Post by The Hilbert Space Post

The July 1st edition of The Hilbert Space Post covers machine learning based quantum error mitigation, improvement of the loss threshold in photonic sensors, and estimation and mitigation of Trotter errors in quantum simulation. Here is this day's selection: 1️⃣ Pauli Weight Hamiltonian Term Selection for Optimized Machine Learning Based Quantum Error Mitigation 🔗 https://lnkd.in/g9BUAAnH 👨👩 Fadhil Shiddiq, Darell Timothy Tarigan, Hadyan Luthfan Prihadi, Jusak Kosasih, Yanoar Sarwono, Leong Chuan Kwek and Freddy Permana Zen 🔬 A new article introduces a machine-learning-based quantum error mitigation method that reduces measurement cost by selecting only the most important Pauli observables. This approach achieves significantly improved performance in noisy quantum simulations. 2️⃣ Improving the loss threshold for quantum advantage in photonic sensors by complete photon counting 🔗 https://lnkd.in/geFy3thq 👨👩 Gerard J. Machado, PhD, Yazeed Alwehaibi, Guillaume Thekkadath, Zhenghao Li, Aonan Zhang, Shang Yu, Adriana Lita, Richard Mirin, Martin Stevens, Ian Walmsley et al. 🔬 Combining nonlinear optical interferometry with full photon-number-resolving detection significantly improves quantum sensing performance under realistic losses, enabling a clear and experimentally verified precision advantage beyond the shot-noise limit. 3️⃣ Theory and practice of Trotter product formulas for quantum chemistry 🔗 https://lnkd.in/gyf5tvTU 👨👩 Pablo Antonio Moreno Casares, William Maxwell, Danial Motlagh, Hitarth Choubisa, Zy Niu, Ignacio Loaiza Ganem, Arne-Christian Voigt, Juan Miguel Arrazola and Stepan Fomichev (Xanadu, Volkswagen Group) 🔬 A new work proposes an improved Trotter-based Hamiltonian simulation framework for quantum chemistry that combines symmetry, randomization, and optimized decompositions to significantly reduce gate costs while using far fewer qubits. 4️⃣ Practical Estimation of Trotter Error for Hamiltonian Simulation 🔗 https://lnkd.in/gBhiQwnQ 👨👩 WIlliam Maxwell, Pablo Antonio Moreno Casares, Robert Lang, Stepan Fomichev, Juan Miguel Arrazola, Soran Jahangiri, Ali Asadi, Luis Alfredo Nuñez Menenses, Thomas Germain and Danial Motlagh (Xanadu) 🔬 A new paper develops improved theoretical bounds, algorithms, and software for estimating Trotter errors in Hamiltonian simulation. It shows that more efficient and scalable error estimation is possible and often far more accurate than standard bounds That’s it for the daily selection. If you enjoyed it, please consider giving us a like or reposting to support our content. Thanks!