diff --git a/src/dr/app/beast/development_parsers.properties b/src/dr/app/beast/development_parsers.properties
index f5dc2ee5e3..39acd06ada 100644
--- a/src/dr/app/beast/development_parsers.properties
+++ b/src/dr/app/beast/development_parsers.properties
@@ -42,6 +42,7 @@ dr.inferencexml.distribution.RowDimensionPoissonPriorParser
 dr.inferencexml.distribution.MomentDistributionModelParser
 dr.inferencexml.distribution.DeterminentalPointProcessPriorParser
 dr.inferencexml.distribution.TruncatedDistributionLikelihoodParser
+dr.inferencexml.distribution.CauchyDistributionModelParser
 
 # STRUCTURED COALESCENT
 dr.evomodel.coalescent.structure.StructuredCoalescentLikelihood
diff --git a/src/dr/inference/distribution/CauchyDistribution.java b/src/dr/inference/distribution/CauchyDistribution.java
index 65a43b2a46..961a4786a6 100644
--- a/src/dr/inference/distribution/CauchyDistribution.java
+++ b/src/dr/inference/distribution/CauchyDistribution.java
@@ -43,7 +43,7 @@ public CauchyDistribution(double median, double scale){
 
     public static double pdf(double x, double median, double scale) {
         double dev = x - median;
-        return  scale / (dev * dev + scale * scale) / Math.PI;
+        return scale / (dev * dev + scale * scale) / Math.PI;
     }
 
     public static double cdf(double x, double median, double scale) {
@@ -69,7 +69,7 @@ public static double quantile(double p, double median, double scale) {
 
     public static double gradLogPdf(double x, double median, double scale) {
         double dev = x - median;
-        return 2 * dev / (dev * dev  + scale * scale);
+        return -2 * dev / (dev * dev  + scale * scale);
     }
 
     public static double logPdf(double x, double median, double scale) {
diff --git a/src/test/dr/inference/distribution/CauchyDistributionTest.java b/src/test/dr/inference/distribution/CauchyDistributionTest.java
new file mode 100644
index 0000000000..1ff7b5fdf1
--- /dev/null
+++ b/src/test/dr/inference/distribution/CauchyDistributionTest.java
@@ -0,0 +1,81 @@
+/*
+ * CauchyDistributionTest.java
+ *
+ * Copyright © 2002-2024 the BEAST Development Team
+ * http://beast.community/about
+ *
+ * This file is part of BEAST.
+ * See the NOTICE file distributed with this work for additional
+ * information regarding copyright ownership and licensing.
+ *
+ * BEAST is free software; you can redistribute it and/or modify
+ * it under the terms of the GNU Lesser General Public License as
+ * published by the Free Software Foundation; either version 2
+ * of the License, or (at your option) any later version.
+ *
+ *  BEAST is distributed in the hope that it will be useful,
+ *  but WITHOUT ANY WARRANTY; without even the implied warranty of
+ *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ *  GNU Lesser General Public License for more details.
+ *
+ * You should have received a copy of the GNU Lesser General Public
+ * License along with BEAST; if not, write to the
+ * Free Software Foundation, Inc., 51 Franklin St, Fifth Floor,
+ * Boston, MA  02110-1301  USA
+ *
+ */
+
+package test.dr.inference.distribution;
+
+import dr.inference.distribution.CauchyDistributionModel;
+import dr.inference.model.Parameter;
+import dr.math.NumericalDerivative;
+import dr.math.UnivariateFunction;
+import junit.framework.TestCase;
+import org.apache.commons.math.distribution.CauchyDistributionImpl;
+
+/**
+ * @author Marc A Suchard
+ */
+
+public class CauchyDistributionTest extends TestCase {
+
+    public CauchyDistributionTest(String name) {
+        super(name);
+    }
+
+    public void setUp() throws Exception {
+        super.setUp();
+    }
+
+    public void testCauchyDistribution() {
+        CauchyDistributionModel d1 = new CauchyDistributionModel(
+                new Parameter.Default(2.0),
+                new Parameter.Default(3.0)
+        );
+
+        CauchyDistributionImpl d2 = new CauchyDistributionImpl(2, 3);
+
+        assertEquals(d1.pdf(-1), d2.density(-1), 1E-10);
+        assertEquals(d1.logPdf(-1), Math.log(d2.density(-1)), 1E-10);
+
+        double dx = NumericalDerivative.firstDerivative(new UnivariateFunction() {
+            @Override
+            public double evaluate(double argument) {
+                return d1.logPdf(argument);
+            }
+
+            @Override
+            public double getLowerBound() {
+                return Double.NEGATIVE_INFINITY;
+            }
+
+            @Override
+            public double getUpperBound() {
+                return Double.POSITIVE_INFINITY;
+            }
+        }, 3.0);
+
+        assertEquals(d1.getGradientLogDensity(new double[] { 3.0 } )[0], dx, 1E-4);
+    }
+}
\ No newline at end of file