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Found 14 papers, 5 papers with code
Coreset selection can accelerate quantum machine learning models with provable generalization
Quantum neural networks (QNNs) and quantum kernels stand as prominent figures in the realm of quantum machine learning, poised to leverage the nascent capabilities of near-term quantum computers to surmount classical machine learning challenges.
BeeTLe: A Framework for Linear B-Cell Epitope Prediction and Classification
The process of identifying and characterizing B-cell epitopes, which are the portions of antigens recognized by antibodies, is important for our understanding of the immune system, and for many applications including vaccine development, therapeutics, and diagnostics.
Transition role of entangled data in quantum machine learning
Recent progress has highlighted its positive impact on learning quantum dynamics, wherein the integration of entanglement into quantum operations or measurements of quantum machine learning (QML) models leads to substantial reductions in training data size, surpassing a specified prediction error threshold.
Power of Quantum Generative Learning
We further employ these generalization bounds to exhibit potential advantages in quantum state preparation and Hamiltonian learning.
Towards a variational Jordan-Lee-Preskill quantum algorithm
Rapid developments of quantum information technology show promising opportunities for simulating quantum field theory in near-term quantum devices.
Variational Quantum Algorithms
Applications such as simulating complicated quantum systems or solving large-scale linear algebra problems are very challenging for classical computers due to the extremely high computational cost.
One-shot dynamical resource theory
Focusing on a general dynamical resource theory of quantum channels, here we consider tasks of one-shot resource distillation and dilution with a single copy of the resource.
Quantum Physics
Mitigating realistic noise in practical noisy intermediate-scale quantum devices
As we numerically test our method with various Hamiltonians under energy relaxation and dephasing noise and digital quantum circuits with additional two-qubit crosstalk, we show an improvement of simulation accuracy by two orders.
Quantum Physics
Theory of variational quantum simulation
In this work, we introduce variational quantum simulation of mixed states under general stochastic evolution.
Quantum Physics
Variational quantum simulation of general processes
Finally, we introduce variational quantum simulation for open system dynamics.
Quantum Physics
A high threshold code for modular hardware with asymmetric noise
We consider an approach to fault tolerant quantum computing based on a simple error detecting code operating as the substrate for a conventional surface code.
Quantum Physics
Quantum computational chemistry
One of the most promising applications of quantum computing is solving classically intractable chemistry problems.
Quantum Physics
Error mitigated quantum computational chemistry
Variational algorithms may solve important chemistry problems on near-future quantum computers.
Quantum Physics
Variational quantum simulation of imaginary time evolution
Imaginary time evolution is a powerful tool for studying quantum systems.
Quantum Physics
