Improving Hamiltonian encodings with the Gray code

Best-Practice Aspects of Quantum-Computer Calculations: A Case Study of the Hydrogen Molecule

“…Quantum computing has recently emerged as a very promising alternative to conventional computational means. Conventional supercomputers, albeit versatile and remarkably reliable, seem to be outpaced by ever-increasing demand for computational power when developing new drugs [ 1 ], modeling nanoparticles [ 2 ], or assessing problems in materials science [ 3 ] and nuclear physics [ 4 , 5 ]. In contrast to the well-established conventional technologies, quantum computers are expected to provide exponentially growing computational power thanks to the their use of quantum effects [ 6 , 7 ], and the first indications of so-called quantum advantage/supremacy have already been demonstrated [ 8 , 9 , 10 ].…”

Nuclear two point correlation functions on a quantum-computer

“…( 5) can be mapped to qubits in various ways as described in Ref. [23] (see also [38] for an alternative based on the Gray code). In the following we will consider the case of two flavors and four lattice sites, with the first quantization mapping already employed in Ref.…”

Bootstrapping the deuteron

“…Inspired by the huge success of artificial intelligence (AI), new variational methods based on artificial neural networks (ANNs) are put forward for few-nucleon systems, incorporating the latest advances in AI into conventional variational methods [3][4][5]. Also, lots of interests are stimulated in developing new theoretical methods on quantum devices, encouraged by the public accessibility of quantum computing clouds via the internet [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20]. These achievements enrich our tools to study nuclear systems.…”