Trying to build something similar to demo MIMO decoding, getting error with my code bqm

Hi, I stumbled across an interesting application of DWave QPUs which is related to telecommunication, the demo provided is for coordinated multipoint MIMO decoder, I want to expand it using NOMA approach I have written code which should be correct based on qubo model found in research paper, However I am facing an error.. below is the code and under it is the error. Any help is appreciated! from dwave.system import LeapHybridSampler import dimod import numpy as np import matplotlib.pyplot as plt # *** NOMA Parameters *** num_users = 2 # Example with two NOMA users modulation_order = 2 # BPSK modulation channel_gains = np.array([0.8, 1.2]) # *** Plot BER vs. Noise Variance *** noise_variances = np.linspace(0.05, 0.5, 10) # Range of noise variances to test ber_results = [] for noise_var in noise_variances: # *** Generate received signal (example) *** transmitted_symbols = np.random.choice([-1, 1], size=num_users) # Generate random BPSK symbols received_signal = np.dot(channel_gains, transmitted_symbols) + np.random.randn(num_users) * np.sqrt(noise_var) # *** Construct the BQM *** bqm = dimod.BinaryQuadraticModel(dimod.Vartype.BINARY) # Linear terms for i in range(num_users): bqm.add_linear_from({i: -2 * received_signal[i] * channel_gains[i]}) # Quadratic terms for i in range(num_users): for j in range(i + 1, num_users): bqm.add_quadratic_from({i: i, j: j, (i, j): 2 * channel_gains[i] * channel_gains[j]}) # *** Solve on the D-Wave QPU *** sampler = LeapHybridSampler() response = sampler.sample(bqm) best_sample = response.first.sample detected_symbols = list(best_sample.values()) # *** Calculate Bit Error Rate (BER) *** num_errors = np.sum(np.abs(transmitted_symbols - detected_symbols)) ber = num_errors / len(transmitted_symbols) ber_results.append(ber) plt.plot(noise_variances, ber_results) plt.xlabel("Noise Variance") plt.ylabel("Bit Error Rate (BER)") plt.title("NOMA Signal Detection (Quantum Annealing)") plt.show() ValueError Traceback (most recent call last) Cell In[12], line 30 28 for i in range(num_users): 29 for j in range(i + 1, num_users): ---> 30 bqm.add_quadratic((i, j), np.dot(channel_gains[i], channel_gains[j]), 0.0) # Use np.dot 32 # *** Solve on the D-Wave QPU *** 33 sampler = LeapHybridSampler() File /Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/dimod/decorators.py:404, in forwarding_method..wrapper(obj, *args, **kwargs) 399 except TypeError: 400 raise TypeError( 401 f"the '__dict__' attribute of {type(obj).__name__!r} " 402 "instance does not support item assignment.") from None --> 404 return method(*args, **kwargs) File /Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/dimod/binary/cybqm/cybqm_template.pyx.pxi:200, in dimod.binary.cybqm.cybqm_float64.cyBQM_template.add_quadratic() ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()" and now you should be able to solve it with all of our requirments