Add an aggregate over full table outside the buckets to every bucket row

I have a query that filters the emails of people who "have a quantity" bigger than the median over all quantities found in the table:

SELECT
    AVG(quantity) AS avg_quantity,
    email   
FROM table 
GROUP BY email
HAVING AVG(quantity) > (SELECT PERCENTILE_DISC(0.5) WITHIN GROUP (ORDER BY quantity) FROM table)

The result is:

123.12    person1@domain1.com
0.5       person2@domain2.com

In addition to this, I would like to add a column which will have for all rows the same value, that of the median calculated in the HAVING clause above. If we suppose this median to be equal to 0.01, then I would like to have the following result:

123.12    person1@domain1.com    0.01
0.5       person2@domain2.com    0.01

I tried to doing a Cartesian product:

WITH (
    SELECT
        AVG(quantity) AS avg_quantity,
        email   
    FROM table 
    GROUP BY email
    HAVING AVG(quantity) > (SELECT PERCENTILE_DISC(0.5) WITHIN GROUP (ORDER BY quantity) FROM table)
) AS tmp
SELECT tmp.*, PERCENTILE_DISC(0.9) WITHIN GROUP (ORDER BY table.quantity)  from tmp, table 

But I get this error:

ERROR: column "tmp. avg_quantity" must appear in the GROUP BY clause or be used in an aggregate function

How can I achieve the above expected output with 3 columns?

You can use it as an uncorrelated scalar subquery right in the select list. Demo at db<>fiddle:

SELECT
    AVG(quantity) AS avg_quantity,
    email,
    (SELECT PERCENTILE_DISC(0.5) WITHIN GROUP (ORDER BY quantity) FROM "table")
FROM "table" 
GROUP BY email
HAVING AVG(quantity) > (SELECT PERCENTILE_DISC(0.5) WITHIN GROUP (ORDER BY quantity) FROM "table");

You're already using the query this way, just elsewhere. You can actually re-use it for both with the CTE you already tried out:

with _(median) as materialized (
  SELECT PERCENTILE_DISC(0.5) WITHIN GROUP (ORDER BY quantity) FROM "table")
SELECT AVG(quantity) AS avg_quantity,
       email,
       (SELECT median from _)
FROM "table" 
GROUP BY email
HAVING AVG(quantity) > (SELECT median from _);

Your idea with a Cartesian product would work too. You're computing one median for the whole table, so the same single result gets glued to every row. It has to be grouped by, but being identical throughout, it does not affect the current grouping.

SELECT AVG(quantity) AS avg_quantity,
       email,
       median
FROM "table"
,(SELECT PERCENTILE_DISC(0.5)WITHIN GROUP(ORDER BY quantity) FROM "table"
 ) AS _(median)
GROUP BY email,median
HAVING AVG(quantity) > median;