Follow-up to PR#2817: Update the user facing Python examples

docs/sphinx/targets/python/pasqal.py

@@ -54,12 +54,13 @@
 omega_max = 1000000
 delta_end = 1000000
 delta_start = 0.0
-omega = ScalarOperator(lambda t: omega_max if time_ramp < t < time_max else 0.0)
+omega = ScalarOperator(lambda t: omega_max
+                       if time_ramp < t.real < time_max else 0.0)
 # Global phase at each step
 phi = ScalarOperator.const(0.0)
 # Global detuning at each step
 delta = ScalarOperator(lambda t: delta_end
-                       if time_ramp < t < time_max else delta_start)
+                       if time_ramp < t.real < time_max else delta_start)
 
 async_result = cudaq.evolve_async(RydbergHamiltonian(atom_sites=register,
                                                      amplitude=omega,

docs/sphinx/targets/python/quera_basic.py

@@ -35,12 +35,13 @@
 steps = [0.0, time_ramp, time_max - time_ramp, time_max]
 schedule = Schedule(steps, ["t"])
 # Rabi frequencies at each step
-omega = ScalarOperator(lambda t: omega_max if time_ramp < t < time_max else 0.0)
+omega = ScalarOperator(lambda t: omega_max
+                       if time_ramp < t.real < time_max else 0.0)
 # Global phase at each step
 phi = ScalarOperator.const(0.0)
 # Global detuning at each step
 delta = ScalarOperator(lambda t: delta_end
-                       if time_ramp < t < time_max else delta_start)
+                       if time_ramp < t.real < time_max else delta_start)
 
 async_result = cudaq.evolve_async(RydbergHamiltonian(atom_sites=register,
                                                      amplitude=omega,

docs/sphinx/targets/python/quera_intro.py

@@ -37,11 +37,11 @@
 def trapezoidal_signal(t):
     slope = omega_const / time_ramp
     y_intercept = slope * time_max
-    if 0 < t < time_ramp + time_plateau:
+    if 0 < t.real < time_ramp + time_plateau:
         return slope * t
-    if time_ramp < t < time_max:
+    if time_ramp < t.real < time_max:
         return omega_const
-    if time_ramp + time_plateau < t < time_max:
+    if time_ramp + time_plateau < t.real < time_max:
         return (-slope * t) + y_intercept
     return 0.0