  We introduce new rounding methods to improve the accuracy of finite precision
quantum arithmetic. These quantum rounding methods are applicable when multiple
samples are being taken from a quantum program. We show how to use multiple
samples to stochastically suppress arithmetic error from rounding. We benchmark
these methods on the multiplication of fixed-point numbers stored in quantum
registers. We show that the gate counts and depths for multiplying to a target
accuracy can be reduced by approximately 2-3X over state of the art methods
while using roughly the same number of qubits.
