diff --git a/src/gausse/optim/objective.py b/src/gausse/optim/objective.py
new file mode 100644
index 0000000..cdc3909
--- /dev/null
+++ b/src/gausse/optim/objective.py
@@ -0,0 +1,101 @@
+"""Целевая функция: КПД — основная цель, стоимость и скорость — вторичные метрики.
+
+Нереализуемые геномы не отбрасываются — получают "мягкий" штраф фитнеса,
+пропорциональный тому, на какой ступени всё сломалось, чтобы у ГА был
+градиент, а не стена (см. PLAN.md).
+"""
+
+from dataclasses import dataclass
+
+from gausse.components.database import ComponentDatabase
+from gausse.optim.search_space import Genome, SearchBounds, decode
+from gausse.physics.inductance import winding_geometry
+from gausse.sim.coilgun import run_coilgun
+
+
+@dataclass
+class EvaluationResult:
+    feasible: bool
+    cost_rub: float
+    fitness: float
+    reason: str | None = None
+    failed_stage_index: int | None = None
+    efficiency: float | None = None
+    exit_velocity_mps: float | None = None
+    energy_breakdown: dict = None
+
+
+def compute_cost_rub(config, db: ComponentDatabase) -> float:
+    total = 0.0
+    for stage in config.stages:
+        wire_od_m = stage.wire.insulation_od_mm / 1000
+        geometry = winding_geometry(stage.tube_od_m, wire_od_m, stage.turns_per_layer, stage.layers)
+        total += geometry.total_wire_length_m * stage.wire.price_per_m
+        total += stage.capacitor.price
+        total += stage.switch.price
+        total += stage.sensor.price
+    total += config.projectile.mass_kg * config.projectile.material.price_per_kg
+    return total
+
+
+def decoded_summary(genome: Genome, db: ComponentDatabase) -> dict:
+    material = db.projectile_materials[genome.projectile.material_idx % len(db.projectile_materials)]
+    stages_summary = []
+    for gene in genome.stages:
+        wire = db.wires[gene.wire_idx % len(db.wires)]
+        capacitor = db.capacitors[gene.capacitor_idx % len(db.capacitors)]
+        switch = db.switches[gene.switch_idx % len(db.switches)]
+        sensor = db.sensors[gene.sensor_idx % len(db.sensors)]
+        stages_summary.append(
+            {
+                "wire": wire.part_id,
+                "capacitor": capacitor.part_number,
+                "switch": switch.part_number,
+                "sensor": sensor.part_number,
+                "turns_per_layer": gene.turns_per_layer,
+                "layers": gene.layers,
+                "sensor_to_coil_distance_m": gene.sensor_to_coil_distance_m,
+                "charge_voltage_fraction": gene.charge_voltage_fraction,
+            }
+        )
+    return {
+        "tube_od_m": genome.tube_od_m,
+        "projectile_material": material.name,
+        "projectile_diameter_m": genome.projectile.diameter_m,
+        "projectile_length_m": genome.projectile.length_m,
+        "stages": stages_summary,
+    }
+
+
+def evaluate(genome: Genome, db: ComponentDatabase, bounds: SearchBounds) -> EvaluationResult:
+    config, _initial_x_m, _initial_v_mps = decode(genome, db, bounds)
+    cost_rub = compute_cost_rub(config, db)
+    result = run_coilgun(config)
+
+    if not result.feasible:
+        n_stages = len(config.stages)
+        progress_fraction = (result.failed_stage_index or 0) / n_stages if n_stages else 0.0
+        fitness = -1.0 + progress_fraction
+        return EvaluationResult(
+            feasible=False,
+            cost_rub=cost_rub,
+            fitness=fitness,
+            reason=result.reason,
+            failed_stage_index=result.failed_stage_index,
+            energy_breakdown={},
+        )
+
+    energy_breakdown = {
+        "total_energy_in_j": result.total_energy_in_j,
+        "total_energy_dissipated_j": result.total_energy_dissipated_j,
+        "total_kinetic_energy_delta_j": result.total_kinetic_energy_delta_j,
+        "exit_kinetic_energy_j": result.exit_kinetic_energy_j,
+    }
+    return EvaluationResult(
+        feasible=True,
+        cost_rub=cost_rub,
+        fitness=result.efficiency,
+        efficiency=result.efficiency,
+        exit_velocity_mps=result.exit_v_mps,
+        energy_breakdown=energy_breakdown,
+    )
diff --git a/src/gausse/optim/search_space.py b/src/gausse/optim/search_space.py
new file mode 100644
index 0000000..688412f
--- /dev/null
+++ b/src/gausse/optim/search_space.py
@@ -0,0 +1,297 @@
+"""Пространство поиска: геном переменной длины (число ступеней эволюционирует).
+
+Геном кодирует только ИНДЕКСЫ в базу реальных компонентов (не сами
+параметры) + непрерывные величины (расстояния, напряжение, геометрия
+снаряда). Это гарантирует, что что бы ни нашёл поиск, оно собрано из
+реально продающихся деталей, а не из выдуманных чисел.
+"""
+
+import copy
+import math
+import random
+from dataclasses import dataclass, field
+
+from gausse.components.database import ComponentDatabase
+from gausse.sim.coilgun import CoilgunConfig
+from gausse.sim.stage import ProjectileConfig, StageConfig
+
+TUBE_WALL_CLEARANCE_M = 0.001
+
+
+@dataclass(frozen=True)
+class SearchBounds:
+    min_stages: int = 1
+    max_stages: int = 4
+    turns_per_layer_min: int = 5
+    turns_per_layer_max: int = 100
+    layers_min: int = 1
+    layers_max: int = 8
+    sensor_to_coil_distance_m_min: float = 0.005
+    sensor_to_coil_distance_m_max: float = 0.05
+    inter_stage_gap_m_min: float = 0.01
+    inter_stage_gap_m_max: float = 0.10
+    tube_od_m_min: float = 0.009
+    tube_od_m_max: float = 0.02
+    projectile_diameter_m_min: float = 0.004
+    projectile_diameter_m_max: float = 0.008
+    projectile_length_m_min: float = 0.01
+    projectile_length_m_max: float = 0.03
+    charge_voltage_fraction_min: float = 0.5
+    charge_voltage_fraction_max: float = 1.0
+    initial_launch_velocity_mps: float = 3.0
+    initial_approach_margin_m: float = 0.02
+
+
+@dataclass
+class StageGene:
+    wire_idx: int
+    capacitor_idx: int
+    switch_idx: int
+    sensor_idx: int
+    turns_per_layer: int
+    layers: int
+    sensor_to_coil_distance_m: float
+    charge_voltage_fraction: float
+
+
+@dataclass
+class ProjectileGene:
+    material_idx: int
+    diameter_m: float
+    length_m: float
+
+
+@dataclass
+class Genome:
+    tube_od_m: float
+    stages: list[StageGene]
+    inter_stage_gaps_m: list[float]
+    projectile: ProjectileGene
+
+
+def _clip(value: float, lo: float, hi: float) -> float:
+    return max(lo, min(hi, value))
+
+
+def sample_stage_gene(db: ComponentDatabase, bounds: SearchBounds, rng: random.Random) -> StageGene:
+    return StageGene(
+        wire_idx=rng.randrange(len(db.wires)),
+        capacitor_idx=rng.randrange(len(db.capacitors)),
+        switch_idx=rng.randrange(len(db.switches)),
+        sensor_idx=rng.randrange(len(db.sensors)),
+        turns_per_layer=rng.randint(bounds.turns_per_layer_min, bounds.turns_per_layer_max),
+        layers=rng.randint(bounds.layers_min, bounds.layers_max),
+        sensor_to_coil_distance_m=rng.uniform(
+            bounds.sensor_to_coil_distance_m_min, bounds.sensor_to_coil_distance_m_max
+        ),
+        charge_voltage_fraction=rng.uniform(
+            bounds.charge_voltage_fraction_min, bounds.charge_voltage_fraction_max
+        ),
+    )
+
+
+def sample_genome(db: ComponentDatabase, bounds: SearchBounds, rng: random.Random) -> Genome:
+    tube_od_m = rng.uniform(bounds.tube_od_m_min, bounds.tube_od_m_max)
+    max_diameter = min(bounds.projectile_diameter_m_max, tube_od_m - TUBE_WALL_CLEARANCE_M)
+    diameter_m = rng.uniform(bounds.projectile_diameter_m_min, max(max_diameter, bounds.projectile_diameter_m_min))
+
+    n_stages = rng.randint(bounds.min_stages, bounds.max_stages)
+    stages = [sample_stage_gene(db, bounds, rng) for _ in range(n_stages)]
+    gaps = [
+        rng.uniform(bounds.inter_stage_gap_m_min, bounds.inter_stage_gap_m_max)
+        for _ in range(n_stages - 1)
+    ]
+    projectile = ProjectileGene(
+        material_idx=rng.randrange(len(db.projectile_materials)),
+        diameter_m=diameter_m,
+        length_m=rng.uniform(bounds.projectile_length_m_min, bounds.projectile_length_m_max),
+    )
+    return Genome(tube_od_m=tube_od_m, stages=stages, inter_stage_gaps_m=gaps, projectile=projectile)
+
+
+def repair(genome: Genome, db: ComponentDatabase, bounds: SearchBounds) -> Genome:
+    """Приводит геном в границы после мутации/скрещивания (клэмп, не отбраковка)."""
+    genome.tube_od_m = _clip(genome.tube_od_m, bounds.tube_od_m_min, bounds.tube_od_m_max)
+    max_diameter = max(genome.tube_od_m - TUBE_WALL_CLEARANCE_M, bounds.projectile_diameter_m_min)
+    genome.projectile.diameter_m = _clip(
+        genome.projectile.diameter_m, bounds.projectile_diameter_m_min, max_diameter
+    )
+    genome.projectile.length_m = _clip(
+        genome.projectile.length_m, bounds.projectile_length_m_min, bounds.projectile_length_m_max
+    )
+    genome.projectile.material_idx = genome.projectile.material_idx % len(db.projectile_materials)
+
+    for stage in genome.stages:
+        stage.wire_idx %= len(db.wires)
+        stage.capacitor_idx %= len(db.capacitors)
+        stage.switch_idx %= len(db.switches)
+        stage.sensor_idx %= len(db.sensors)
+        stage.turns_per_layer = int(_clip(stage.turns_per_layer, bounds.turns_per_layer_min, bounds.turns_per_layer_max))
+        stage.layers = int(_clip(stage.layers, bounds.layers_min, bounds.layers_max))
+        stage.sensor_to_coil_distance_m = _clip(
+            stage.sensor_to_coil_distance_m,
+            bounds.sensor_to_coil_distance_m_min,
+            bounds.sensor_to_coil_distance_m_max,
+        )
+        stage.charge_voltage_fraction = _clip(
+            stage.charge_voltage_fraction,
+            bounds.charge_voltage_fraction_min,
+            bounds.charge_voltage_fraction_max,
+        )
+    genome.inter_stage_gaps_m = [
+        _clip(g, bounds.inter_stage_gap_m_min, bounds.inter_stage_gap_m_max)
+        for g in genome.inter_stage_gaps_m[: len(genome.stages) - 1]
+    ]
+    while len(genome.inter_stage_gaps_m) < len(genome.stages) - 1:
+        genome.inter_stage_gaps_m.append(
+            (bounds.inter_stage_gap_m_min + bounds.inter_stage_gap_m_max) / 2
+        )
+    return genome
+
+
+def decode(genome: Genome, db: ComponentDatabase, bounds: SearchBounds) -> tuple[CoilgunConfig, float, float]:
+    """Возвращает (CoilgunConfig, initial_x_m, initial_v_mps)."""
+    material = db.projectile_materials[genome.projectile.material_idx % len(db.projectile_materials)]
+    projectile = ProjectileConfig(
+        material=material,
+        diameter_m=genome.projectile.diameter_m,
+        length_m=genome.projectile.length_m,
+    )
+
+    stage_configs = []
+    for gene in genome.stages:
+        wire = db.wires[gene.wire_idx % len(db.wires)]
+        capacitor = db.capacitors[gene.capacitor_idx % len(db.capacitors)]
+        switch = db.switches[gene.switch_idx % len(db.switches)]
+        sensor = db.sensors[gene.sensor_idx % len(db.sensors)]
+        max_voltage = min(capacitor.voltage_v, switch.max_voltage_v)
+        charge_voltage_v = gene.charge_voltage_fraction * max_voltage
+        stage_configs.append(
+            StageConfig(
+                wire=wire,
+                capacitor=capacitor,
+                switch=switch,
+                sensor=sensor,
+                tube_od_m=genome.tube_od_m,
+                turns_per_layer=gene.turns_per_layer,
+                layers=gene.layers,
+                sensor_to_coil_distance_m=gene.sensor_to_coil_distance_m,
+                charge_voltage_v=charge_voltage_v,
+            )
+        )
+
+    config = CoilgunConfig(
+        stages=stage_configs,
+        inter_stage_gaps_m=list(genome.inter_stage_gaps_m),
+        projectile=projectile,
+        initial_x_m=-(stage_configs[0].sensor_to_coil_distance_m + bounds.initial_approach_margin_m),
+        initial_v_mps=bounds.initial_launch_velocity_mps,
+    )
+    return config, config.initial_x_m, config.initial_v_mps
+
+
+def mutate(genome: Genome, db: ComponentDatabase, bounds: SearchBounds, rng: random.Random, rate: float = 0.2) -> Genome:
+    child = copy.deepcopy(genome)
+
+    if rng.random() < rate:
+        child.tube_od_m = rng.uniform(bounds.tube_od_m_min, bounds.tube_od_m_max)
+
+    for stage in child.stages:
+        if rng.random() < rate:
+            stage.wire_idx = rng.randrange(len(db.wires))
+        if rng.random() < rate:
+            stage.capacitor_idx = rng.randrange(len(db.capacitors))
+        if rng.random() < rate:
+            stage.switch_idx = rng.randrange(len(db.switches))
+        if rng.random() < rate:
+            stage.sensor_idx = rng.randrange(len(db.sensors))
+        if rng.random() < rate:
+            stage.turns_per_layer += rng.randint(-10, 10)
+        if rng.random() < rate:
+            stage.layers += rng.randint(-1, 1)
+        if rng.random() < rate:
+            stage.sensor_to_coil_distance_m *= rng.uniform(0.7, 1.3)
+        if rng.random() < rate:
+            stage.charge_voltage_fraction *= rng.uniform(0.9, 1.1)
+
+    for i in range(len(child.inter_stage_gaps_m)):
+        if rng.random() < rate:
+            child.inter_stage_gaps_m[i] *= rng.uniform(0.7, 1.3)
+
+    if rng.random() < rate:
+        child.projectile.material_idx = rng.randrange(len(db.projectile_materials))
+    if rng.random() < rate:
+        child.projectile.diameter_m *= rng.uniform(0.8, 1.2)
+    if rng.random() < rate:
+        child.projectile.length_m *= rng.uniform(0.8, 1.2)
+
+    # структурные операторы: число ступеней тоже эволюционирует
+    structural_roll = rng.random()
+    if structural_roll < rate / 3 and len(child.stages) < bounds.max_stages:
+        new_stage = sample_stage_gene(db, bounds, rng)
+        child.stages.append(new_stage)
+        child.inter_stage_gaps_m.append(
+            rng.uniform(bounds.inter_stage_gap_m_min, bounds.inter_stage_gap_m_max)
+        )
+    elif structural_roll < 2 * rate / 3 and len(child.stages) > bounds.min_stages:
+        idx = rng.randrange(len(child.stages))
+        child.stages.pop(idx)
+        if child.inter_stage_gaps_m:
+            child.inter_stage_gaps_m.pop(min(idx, len(child.inter_stage_gaps_m) - 1))
+    elif structural_roll < rate and len(child.stages) < bounds.max_stages:
+        idx = rng.randrange(len(child.stages))
+        child.stages.insert(idx, copy.deepcopy(child.stages[idx]))
+        child.inter_stage_gaps_m.append(
+            rng.uniform(bounds.inter_stage_gap_m_min, bounds.inter_stage_gap_m_max)
+        )
+
+    return repair(child, db, bounds)
+
+
+def crossover(parent_a: Genome, parent_b: Genome, rng: random.Random) -> Genome:
+    """Обмен целыми ступенями между родителями — ступень физически цельная единица."""
+    n = rng.choice([len(parent_a.stages), len(parent_b.stages)])
+    stages = []
+    for i in range(n):
+        source = parent_a if rng.random() < 0.5 else parent_b
+        if i < len(source.stages):
+            stages.append(copy.deepcopy(source.stages[i]))
+        else:
+            fallback = parent_a if source is parent_b else parent_b
+            stages.append(copy.deepcopy(fallback.stages[i % len(fallback.stages)]))
+
+    gaps = []
+    for i in range(n - 1):
+        source = parent_a if rng.random() < 0.5 else parent_b
+        if i < len(source.inter_stage_gaps_m):
+            gaps.append(source.inter_stage_gaps_m[i])
+        else:
+            gaps.append(parent_a.inter_stage_gaps_m[i % max(len(parent_a.inter_stage_gaps_m), 1)])
+
+    projectile_source = parent_a if rng.random() < 0.5 else parent_b
+    tube_source = parent_a if rng.random() < 0.5 else parent_b
+
+    return Genome(
+        tube_od_m=tube_source.tube_od_m,
+        stages=stages,
+        inter_stage_gaps_m=gaps,
+        projectile=copy.deepcopy(projectile_source.projectile),
+    )
+
+
+def genome_to_dict(genome: Genome) -> dict:
+    return {
+        "tube_od_m": genome.tube_od_m,
+        "stages": [vars(s) for s in genome.stages],
+        "inter_stage_gaps_m": genome.inter_stage_gaps_m,
+        "projectile": vars(genome.projectile),
+    }
+
+
+def genome_from_dict(data: dict) -> Genome:
+    return Genome(
+        tube_od_m=data["tube_od_m"],
+        stages=[StageGene(**s) for s in data["stages"]],
+        inter_stage_gaps_m=list(data["inter_stage_gaps_m"]),
+        projectile=ProjectileGene(**data["projectile"]),
+    )
diff --git a/tests/test_objective.py b/tests/test_objective.py
new file mode 100644
index 0000000..0ad0977
--- /dev/null
+++ b/tests/test_objective.py
@@ -0,0 +1,60 @@
+import random
+
+from gausse.components.database import ComponentDatabase
+from gausse.optim.objective import compute_cost_rub, decoded_summary, evaluate
+from gausse.optim.search_space import SearchBounds, decode, sample_genome
+
+DB = ComponentDatabase.load()
+BOUNDS = SearchBounds()
+
+
+def test_evaluate_feasible_genome_has_fitness_equal_efficiency():
+    rng = random.Random(2)
+    found_feasible = False
+    for _ in range(50):
+        genome = sample_genome(DB, BOUNDS, rng)
+        result = evaluate(genome, DB, BOUNDS)
+        if result.feasible:
+            found_feasible = True
+            assert result.fitness == result.efficiency
+            assert 0.0 <= result.efficiency <= 1.0
+            assert result.cost_rub > 0
+            break
+    assert found_feasible, "ни один из 50 случайных геномов не оказался реализуемым"
+
+
+def test_evaluate_infeasible_genome_has_negative_fitness_and_reason():
+    rng = random.Random(9)
+    genome = sample_genome(DB, BOUNDS, rng)
+    # индукционный датчик требует скорости >= порог/чувствительность = 5 м/с,
+    # а старт по умолчанию 3 м/с -- первая ступень обязана провалиться
+    inductive_idx = next(i for i, s in enumerate(DB.sensors) if s.kind == "inductive")
+    genome.stages[0].sensor_idx = inductive_idx
+    result = evaluate(genome, DB, BOUNDS)
+    assert not result.feasible
+    assert result.fitness < 0
+    assert result.reason is not None
+    assert result.failed_stage_index == 0
+
+
+def test_compute_cost_rub_is_positive_and_scales_with_stage_count():
+    rng = random.Random(4)
+    genome = sample_genome(DB, BOUNDS, rng)
+    config, _, _ = decode(genome, DB, BOUNDS)
+    cost = compute_cost_rub(config, DB)
+    assert cost > 0
+
+    genome.stages.append(genome.stages[0])
+    genome.inter_stage_gaps_m.append(0.05)
+    config2, _, _ = decode(genome, DB, BOUNDS)
+    cost2 = compute_cost_rub(config2, DB)
+    assert cost2 > cost
+
+
+def test_decoded_summary_uses_real_part_numbers():
+    rng = random.Random(6)
+    genome = sample_genome(DB, BOUNDS, rng)
+    summary = decoded_summary(genome, DB)
+    assert len(summary["stages"]) == len(genome.stages)
+    real_wire_ids = {w.part_id for w in DB.wires}
+    assert all(s["wire"] in real_wire_ids for s in summary["stages"])
diff --git a/tests/test_search_space.py b/tests/test_search_space.py
new file mode 100644
index 0000000..f486f36
--- /dev/null
+++ b/tests/test_search_space.py
@@ -0,0 +1,90 @@
+import random
+
+import pytest
+
+from gausse.components.database import ComponentDatabase
+from gausse.optim.search_space import (
+    TUBE_WALL_CLEARANCE_M,
+    SearchBounds,
+    crossover,
+    decode,
+    genome_from_dict,
+    genome_to_dict,
+    mutate,
+    repair,
+    sample_genome,
+)
+
+DB = ComponentDatabase.load()
+BOUNDS = SearchBounds()
+
+
+def test_sample_genome_respects_bounds():
+    rng = random.Random(42)
+    for _ in range(50):
+        genome = sample_genome(DB, BOUNDS, rng)
+        assert BOUNDS.min_stages <= len(genome.stages) <= BOUNDS.max_stages
+        assert len(genome.inter_stage_gaps_m) == len(genome.stages) - 1
+        assert BOUNDS.tube_od_m_min <= genome.tube_od_m <= BOUNDS.tube_od_m_max
+        assert genome.projectile.diameter_m <= genome.tube_od_m - TUBE_WALL_CLEARANCE_M
+        for stage in genome.stages:
+            assert 0 <= stage.wire_idx < len(DB.wires)
+            assert BOUNDS.turns_per_layer_min <= stage.turns_per_layer <= BOUNDS.turns_per_layer_max
+            assert BOUNDS.layers_min <= stage.layers <= BOUNDS.layers_max
+
+
+def test_decode_produces_valid_config():
+    rng = random.Random(1)
+    genome = sample_genome(DB, BOUNDS, rng)
+    config, initial_x_m, initial_v_mps = decode(genome, DB, BOUNDS)
+    assert len(config.stages) == len(genome.stages)
+    assert len(config.inter_stage_gaps_m) == len(genome.stages) - 1
+    assert initial_x_m < -config.stages[0].sensor_to_coil_distance_m
+    assert initial_v_mps == BOUNDS.initial_launch_velocity_mps
+    for stage_config, gene in zip(config.stages, genome.stages):
+        max_voltage = min(stage_config.capacitor.voltage_v, stage_config.switch.max_voltage_v)
+        assert stage_config.charge_voltage_v <= max_voltage + 1e-9
+
+
+def test_mutate_keeps_genome_within_bounds():
+    rng = random.Random(7)
+    genome = sample_genome(DB, BOUNDS, rng)
+    for _ in range(200):
+        genome = mutate(genome, DB, BOUNDS, rng, rate=0.5)
+        assert BOUNDS.min_stages <= len(genome.stages) <= BOUNDS.max_stages
+        assert len(genome.inter_stage_gaps_m) == len(genome.stages) - 1
+        assert BOUNDS.tube_od_m_min <= genome.tube_od_m <= BOUNDS.tube_od_m_max
+        assert genome.projectile.diameter_m <= genome.tube_od_m - TUBE_WALL_CLEARANCE_M + 1e-9
+        # decode должен всегда успевать без исключений после repair
+        decode(genome, DB, BOUNDS)
+
+
+def test_mutate_can_change_stage_count():
+    rng = random.Random(3)
+    small_bounds = SearchBounds(min_stages=1, max_stages=3)
+    genome = sample_genome(DB, small_bounds, rng)
+    genome.stages = genome.stages[:1]
+    genome.inter_stage_gaps_m = []
+    counts = set()
+    for _ in range(100):
+        genome = mutate(genome, DB, small_bounds, rng, rate=0.6)
+        counts.add(len(genome.stages))
+    assert len(counts) > 1  # число ступеней реально меняется, не застряло
+
+
+def test_crossover_produces_decodable_child():
+    rng = random.Random(11)
+    a = sample_genome(DB, BOUNDS, rng)
+    b = sample_genome(DB, BOUNDS, rng)
+    for _ in range(20):
+        child = crossover(a, b, rng)
+        child = repair(child, DB, BOUNDS)
+        config, _, _ = decode(child, DB, BOUNDS)
+        assert len(config.stages) == len(child.stages)
+
+
+def test_genome_dict_roundtrip():
+    rng = random.Random(5)
+    genome = sample_genome(DB, BOUNDS, rng)
+    restored = genome_from_dict(genome_to_dict(genome))
+    assert restored == genome