Efficient Quantum Circuits for Non-Unitary and Unitary Diagonal Operators with Space-Time-Accuracy trade-offs
- URL: http://arxiv.org/abs/2404.02819v3
- Date: Tue, 25 Jun 2024 12:15:43 GMT
- Title: Efficient Quantum Circuits for Non-Unitary and Unitary Diagonal Operators with Space-Time-Accuracy trade-offs
- Authors: Julien Zylberman, Ugo Nzongani, Andrea Simonetto, Fabrice Debbasch,
- Abstract summary: Unitary and non-unitary diagonal operators are fundamental building blocks in quantum algorithms.
We introduce a general approach to implement unitary and non-unitary diagonal operators with efficient-adjustable-depth quantum circuits.
- Score: 1.0749601922718608
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Unitary and non-unitary diagonal operators are fundamental building blocks in quantum algorithms with applications in the resolution of partial differential equations, Hamiltonian simulations, the loading of classical data on quantum computers (quantum state preparation) and many others. In this paper, we introduce a general approach to implement unitary and non-unitary diagonal operators with efficient-adjustable-depth quantum circuits. The depth, i.e., the number of layers of quantum gates of the quantum circuit, is reducible with respect either to the width, i.e, the number of ancilla qubits, or to the accuracy between the implemented operator and the target one. While exact methods have an optimal exponential scaling either in terms of size, i.e., the total number of primitive quantum gates, or width, approximate methods prove to be efficient for the class of diagonal operators depending on smooth, at least differentiable, functions. Our approach is general enough to allow any method for diagonal operators to become adjustable-depth or approximate, decreasing the depth of the circuit by increasing its width or its approximation level. This feature offers flexibility and can match with the hardware limitations in coherence time or cumulative gate error. We illustrate these methods by performing quantum state preparation and non-unitary-real-space simulation of the diffusion equation. This simulation paves the way to efficient implementations of stochastic models useful in physics, chemistry, biology, image processing and finance.
Related papers
- Quantum Circuit Optimization using Differentiable Programming of Tensor Network States [0.0]
The said algorithm runs on classical hardware and finds shallow, accurate quantum circuits.
All circuits achieve high state fidelities within reasonable CPU time and modest memory requirements.
arXiv Detail & Related papers (2024-08-22T17:48:53Z) - Efficient Learning for Linear Properties of Bounded-Gate Quantum Circuits [63.733312560668274]
Given a quantum circuit containing d tunable RZ gates and G-d Clifford gates, can a learner perform purely classical inference to efficiently predict its linear properties?
We prove that the sample complexity scaling linearly in d is necessary and sufficient to achieve a small prediction error, while the corresponding computational complexity may scale exponentially in d.
We devise a kernel-based learning model capable of trading off prediction error and computational complexity, transitioning from exponential to scaling in many practical settings.
arXiv Detail & Related papers (2024-08-22T08:21:28Z) - Parallel Quantum Computing Simulations via Quantum Accelerator Platform Virtualization [44.99833362998488]
We present a model for parallelizing simulation of quantum circuit executions.
The model can take advantage of its backend-agnostic features, enabling parallel quantum circuit execution over any target backend.
arXiv Detail & Related papers (2024-06-05T17:16:07Z) - Boundary Treatment for Variational Quantum Simulations of Partial Differential Equations on Quantum Computers [1.6318838452579472]
The paper presents a variational quantum algorithm to solve initial-boundary value problems described by partial differential equations.
The approach uses classical/quantum hardware that is well suited for quantum computers of the current noisy intermediate-scale quantum era.
arXiv Detail & Related papers (2024-02-28T18:19:33Z) - A two-circuit approach to reducing quantum resources for the quantum lattice Boltzmann method [41.66129197681683]
Current quantum algorithms for solving CFD problems use a single quantum circuit and, in some cases, lattice-based methods.
We introduce the a novel multiple circuits algorithm that makes use of a quantum lattice Boltzmann method (QLBM)
The problem is cast as a stream function--vorticity formulation of the 2D Navier-Stokes equations and verified and tested on a 2D lid-driven cavity flow.
arXiv Detail & Related papers (2024-01-20T15:32:01Z) - Efficient estimation of trainability for variational quantum circuits [43.028111013960206]
We find an efficient method to compute the cost function and its variance for a wide class of variational quantum circuits.
This method can be used to certify trainability for variational quantum circuits and explore design strategies that can overcome the barren plateau problem.
arXiv Detail & Related papers (2023-02-09T14:05:18Z) - Approximate encoding of quantum states using shallow circuits [0.0]
A common requirement of quantum simulations and algorithms is the preparation of complex states through sequences of 2-qubit gates.
Here, we aim at creating an approximate encoding of the target state using a limited number of gates.
Our work offers a universal method to prepare target states using local gates and represents a significant improvement over known strategies.
arXiv Detail & Related papers (2022-06-30T18:00:04Z) - Effective non-local parity-dependent couplings in qubit chains [0.0]
We harness the simultaneous coupling of qubits on a chain and engineer a set of non-local parity-dependent quantum operations.
The resulting effective long-range couplings directly implement a parametrizable Trotter-step for Jordan-Wigner fermions.
We present numerical simulations of the gate operation in a superconducting quantum circuit architecture.
arXiv Detail & Related papers (2022-03-14T17:33:40Z) - Quantum amplitude damping for solving homogeneous linear differential
equations: A noninterferometric algorithm [0.0]
This work proposes a novel approach by using the Quantum Amplitude Damping operation as a resource, in order to construct an efficient quantum algorithm for solving homogeneous LDEs.
We show that such an open quantum system-inspired circuitry allows for constructing the real exponential terms in the solution in a non-interferometric.
arXiv Detail & Related papers (2021-11-10T11:25:32Z) - Variational Quantum Optimization with Multi-Basis Encodings [62.72309460291971]
We introduce a new variational quantum algorithm that benefits from two innovations: multi-basis graph complexity and nonlinear activation functions.
Our results in increased optimization performance, two increase in effective landscapes and a reduction in measurement progress.
arXiv Detail & Related papers (2021-06-24T20:16:02Z) - Programming a quantum computer with quantum instructions [39.994876450026865]
We use a density matrixiation protocol to execute quantum instructions on quantum data.
A fixed sequence of classically-defined gates performs an operation that uniquely depends on an auxiliary quantum instruction state.
The utilization of quantum instructions obviates the need for costly tomographic state reconstruction and recompilation.
arXiv Detail & Related papers (2020-01-23T22:43:29Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.