Scalable quantum circuits for n-qubit unitary matrices

04/27/2023
by   Rohit Sarma Sarkar, et al.
0

This work presents an optimization-based scalable quantum neural network framework for approximating n-qubit unitaries through generic parametric representation of unitaries, which are obtained as product of exponential of basis elements of a new basis that we propose as an alternative to Pauli string basis. We call this basis as the Standard Recursive Block Basis, which is constructed using a recursive method, and its elements are permutation-similar to block Hermitian unitary matrices.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
11/08/2020

LDU factorization

LU-factorization of matrices is one of the fundamental algorithms of lin...
research
03/19/2022

Explicit Quantum Circuits for Block Encodings of Certain Sparse Matrices

Many standard linear algebra problems can be solved on a quantum compute...
research
07/13/2022

Recursive Methods for Synthesizing Permutations on Limited-Connectivity Quantum Computers

We describe a family of recursive methods for the synthesis of qubit per...
research
04/22/2022

A Multigraph Approach for Performing the Quantum Schur Transform

We take inspiration from the Okounkov-Vershik approach to the representa...
research
01/23/2019

On basis images for the digital image representation

Digital array orthogonal transformations that can be presented as a deco...
research
01/25/2023

Quantum Encryption of superposition states with Quantum Permutation Pad in IBM Quantum Computers

We present an implementation of Kuang and Bettenburg's Quantum Permutati...
research
07/29/2021

Calculating elements of matrix functions using divided differences

We introduce a method for calculating individual elements of matrix func...

Please sign up or login with your details

Forgot password? Click here to reset