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arXiv:1611.02680

A simpler algorithm to mark the unknown eigenstates

Avatar Tulsi

Published Nov 8, 2016• 0 citations
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Abstract

For an unknown eigenstate $|ψ\rangle$ of a unitary operator $U$, suppose we have an estimate of the corresponding eigenvalue which is separated from all other eigenvalues by a minimum gap of magnitude $Δ$. In the eigenstate-marking problem (EMP), the goal is to implement a selective phase transformation of the $|ψ\rangle$ state (known as \emph{marking} the $|ψ\rangle$ state in the language of the quantum search algorithms). The EMP finds important applications in the construction of several quantum algorithms. The best known algorithm for the EMP combines the ideas of the phase estimation algorithm and the majority-voting. It uses $Θ(\frac{1}Δ\ln \frac{1}ε)$ applications of $U$ where $ε$ is the tolerable error. It needs $Θ\left(\ln \frac{1}Δ\right)$ ancilla qubits for the phase estimation and another $Θ\left(\ln \frac{1}ε\right)$ ancilla qubits for the majority-voting. In this paper, we show that the majority-voting is not a crucial requirement for the EMP and the same purpose can also be achieved using the fixed-point quantum search algorithm which does not need any ancilla qubits. In the case of majority-voting, these ancilla qubits were needed to do controlled transformations which are harder to implement physically. Using fixed-point quantum search, we get rid off these $Θ\left(\ln \frac{1}ε\right)$ ancilla qubits and same number of controlled transformations. Thus we get a much simpler algorithm for marking the unknown eigenstates. However, the required number of applications of $U$ increases by the factor of $Θ\left(\ln \frac{1}ε\right)$. This tradeoff can be beneficial in typical situations where spatial resources are more constrained or where the controlled transformations are very expensive.

DOI
10.48550/arxiv.1611.02680

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For an unknown eigenstate ∣ψ⟩|ψ\rangle∣ψ⟩ of a unitary operator UUU, suppose we have an estimate of the corresponding eigenvalue which is separated from all other eigenvalues by a minimum gap of magnitude ΔΔΔ. In the eigenstate-marking problem (EMP), the goal is to implement a selective phase transformation of the ∣ψ⟩|ψ\rangle∣ψ⟩ state (known as \emph{marking} the ∣ψ⟩|ψ\rangle∣ψ⟩ state in the language of the quantum search algorithms). The EMP finds important applications in the construction of several quantum algorithms. The best known algorithm for the EMP combines the ideas of the phase estimation algorithm and the majority-voting. It uses Θ(1Δln⁡1ε)Θ(\frac{1}Δ\ln \frac{1}ε)Θ(Δ1​lnε1​) applications of UUU where εεε is the tolerable error. It needs Θ(ln⁡1Δ)Θ\left(\ln \frac{1}Δ\right)Θ(lnΔ1​) ancilla qubits for the phase estimation and another Θ(ln⁡1ε)Θ\left(\ln \frac{1}ε\right)Θ(lnε1​) ancilla qubits for the majority-voting. In this paper, we show that the majority-voting is not a crucial requirement for the EMP and the same purpose can also be achieved using the fixed-point quantum search algorithm which does not need any ancilla qubits. In the case of majority-voting, these ancilla qubits were needed to do controlled transformations which are harder to implement physically. Using fixed-point quantum search, we get rid off these Θ(ln⁡1ε)Θ\left(\ln \frac{1}ε\right)Θ(lnε1​) ancilla qubits and same number of controlled transformations. Thus we get a much simpler algorithm for marking the unknown eigenstates. However, the required number of applications of UUU increases by the factor of Θ(ln⁡1ε)Θ\left(\ln \frac{1}ε\right)Θ(lnε1​). This tradeoff can be beneficial in typical situations where spatial resources are more constrained or where the controlled transformations are very expensive.
A basic building block of many quantum algorithms is the Phase Estimation algorithm (PEA). It estimates an eigenphase ϕ\phiϕ of a unitary operator UUU using a copy of the corresponding eigenstate ∣ϕ⟩|\phi\rangle∣ϕ⟩. Suppose, in place of ∣ϕ⟩|\phi\rangle∣ϕ⟩, we have a copy of an approximate eigenstate ∣ψ⟩|\psi\rangle∣ψ⟩ whose overlap magnitude with ∣ϕ⟩|\phi\rangle∣ϕ⟩ is at least 2/3\sqrt{2/3}2/3​. Then PEA fails with a constant probability. However, using multiple copies of ∣ψ⟩|\psi\rangle∣ψ⟩, the failure probaility can be made to decrease exponentially with the number of copies. In this paper, we show that as long as we can perform a selective inversion of ∣ψ⟩|\psi\rangle∣ψ⟩, a single copy is sufficient to estimate ϕ\phiϕ. An important application is to improve the spatial complexity of eigenpath traversal algorithm, a digital analogue of quantum adiabatic evolution, having applications ranging from quantum physics simulation to optimization. Here the goal is to travel a path of eigenstates of nnn different unitary operators satisfying some conditions. The fastest algorithm is due to Boixo, Knill and Somma (BKS) which needs Θ(ln⁡n)\Theta(\ln n)Θ(lnn) copies of the eigenstate. Using our algorithm, BKS algorithm can work using just a single copy of the eigenstate.
Quantum computing can provide speedups in solving many problems as the evolution of a quantum system is described by a unitary operator in an exponentially large Hilbert space. Such unitary operators change the phase of their eigenstates and make quantum algorithms fundamentally different from their classical counterparts. Based on this unique principle of quantum computing, we develop an algorithmic toolbox, quantum phase processing, that can directly apply arbitrary trigonometric transformations to eigenphases of a unitary operator. The quantum phase processing circuit is constructed simply, consisting of single-qubit rotations and controlled unitaries, typically using only one ancilla qubit. Besides the capability of phase transformation, quantum phase processing in particular can extract the eigeninformation of quantum systems by simply measuring the ancilla qubit, making it naturally compatible with indirect measurement. Quantum phase processing complements another powerful framework known as quantum singular value transformation and leads to more intuitive and efficient quantum algorithms for solving problems that are particularly phase related. As a notable application, we propose a quantum phase estimation algorithm without quantum Fourier transform, which requires the fewest ancilla qubits and matches the best performance so far. We further exploit the power of our method by investigating a plethora of applications in Hamiltonian simulation, entanglement spectroscopy, and quantum entropy estimation, demonstrating improvements or optimality for almost all cases.
Quantum phase estimation is one of the most important tools in quantum algorithms. It can be made non-adaptive (meaning all applications of the unitary UφU_φUφ​ happen simultaneously) without using more applications of UφU_φUφ​, albeit at the expense of using many more qubits. It is also known that there is no advantage for adaptive algorithms in the case where the phase that needs to be estimated is arbitrary or is uniformly random. Here we give examples of a special case of phase estimation, with a promise on the values that the unknown phase can take, where adaptive methods are provably better than non-adaptive methods by a factor of nearly 2 in the number of uses of UφU_φUφ​. We also prove some upper bounds on the maximum advantage that adaptive algorithms for phase estimation can achieve over non-adaptive ones.
The standard quantum search lacks a feature, enjoyed by many classical algorithms, of having a fixed point, i.e. monotonic convergence towards the solution. Recently a fixed point quantum search algorithm has been discovered, referred to as the Phase-π/3π/3π/3 search algorithm, which gets around this limitation. While searching a database for a target state, this algorithm reduces the error probability from εεε to ε2q+1ε^{2q+1}ε2q+1 using qqq oracle queries, which has since been proved to be asymptotically optimal. A different algorithm is presented here, which has the same worst-case behavior as the Phase-π/3π/3π/3 search algorithm but much better average-case behavior. Furthermore the new algorithm gives ε2q+1ε^{2q+1}ε2q+1 convergence for all integral qqq, whereas the Phase-π/3π/3π/3 search algorithm requires qqq to be (3n−1)/2(3^{n}-1)/2(3n−1)/2 with nnn a positive integer. In the new algorithm, the operations are controlled by two ancilla qubits, and fixed point behavior is achieved by irreversible measurement operations applied to these ancillas. It is an example of how measurement can allow us to bypass some restrictions imposed by unitarity on quantum computing.
Quantum searching requires precise knowledge of problem parameters (such as the fraction of target states) for efficient operation. Recently an algorithm has been discovered, referred to as the Phase-pi/3\\pi/3pi/3 search algorithm, which gets around this limitation. This algorithm can search a database with the fraction of target states equal to 1−epsilon1-\\epsilon1−epsilon so that in qqq queries it produces a probability of error equal to epsilon2q+1\\epsilon^{2q+1}epsilon2q+1 which has since been proved to be optimal. This paper gives a different algorithm which has the same worst-case behavior as the Phase-pi/3\\pi/3pi/3 search algorithm but much better average-case behavior. Furthermore the new algorithm gives epsilon2q+1\\epsilon^{2q+1}epsilon2q+1 convergence for all integral qqq, the Phase-pi/3\\pi/3pi/3 search algorithm, requires qqq to be (3n−1)/2(3^{n}-1)/2(3n−1)/2, with nnn a positive integer. In the new algorithm, the operations are controlled in a special way by two ancilla qubits, and fixed point behavior is achieved by irreversible measurement operations.
The standard quantum search algorithm lacks a feature, enjoyed by many classical algorithms, of having a fixed-point, i.e. a monotonic convergence towards the solution. Here we present two variations of the quantum search algorithm, which get around this limitation. The first replaces selective inversions in the algorithm by selective phase shifts of π3\fracπ{3}3π​. The second controls the selective inversion operations using two ancilla qubits, and irreversible measurement operations on the ancilla qubits drive the starting state towards the target state. Using qqq oracle queries, these variations reduce the probability of finding a non-target state from εεε to ε2q+1ε^{2q+1}ε2q+1, which is asymptotically optimal. Similar ideas can lead to robust quantum algorithms, and provide conceptually new schemes for error correction.