diff --git a/treccovid_semantic_search/index-1M.json b/treccovid_semantic_search/index-1M.json
new file mode 100644
index 00000000..e1489ebb
--- /dev/null
+++ b/treccovid_semantic_search/index-1M.json
@@ -0,0 +1,45 @@
+{
+  "settings": {
+    "index.number_of_shards": {{number_of_shards | default(1)}},
+    "index.number_of_replicas": {{number_of_replicas | default(0)}},
+    "index.queries.cache.enabled": {{query_cache_enabled | default(false) | tojson}},
+    "index.requests.cache.enable": {{requests_cache_enabled | default(false) | tojson}},
+    "index.merge.policy.max_merged_segment": "100GB",
+    "index.knn": true,
+    "default_pipeline": "nlp-ingest-pipeline"
+  },
+  "mappings": {
+    "dynamic": "true",
+    "_source": {
+      "enabled": {{ source_enabled | default(true) | tojson }}
+    },
+    "properties": {
+      "title": {
+        "type": "text"
+      },
+      "text": {
+        "type": "text"
+      },
+      "metadata": {
+        "type": "nested",
+        "properties": {
+          "url": {
+            "type": "text"
+          },
+          "pubmed_id": {
+            "type": "integer"
+          }
+        }
+      }, 
+      "passage_embedding": {
+        "type": "knn_vector",
+        "dimension": 768,
+        "method": {
+            "name": "hnsw",
+            "space_type": "innerproduct",
+            "engine": "faiss"
+        }
+      }
+    }
+  }
+}
diff --git a/treccovid_semantic_search/operations/default.json b/treccovid_semantic_search/operations/default.json
index ac3a65e7..0dbf85cf 100644
--- a/treccovid_semantic_search/operations/default.json
+++ b/treccovid_semantic_search/operations/default.json
@@ -48,6 +48,26 @@
         }
       }
     },
+    {
+      "name": "create-normalization-processor-search-pipeline",
+      "operation-type": "create-search-pipeline",
+      "id": "nlp-normalization-search-pipeline",
+      "body": {
+        "description": "Post processor for hybrid search with min_max normalization and arithmetic_mean combination",
+        "phase_results_processors": [
+          {
+              "normalization-processor": {
+                  "normalization": {
+                      "technique": "min_max"
+                  },
+                  "combination": {
+                      "technique": "arithmetic_mean"
+                  }
+              }
+          }
+        ]
+      }
+    },
     {
       "name": "semantic-search",
       "operation-type": "search",
@@ -69,4 +89,62 @@
           }
         }
       }
+    },
+    {
+      "name": "semantic-search-neural",
+      "operation-type": "search",
+      "variable-queries": {{variable_queries | default(0)}},
+      "param-source": "semantic-search-neural-source",
+      "body": {
+        "_source": {
+          "excludes": [
+            "passage_embedding"
+          ]
+        },
+        "query": {
+          "neural": {
+            "passage_embedding": {
+              "query_text": "what types of rapid testing for Covid-19 have been developed?",
+              "model_id": "",
+              "k": {{k | default(10)}}
+            }
+          }
+        }
+      }
+    },
+    {
+      "name": "hybrid-search-bm25-neural",
+      "operation-type": "search",
+      "request-params": {
+        "search_pipeline": "nlp-normalization-search-pipeline"
+      },
+      "variable-queries": {{variable_queries | default(0)}},
+      "param-source": "hybrid-query-bm25-neural-search-source",
+      "body": {
+        "_source": {
+          "excludes": [
+            "passage_embedding"
+          ]
+        },
+        "query": {
+          "hybrid": {
+            "queries": [
+              {
+                "match": {
+                  "title": ""
+                }
+              },
+              {
+                "neural": {
+                  "passage_embedding": {
+                    "query_text": "what types of rapid testing for Covid-19 have been developed?",
+                    "model_id": "",
+                    "k": {{k | default(10)}}
+                  }
+                }
+              }
+            ] 
+          }
+        }
+      }
     }
diff --git a/treccovid_semantic_search/params.json b/treccovid_semantic_search/params.json
new file mode 100644
index 00000000..7f17ce4f
--- /dev/null
+++ b/treccovid_semantic_search/params.json
@@ -0,0 +1,13 @@
+{
+    "bulk_indexing_clients": 4,
+    "bulk_size": 200,
+    "number_of_replicas": 1,
+    "number_of_shards" :8,
+    "ingest_percentage":2,
+    "search_clients": 8,
+    "warmup_iterations": 20,
+    "iterations": 100,
+    "k": 100,
+    "corpus_size": "1M",
+    "variable_queries": 10
+}
diff --git a/treccovid_semantic_search/test_procedures/default.json b/treccovid_semantic_search/test_procedures/default.json
index 12c1f675..d80fb0d7 100644
--- a/treccovid_semantic_search/test_procedures/default.json
+++ b/treccovid_semantic_search/test_procedures/default.json
@@ -12,7 +12,6 @@
                 "plugins": {
                   "ml_commons": {
                     "only_run_on_ml_node": "false",
-                    "native_memory_threshold": "99",
                     "allow_registering_model_via_local_file": "true",
                     "allow_registering_model_via_url": "true"
                   }
@@ -109,4 +108,133 @@
           "clients": {{ search_clients | default(1)}}
         }
       ]
+    },
+    {
+      "name": "index-merge-search-vector",
+      "description": "Indexes the corpus with vector embedding and then runs queries with vector embedding.",
+      "default": false,
+      "schedule": [
+        {
+          "name": "cluster-settings",
+          "operation": {
+            "operation-type": "put-settings",
+            "body": {
+              "persistent": {
+                "plugins": {
+                  "ml_commons": {
+                    "only_run_on_ml_node": "false",
+                    "native_memory_threshold": "99",
+                    "allow_registering_model_via_local_file": "true",
+                    "allow_registering_model_via_url": "true"
+                  }
+                }
+              }
+            }
+          }
+        },
+        {
+          "operation": "delete-index"
+        },
+        {
+          "operation": "delete-ingest-pipeline"
+        },
+        {
+          "operation": {
+            "operation-type": "delete-ml-model",
+            "model-name": "{{ model_name | default('huggingface/sentence-transformers/all-mpnet-base-v2')}}"
+          }
+        },
+        {
+          "operation": {
+            "operation-type": "register-ml-model",
+            "model-name": "{{ model_name | default('huggingface/sentence-transformers/all-mpnet-base-v2')}}",
+            "model-version": "{{ model_version | default('1.0.1') }}",
+            "model-format": "{{ model_format | default('TORCH_SCRIPT') }}",
+            "model-config-file": "{{ model_config_file | default('') }}"
+          }
+        },
+        {
+          "operation": "deploy-ml-model"
+        },
+        {
+          "operation": "create-ingest-pipeline"
+        },
+        {
+          "operation": {
+            "operation-type": "create-index",
+            "settings": {%- if index_settings is defined %} {{index_settings | tojson}} {%- else %} {
+              "index.refresh_interval": "5s",
+              "index.translog.flush_threshold_size": "1g"
+            }{%- endif %}
+          }
+        },
+        {
+          "name": "check-cluster-health",
+          "operation": {
+            "operation-type": "cluster-health",
+            "index": "treccovid1m",
+            "request-params": {
+              "wait_for_status": "{{cluster_health | default('green')}}",
+              "wait_for_no_relocating_shards": "true"
+            },
+            "retry-until-success": true
+          }
+        },
+        {
+          "operation": "index-append",
+          "warmup-time-period": 60,
+          "clients": {{bulk_indexing_clients | default(1)}},
+          "ignore-response-error-level": "{{error_level | default('non-fatal')}}"
+        },
+        {
+          "name": "refresh-after-index",
+          "operation": "refresh"
+        },
+        {
+          "operation": {
+            "operation-type": "force-merge",
+            "request-timeout": 7200{%- if force_merge_max_num_segments is defined %},
+            "max-num-segments": {{ force_merge_max_num_segments | tojson }}
+            {%- endif %}
+          }
+        },
+        {
+          "name": "refresh-after-force-merge",
+          "operation": "refresh"
+        },
+        {
+          "operation": "wait-until-merges-finish"
+        }
+      ]
+    },
+    {
+      "name": "run-search-semantic",
+      "description": "Runs search workload for experiment 3: neural query search",
+      "default": false,
+      "schedule": [
+          {
+              "name": "check-cluster-health-before-index-creation",
+              "operation": {
+                "operation-type": "cluster-health",
+                "index": "treccovid1m",
+                "request-params": {
+                  "wait_for_status": "{{cluster_health | default('green')}}",
+                  "wait_for_no_relocating_shards": "true"
+                },
+                "retry-until-success": true
+              }
+          },
+          {
+            "operation": "semantic-search-neural",
+            "warmup-iterations": {{warmup_iterations | default(50) | tojson}},
+            "iterations": {{iterations | default(100) | tojson }},
+            "clients": {{ search_clients | default(1)}}
+          },
+          {
+            "operation": "hybrid-search-bm25-neural",
+            "warmup-iterations": {{warmup_iterations | default(50) | tojson}},
+            "iterations": {{iterations | default(100) | tojson }},
+            "clients": {{ search_clients | default(1)}}
+          }
+      ]
     }
diff --git a/treccovid_semantic_search/workload.json b/treccovid_semantic_search/workload.json
index 761d1d0e..92cedd57 100644
--- a/treccovid_semantic_search/workload.json
+++ b/treccovid_semantic_search/workload.json
@@ -1,15 +1,25 @@
 {% import "benchmark.helpers" as benchmark with context %}
-
 {
   "version": 2,
     "description": "Trec-Covid is a dataset collection of documents about COVID-19 information.",
   "indices": [
+    {% if not corpus_size %}
+      {% set corpus_size = '100' %}
+    {% endif %}
+    {% if corpus_size == '100' %}    
     {
       "name": "treccovid",
       "body": "index.json"
     }
+    {% elif corpus_size == '1M' %}
+    {
+      "name": "treccovid1m",
+      "body": "index-1M.json"
+    }
+    {% endif %}
   ],
   "corpora": [
+    {% if corpus_size == '100' %}    
     {
       "name": "treccovid",
       "base-url": "https://dbyiw3u3rf9yr.cloudfront.net/corpora/treccovid",
@@ -18,10 +28,24 @@
           "source-file": "documents.json.bz2",
           "document-count": 129192,
           "compressed-bytes": 51187469,
-          "uncompressed-bytes": 211980208
+          "uncompressed-bytes": 211980208,
+          "target-index": "treccovid"
+        }
+      ]
+    }
+    {% elif corpus_size == '1M' %}
+    {
+      "name": "treccovid1m",
+      "base-url": "https://github.com/martin-gaievski/neural-search/releases/download/trec_covid_dataset_1m_v2",
+      "documents": [
+        {
+          "source-file": "documents.json.zip",
+          "document-count": 1027986,
+          "target-index": "treccovid1m"
         }
       ]
     }
+    {% endif %}
   ],
   "operations": [
     {{ benchmark.collect(parts="operations/*.json") }}
diff --git a/treccovid_semantic_search/workload.py b/treccovid_semantic_search/workload.py
index 1eaa0436..50712aea 100644
--- a/treccovid_semantic_search/workload.py
+++ b/treccovid_semantic_search/workload.py
@@ -70,6 +70,117 @@ def params(self):
                 params['body']['query']['neural']['passage_embedding']['query_text'] = query_text
         return params
 
+class QueryParamSourceNeural:
+    def __init__(self, workload, params, **kwargs):
+        if len(workload.indices) == 1:
+            index = workload.indices[0].name
+            if len(workload.indices[0].types) == 1:
+                type = workload.indices[0].types[0].name
+            else:
+                type = None
+        else:
+            index = "_all"
+            type = None
+
+        self._params = params
+        self._params['index'] = index
+        self._params['type'] = type
+        self._params['variable-queries'] = params.get("variable-queries", 0)
+        self.infinite = True
+
+        if self._params['variable-queries'] > 0:
+            with open(script_dir + os.sep + 'workload_queries.json', 'r') as f:
+                d = json.loads(f.read())
+                source_file = d['source-file']
+                base_url = d['base-url']
+                compressed_bytes = d['compressed-bytes']
+                uncompressed_bytes = d['uncompressed-bytes']
+                compressed_path = script_dir + os.sep + source_file
+                uncompressed_path = script_dir + os.sep + Path(source_file).stem
+            if not os.path.exists(compressed_path):
+                downloader = Downloader(False, False)
+                downloader.download(base_url, None, compressed_path, compressed_bytes)
+            if not os.path.exists(uncompressed_path):
+                decompressor = Decompressor()
+                decompressor.decompress(compressed_path, uncompressed_path, uncompressed_bytes)
+
+    def partition(self, partition_index, total_partitions):
+        return self
+
+    def params(self):
+        params = self._params
+        with open('model_id.json', 'r') as f:
+            d = json.loads(f.read())
+            params['body']['query']['neural']['passage_embedding']['model_id'] = d['model_id']
+        count = self._params.get("variable-queries", 0)
+        if count > 0:
+            script_dir = os.path.dirname(os.path.realpath(__file__))
+            with open(script_dir + '/queries.json', 'r') as f:
+                lines = f.read().splitlines()
+                line =random.choice(lines)
+                query_text = json.loads(line)['text']
+                params['body']['query']['neural']['passage_embedding']['query_text'] = query_text
+
+        return params
+
+class QueryParamSourceHybridBm25Neural:
+    def __init__(self, workload, params, **kwargs):
+        if len(workload.indices) == 1:
+            index = workload.indices[0].name
+            if len(workload.indices[0].types) == 1:
+                type = workload.indices[0].types[0].name
+            else:
+                type = None
+        else:
+            index = "_all"
+            type = None
+
+        self._params = params
+        self._params['index'] = index
+        self._params['type'] = type
+        self._params['variable-queries'] = params.get("variable-queries", 0)
+        self.infinite = True
+
+        if self._params['variable-queries'] > 0:
+            with open(script_dir + os.sep + 'workload_queries.json', 'r') as f:
+                d = json.loads(f.read())
+                source_file = d['source-file']
+                base_url = d['base-url']
+                compressed_bytes = d['compressed-bytes']
+                uncompressed_bytes = d['uncompressed-bytes']
+                compressed_path = script_dir + os.sep + source_file
+                uncompressed_path = script_dir + os.sep + Path(source_file).stem
+            if not os.path.exists(compressed_path):
+                downloader = Downloader(False, False)
+                downloader.download(base_url, None, compressed_path, compressed_bytes)
+            if not os.path.exists(uncompressed_path):
+                decompressor = Decompressor()
+                decompressor.decompress(compressed_path, uncompressed_path, uncompressed_bytes)
+
+    def partition(self, partition_index, total_partitions):
+        return self
+
+    def params(self):
+        params = self._params
+        count = self._params.get("variable-queries", 0)
+        if count > 0:
+            script_dir = os.path.dirname(os.path.realpath(__file__))
+            model_id = ''
+            with open('model_id.json', 'r') as f:
+                    d = json.loads(f.read())
+                    model_id = d['model_id']
+            with open(script_dir + '/queries.json', 'r') as f:
+                lines = f.read().splitlines()
+                line =random.choice(lines)
+                query_text = json.loads(line)['text']
+                match_query = random.choice(query_text.split()).lower()
+                params['body']['query']['hybrid']['queries'][0]['match']['title'] = match_query                
+                params['body']['query']['hybrid']['queries'][1]['neural']['passage_embedding']['model_id'] = model_id
+                params['body']['query']['hybrid']['queries'][1]['neural']['passage_embedding']['query_text'] = query_text
+        return params
+
 def register(registry):
     registry.register_param_source("semantic-search-source", QueryParamSource)
+    registry.register_param_source("semantic-search-neural-source", QueryParamSourceNeural)
+    registry.register_param_source("hybrid-query-bm25-neural-search-source", QueryParamSourceHybridBm25Neural)
     registry.register_param_source("create-ingest-pipeline", ingest_pipeline_param_source)