# Quantum Chemistry

Published articles for Quantum Chemistry.

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## Thermodynamic sampling of disordered materials with an analog Hamiltonian Rydberg simulator

DevFeed: [Thermodynamic sampling of disordered materials with an analog Hamiltonian Rydberg simulator](<https://devfeed.tech/articles/thermodynamic-sampling-of-disordered-materials-with-an-analog-hamiltonian-rydberg-simulator-50169.md>)

Original publisher: [Read original article](<https://aws.amazon.com/blogs/quantum-computing/thermodynamic-sampling-of-disordered-materials-with-an-analog-hamiltonian-rydberg-simulator-2/>)

Author: Mao Lin

Published: 2026-07-23T20:03:07Z

Content type: article

Language: en

Sources: [AWS Quantum Technologies Blog](<https://devfeed.tech/sources/aws-quantum-technologies-blog.md>)

Topics: [simulator](<https://devfeed.tech/topics/simulator.md>), [amazon](<https://devfeed.tech/topics/amazon.md>), [Hardware](<https://devfeed.tech/topics/hardware.md>), [Benchmark](<https://devfeed.tech/topics/benchmark.md>)

Tags: [amazon](<https://devfeed.tech/tags/amazon.md>), [amazon-braket](<https://devfeed.tech/tags/amazon-braket.md>), [benchmark](<https://devfeed.tech/tags/benchmark.md>), [customer-solutions](<https://devfeed.tech/tags/customer-solutions.md>), [hamiltonian](<https://devfeed.tech/tags/hamiltonian.md>), [hardware](<https://devfeed.tech/tags/hardware.md>), [quantum](<https://devfeed.tech/tags/quantum.md>), [quantum-algorithms](<https://devfeed.tech/tags/quantum-algorithms.md>), [quantum-chemistry](<https://devfeed.tech/tags/quantum-chemistry.md>), [quantum-computing](<https://devfeed.tech/tags/quantum-computing.md>), [quantum-technologies](<https://devfeed.tech/tags/quantum-technologies.md>), [research](<https://devfeed.tech/tags/research.md>), [science](<https://devfeed.tech/tags/science.md>), [simulator](<https://devfeed.tech/tags/simulator.md>), [technical-how-to](<https://devfeed.tech/tags/technical-how-to.md>), [thought-leadership](<https://devfeed.tech/tags/thought-leadership.md>)

### AI overview

The post reports using the QuEra Aquila neutral-atom device through Amazon Braket as a thermodynamic sampler for material models. It maps a density-functional-theory-derived energy model for nitrogen-doped graphene onto Rydberg atoms, validates a 28-site system, and benchmarks a 78-site system against classical Monte Carlo sampling.

### Source excerpt

This post was contributed by Mao Lin, Bruno Camino, John Buckeridge and Scott M. Woodley Many advanced materials -- from battery electrodes to semiconductor alloys -- owe their useful properties to atomic-scale disorder. But predicting how atoms arrange themselves at a given temperature is hard: the number of possible configurations explodes combinatorially and sampling them [...]

## Classiq and AWS Power Quantum-Classical Chemistry Innovation in Singapore with Hatch

DevFeed: [Classiq and AWS Power Quantum-Classical Chemistry Innovation in Singapore with Hatch](<https://devfeed.tech/articles/classiq-and-aws-power-quantum-classical-chemistry-innovation-in-singapore-with-hatch-50164.md>)

Original publisher: [Read original article](<https://aws.amazon.com/blogs/quantum-computing/classiq-and-aws-power-quantum-classical-chemistry-innovation-in-singapore-with-hatch/>)

Author: Roie Dann

Published: 2026-06-22T13:40:35Z

Content type: article

Language: en

Sources: [AWS Quantum Technologies Blog](<https://devfeed.tech/sources/aws-quantum-technologies-blog.md>)

Topics: [Quantum Computing](<https://devfeed.tech/topics/quantum-computing.md>), [Amazon Web Services](<https://devfeed.tech/topics/aws.md>), [Amazon EC2](<https://devfeed.tech/topics/amazon-ec2.md>), [cloud-infrastructure](<https://devfeed.tech/topics/cloud-infrastructure.md>), [Computing](<https://devfeed.tech/topics/computing.md>)

Tags: [amazon-braket](<https://devfeed.tech/tags/amazon-braket.md>), [amazon-ec2](<https://devfeed.tech/tags/amazon-ec2.md>), [amazon-elastic-block-store-amazon-ebs](<https://devfeed.tech/tags/amazon-elastic-block-store-amazon-ebs.md>), [aws](<https://devfeed.tech/tags/aws.md>), [aws-batch](<https://devfeed.tech/tags/aws-batch.md>), [chemistry](<https://devfeed.tech/tags/chemistry.md>), [classiq](<https://devfeed.tech/tags/classiq.md>), [cloud-infrastructure](<https://devfeed.tech/tags/cloud-infrastructure.md>), [compute](<https://devfeed.tech/tags/compute.md>), [computing](<https://devfeed.tech/tags/computing.md>), [customer-solutions](<https://devfeed.tech/tags/customer-solutions.md>), [development](<https://devfeed.tech/tags/development.md>), [early-stage](<https://devfeed.tech/tags/early-stage.md>), [energy](<https://devfeed.tech/tags/energy.md>), [partner-solutions](<https://devfeed.tech/tags/partner-solutions.md>), [quantum](<https://devfeed.tech/tags/quantum.md>), [quantum-algorithms](<https://devfeed.tech/tags/quantum-algorithms.md>), [quantum-chemistry](<https://devfeed.tech/tags/quantum-chemistry.md>), [quantum-classical](<https://devfeed.tech/tags/quantum-classical.md>), [quantum-computing](<https://devfeed.tech/tags/quantum-computing.md>), [quantum-research](<https://devfeed.tech/tags/quantum-research.md>), [quantum-technologies](<https://devfeed.tech/tags/quantum-technologies.md>), [research](<https://devfeed.tech/tags/research.md>), [singapore](<https://devfeed.tech/tags/singapore.md>), [storage](<https://devfeed.tech/tags/storage.md>), [technical-how-to](<https://devfeed.tech/tags/technical-how-to.md>)

### AI overview

This post describes Classiq's quantum-classical pipeline for estimating molecular binding energies in computational chemistry. The workflow combines parallelized Density Functional Theory calculations with a variational quantum eigensolver, using Amazon EC2 cloud infrastructure for classical computation and quantum computing to account for quantum correlations.

### Source excerpt

Introduction In biochemical processes development and analysis, binding energy, the energy released when a small molecule docks into a protein's active site, determines how strongly a compound, such as a ligand, interacts with its protein target. Early-stage computational prediction of this quantity helps research teams prioritize candidates before committing to resource-intensive laboratory testing. Conventional methods [...]