As already noted in comments, at the level of JavaScript numbers such a function can't exist, simply because assuming that we're working with integer-valued IEEE 754 binary64 floats there are more possible input pairs than possible output values.
But to the mathematical question of whether there is a simple, injective function from pairs of integers to a single integer, the answer is yes. Here's one such function that uses only addition and multiplication, so should fit the questioner's "using only mathematical operators" constraint.
First we map each of the inputs from the domain of integers to the domain of nonnegative integers. The polynomial map x ↦ 2*x*x + x will do that for us, and maps distinct values to distinct values. (Sketch of proof: if 2*x*x + x == 2*y*y + y for some integers x and y, then rearranging and factoring gives (x - y) * (2*x + 2*y + 1) == 0; the second factor can never be zero for integers x and y, so the first factor must be zero and x == y.)
Second, given a pair of nonnegative integers (a, b), we map that pair to a single (nonnegative) integer using (a, b) ↦ (a + b)*(a + b) + a. It's easy to see that this, too, is injective: given the value of (a + b)*(a + b) + a, I can recover the value of a + b by taking the integer square root, and from there recover a and b.
Here's some Python code demonstrating the above:
def encode_pair(x, y):
""" Encode a pair of integers as a single (nonnegative) integer. """
a = 2*x*x + x
b = 2*y*y + y
return (a + b)*(a + b) + a
We can easily check that there are no repetitions for small x and y: here we take all pairs (x, y) with -500 <= x < 500 and -500 <= y < 500, and find the set containing encode_pair(x, y) for each combination. If all goes well, we should end up with a set with exactly 1 million entries, one per input combination.
>>> all_outputs = {encode_pair(x, y) for x in range(-500, 500) for y in range(-500, 500)}
>>> len(all_outputs)
1000000
>>> min(all_outputs)
0
But perhaps a more convincing way to establish the injectivity is to give an explicit inverse, showing that the original (x, y) can be recovered from the output. Here's that inverse function. It makes use of Python's integer square root operation math.isqrt, which is available only for Python >= 3.8, but is easy to implement yourself if you need it.
from math import isqrt
def decode_pair(n):
""" Decode an integer produced by encode_pair. """
a_plus_b = isqrt(n)
a = n - a_plus_b*a_plus_b
b = a_plus_b - a
c = isqrt(8*a + 1)
d = isqrt(8*b + 1)
return ((2 - c%4) * c - 1) // 4, ((2 - d%4) * d - 1) // 4
Example usage:
>>> encode_pair(3, 7)
15897
>>> decode_pair(15897)
(3, 7)
Depending on what you allow as a "mathematical operator" (which isn't really a particularly well-defined term), there are tighter functions possible. Here's a variant of the above that provides not just an injection but a bijection: every integer appears as the encoding of some pair of integers. It extends the set of mathematical operators used to include subtraction, division and absolute value. (Note that all divisions appearing in encode_pair are exact integer divisions, without any remainder.)
def encode_pair(x, y):
""" Encode a pair of integers as a single integer.
This gives a bijective map Z x Z -> Z.
"""
ax = (abs(2 * x + 1) - 1) // 2 # x if x >= 0, -1-x if x < 0
sx = (ax - x) // (2 * ax + 1) # 0 if x >= 0, 1 if x < 0
ay = (abs(2 * y + 1) - 1) // 2 # y if y >= 0, -1-y if y < 0
sy = (ay - y) // (2 * ay + 1) # 0 if y >= 0, 1 if y < 0
xy = (ax + ay + 1) * (ax + ay) // 2 + ax # encode ax and ay as xy
an = 2 * xy + sx # encode xy and sx as an
n = an - (2 * an + 1) * sy # encode an and sy as n
return n
def decode_pair(n):
""" Inverse of encode_pair. """
# decode an and sy from n
an = (abs(2 * n + 1) - 1) // 2
sy = (an - n) // (2 * an + 1)
# decode xy and sx from an
sx = an % 2
xy = an // 2
# decode ax and ay from xy
ax_plus_ay = (isqrt(8 * xy + 1) - 1) // 2
ax = xy - ax_plus_ay * (ax_plus_ay + 1) // 2
ay = ax_plus_ay - ax
# recover x from ax and sx, and y from ay and sy
x = ax - (1 + 2 * ax) * sx
y = ay - (1 + 2 * ay) * sy
return x, y
And now every integer appears as the encoding of exactly one pair, so we can start with an arbitrary integer, decode it to a pair, and re-encode to recover the same integer:
>>> n = -12345
>>> decode_pair(n)
(67, -44)
>>> encode_pair(67, -44)
-12345
The encode_pair function above is deliberately quite verbose, in order to explain all the steps involved. But the code and the algebra can be simplified: here's exactly the same computation expressed more compactly.
def encode_pair_cryptic(x, y):
""" Encode a pair of integers as a single integer.
This gives a bijective map Z x Z -> Z.
"""
c = abs(2 * x + 1)
d = abs(2 * y + 1)
e = (2 * y + 1) * ((c + d)**2 * c + 2 * (c - d) * c - 4 * x - 2)
return (e - 2 * c * d) // (4 * c * d)
encode_pair_cryptic gives exactly the same results as encode_pair. I'll give one example, and leave the reader to figure out the equivalence.
>>> encode_pair(47, -53)
-9995
>>> encode_pair_cryptic(47, -53)
-9995