## Bug description

See [this graph (internal link)](https://app.posthog.com/insights?insight=TRENDS&actions=%5B%7B%22id%22%3A4912%2C%22math%22%3A%22dau%22%2C%22name%22%3A%22Discovered%20Learning%22%2C%22type%22%3A%22actions%22%2C%22order%22%3A0%2C%22properties%22%3A%5B%7B%22key%22%3A%22realm%22%2C%22type%22%3A%22person%22%2C%22value%22%3A%5B%22cloud%22%5D%2C%22operator%22%3A%22exact%22%7D%5D%2C%22math_property%22%3Anull%7D%2C%7B%22id%22%3A7307%2C%22math%22%3A%22total%22%2C%22name%22%3A%22Insights%20Error%20or%20Timeout%20-%20Cloud%22%2C%22type%22%3A%22actions%22%2C%22order%22%3A1%2C%22properties%22%3A%5B%5D%2C%22math_property%22%3Anull%7D%5D&display=ActionsLineGraph&formula=B%2FA&interval=week&date_from=-90d&filter_test_accounts=true&properties=%5B%5D&breakdown=realm&breakdown_type=person#fromItem=190864&fromItemName=%23%20Errors%20Seen%20%2F%20Activated%20User%20-%20Cloud&fromDashboard=3346)

Using formulas + break down doesn't work.

## Expected behavior

Should work.

## How to reproduce

1.
2.
3.

## Environment

- [ ] PostHog Cloud
- [ ] self-hosted PostHog, version/commit: _please provide_

## Additional context



#### *Thank you* for your bug report – we love squashing them!

ee/clickhouse/queries/trends/breakdown.py
BREAKDOWN_ACTIVE_USER_CONDITIONS_SQL,
    BREAKDOWN_ACTIVE_USER_INNER_SQL,
    BREAKDOWN_AGGREGATE_QUERY_SQL,
    BREAKDOWN_COHORT_JOIN_SQL,
    BREAKDOWN_INNER_SQL,
    BREAKDOWN_PERSON_PROP_JOIN_SQL,
    BREAKDOWN_PROP_JOIN_SQL,
    BREAKDOWN_QUERY_SQL,
)
from posthog.constants import MONTHLY_ACTIVE, TREND_FILTER_TYPE_ACTIONS, TRENDS_DISPLAY_BY_VALUE, WEEKLY_ACTIVE
from posthog.models.entity import Entity
from posthog.models.filters import Filter
class ClickhouseTrendsBreakdown:
    def _format_breakdown_query(self, entity: Entity, filter: Filter, team_id: int) -> Tuple[str, Dict, Callable]:
        
        params: Dict[str, Any] = {"team_id": team_id}
        interval_annotation = get_trunc_func_ch(filter.interval)
        num_intervals, seconds_in_interval, round_interval = get_time_diff(
            filter.interval, filter.date_from, filter.date_to, team_id
        )
        _, parsed_date_to, date_params = parse_timestamps(filter=filter, team_id=team_id)
        props_to_filter = [*filter.properties, *entity.properties]
        prop_filters, prop_filter_params = parse_prop_clauses(
            props_to_filter,
            team_id,
            table_name="e",
            filter_test_accounts=filter.filter_test_accounts,
            allow_denormalized_props=True,
        )
        aggregate_operation, _, math_params = process_math(entity)