Fri·Oct 15, 2021Friday·October 15, 2021

1. 01*

   Progress in $x$-dependent partonic distributions from lattice QCD

   Krzysztof Cichy🇵🇱

   We review the latest progress in lattice QCD calculations of the partonic structure of hadrons. This structure is, in particular, described in terms of $x$-dependent distributions, the simplest of which are the standard parton distribution functions (PDFs). The lattice calculations rely on matrix elements probing spatial correlations between partons in a boosted hadron, that can be matched to light-cone correlations defining the relevant distributions. We discuss the recent theoretical and practical refinements of this strategy, as well as new exploratory directions. The latter include generalized parton distributions (GPDs), distributions beyond leading twist, flavor-singlet distributions and transverse-momentum dependent PDFs (TMDs). We also shortly consider the potential future impact of lattice data on phenomenology.

   hep-lathep-phPoS(2022)·60 citations
2. 02*

   Large scale multi-node simulations of ${\mathbb{Z}}_2$ gauge theory quantum circuits using Google Cloud Platform

   Erik Gustafson (1)🇺🇸 · Burt Holzman (1)🇺🇸 · James Kowalkowski (1)🇺🇸 · Henry Lamm (1)🇺🇸 · Andy C. Y. Li (1)🇺🇸 · Gabriel Perdue (1)🇺🇸 · Sergio Boixo (2)🇺🇸 · Sergei Isakov (2)🇺🇸 · Orion Martin (2)🇺🇸 · Ross Thomson (2)🇺🇸 · Catherine Vollgraff Heidweiller (2)🇺🇸 · Jackson Beall (3)🇺🇸 and 3 other authors

   Simulating quantum field theories on a quantum computer is one of the most exciting fundamental physics applications of quantum information science. Dynamical time evolution of quantum fields is a challenge that is beyond the capabilities of classical computing, but it can teach us important lessons about the fundamental fabric of space and time. Whether we may answer scientific questions of interest using near-term quantum computing hardware is an open question that requires a detailed simulation study of quantum noise. Here we present a large scale simulation study powered by a multi-node implementation of qsim using the Google Cloud Platform. We additionally employ newly-developed GPU capabilities in qsim and show how Tensor Processing Units -- Application-specific Integrated Circuits (ASICs) specialized for Machine Learning -- may be used to dramatically speed up the simulation of large quantum circuits. We demonstrate the use of high performance cloud computing for simulating ${\mathbb{Z}}_2$ quantum field theories on system sizes up to 36 qubits. We find this lattice size is not able to simulate our problem and observable combination with sufficient accuracy, implying more challenging observables of interest for this theory are likely beyond the reach of classical computation using exact circuit simulation.

   ↳ quant-phhep-lat19 citations
3. 03*

   Effective range expansion for narrow near-threshold resonances

   Vadim Baru🇩🇪 · Xiang-Kun Dong🇨🇳 · Meng-Lin Du🇪🇸 · Arseniy Filin🇩🇪 · Feng-Kun Guo🇨🇳 · Christoph Hanhart🇩🇪 · Alexey Nefediev🇷🇺 · Juan Nieves🇪🇸 · Qian Wang🇨🇳

   We discuss some general features of the effective range expansion, the content of its parameters with respect to the nature of the pertinent near-threshold states and the necessary modifications in the presence of coupled channels, isospin violations and unstable constituents. As illustrative examples, we analyse the properties of the ${\chi }_{c1}(3872)$ and $T_{cc}^{+}$ states supporting the claim that these exotic states have a predominantly molecular nature.

   ↳ hep-phhep-exhep-latnucl-thPLB(2022)·91 citations

* Reconstructed cohort: no mailing for this day survives in the archive. Papers are grouped by their submission times and arXiv's announcement cut-off, assuming announcement without delay; positions follow identifier order. Validated at ~91% exact-day agreement against the archived era.