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Quantum Information and Measurement (QIM)

Supervised learning of time-independent Hamiltonians for gate design

Luca Innocenti, Leonardo Banchi, Alessandro Ferraro, Sougato Bose, Mauro Paternostro

Published Jan 1, 2019• 2 citations
Publisher

Abstract

We present a general framework to approach the problem of finding time-independent dynamics generating target unitary evolutions. More specifically, given a target unitary gate G over a set of qubits, and a parametrized Hamiltonian of the form H ( λ ) = ∑ i λ i σ i with σi Hermitian operators over the qubits, we want to find a set of values λ0 such that exp ( i H ( λ 0 ) ) = G. We show that this problem is equivalently stated as a set of conditions over the spectrum of H ( λ ), reducing the problem to an inverse eigenvalue problem. We show how to solve this problem in some physically relevant instances, like for example to find time-independent dynamics implementing Toffoli and Fredkin gates without the need for ancillary gates or effective evolutions.

DOI
10.1364/qim.2019.f5a.28

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We present a general framework to approach the problem of finding time-independent dynamics generating target unitary evolutions. More specifically, given a target unitary gate G over a set of qubits, and a parametrized Hamiltonian of the form H ( λ ) = ∑ i λ i σ i with σi Hermitian operators over the qubits, we want to find a set of values λ0 such that exp ( i H ( λ 0 ) ) = G. We show that this problem is equivalently stated as a set of conditions over the spectrum of H ( λ ), reducing the problem to an inverse eigenvalue problem. We show how to solve this problem in some physically relevant instances, like for example to find time-independent dynamics implementing Toffoli and Fredkin gates without the need for ancillary gates or effective evolutions.
Abstract We present a general framework to tackle the problem of finding time-independent dynamics generating target unitary evolutions. We show that this problem is equivalently stated as a set of conditions over the spectrum of the time-independent gate generator, thus translating the task into an inverse eigenvalue problem. We illustrate our methodology by identifying suitable time-independent generators implementing Toffoli and Fredkin gates without the need for ancillae or effective evolutions. We show how the same conditions can be used to solve the problem numerically, via supervised learning techniques. In turn, this allows us to solve problems that are not amenable, in general, to direct analytical solution, providing at the same time a high degree of flexibility over the types of gate-design problems that can be approached. As a significant example, we find generators for the Toffoli gate using only diagonal pairwise interactions, which are easier to implement in some experimental architectures. To showcase the flexibility of the supervised learning approach, we give an example of a non-trivial four-qubit gate that is implementable using only diagonal, pairwise interactions.
Abstract We put forward a strategy to encode a quantum operation into the unmodulated dynamics of a quantum network without the need for external control pulses, measurements or active feedback. Our optimisation scheme, inspired by supervised machine learning, consists in engineering the pairwise couplings between the network qubits so that the target quantum operation is encoded in the natural reduced dynamics of a network section. The efficacy of the proposed scheme is demonstrated by the finding of uncontrolled four-qubit networks that implement either the Toffoli gate, the Fredkin gate or remote logic operations. The proposed Toffoli gate is stable against imperfections, has a high fidelity for fault-tolerant quantum computation and is fast, being based on the non-equilibrium dynamics.
Larger multi-qubit quantum gates allow shallower, more efficient quantum circuits, which could decrease the prohibitive effect of noise on algorithms for noisy intermediate-scale quantum (NISQ) devices and fault-tolerant error correction schemes. Such multi-qubit gates can potentially be generated by time-independent Hamiltonians comprising only physical (one- and two-local) interaction terms. Here, we present an algorithm that finds the time-independent Hamiltonian for a target quantum gate on nnn qubits by using the geodesic on the Riemannian manifold of SU(2n)\mathrm{SU}(2^n)SU(2n). Differential programming is used to determine how the Hamiltonian should be updated in order to follow the geodesic to the target unitary as closely as possible. We show that our geodesic algorithm outperforms gradient descent methods for standard multi-qubit gates such as Toffoli and Fredkin. The geodesic algorithm is then used to find previously unavailable multi-qubit gates implementing high fidelity parity checks, which could be used in a wide array of quantum codes and increase the clock speed of fault-tolerant quantum computers. The geodesic algorithm is demonstrated on an example relevant to current experimental hardware, illustrating a circuit speed up.
Implementing quantum operations in the form of natural Hamiltonian dynamics is desirable, since they almost require no external control or feedback. In this work, we propose a NISQ-friendly quantum-classical hybrid approach to designing a time-independent Hamiltonian that generates a given multi-qubit unitary. In particular, we execute a Variational Quantum Algorithm, whose ansatz is carefully chosen to be a sequence of appropriately parametrized unitaries describing at most two-qubit nearest neighbour interactions, dictating the target unitary. Subsequently, we apply our approach to simulate multi-qubit target gates, with and without stochastic noise. We demonstrate that our strategy allows us to implement a Toffoli gate with sufficiently high fidelity, as compared to the other similar techniques. Our approach is an example of the usage of quantum computing for the design of quantum computers.
Larger multiqubit quantum gates allow shallower, more efficient quantum circuits, which could decrease the prohibitive effect of noise on algorithms for noisy intermediate-scale quantum (NISQ) devices and fault-tolerant error correction schemes. Such multiqubit gates can potentially be generated by time-independent Hamiltonians comprising only physical (one- and two-local) interaction terms. Here, we present an algorithm that finds the time-independent Hamiltonian for a target quantum gate on n qubits by using the geodesic on the Riemannian manifold of SU ( 2 n ) . Differential programming is used to determine how the Hamiltonian should be updated to follow the geodesic to the target unitary as closely as possible. We show that our geodesic algorithm outperforms gradient descent methods for standard multiqubit gates such as Toffoli and Fredkin. The geodesic algorithm is then used to find previously unavailable multiqubit gates implementing high-fidelity parity checks, which could be used in a wide array of quantum codes and increase the clock speed of fault-tolerant quantum computers. The geodesic algorithm is demonstrated on an example relevant to current experimental hardware, illustrating a circuit speed up.
In this paper we propose a systematic method to solve the inverse dynamical problem for a quantum system governed by the von Neumann equation: to find a class of Hamiltonians reproducing a prescribed time evolution of a pure or mixed state of the system. Our approach exploits the equivalence between an action of the group of evolution operators over the state space and an adjoint action of the unitary group over Hermitian matrices. The method is illustrated by two examples involving a pure and a mixed state.