We study the complexity of quantum decomposable randomized encodings (QDRE). We establish a bi-directional connection between the QDRE model and the communication complexity model of quantum private simultaneous message protocols (QPSM), where classical communication is free, and quantum communication is the primary complexity measure. We show the following upper and lower bounds. (1) For every quantum channel mapping
n to
m qubits, we give a QPSM protocol with quantum communication
m, using exponential pre-shared entanglement. In particular, constant-output channels have
O(1) quantum communication, and classical-output channels require no quantum communication. (2) With
O(n) pre-shared entanglement, every one-qubit-output channel has an
O(n)-quantum-communication QPSM protocol. Conversely, there exists a channel and a constant
c>0 for which any protocol with at most
cn pre-shared entanglement requires
Ω(n) quantum communication. (3) In contrast, we identify a structured class of quantum channels, Clifford-induced channels, for which there exist QPSM protocols with
O(n) pre-shared entangled qubits and only
O(1) quantum communication complexity. Through our connection, we obtain analogous upper and lower bounds on the quantum encoding size of QDRE. Our results show that the amount of pre-shared entanglement plays a central role in quantum encoding size and quantum communication complexity.
The private simultaneous messages model is a non-interactive version of the multiparty secure computation, which has been intensively studied to examine the communication cost of the secure computation. We consider its quantum counterpart, the private simultaneous quantum messages (PSQM) model, and examine the advantages of quantum communication and prior entanglement of this model. In the PSQM model,
k parties
P1,…,Pk initially share a common random string (or entangled states in a stronger setting), and they have private classical inputs
x1,…,xk. Every
Pi generates a quantum message from the private input
xi and the shared random string (entangled states), and then sends it to the referee
R. Receiving the messages,
R computes
F(x1,…,xk). Then,
R learns nothing except for
F(x1,…,xk) as the privacy condition. We obtain the following results for this PSQM model. (1) We demonstrate that the privacy condition inevitably increases the communication cost in the two-party PSQM model as well as in the classical case presented by Applebaum, Holenstein, Mishra, and Shayevitz. In particular, we prove a lower bound
(3−o(1))n of the communication complexity in two-party PSQM protocols with a shared random string for random Boolean functions of
2n-bit input, which is larger than the trivial upper bound
2n of the communication complexity without the privacy condition. (2) We demonstrate a factor two gap between the communication complexity of PSQM protocols with shared entangled states and with shared random strings by designing a multiparty PSQM protocol with shared entangled states for a total function that extends the two-party equality function. (3) We demonstrate an exponential gap between the communication complexity of PSQM protocols with shared entangled states and with shared random strings for a two-party partial function.