//@version=5

indicator("Neuro-Quantum Trading Nexus", overlay=true, max_lines_count=500, max_labels_count=500, precision=6)

// ======== Quantum Core ======== //

var int MAX_NEURONS = 256

var array<float> synaptic_weights = array.new_float(MAX_NEURONS, 0.0)

var matrix<float> neural_states = matrix.new<float>(MAX_NEURONS, MAX_NEURONS)

quantum_entanglement(array<float> src, int depth) =>

sum = 0.0

e = math.e

for i = 0 to math.min(depth, array.size(src)) - 1

    val = array.get(src, i)

    phase_shift = math.sin(math.atan(math.abs(val)) \* math.pi / e)

    sum += phase_shift \* math.log(math.abs(val) + 1e-10)

security(syminfo.tickerid, "D", sum / depth)

// ======== LSTM Network ======== //

var int memory_cells = 64

var array<float> lstm_memory = array.new_float(memory_cells, 0.0)

var array<float> attention_scores = array.new_float(memory_cells, 0.0)

lstm_attention(float input) =>

src_array = array.from(input, volume)

forget_gate = 1 / (1 + math.exp(-quantum_entanglement(src_array, 2)))



for i = 0 to memory_cells - 1

    array.set(lstm_memory, i, array.get(lstm_memory, i) \* forget_gate + input \* 0.01)



max_score = -math.inf

sum_scores = 0.0

for i = 0 to memory_cells - 1

    score = math.abs(array.get(lstm_memory, i) - close) \* volume

    array.set(attention_scores, i, score)

    if score \> max_score

        max_score := score



if max_score != 0

    for i = 0 to memory_cells - 1

        normalized = array.get(attention_scores, i) / max_score

        array.set(attention_scores, i, normalized)

        sum_scores += normalized



output = 0.0

if sum_scores != 0

    for i = 0 to memory_cells - 1

        output += array.get(lstm_memory, i) \* (array.get(attention_scores, i) / sum_scores)

output

// ======== Market Analysis ======== //

var matrix<float> market_tensor = matrix.new<float>(3, 3, 0.0)

multidimensional_analysis() =>

ft = math.sum(ta.change(close) \* math.cos(math.pi \* bar_index / 14), 14)

volume_sum = ta.sum(volume, 50)

entropy = -math.sum((volume / volume_sum) \* math.log(math.abs(volume / volume_sum + 1e-10))

d2 = ta.ema(ta.ema(close, 3) - ta.ema(close, 5), 3)



matrix.set(market_tensor, 0, 0, ft)

matrix.set(market_tensor, 0, 1, entropy)

matrix.set(market_tensor, 0, 2, d2)



ft \* entropy \* d2 - ft \* volume - entropy \* close

// ======== Prediction System ======== //

quantum_predict() =>

eigen_value = 0.0

for i = 0 to 2

    for j = 0 to 2

        eigen_value += matrix.get(market_tensor, i, j) \* math.pow(-1, i + j)



wave_function = math.sin(math.atan(eigen_value) \* math.pi)

probability_density = math.pow(wave_function, 2)

uncertainty = math.abs(ta.vwap(close) - close) / ta.atr(14)

(probability_density \* wave_function) / (uncertainty + 1e-10)

// ======== Trading Logic ======== //

var float buy_zone = na

var float sell_zone = na

svm_boundary() =>

alpha = 0.02

margin = ta.ema(quantum_predict() - multidimensional_analysis(), 3)

math.abs(margin) \> alpha ? margin : 0

boundary = svm_boundary()

if boundary > 0.618

buy_zone := low - ta.atr(14) \* 0.236

label.new(bar_index, low, "QUANTUM\\nBUY ZONE", color=color.rgb(0, 255, 0, 80), textcolor=#FFFFFF, style=label.style_label_up, size=size.large)

if boundary < -0.618

sell_zone := high + ta.atr(14) \* 0.236

label.new(bar_index, high, "ANTI-MATTER\\nSELL ZONE", color=color.rgb(255, 0, 0, 80), textcolor=#FFFFFF, style=label.style_label_down, size=size.large)

// ======== Visuals ======== //

plotshape(boundary > 0.618, style=shape.triangleup, location=location.belowbar, color=#00FF00, size=size.huge)

plotshape(boundary < -0.618, style=shape.triangledown, location=location.abovebar, color=#FF0000, size=size.huge)

hline(buy_zone, "Buy Frontier", color=#00FF00, linestyle=hline.style_dotted)

hline(sell_zone, "Sell Event Horizon", color=#FF0000, linestyle=hline.style_dotted)

// ======== Risk Management ======== //

var bool black_hole_warning = false

q_pred = quantum_predict()

black_hole_warning := q_pred > 3 * ta.stdev(q_pred, 100)

bgcolor(black_hole_warning ? color.new(#FFA500, 90) : na)

```