Multiclass classification using quantum convolutional neural networks with hybrid quantum-classical learning
D Bokhan, AS Mastiukova, AS Boev… - Frontiers in …, 2022 - frontiersin.org
Multiclass classification is of great interest for various applications, for example, it is a
common task in computer vision, where one needs to categorize an image into three or …
common task in computer vision, where one needs to categorize an image into three or …
Characterization and verification of trotterized digital quantum simulation via hamiltonian and liouvillian learning
The goal of digital quantum simulation is to approximate the dynamics of a given target
Hamiltonian via a sequence of quantum gates, a procedure known as Trotterization. The …
Hamiltonian via a sequence of quantum gates, a procedure known as Trotterization. The …
The advantage of quantum control in many-body Hamiltonian learning
We study the problem of learning the Hamiltonian of a many-body quantum system from
experimental data. We show that the rate of learning depends on the amount of control …
experimental data. We show that the rate of learning depends on the amount of control …
Mitigating crosstalk errors by randomized compiling: Simulation of the BCS model on a superconducting quantum computer
We develop and apply an extension of the randomized compiling (RC) protocol that includes
a special treatment of neighboring qubits and dramatically reduces crosstalk effects caused …
a special treatment of neighboring qubits and dramatically reduces crosstalk effects caused …
Realizing symmetry-protected topological phases in a spin-1/2 chain with next-nearest-neighbor hopping on superconducting qubits
Quantum simulation on near-term quantum hardware is a topic of intense interest. The
preparation of novel quantum states of matter provides a quantitative assessment of the …
preparation of novel quantum states of matter provides a quantitative assessment of the …
Co-Design quantum simulation of nanoscale NMR
Quantum computers have the potential to efficiently simulate the dynamics of nanoscale
NMR systems. In this work, we demonstrate that a noisy intermediate-scale quantum …
NMR systems. In this work, we demonstrate that a noisy intermediate-scale quantum …
Quantum computation of molecular structure using data from challenging-to-classically-simulate nuclear magnetic resonance experiments
We propose a quantum algorithm for inferring the molecular nuclear spin Hamiltonian from
time-resolved measurements of spin-spin correlators, which can be obtained via nuclear …
time-resolved measurements of spin-spin correlators, which can be obtained via nuclear …
Quantum simulation of highly-oscillatory many-body Hamiltonians for near-term devices
We develop a fourth-order Magnus expansion based quantum algorithm for the simulation of
many-body problems involving two-level quantum systems with time-dependent …
many-body problems involving two-level quantum systems with time-dependent …
Prospects for NMR Spectral Prediction on Fault-Tolerant Quantum Computers
JE Elenewski, CM Camara, A Kalev - arXiv preprint arXiv:2406.09340, 2024 - arxiv.org
Nuclear magnetic resonance spectroscopy is a prominent analytical tool, with applications
throughout chemistry, medicine and solid-state physics. While conventional NMR …
throughout chemistry, medicine and solid-state physics. While conventional NMR …
Simulating Non-Markovian Dynamics in Multidimensional Electronic Spectroscopy via Quantum Algorithm
Including the effect of the molecular environment in the numerical modeling of time-resolved
electronic spectroscopy remains an important challenge in computational spectroscopy. In …
electronic spectroscopy remains an important challenge in computational spectroscopy. In …