Learning quantum states prepared by shallow circuits in polynomial time
- URL: http://arxiv.org/abs/2410.23618v1
- Date: Thu, 31 Oct 2024 04:12:49 GMT
- Title: Learning quantum states prepared by shallow circuits in polynomial time
- Authors: Zeph Landau, Yunchao Liu,
- Abstract summary: We learn a constant depth quantum circuit that prepares $vertpsirangle$ on a finite-dimensional lattice.
The algorithm extends to the case when the depth of $U$ is $mathrmpolylog(n)$, with a quasi-polynomial run-time.
As an application, we give an efficient algorithm to test whether an unknown quantum state on a lattice has low or high quantum circuit complexity.
- Score: 1.127500169412367
- License:
- Abstract: We give a polynomial time algorithm that, given copies of an unknown quantum state $\vert\psi\rangle=U\vert 0^n\rangle$ that is prepared by an unknown constant depth circuit $U$ on a finite-dimensional lattice, learns a constant depth quantum circuit that prepares $\vert\psi\rangle$. The algorithm extends to the case when the depth of $U$ is $\mathrm{polylog}(n)$, with a quasi-polynomial run-time. The key new idea is a simple and general procedure that efficiently reconstructs the global state $\vert\psi\rangle$ from its local reduced density matrices. As an application, we give an efficient algorithm to test whether an unknown quantum state on a lattice has low or high quantum circuit complexity.
Related papers
- Learning shallow quantum circuits with many-qubit gates [1.879968161594709]
We present the first computationally-efficient algorithm for average-case learning of quantum circuits with many-qubit gates.
We show that the learned unitary can be efficiently synthesized in poly-logarithmic depth.
arXiv Detail & Related papers (2024-10-22T04:48:36Z) - On the practicality of quantum sieving algorithms for the shortest vector problem [42.70026220176376]
lattice-based cryptography is one of the main candidates of post-quantum cryptography.
cryptographic security against quantum attackers is based on lattice problems like the shortest vector problem (SVP)
Asymptotic quantum speedups for solving SVP are known and rely on Grover's search.
arXiv Detail & Related papers (2024-10-17T16:54:41Z) - Classically estimating observables of noiseless quantum circuits [36.688706661620905]
We present a classical algorithm for estimating expectation values of arbitrary observables on most quantum circuits.
For non-classically-simulable input states or observables, the expectation values can be estimated by augmenting our algorithm with classical shadows of the relevant state or observable.
arXiv Detail & Related papers (2024-09-03T08:44:33Z) - Anti-Concentration for the Unitary Haar Measure and Applications to Random Quantum Circuits [12.786353781073242]
We prove a Carbery-Wright style anti-concentration inequality for the unitary Haar measure.
We show that the scrambling speed of a random quantum circuit is lower bounded.
arXiv Detail & Related papers (2024-07-28T19:10:46Z) - Quantum algorithms for Hopcroft's problem [45.45456673484445]
We study quantum algorithms for Hopcroft's problem which is a fundamental problem in computational geometry.
The classical complexity of this problem is well-studied, with the best known algorithm running in $O(n4/3)$ time.
Our results are two different quantum algorithms with time complexity $widetilde O(n5/6)$.
arXiv Detail & Related papers (2024-05-02T10:29:06Z) - Learning shallow quantum circuits [7.411898489476803]
We present an algorithm for learning the description of any unknown $n$-qubit shallow quantum circuit $U$.
We also provide a classical algorithm for learning the description of any unknown $n$-qubit state $lvert psi rangle$.
Our approach uses a quantum circuit representation based on local inversions and a technique to combine these inversions.
arXiv Detail & Related papers (2024-01-18T16:05:00Z) - Quantum State Preparation with Optimal Circuit Depth: Implementations
and Applications [10.436969366019015]
We show that any $Theta(n)$-depth circuit can be prepared with a $Theta(log(nd)) with $O(ndlog d)$ ancillary qubits.
We discuss applications of the results in different quantum computing tasks, such as Hamiltonian simulation, solving linear systems of equations, and realizing quantum random access memories.
arXiv Detail & Related papers (2022-01-27T13:16:30Z) - Synthesis of Quantum Circuits with an Island Genetic Algorithm [44.99833362998488]
Given a unitary matrix that performs certain operation, obtaining the equivalent quantum circuit is a non-trivial task.
Three problems are explored: the coin for the quantum walker, the Toffoli gate and the Fredkin gate.
The algorithm proposed proved to be efficient in decomposition of quantum circuits, and as a generic approach, it is limited only by the available computational power.
arXiv Detail & Related papers (2021-06-06T13:15:25Z) - Quantum Algorithm for Fidelity Estimation [8.270684567157987]
For two unknown mixed quantum states $rho$ and $sigma$ in an $N$-dimensional space, computing their fidelity $F(rho,sigma)$ is a basic problem.
We propose a quantum algorithm that solves this problem in $namepoly(log (N), r, 1/varepsilon)$ time.
arXiv Detail & Related papers (2021-03-16T13:57:01Z) - Efficient Algorithms for Causal Order Discovery in Quantum Networks [44.356294905844834]
Given black-box access to the input and output systems, we develop the first efficient quantum causal order discovery algorithm.
We model the causal order with quantum combs, and our algorithms output the order of inputs and outputs that the given process is compatible with.
Our algorithms will provide efficient ways to detect and optimize available transmission paths in quantum communication networks.
arXiv Detail & Related papers (2020-12-03T07:12:08Z) - Quantum Gram-Schmidt Processes and Their Application to Efficient State
Read-out for Quantum Algorithms [87.04438831673063]
We present an efficient read-out protocol that yields the classical vector form of the generated state.
Our protocol suits the case that the output state lies in the row space of the input matrix.
One of our technical tools is an efficient quantum algorithm for performing the Gram-Schmidt orthonormal procedure.
arXiv Detail & Related papers (2020-04-14T11:05:26Z)
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.