diff --git a/chuck/tasks/graph_analytics/task.py b/chuck/tasks/graph_analytics/task.py
index 79cb5d3..7504003 100644
--- a/chuck/tasks/graph_analytics/task.py
+++ b/chuck/tasks/graph_analytics/task.py
@@ -4,6 +4,7 @@
 from typing import Any
 
 from ...common import TaskSpec, round6
+import numpy as np
 
 
 def generate(node_count: int, seed: int) -> dict[str, list[str]]:
@@ -19,28 +20,36 @@ def generate(node_count: int, seed: int) -> dict[str, list[str]]:
     return graph
 
 
-def solve(graph: dict[str, list[str]], iterations: int = 16, damping: float = 0.85) -> dict[str, Any]:
-    nodes = sorted(graph)
-    if not nodes:
+def solve(graph: dict[str, list[str]] , iterations: int = 16, damping: float = 0.85) -> dict[str, Any]:
+    if not graph:
         return {"node_count": 0, "top_node": "", "top_score": 0.0, "checksum": 0.0}
 
-    rank = {node: 1.0 / len(nodes) for node in nodes}
-    outgoing = {node: graph[node] if graph[node] else nodes for node in nodes}
-    base = (1.0 - damping) / len(nodes)
+    nodes = sorted(graph)
+    N = len(nodes)
+    idx_map = {node: i for i, node in enumerate(nodes)}
+
+    rows = np.array([idx_map[src] for src, targets in graph.items() for _ in targets], dtype=np.int64)
+    cols = np.array([idx_map[tgt] for _, targets in graph.items() for tgt in targets], dtype=np.int64)
+    out_degree = np.bincount(rows, minlength=N).astype(np.float64)
+
+    rank = np.full((N,), 1.0/N, dtype=np.float64)
+    base = (1.0 - damping) / N
+    trans_wt = damping / out_degree
+
     for _ in range(iterations):
-        new_rank = {node: base for node in nodes}
-        for node in nodes:
-            share = rank[node] / len(outgoing[node])
-            for target in outgoing[node]:
-                new_rank[target] += damping * share
-        rank = new_rank
-    top_node = max(nodes, key=lambda node: (rank[node], node))
-    checksum = sum((index + 1) * rank[node] for index, node in enumerate(nodes))
+        msgs = (rank * trans_wt)[rows]
+        recieved = np.bincount(cols, weights=msgs, minlength=N)
+        rank = recieved + base
+
+    top_node = int(np.argmax(rank))
+    mult = np.arange(1, N+1)
+    checksum = float(np.dot(mult, rank))
+
     return {
-        "node_count": len(nodes),
-        "top_node": top_node,
-        "top_score": round6(rank[top_node]),
-        "checksum": round6(checksum),
+        "node_count": N,
+        "top_node": f"n{top_node:04d}",
+        "top_score": round6(float(rank[top_node])),
+        "checksum" : round6(checksum),
     }
 
 
diff --git a/pyproject.toml b/pyproject.toml
index 11341c3..ebbf51b 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -8,6 +8,9 @@ version = "0.1.0"
 description = "Solver toolkit for 10 computational tasks with optional native C++ backends"
 requires-python = ">=3.10"
 readme = "README.md"
+dependencies = [
+    "numpy"
+]
 
 [tool.setuptools]