Excited to share this news that "Stabilizer ground states for simulating quantum many-body physics: theory, algorithms, and applications" is now officially published on Quantum (finally!).🥳 https://t.co/V0Bhltaf1H via @quantumjournal
https://t.co/OAtcLE7iKd Excited to share my husband @sunjiace’s recent work on stochastic tensor contraction CC. A real revolutionary work on classical electronic structure. On an order of improvements of DLPNO CC in terms of accuracy & costs, nearly the same cost of wB97!
🥳excited to see our, Orbformer, a wavefunction foundation model trained on the 2nd row elements, is released. By using pretaining-finetuning, one can compute multiref systems fast & accurately. Please check out the series of posts from Adam 😊
🎉Excited to see NERD is published on @JChemPhys
https://t.co/twFHZPUBSP Appreciate all the suggestions from reviewers and the supports from @MSFTResearch leaders and JCP editor office!
🥳Happy to share our work on extracting extremely accurate electron densities (and many related properties) from wavefunctions. Feel honored to work with all these talented colleagues in @MSFTResearch AI for Science Lab
🥳Excited to announce that our work on using a double adaptive-region BO (DARBO) [a modified ver of TuRBO] to opt QAOA is published on @CommsPhys. Robust on real Quantum devices w/ noises!
📰Paper: https://t.co/4Ng5SXGm6C
👩💻Code: https://t.co/9Ws4T4WaP6
We really appreciate the suggestions from reviewers and the help from editors. Hope our work would be helpful for quantum computing for quantum chemistry field.😊
We are happy to see our work on quantum circuit engineering algorithm is now published on JCTC. @JCIM_JCTC@jctc_papers https://t.co/BVhMx8ciz0 Please see the summary below we posted 5 mons ago 🤩
(1/3) I am thrilled to announce that @AI_for_Science workshop is back with #NeurIPS2023! This year we put together several new programs with a new theme "from theory to practice", including a panel discussion to align the expectation between academia and funding agencies.
🖥️An easy-to-use GUI with support of Windows, MacOS and Linux. No GPT is needed and 100% free.
🧑🔬👩🔬Terrific for non-native speakers to read papers in other languages.
📺Please checkout our user guide video: https://t.co/FFwmD8qVex
🥳We're happy to announce MathTranslate w/ GUI https://t.co/0CtWr16DIj.
📖A free latex-based open-source github project to translate arxiv papers to any other languages with perfect treatments of equations, references, figures... 📄With mathpix, you can also translate any pdf.
2/2 We design the Clifford-based Hamiltonian transformation that
(1) ensures the initial state is the Hartree–Fock state
(2) maximizes the initial energy gradients
(3) imposes negligible classical processing cost.
1/2 🥳Excited to share our new work https://t.co/8zV5jh4Dkr. Present a Clifford-based Hamiltonian engineering algorithm (CHEM) to achieve chemical accuracy with shallow quantum circuits for VQE. Demonstrated on systems as large as 12 qubits w/ fewer than 30 2-qubit gates.
This work is published on JCTC @JCIM_JCTC now: https://t.co/PNjYEMC8WX.
Welcome everyone's comments and hope our software can contribute the field of Quantum Computing for Quantum Chemistry.
However, qualitative discrepancy for the electronic noise is not improved with the semi-analytical model. Our work suggests that the exp noise behavior mostly likely arises from space charge domain formation rather than intervalley scattering, as has been assumed for many decades
🥳Excited to share our new published paper on @PhysRevB on transport & noise of hot e in GaAs! https://t.co/fgkjZQ7jKn It introduces a semi-analytical model for e transport in GaAs to describe e-ph interactions, allowing the prior approx used in the ab-initio calcs to be lifted.