clean up the console logging for the IBM QPU workflow.

em/ui.py

@@ -138,17 +138,6 @@ def _build_overview_card():
                 density="compact",
                 color="primary",
             )
-            vuetify3.VDivider(classes="my-0")
-            vuetify3.VCardSubtitle("Governing Equations", classes="text-caption font-weight-bold mt-0", style="font-size: 0.7rem;")
-            vuetify3.VDivider(classes="mb-0")
-            vuetify3.VListItemTitle("Maxwell's time-domain, 2D, TEz polarized.", classes="text-caption", style="font-size: 0.7rem;")
-            vuetify3.VCardSubtitle("Inputs", classes="text-caption font-weight-bold mt-0", style="font-size: 0.7rem;")
-            vuetify3.VDivider(classes="mb-0")
-            vuetify3.VListItemTitle("Geometry, excitation, medium, output visualization preferences.", classes="text-caption", style="font-size: 0.7rem;")
-            vuetify3.VCardSubtitle("Outputs", classes="text-caption font-weight-bold mt-0", style="font-size: 0.7rem;")
-            vuetify3.VDivider(classes="mb-0")
-            vuetify3.VListItemTitle("Surface plots of field components OR time evolution of field components at specified points.", classes="text-caption", style="font-size: 0.7rem;")
-
 
 def _build_geometry_card():
     """Build the Geometry configuration card."""

qlbm/qlbm_sample_app.py

@@ -519,38 +519,25 @@ def run_sampling_hw_ibm(
 
   def get_job_result(j):
     result = j.result()   # PrimitiveResult (a container of PubResults)
-    log(str(result))
+    log("Waiting for job results (this may take time)...")
 
     output=[]
 
     for T_total,pub in zip(T_list,result):
 
-      # We'll inspect the first PUB result
-      log(f"PUB metadata: {pub.metadata if hasattr(pub, 'metadata') else '<no metadata>'}")
-
-      # 1) Try to obtain counts via the recommended API
-      try:
-          counts = pub.data.meas.get_counts()
-          log("\nCounts (pub.data.meas.get_counts()) sample:")
-          log(str({k: counts[k] for k in list(counts)[:10]}))
-      except Exception as e:
-          log(f"Couldn't call pub.data.meas.get_counts(): {e}")
-          counts = None
-
-      # 2) Try join_data() (to combine multiple regs) and get_counts() on it
+      # Try join_data() to combine multiple regs and get_counts() on it
       try:
           joined = pub.join_data()    # join_data concatenates registers along bits axis
           joined_counts = joined.get_counts()
-          log("\nJoined counts (pub.join_data().get_counts()) sample:")
-          log(str({k: joined_counts[k] for k in list(joined_counts)[:10]}))
       except Exception as e:
-          log(f"join_data()/joined.get_counts() not available or failed: {e}")
+          log(f"Error retrieving counts: {e}")
           joined_counts = None
 
-
-      pts, counts = load_samples(joined_counts, T_total, logger=log)
+      # Suppress verbose logging by passing None as logger
+      pts, counts = load_samples(joined_counts, T_total, logger=None)
       output+=[estimate_density(pts, counts, bandwidth=0.05, grid_size=output_resolution)]
 
+    log(f"Processing complete: {len(output)} timestep(s)")
     fig = plot_density_isosurface_slider(output, T_list)
     return output, fig
   
@@ -590,16 +577,29 @@ def run_sampling_sim(
   output : list[ndarray]
       List of 3D density arrays, one per timestep
   fig : go.Figure
-      Plotly figure with slider animation through all timesteps
+    Plotly figure with slider animation through all timesteps (includes T=0 snapshot when available)
   """
   
   if type(ux)==str:
     ux,uy,uz=str_to_lambda(ux,uy,uz)
 
   # Convert string init_state_prep_circ to circuit if needed (matches original logic)
-  if type(init_state_prep_circ)==str:
+  init_state_label = init_state_prep_circ if isinstance(init_state_prep_circ, str) else "custom"
+  if isinstance(init_state_prep_circ, str):
     init_state_prep_circ=get_named_init_state_circuit(n,init_state_prep_circ)
 
+  initial_snapshot = None
+  try:
+    initial_snapshot = show_initial_distribution(
+        n=n,
+        init_state_name=str(init_state_label),
+        plot=False,
+        return_data=True,
+        init_state_circuit=init_state_prep_circ,
+    )
+  except Exception as exc:
+    print(f"Warning: Unable to compute initial distribution snapshot: {exc}")
+
   qc_list=get_circuit(n,ux,uy,uz,init_state_prep_circ,T_list,vel_resolution,measure=False)
   backend = AerSimulator(method = 'statevector')
   output=[]
@@ -655,8 +655,18 @@ def run_sampling_sim(
   x_coords = np.linspace(0, 1, 2**n)
   X = np.meshgrid(x_coords, x_coords, x_coords, indexing='ij')
 
-  # Create figure with slider for all timesteps
-  fig = _create_slider_figure(output, T_list, X)
+  outputs_for_plot = output.copy()
+  times_for_plot = list(T_list)
+  if initial_snapshot is not None:
+    initial_density, _ = initial_snapshot
+    if times_for_plot and times_for_plot[0] == 0:
+      outputs_for_plot[0] = initial_density
+    else:
+      outputs_for_plot = [initial_density] + outputs_for_plot
+      times_for_plot = [0] + times_for_plot
+
+  # Create figure with slider for all timesteps (including T=0 if available)
+  fig = _create_slider_figure(outputs_for_plot, times_for_plot, X)
   return output, fig
 
 
@@ -739,8 +749,8 @@ def _create_slider_figure(output_list, T_list, X):
 
 
 def show_initial_distribution(
-    n: int,
-    init_state_name: str,
+  n: int,
+  init_state_name: str = "sin",
     # Sinusoidal parameters (frequency multipliers)
     sine_k_x: float = 1.0,
     sine_k_y: float = 1.0,
@@ -751,8 +761,9 @@ def show_initial_distribution(
     gauss_cz: float = None,
     gauss_sigma: float = None,
     # Display options
-    plot: bool = True,
-    return_data: bool = False,
+  plot: bool = True,
+  return_data: bool = False,
+  init_state_circuit=None,
 ):
   """
   Visualize the initial distribution by running the state preparation circuit
@@ -774,6 +785,10 @@ def show_initial_distribution(
       Whether to display the 3D isosurface plot (default=True)
   return_data : bool
       Whether to return the distribution data (default=False)
+  init_state_circuit : QuantumCircuit, optional
+    Pre-built circuit to evaluate. When provided, ``init_state_name`` and the
+    associated parameters are ignored and the supplied circuit is simulated
+    directly.
   
   Returns
   -------
@@ -787,18 +802,23 @@ def show_initial_distribution(
   """
   N = 2**n
   
-  # Get the state preparation circuit from get_named_init_state_circuit
-  init_state_prep_circ = get_named_init_state_circuit(
-      n,
-      init_state_name,
-      sine_k_x=sine_k_x,
-      sine_k_y=sine_k_y,
-      sine_k_z=sine_k_z,
-      gauss_cx=gauss_cx,
-      gauss_cy=gauss_cy,
-      gauss_cz=gauss_cz,
-      gauss_sigma=gauss_sigma,
-  )
+  # Determine the state preparation circuit. Either use the provided circuit
+  # (useful when custom circuits are passed in) or construct one from the
+  # named presets for standalone previews.
+  if init_state_circuit is not None:
+    init_state_prep_circ = init_state_circuit.copy()
+  else:
+    init_state_prep_circ = get_named_init_state_circuit(
+        n,
+        init_state_name,
+        sine_k_x=sine_k_x,
+        sine_k_y=sine_k_y,
+        sine_k_z=sine_k_z,
+        gauss_cx=gauss_cx,
+        gauss_cy=gauss_cy,
+        gauss_cz=gauss_cz,
+        gauss_sigma=gauss_sigma,
+    )
   
   # Run the circuit on statevector simulator to extract the initial state
   backend = AerSimulator(method='statevector')

qlbm_embedded.py

@@ -674,7 +674,7 @@ def _create_box_figure(lx, ly, lz, title):
         j=[3, 4, 1, 2, 5, 6, 5, 2, 0, 1, 6, 3],
         k=[0, 7, 2, 3, 6, 7, 1, 1, 5, 5, 7, 6],
         opacity=0.2,
-        color='blue',
+        color="rgba(255,218,185,0.25)",
         flatshading=True,
         name=title,
         showscale=False
@@ -1064,17 +1064,8 @@ def run_simulation():
     elif _state.qlbm_backend_type == "QPU":
         backend_info += f" - {_state.qlbm_selected_qpu}"
     
-    config_lines = [
-        "Job Initiated",
-        f"  Grid Size: {_state.qlbm_grid_size} × {_state.qlbm_grid_size} × {_state.qlbm_grid_size}",
-        f"  Time Steps: {_state.qlbm_time_steps}",
-        f"  Distribution: {_state.qlbm_dist_type}",
-        f"  Boundary: {_state.qlbm_boundary_condition}",
-        f"  Backend: {backend_info}",
-        f"  Velocity: vx={_state.qlbm_vx_expr}, vy={_state.qlbm_vy_expr}, vz={_state.qlbm_vz_expr}",
-    ]
-    for line in config_lines:
-        log_to_console(line)
+    log_to_console("Job Initiated")
+    log_to_console(f"Grid Size: {_state.qlbm_grid_size}×{_state.qlbm_grid_size}×{_state.qlbm_grid_size}, Time Steps: {_state.qlbm_time_steps}, Distribution: {_state.qlbm_dist_type}, Boundary: {_state.qlbm_boundary_condition}, Backend: {backend_info}, Velocity: vx={_state.qlbm_vx_expr}, vy={_state.qlbm_vy_expr}, vz={_state.qlbm_vz_expr}")
     
     last_logged_percent = 0
     def _progress_callback(percent):