50 research outputs found
Quantum Algorithm for Finding the Optimal Variable Ordering for Binary Decision Diagrams
An ordered binary decision diagram (OBDD) is a directed acyclic graph that represents a Boolean function. Since OBDDs have many nice properties as data structures, they have been extensively studied for decades in both theoretical and practical fields, such as VLSI (Very Large Scale Integration) design, formal verification, machine learning, and combinatorial problems. Arguably, the most crucial problem in using OBDDs is that they may vary exponentially in size depending on their variable ordering (i.e., the order in which the variables are to be read) when they represent the same function. Indeed, it is NP hard to find an optimal variable ordering that minimizes an OBDD for a given function. Friedman and Supowit provided a clever deterministic algorithm with time/space complexity O^?(3?), where n is the number of variables of the function, which is much better than the trivial brute-force bound O^?(n!2?). This paper shows that a further speedup is possible with quantum computers by presenting a quantum algorithm that produces a minimum OBDD together with the corresponding variable ordering in O^?(2.77286?) time and space with an exponentially small error probability. Moreover, this algorithm can be adapted to constructing other minimum decision diagrams such as zero-suppressed BDDs
Computing on Anonymous Quantum Network
This paper considers distributed computing on an anonymous quantum network, a
network in which no party has a unique identifier and quantum communication and
computation are available. It is proved that the leader election problem can
exactly (i.e., without error in bounded time) be solved with at most the same
complexity up to a constant factor as that of exactly computing symmetric
functions (without intermediate measurements for a distributed and superposed
input), if the number of parties is given to every party. A corollary of this
result is a more efficient quantum leader election algorithm than existing
ones: the new quantum algorithm runs in O(n) rounds with bit complexity
O(mn^2), on an anonymous quantum network with n parties and m communication
links. Another corollary is the first quantum algorithm that exactly computes
any computable Boolean function with round complexity O(n) and with smaller bit
complexity than that of existing classical algorithms in the worst case over
all (computable) Boolean functions and network topologies. More generally, any
n-qubit state can be shared with that complexity on an anonymous quantum
network with n parties.Comment: 25 page
Power of Uninitialized Qubits in Shallow Quantum Circuits
We study the computational power of shallow quantum circuits
with O(log n) initialized and n^{O(1)} uninitialized ancillary
qubits, where n is the input length and the initial state of
the uninitialized ancillary qubits is arbitrary. First, we show
that such a circuit can compute any symmetric function on n bits
that is classically computable in polynomial time. Then, we
regard such a circuit as an oracle and show that a
polynomial-time classical algorithm with the oracle can estimate
the elements of any unitary matrix corresponding to a
constant-depth quantum circuit on n qubits. Since it seems unlikely
that these tasks can be done with only O(log n) initialized
ancillary qubits, our results give evidences that adding
uninitialized ancillary qubits increases the computational power
of shallow quantum circuits with only O(log n) initialized
ancillary qubits. Lastly, to understand the limitations of
uninitialized ancillary qubits, we focus on
near-logarithmic-depth quantum circuits with them and show
the impossibility of computing the parity function on n bits
Probabilistic state synthesis based on optimal convex approximation
When preparing a pure state with a quantum circuit, there is an unavoidable
approximation error due to the compilation error in fault-tolerant
implementation. A recently proposed approach called probabilistic state
synthesis, where the circuit is probabilistically sampled, is able to reduce
the approximation error compared to conventional deterministic synthesis. In
this paper, we demonstrate that the optimal probabilistic synthesis
quadratically reduces the approximation error. Moreover, we show that a
deterministic synthesis algorithm can be efficiently converted into a
probabilistic one that achieves this quadratic error reduction. We also
numerically demonstrate how this conversion reduces the -count and
analytically prove that this conversion halves an information-theoretic lower
bound on the circuit size. In order to derive these results, we prove general
theorems about the optimal convex approximation of a quantum state.
Furthermore, we demonstrate that this theorem can be used to analyze an
entanglement measure.Comment: 24 pages, 5 figures. ArXiv:2111.05531 is a preliminary version of
this pape
Classically Simulating Quantum Circuits with Local Depolarizing Noise
We study the effect of noise on the classical simulatability of quantum circuits defined by computationally tractable (CT) states and efficiently computable sparse (ECS) operations. Examples of such circuits, which we call CT-ECS circuits, are IQP, Clifford Magic, and conjugated Clifford circuits. This means that there exist various CT-ECS circuits such that their output probability distributions are anti-concentrated and not classically simulatable in the noise-free setting (under plausible assumptions). First, we consider a noise model where a depolarizing channel with an arbitrarily small constant rate is applied to each qubit at the end of computation. We show that, under this noise model, if an approximate value of the noise rate is known, any CT-ECS circuit with an anti-concentrated output probability distribution is classically simulatable. This indicates that the presence of small noise drastically affects the classical simulatability of CT-ECS circuits. Then, we consider an extension of the noise model where the noise rate can vary with each qubit, and provide a similar sufficient condition for classically simulating CT-ECS circuits with anti-concentrated output probability distributions
Sumcheck-based delegation of quantum computing to rational server
Delegated quantum computing enables a client with a weak computational power
to delegate quantum computing to a remote quantum server in such a way that the
integrity of the server is efficiently verified by the client. Recently, a new
model of delegated quantum computing has been proposed, namely, rational
delegated quantum computing. In this model, after the client interacts with the
server, the client pays a reward to the server. The rational server sends
messages that maximize the expected value of the reward. It is known that the
classical client can delegate universal quantum computing to the rational
quantum server in one round. In this paper, we propose novel one-round rational
delegated quantum computing protocols by generalizing the classical rational
sumcheck protocol. The construction of the previous rational protocols depends
on gate sets, while our sumcheck technique can be easily realized with any
local gate set. Furthermore, as with the previous protocols, our reward
function satisfies natural requirements. We also discuss the reward gap. Simply
speaking, the reward gap is a minimum loss on the expected value of the
server's reward incurred by the server's behavior that makes the client accept
an incorrect answer. Although our sumcheck-based protocols have only
exponentially small reward gaps as with the previous protocols, we show that a
constant reward gap can be achieved if two non-communicating but entangled
rational servers are allowed. We also discuss that a single rational server is
sufficient under the (widely-believed) assumption that the learning-with-errors
problem is hard for polynomial-time quantum computing. Apart from these
results, we show, under a certain condition, the equivalence between
and delegated quantum computing protocols. Based on this
equivalence, we give a reward-gap amplification method.Comment: 28 pages, 1 figure, Because of the character limitation, the abstract
was shortened compared with the PDF fil