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Register a new userAsymptotically Optimal Circuit Depth for Quantum State Preparation and General Unitary Synthesis
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The Quantum State Preparation problem aims to prepare an n-qubit quantum state $|psi_vrangle=sum_{k=0}^{2^n-1}v_k|krangle$ from initial state $|0rangle^{otimes n}$, for a given vector $v=(v_0,ldots,v_{2^n-1})inmathbb{C}^{2^n}$ with $|v|_2=1$. The problem is of fundamental importance in quantum algorithm design, Hamiltonian simulation and quantum machine learning, yet its circuit depth complexity remains open in the general case with ancillary qubits. In this paper, we study efficient constructions of quantum circuits for preparing a quantum state: Given $m=O(2^n/n^2)$ ancillary qubits, we construct a circuit to prepare $|psi_vrangle$ with depth $Theta(2^n/(m+n))$, which is optimal in this regime. In particular, when $m=Theta(2^n/n^2)$, the circuit depth is $Theta(n^2)$, which is an exponential improvement of the previous bound of $O(2^n)$. For $m=omega(2^n/n^2)$, we prove a lower bound of $Omega(n)$, an exponential improvement over the previous lower bound of $Omega(log n)$, leaving a polynomial gap between $Omega(n)$ and $O(n^2)$ for the depth complexity. These results also imply a tight bound of $Theta(4^n/(m+n))$ for depth of circuits implementing a general n-qubit unitary using $m=O(2^n/n)$ ancillary qubits. This closes a gap for circuits without ancillary qubits; for circuits with sufficiently many ancillary qubits, this gives a quadratic saving from $O(4^n)$ to $tildeTheta(2^n)$.Our circuits are deterministic, prepare the state and carry out the unitary precisely, utilize the ancillary qubits tightly and the depths are optimal in a wide range of parameter regime. The results can be viewed as (optimal) time-space tradeoff bounds, which is not only theoretically interesting, but also practically relevant in the current trend that the number of qubits starts to take off, by showing a way to use a large number of qubits to compensate the short qubit lifetime.
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Efficient synthesis of arbitrary quantum states and unitaries from a universal fault-tolerant gate-set e.g. Clifford+T is a key subroutine in quantum computation. As large quantum algorithms feature many qubits that encode coherent quantum information but remain idle for parts of the computation, these should be used if it minimizes overall gate counts, especially that of the expensive T-gates. We present a quantum algorithm for preparing any dimension-$N$ pure quantum state specified by a list of $N$ classical numbers, that realizes a trade-off between space and T-gates. Our scheme uses $mathcal{O}(log{(N/epsilon)})$ clean qubits and a tunable number of $sim(lambdalog{(frac{log{N}}{epsilon})})$ dirty qubits, to reduce the T-gate cost to $mathcal{O}(frac{N}{lambda}+lambdalog^2{frac{N}{epsilon}})$. This trade-off is optimal up to logarithmic factors, proven through an unconditional gate counting lower bound, and is, in the best case, a quadratic improvement in T-count over prior ancillary-free approaches. We prove similar statements for unitary synthesis by reduction to state preparation.
We present an approach to single-shot high-fidelity preparation of an $n$-qubit state based on neighboring optimal control theory. This represents a new application of the neighboring optimal control formalism which was originally developed to produce single-shot high-fidelity quantum gates. To illustrate the approach, and to provide a proof-of-principle, we use it to prepare the two qubit Bell state $|beta_{01}rangle = (1/sqrt{2})left[, |01rangle + |10rangle,right]$ with an error probability $epsilonsim 10^{-6}$ ($10^{-5}$) for ideal (non-ideal) control. Using standard methods in the literature, these high-fidelity Bell states can be leveraged to fault-tolerantly prepare the logical state $|overline{beta}_{01}rangle$.
Quantum circuit synthesis is the process in which an arbitrary unitary operation is decomposed into a sequence of gates from a universal set, typically one which a quantum computer can implement both efficiently and fault-tolerantly. As physical implementations of quantum computers improve, the need is growing for tools which can effectively synthesize components of the circuits and algorithms they will run. Existing algorithms for exact, multi-qubit circuit synthesis scale exponentially in the number of qubits and circuit depth, leaving synthesis intractable for circuits on more than a handful of qubits. Even modest improvements in circuit synthesis procedures may lead to significant advances, pushing forward the boundaries of not only the size of solvable circuit synthesis problems, but also in what can be realized physically as a result of having more efficient circuits. We present a method for quantum circuit synthesis using deterministic walks. Also termed pseudorandom walks, these are walks in which once a starting point is chosen, its path is completely determined. We apply our method to construct a parallel framework for circuit synthesis, and implement one such version performing optimal $T$-count synthesis over the Clifford+$T$ gate set. We use our software to present examples where parallelization offers a significant speedup on the runtime, as well as directly confirm that the 4-qubit 1-bit full adder has optimal $T$-count 7 and $T$-depth 3.
We present a method that outputs a sequence of simple unitary operations to prepare a given quantum state that is a generalized coherent state. Our method takes as inputs the expectation values of some relevant observables on the state to be prepared. Such expectation values can be estimated by performing projective measurements on $O(M^3 log(M/delta)/epsilon^2)$ copies of the state, where $M$ is the dimension of an associated Lie algebra, $epsilon$ is a precision parameter, and $1-delta$ is the required confidence level. The method can be implemented on a classical computer and runs in time $O(M^4 log(M/epsilon))$. It provides $O(M log(M/epsilon))$ simple unitaries that form the sequence. The number of all computational resources is then polynomial in $M$, making the whole procedure very efficient in those cases where $M$ is significantly smaller than the Hilbert space dimension. When the algebra of relevant observables is determined by some Pauli matrices, each simple unitary may be easily decomposed into two-qubit gates. We discuss applications to quantum state tomography and classical simulations of quantum circuits.
Quantum computation represents a revolutionary means for solving problems in quantum chemistry. However, due to the limited coherence time and relatively low gate fidelity in the current noisy intermediate-scale quantum (NISQ) devices, realization of quantum algorithms for large chemical systems remains a major challenge. In this work, we demonstrate how the circuit depth of the unitary coupled cluster ansatz in the algorithm of variational quantum eigensolver can be significantly reduced by an energy-sorting strategy. Specifically, subsets of excitation operators are pre-screened from the unitary coupled-cluster singles and doubles (UCCSD) operator pool according to its contribution to the total energy. The procedure is then iteratively repeated until the convergence of the final energy to within the chemical accuracy. For demonstration, this method has been sucessfully applied to systems of molecules and periodic hydrogen chain. Particularly, a reduction up to 14 times in the number of operators is observed while retaining the accuracy of the origin UCCSD operator pools. This method can be widely extended to other variational ansatz other than UCC.
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