)..];
 
                     // Note: The remaining entries are below the diagonal
-                    for (&k, &l_ki) in row_indices.iter().zip(a_values) {
-                        let x_kj = x_col_j[k];
-                        x_ii -= l_ki * x_kj;
+                    for (k, l_ki) in row_indices.iter().zip(a_values) {
+                        let x_kj = x_col_j[*k].clone();
+                        x_ii -= l_ki.clone() * x_kj;
                     }
 
                     x_col_j[i] = x_ii / l_ii;