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In previous work, we constructed a statistical framework for estimating the rate of clustered ionization from charged particle radiation in DNA. This model is extended to include contributions from secondary electrons. Using a simple…

Medical Physics · Physics 2023-11-17 Kay Kinoshita , Yusra Zabarmawi

A method of slowing, accelerating, cooling, and bunching molecules and neutral atoms using time-varying electric field gradients is demonstrated with cesium atoms in a fountain. The effects are measured and found to be in agreement with…

Atomic Physics · Physics 2009-10-31 Jason A. Maddi , Timothy P. Dinneen , Harvey Gould

In molecular photofragmentation processes by soft X-rays, a number of ionic fragments can be produced, each having a different abundance and correlation with the emitted electron kinetic energy. For investigating these fragmentation…

Atomic Physics · Physics 2007-05-23 G. Pruemper , K. Ueda

An overview of quantum-mechanical methods to generate cross-section data for electron collisions with atoms and molecules is presented. Particular emphasis is placed on the time-independent close-coupling approach, since it is particularly…

Plasma Physics · Physics 2016-10-21 Klaus Bartschat , Jonathan Tennyson , Oleg Zatsarinny

The matrix element method utilizes ab initio calculations of probability densities as powerful discriminants for processes of interest in experimental particle physics. The method has already been used successfully at previous and current…

Computational Physics · Physics 2015-05-20 Doug Schouten , Adam DeAbreu , Bernd Stelzer

Scattering by an isolated defect embedded in a dielectric medium of two dimensional periodicity is of interest in many sub-fields of electrodynamics. Present approaches to compute this scattering rely either on the Born approximation and…

Mesoscale and Nanoscale Physics · Physics 2021-05-10 Kuljit S. Virk

The quantum molecule consisting of three quantum dots that forms a triangle with its centers is studied. The electron wave function in the nanosystem is written using the linear combination of orbital quantum wells. The dispersion equation…

Mesoscale and Nanoscale Physics · Physics 2020-03-05 I. V. Bilynskyi , V. B. Hols'kyi , R. Ya. Leshko

We propose an approach for exploiting machine learning to approximate electronic fields in crystalline solids subjected to deformation. Strain engineering is emerging as a widely used method for tuning the properties of materials, and this…

Materials Science · Physics 2021-12-28 Ying Shi Teh , Swarnava Ghosh , Kaushik Bhattacharya

Quantum computers are ideal for solving chemistry problems due to their polynomial scaling with system size in contrast to classical computers which scale exponentially. Until now molecular energy calculations using quantum computing…

Quantum Physics · Physics 2019-08-15 Alexander Teplukhin , Brian K. Kendrick , Dmitri Babikov

We present a computational methodology to directly calculate and visualize the directional components of the Coulomb, radiation, and total electromagnetic fields, as well as the scalar and vector potentials, generated by moving point…

Computational Physics · Physics 2021-05-05 Matthew J. Filipovich , Stephen Hughes

We propose a method for the simulation of particle fragmentation based on the calculation of the energy landscape inside the particle. The landscape of strain energy is calculated in terms of internal stress using the principles of damage…

Soft Condensed Matter · Physics 2020-04-01 Yupeng Jiang , Fernando Alonso-Marroquin , Hans J Herrmann , Peter Mora

We present a quantum algorithm for the calculation of scattering amplitudes of massive charged scalar particles in scalar quantum electrodynamics. Our algorithm is based on continuous-variable quantum computing architecture resulting in…

Quantum Physics · Physics 2018-02-21 Kübra Yeter-Aydeniz , George Siopsis

The Electron Ion Collider (EIC) is the next generation of precision QCD facility to be built at Brookhaven National Laboratory in conjunction with Thomas Jefferson National Laboratory. There are a significant number of software and…

Instrumentation and Detectors · Physics 2022-12-20 J. C. Bernauer , C. T. Dean , C. Fanelli , J. Huang , K. Kauder , D. Lawrence , J. D. Osborn , C. Paus , J. K. Adkins , Y. Akiba , A. Albataineh , M. Amaryan , I. C. Arsene , C. Ayerbe Gayoso , J. Bae , X. Bai , M. D. Baker , M. Bashkanov , R. Bellwied , F. Benmokhtar , V. Berdnikov , F. Bock , W. Boeglin , M. Borysova , E. Brash , P. Brindza , W. J. Briscoe , M. Brooks , S. Bueltmann , M. H. S. Bukhari , A. Bylinkin , R. Capobianco , W. -C. Chang , Y. Cheon , K. Chen , K. -F. Chen , K. -Y. Cheng , M. Chiu , T. Chujo , Z. Citron , E. Cline , E. Cohen , T. Cormier , Y. Corrales Morales , C. Cotton , J. Crafts , C. Crawford , S. Creekmore , C. Cuevas , J. Cunningham , G. David , M. Demarteau , S. Diehl , N. Doshita , R. Dupré , J. M. Durham , R. Dzhygadlo , R. Ehlers , L. El Fassi , A. Emmert , R. Ent , R. Fatemi , S. Fegan , M. Finger , M. Finger , J. Frantz , M. Friedman , I. Friscic , D. Gangadharan , S. Gardner , K. Gates , F. Geurts , R. Gilman , D. Glazier , E. Glimos , Y. Goto , N. Grau , S. V. Greene , A. Q. Guo , L. Guo , S. K. Ha , J. Haggerty , T. Hayward , X. He , O. Hen , D. W. Higinbotham , M. Hoballah , T. Horn , A. Hoghmrtsyan , P. -h. J. Hsu , G. Huber , A. Hutson , K. Y. Hwang , C. Hyde , M. Inaba , T. Iwata , H. S. Jo , K. Joo , N. Kalantarians , G. Kalicy , K. Kawade , S. J. D. Kay , A. Kim , B. Kim , C. Kim , M. Kim , Y. Kim , Y. Kim , E. Kistenev , V. Klimenko , S. H. Ko , I. Korover , W. Korsch , G. Krintiras , S. Kuhn , C. -M. Kuo , T. Kutz , J. Lajoie , S. Lebedev , H. Lee , J. S. H. Lee , S. W. Lee , Y. -J. Lee , W. Li , W. Li , X. Li , X. Li , Y. T. Liang , S. Lim , C. -h. Lin , D. X. Lin , K. Liu , M. X. Liu , K. Livingston , N. Liyanage , W. J. Llope , C. Loizides , E. Long , R. -S. Lu , Z. Lu , W. Lynch , D. Marchand , M. Marcisovsky , P. Markowitz , H. Marukyan , P. McGaughey , M. Mihovilovic , R. G. Milner , A. Milov , Y. Miyachi , A. Mkrtchyan , P. Monaghan , R. Montgomery , D. Morrison , A. Movsisyan , H. Mkrtchyan , A. Mkrtchyan , C. Munoz Camacho , M. Murray , K. Nagai , J. Nagle , I. Nakagawa , C. Nattrass , D. Nguyen , S. Niccolai , R. Nouicer , G. Nukazuka , M. Nycz , V. A. Okorokov , S. Orešić , C. O'Shaughnessy , S. Paganis , Z Papandreou , S. F. Pate , M. Patel , G. Penman , M. G. Perdekamp , D. V. Perepelitsa , H. Periera da Costa , K. Peters , W. Phelps , E. Piasetzky , C. Pinkenburg , I. Prochazka , T. Protzman , M. L. Purschke , J. Putschke , J. R. Pybus , R. Rajput-Ghoshal , J. Rasson , B. Raue , K. Read , K. Røed , R. Reed , J. Reinhold , E. L. Renner , J. Richards , C. Riedl , T. Rinn , J. Roche , G. M. Roland , G. Ron , M. Rosati , C. Royon , J. Ryu , S. Salur , N. Santiesteban , R. Santos , M. Sarsour , J. Schambach , A. Schmidt , N. Schmidt , C. Schwarz , J. Schwiening , R. Seidl , A. Sickles , P. Simmerling , S. Sirca , D. Sharma , Z. Shi , T. -A. Shibata , C. -W. Shih , S. Shimizu , U. Shrestha , K. Slifer , K. Smith , D. Sokhan , R. Soltz , W. Sondheim , J. Song , J. Song , I. I. Strakovsky , P. Steinberg , P. Stepanov , J. Stevens , J. Strube , P. Sun , X. Sun , K. Suresh , V. Tadevosyan , W. -C. Tang , S. Tapia Araya , S. Tarafdar , L. Teodorescu , A. Timmins , L. Tomasek , N. Trotta , R. Trotta , T. S. Tveter , E. Umaka , A. Usman , H. W. van Hecke , C. Van Hulse , J. Velkovska , E. Voutier , P. K. Wang , Q. Wang , Y. Wang , Y. Wang , D. P. Watts , N. Wickramaarachchi , L. Weinstein , M. Williams , C. -P. Wong , L. Wood , M. H. Wood , C. Woody , B. Wyslouch , Z. Xiao , Y. Yamazaki , Y. Yang , Z. Ye , H. D. Yoo , M. Yurov , N. Zachariou , W. A. Zajc , J. Zhang , Y. Zhang , Y. X. Zhao , X. Zheng , P. Zhuang

We study the problem of learning unknown parameters in stochastic interacting particle systems with polynomial drift, interaction and diffusion functions from the path of one single particle in the system. Our estimator is obtained by…

Numerical Analysis · Mathematics 2024-01-30 Grigorios A. Pavliotis , Andrea Zanoni

An important application for near-term quantum computing lies in optimization tasks, with applications ranging from quantum chemistry and drug discovery to machine learning. In many settings --- most prominently in so-called parametrized or…

Quantum Physics · Physics 2019-03-27 Maria Schuld , Ville Bergholm , Christian Gogolin , Josh Izaac , Nathan Killoran

Trapped ions are a promising tool for building a large-scale quantum computer. However, the number of required radiation fields for the realisation of quantum gates in any proposed ion-based architecture scales with the number of ions…

Multipartite entanglement is a crucial resource for a wide range of quantum information processing tasks, including quantum metrology, quantum computing, and quantum communication. The verification of multipartite entanglement, along with…

Quantum Physics · Physics 2024-12-24 Kai Wu , Zhihua Chen , Zhen-Peng Xu , Zhihao Ma , Shao-Ming Fei

The problem of evaluating potential integrals on planar triangular elements has been addressed using a polar coordinate decomposition. The resulting formulae are general, exact, easily implemented, and have only one special case, that of a…

Numerical Analysis · Mathematics 2013-03-01 Michael Carley

We present a scheme in which an ion trap quantum computer can be used to make arbitrarily accurate measurements of the quadrature phase variables for the collective vibrational motion of the ion. The electronic states of the ion become the…

Quantum Physics · Physics 2007-05-23 C. D'Helon , G. J. Milburn

The Vlasov-Maxwell system of equations, which describes classical plasma physics, is extremely challenging to solve, even by numerical simulation on powerful computers. By linearizing and assuming a Maxwellian background distribution…

Quantum Physics · Physics 2019-12-19 Alexander Engel , Graeme Smith , Scott E. Parker
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