Added new initial dist (multi_dirac_delta); fixed mistake with velocity field implementation

=4.2.0

@@ -0,0 +1,21 @@
+Collecting nbformat
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+Collecting rpds-py>=0.7.1
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+Successfully installed fastjsonschema-2.21.2 jsonschema-4.25.1 jsonschema-specifications-2025.9.1 jupyter-core-5.9.1 nbformat-5.10.4 referencing-0.37.0 rpds-py-0.30.0

qlbm/qlbm_sample_app.py

@@ -253,6 +253,13 @@ def stream(qc,pos_qr,dir_qr,n):
 
 def get_circuit(n,ux,uy,uz,init_state_prep_circ,T_list,vel_resolution=32,measure=True):
 
+  ux_str,uy_str,uz_str=None,None,None
+  if type(ux)==str:
+    ux_str,uy_str,uz_str=ux,uy,uz
+    ux,uy,uz=str_to_lambda(ux_str,uy_str,uz_str)
+
+  if type(init_state_prep_circ)==str:
+    init_state_prep_circ=get_named_init_state_circuit(n,init_state_prep_circ)
 
   dirs=[[0,0,0],[1,0,0],[-1,0,0],[0,1,0],[0,-1,0],[0,0,1],[0,0,-1]]
   wts = np.array([2/8, 1/8, 1/8, 1/8, 1/8, 1/8, 1/8])
@@ -277,20 +284,32 @@ def get_circuit(n,ux,uy,uz,init_state_prep_circ,T_list,vel_resolution=32,measure
 
     qc.compose(init_state_prep_circ,[qubit for qr in pos_qr for qubit in list(qr)], inplace=True)
 
+    uniform_bool=False
 
-    for i in range(dim):
-      qc.compose(QFT(n, inverse=False, do_swaps=False), pos_qr[i], inplace=True)
+    if 'x' not in ux_str+uy_str+uz_str and 'y' not in ux_str+uy_str+uz_str and 'z' not in ux_str+uy_str+uz_str:
+      uniform_bool=True
+    
+    if uniform_bool:
+      for i in range(dim):
+        qc.compose(QFT(n, inverse=False, do_swaps=False), pos_qr[i], inplace=True)
 
     for T in list(range(T_total))[::-1]:
 
       prep(qc,pos_qr,dir_qr)
+      if not uniform_bool:
+        for i in range(dim):
+          qc.compose(QFT(n, inverse=False, do_swaps=False), pos_qr[i], inplace=True)
       stream(qc,pos_qr,dir_qr,n)
+      if not uniform_bool:
+        for i in range(dim):
+          qc.compose(QFT(n, inverse=True, do_swaps=False), pos_qr[i], inplace=True)
       unprep(qc,pos_qr,dir_qr)
 
       qc.measure(dir_qr,dir_cr[T])
 
-    for i in range(dim):
-      qc.compose(QFT(n, inverse=True, do_swaps=False), pos_qr[i], inplace=True)
+    if uniform_bool:
+      for i in range(dim):
+        qc.compose(QFT(n, inverse=True, do_swaps=False), pos_qr[i], inplace=True)
 
     if measure:
       for i in range(dim):
@@ -332,10 +351,14 @@ def get_named_init_state_circuit(
     gauss_cy: float = None,  # Center Y (0-1 normalized), defaults to 0.5
     gauss_cz: float = None,  # Center Z (0-1 normalized), defaults to 0.5
     gauss_sigma: float = None,  # Spread, defaults to 0.2 in normalized units
+    # Multi-dirac-delta parameters
+    mdd_kx_log2: int = 1, # Integer greater than >=1. Number of dirac-deltas along x is 2^mdd_kx_log2
+    mdd_ky_log2: int = 1, # Integer greater than >=1. Number of dirac-deltas along y is 2^mdd_ky_log2
+    mdd_kz_log2: int = 1  # Integer greater than >=1. Number of dirac-deltas along z is 2^mdd_kz_log2
 ):
   """
   Create initial state preparation circuit with configurable parameters.
-  
+ 
   Parameters
   ----------
   n : int
@@ -348,7 +371,8 @@ def get_named_init_state_circuit(
       Center coordinates in [0,1] for Gaussian (default=0.5)
   gauss_sigma : float
       Spread of Gaussian in normalized units (default=0.2)
-  
+  mdd_kx_log2, mdd_ky_log2, mdd_kz_log2 : int
+      log2 of frequency multipliers for dirac-delta array distribution (default=1) 
   Returns
   -------
   QuantumCircuit
@@ -362,6 +386,14 @@ def get_named_init_state_circuit(
     init_state_prep_circ.x(2*n-1)
     init_state_prep_circ.x(3*n-1)
 
+  elif init_state_name == "multi_dirac_delta":
+    init_state_prep_circ.h(range(n-mdd_kx_log2,n))
+    init_state_prep_circ.x(n-1-mdd_kx_log2)
+    init_state_prep_circ.h(range(2*n-mdd_ky_log2,2*n))
+    init_state_prep_circ.x(2*n-1-mdd_ky_log2)
+    init_state_prep_circ.h(range(3*n-mdd_kz_log2,3*n))
+    init_state_prep_circ.x(3*n-1-mdd_kz_log2)
+
   elif init_state_name == "sin":
     # Configurable frequency sinusoidal distribution
     # f(x,y,z) = 1 + sin(2π * kx * x) * sin(2π * ky * y) * sin(2π * kz * z)
@@ -486,12 +518,12 @@ def run_sampling_hw_ibm(
       else:
           print(msg)
 
-  if type(ux)==str:
-    ux,uy,uz=str_to_lambda(ux,uy,uz)
+  # 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_prep_circ=get_named_init_state_circuit(n,init_state_prep_circ)
+  # # Convert string init_state_prep_circ to circuit if needed (matches original logic)
+  # if type(init_state_prep_circ)==str:
+  #   init_state_prep_circ=get_named_init_state_circuit(n,init_state_prep_circ)
 
   qc_list=get_circuit(n,ux,uy,uz,init_state_prep_circ,T_list,vel_resolution)
 
@@ -580,13 +612,13 @@ def run_sampling_sim(
     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)
+  # 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)
+  # # Convert string init_state_prep_circ to circuit if needed (matches original logic)
   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)
+  # 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:
@@ -892,51 +924,52 @@ def show_initial_distribution(
 
 if __name__=="__main__":
 
-  n=3
+  n=4
 
   # # Step 1: Create the initial state circuit ONCE with all parameters
-  init_state_prep_circ = get_named_init_state_circuit(
-      n=n,
-      init_state_name="sin",  # or "gaussian", "dirac_delta"
-      sine_k_x=1.0,
-      sine_k_y=1.0,
-      sine_k_z=1.0
-      # gauss_cx=0.5,  # Uncomment for Gaussian
-      # gauss_cy=0.5,
-      # gauss_cz=0.5,
-      # gauss_sigma=0.2,
-  )
-  
-  #   # Alternative: Run on local simulator
-  # output, fig = run_sampling_sim(
+  # init_state_prep_circ = get_named_init_state_circuit(
   #     n=n,
-  #     ux="sin(2*pi*y)*sin(2*pi*z)",
-  #     uy="sin(2*pi*x)*sin(2*pi*z)",
-  #     uz="sin(2*pi*x)*sin(2*pi*y)",
-  #     init_state_prep_circ=init_state_prep_circ,
-  #     T_list=[1,3,5],
-  #     vel_resolution=2
+  #     init_state_name="multi_dirac_delta",  # or "gaussian", "dirac_delta"
+  #     sine_k_x=1.0,
+  #     sine_k_y=1.0,
+  #     sine_k_z=1.0
+  #     # gauss_cx=0.5,  # Uncomment for Gaussian
+  #     # gauss_cy=0.5,
+  #     # gauss_cz=0.5,
+  #     # gauss_sigma=0.2,
   # )
-  # fig.show()
+  
+    # Alternative: Run on local simulator
+  output, fig = run_sampling_sim(
+      n=n,
+      ux="sin(2*pi*y)",
+      uy="-sin(2*pi*x)",
+      uz="1",
+      init_state_prep_circ="multi_dirac_delta",
+      T_list=[1,3,5],
+      vel_resolution=16
+  )
+  print(output)
+  fig.show(renderer="browser")
 
   # Step 2: (Optional) Preview the initial distribution
   # show_initial_distribution(n=n, init_state_name="sin", sine_k_x=1, sine_k_y=1, sine_k_z=1)
 
   # Step 3: Run simulation - pass the pre-built circuit
-  job, get_job_result = run_sampling_hw_ibm(
-      n=n,
-      ux=lambda x,y,z: 1,
-      uy=lambda x,y,z: 1,
-      uz=lambda x,y,z: 1,
-      init_state_prep_circ=init_state_prep_circ,  # Pass the circuit directly
-      T_list=[1],
-      shots=2**19,
-      vel_resolution=2,
-  )
+  # job, get_job_result = run_sampling_hw_ibm(
+  #     n=n,
+  #     ux=lambda x,y,z: 1,
+  #     uy=lambda x,y,z: 1,
+  #     uz=lambda x,y,z: 1,
+  #     init_state_prep_circ=init_state_prep_circ,  # Pass the circuit directly
+  #     T_list=[1],
+  #     shots=2**19,
+  #     vel_resolution=2,
+  # )
 
-  output = get_job_result(job)
-  for xx, yy, zz, dens in output:
-    plot_density_isosurface(xx, yy, zz, dens)
+  # output = get_job_result(job)
+  # for xx, yy, zz, dens in output:
+  #   plot_density_isosurface(xx, yy, zz, dens)