Hasil untuk "Physical and theoretical chemistry"

Joe Pratt-Johns, Toby St. Clere Smithe, Chris Guiver et al.

We construct a functor that gives a dynamics to an algebraic model of interacting components. The construction generalises a computational model of Fontana and Buss in the field of artificial life known as AlChemy, in which molecules and their chemical interactions are emulated by lambda calculus terms and their application and subsequent reduction. We discuss future directions for the application of category theory to algebraic artificial chemistry as an organisational tool, with a focus on formalising the connection between the algebraic and the dynamical facets of such models.

Andrea Cernuschi, Thomas Thuillier, Laurent Garrigues

The Electron Cyclotron Resonance Ion Plasma ACcelerator (ECRIPAC) is an original concept for a plasma-based particle accelerator able to generate pulsed ion beams with adjustable energy, targeting mostly medical applications. This paper thoroughly reviews the working principle and physical theory behind the ECRIPAC accelerator concept, incorporating significant corrections to the existing limited literature on the subject, making it a suitable reference for future studies. Mathematical derivations for several physical formulas are also included. Moreover, a detailed theoretical investigation of the stability condition for the ion acceleration is presented, highlighting more stringent limitations than previously anticipated. Next, the impact of several physical parameters on the accelerator design is analyzed, providing an overview of achievable external fields and plasma characteristics allowing a stable ion acceleration.

An-Jun Liu, Bryan K. Clark

The ground state of second-quantized quantum chemistry Hamiltonians is key to determining molecular properties. Neural quantum states (NQS) offer flexible and expressive wavefunction ansatze for this task but face two main challenges: highly peaked ground-state wavefunctions hinder efficient sampling, and local energy evaluations scale quartically with system size, incurring significant computational costs. In this work, we overcome these challenges by introducing a suite of algorithmic enhancements, which includes efficient periodic compact subspace construction, truncated local energy evaluations, improved stochastic sampling, and physics-informed modifications. Applying these techniques to the neural network backflow (NNBF) ansatz, we demonstrate significant gains in both accuracy and scalability. Our enhanced method surpasses traditional quantum chemistry methods like CCSD and CCSD(T), outperforms other NQS approaches, and achieves competitive energies with state-of-the-art ab initio techniques such as HCI, ASCI, FCIQMC, and DMRG. A series of ablation and comparative studies quantifies the contribution of each enhancement to the observed improvements in accuracy and efficiency. Furthermore, we investigate the representational capacity of the ansatz, finding that its performance correlates with the inverse participation ratio (IPR), with more delocalized states being more challenging to approximate.

Manuel Morales-Alvarado, Daniel Conde, Josh Bendavid et al.

We study the potential of symbolic regression (SR) to derive compact and precise analytic expressions that can improve the accuracy and simplicity of phenomenological analyses at the Large Hadron Collider (LHC). As a benchmark, we apply SR to equation recovery in quantum electrodynamics (QED), where established analytical results from quantum field theory provide a reliable framework for evaluation. This benchmark serves to validate the performance and reliability of SR before extending its application to structure functions in the Drell-Yan process mediated by virtual photons, which lack analytic representations from first principles. By combining the simplicity of analytic expressions with the predictive power of machine learning techniques, SR offers a useful tool for facilitating phenomenological analyses in high energy physics.

Sándor Demes, Cheikh Tidiane Bop, Malek Ben Khalifa et al.

Recent astronomical observations revealed an increasing molecular complexity in the interstellar medium through the detection of a series of large cyclic carbon species. To correctly interpret these detections, a complex analysis is necessary that takes into account the non-local thermodynamic equilibrium (non-LTE) conditions of the emitting media (e.g. when energy level populations deviate from a Boltzman distribution). This requires proper state-to-state collisional data for the excitation and de-excitation processes of the molecular levels. Cyclopentadiene (c-C5H6), which was recently detected in multiple cold interstellar clouds, is extensively studied in many aspects due to its large importance for chemistry in general. At the same time, there are no collisional data available for this species, which are necessary for a more precise interpretation of the corresponding detections. In this work, we first provide an accurate 3D rigid-rotor interaction potential for the [c-C5H6 + He] complex from high-level of ab initio theories, which has been used to study their inelastic collision by the exact close coupling quantum scattering method. To the best of our knowledge, this is the first study where this method is systematically applied to treat the dynamics of molecular collisions involving more than ten atoms. We also analyse the collisional propensity rules and the differences in contrast to calculations, where the approximate coupled states scattering methods is used.

Ron van der Meyden

Convertible instruments are contracts, used in venture financing, which give investors the right to receive shares in the venture in certain circumstances. In liquidity events, investors may have the option to either receive back their principal investment, or to receive a proportional payment after conversion of the contract to a shareholding. In each case, the value of the payment may depend on the choices made by other investors who hold such convertible contracts. A liquidity event therefore sets up a game theoretic optimization problem. The paper defines a general model for such games, which is shown to cover all instances of the Y Combinator Simple Agreement for Future Equity (SAFE) contracts, a type of convertible instrument that is commonly used to finance startup ventures. The paper shows that, in general, pure strategy Nash equilibria do not necessarily exist in this model, and there may not exist an optimum pure strategy Nash equilibrium in cases where pure strategy Nash equilibria do exist. However, it is shown when all contracts are uniformly one of the SAFE contract types, an optimum pure strategy Nash equilibrium exists. Polynomial time algorithms for computing (optimum) pure strategy Nash equilibria in these cases are developed.

M. Reitner, P. Chalupa, L. Del Re et al.

While the breakdown of the perturbation expansion for the many-electron problem has several formal consequences, here we unveil its physical effect: Flipping the sign of the effective electronic interaction in specific scattering channels. By decomposing local and uniform susceptibilities of the Hubbard model via their spectral representations, we prove how entering the non-perturbative regime causes an enhancement of the charge response, ultimately responsible for the phase-separation instabilities close to the Mott MIT. Our analysis opens a new route for understanding phase-transitions in the non-perturbative regime and clarifies why attractive effects emerging from a strong repulsion can induce phase-separations, but not s-wave pairing or charge-density wave instabilities.

Yuemin Bian, Xiang-Qun Xie

The de novo design of molecular structures using deep learning generative models introduces an encouraging solution to drug discovery in the face of the continuously increased cost of new drug development. From the generation of original texts, images, and videos, to the scratching of novel molecular structures, the incredible creativity of deep learning generative models surprised us about the height machine intelligence can achieve. The purpose of this paper is to review the latest advances in generative chemistry which relies on generative modeling to expedite the drug discovery process. This review starts with a brief history of artificial intelligence in drug discovery to outline this emerging paradigm. Commonly used chemical databases, molecular representations, and tools in cheminformatics and machine learning are covered as the infrastructure for the generative chemistry. The detailed discussions on utilizing cutting-edge generative architectures, including recurrent neural network, variational autoencoder, adversarial autoencoder, and generative adversarial network for compound generation are focused. Challenges and future perspectives follow.

Gisela Esplugues, Stephanie Cazaux, Paola Caselli et al.

When studying the chemistry of PDRs, time dependence becomes important as visual extinction increases, since certain chemical timescales are comparable to the cloud lifetime. Dust temperature is also a key factor, since it significantly influences gas temperature and mobility on dust grains, determining the chemistry occurring on grain surfaces. We present a study of the dust temperature impact and time effects on the chemistry of different PDRs, using an updated version of the Meijerink PDR code and combining it with the time-dependent code Nahoon. We find the largest temperature effects in the inner regions of high $G$$_{\mathrm{0}}$ PDRs, where high dust temperatures favour the formation of simple oxygen-bearing molecules (especially that of O$_2$), while the formation of complex organic molecules is much more efficient at low dust temperatures. We also find that time-dependent effects strongly depend on the PDR type, since long timescales promote the destruction of oxygen-bearing molecules in the inner parts of low $G$$_{\mathrm{0}}$ PDRs, while favouring their formation and that of carbon-bearing molecules in high $G$$_{\mathrm{0}}$ PDRs. From the chemical evolution, we also conclude that, in dense PDRs, CO$_2$ is a late-forming ice compared to water ice, and confirm a layered ice structure on dust grains, with H$_2$O in lower layers than CO$_2$. Regarding steady state, the PDR edge reaches chemical equilibrium at early times ($\lesssim$10$^5$ yr). This time is even shorter ($<$10$^4$ yr) for high $G$$_{\mathrm{0}}$ PDRs. By contrast, inner regions reach equilibrium much later, especially low $G$$_{\mathrm{0}}$ PDRs, where steady state is reached at $\sim$10$^6$-10$^7$ yr.

Dávid Csercsik, Franz Hubert, Balázs R. Sziklai et al.

Existing cooperative game theoretic studies of bargaining power in gas pipeline systems are based on the so called characteristic function form (CFF). This approach is potentially misleading if some pipelines fall under regulated third party access (TPA). TPA, which is by now the norm in the EU, obliges the owner of a pipeline to transport gas for others, provided they pay a regulated transport fee. From a game theoretic perspective, this institutional setting creates so called "externalities," the description of which requires partition function form (PFF) games. In this paper we propose a method to compute payoffs, reflecting the power structure, for a pipeline system with regulated TPA. The method is based on an iterative flow mechanism to determine gas flows and transport fees for individual players and uses the recursive core and the minimal claim function to convert the PPF game back into a CFF game, which can be solved by standard methods. We illustrate the approach with a simple stylized numerical example of the gas network in Central Eastern Europe with a focus on Ukraine's power index as a major transit country.

Raphael F. Ribeiro, Luis A. Martínez-Martínez, Matthew Du et al.

Molecular polaritons are the optical excitations which emerge when molecular transitions interact strongly with confined electromagnetic fields. Increasing interest in the hybrid molecular-photonic materials that host these excitations stems from recent observations of their novel and tunable chemistry. Some of the remarkable functionalities exhibited by polaritons include the ability to induce long-range excitation energy transfer, enhance charge conductivity, and inhibit or enhance chemical reactions. In this review, we explain the effective theories of molecular polaritons which form a basis for the interpretation and guidance of experiments at the strong coupling limit. The theoretical discussion is illustrated with the analysis of innovative applications of strongly coupled molecular-photonic systems to chemical phenomena of fundamental importance to future technologies.

Daniel Kitzmann, Kevin Heng, Paul B. Rimmer et al.

The atmospheric temperatures of the ultra-hot Jupiter KELT-9b straddle the transition between gas giants and stars, and therefore between two traditionally distinct regimes of atmospheric chemistry. Previous theoretical studies assume the atmosphere of KELT-9b to be in chemical equilibrium. Despite the high ultraviolet flux from KELT-9, we show using photochemical kinetics calculations that the observable atmosphere of KELT-9b is predicted to be close to chemical equilibrium, which greatly simplifies any theoretical interpretation of its spectra. It also makes the atmosphere of KELT-9b, which is expected to be cloudfree, a tightly constrained chemical system that lends itself to a clean set of theoretical predictions. Due to the lower pressures probed in transmission (compared to emission) spectroscopy, we predict the abundance of water to vary by several orders of magnitude across the atmospheric limb depending on temperature, which makes water a sensitive thermometer. Carbon monoxide is predicted to be the dominant molecule under a wide range of scenarios, rendering it a robust diagnostic of the metallicity when analyzed in tandem with water. All of the other usual suspects (acetylene, ammonia, carbon dioxide, hydrogen cyanide, methane) are predicted to be subdominant at solar metallicity, while atomic oxygen, iron and magnesium are predicted to have relative abundances as high as 1 part in 10,000. Neutral atomic iron is predicted to be seen through a forest of optical and near-infrared lines, which makes KELT-9b suitable for high-resolution ground-based spectroscopy with HARPS-N or CARMENES. We summarize future observational prospects of characterizing the atmosphere of KELT-9b.

Bikas K. Chakrabarti

We review the developments of the statistical physics of fracture and earthquake over the last four decades. We argue that major progress has been made in this field and that the key concepts should now become integral part of the (under-) graduate level text books in condensed matter physics. For arguing in favor of this, we compare the development (citations) with the same for some other related topics in condensed matter, for which Nobel prizes have already been awarded.

Emiliano Cortés, Wei Xie, Javier Cambiasso et al.

Nanoscale localization of electromagnetic fields near metallic nanostructures underpins the fundamentals and applications of plasmonics. The unavoidable energy loss from plasmon decay, initially seen as a detriment, has now expanded the scope of plasmonic applications to exploit the generated hot carriers. However, quantitative understanding of the spatial localization of these hot carriers, akin to electromagnetic near-field maps, has been elusive. Here we spatially map hot-electron-driven reduction chemistry with 15 nanometre resolution as a function of time and electromagnetic field polarization for different plasmonic nanostructures. We combine experiments employing a six-electron photo-recycling process that modify the terminal group of a self-assembled monolayer on plasmonic silver nanoantennas, with theoretical predictions from first-principles calculations of non-equilibrium hot-carrier transport in these systems. The resulting localization of reactive regions, determined by hot carrier transport from high-field regions, paves the way for hot-carrier extraction science and nanoscale regio-selective surface chemistry.

M. Hentschinski

Physical anomalous dimensions are a formulation of the DGLAP evolution of Deep Inelastic structure functions which is independent of factorization scheme and -scale. In this proceedings we provide an outlook on possible applications, in particular in the search of saturation effects. As an original contribution we present a short study of the renormalization scale dependence of physical evolved structure functions for large initial scale $Q_0^2=30$GeV$^2$

A. I. Vasyunin, E. Herbst

The observed gas-phase molecular inventory of hot cores is believed to be significantly impacted by the products of chemistry in interstellar ices. In this study, we report the construction of a full macroscopic Monte Carlo model of both the gas-phase chemistry and the chemistry occurring in the icy mantles of interstellar grains. Our model treats icy grain mantles in a layer-by-layer manner, which incorporates laboratory data on ice desorption correctly. The ice treatment includes a distinction between a reactive ice surface and an inert bulk. The treatment also distinguishes between zeroth and first order desorption, and includes the entrapment of volatile species in more refractory ice mantles. We apply the model to the investigation of the chemistry in hot cores, in which a thick ice mantle built up during the previous cold phase of protostellar evolution undergoes surface reactions and is eventually evaporated. For the first time, the impact of a detailed multilayer approach to grain mantle formation on the warm-up chemistry is explored. The use of a multilayer ice structure has a mixed impact on the abundances of organic species formed during the warm-up phase. For example, the abundance of gaseous HCOOCH3 is lower in the multilayer model than in previous grain models that do not distinguish between layers (so-called "two phase" models). Other gaseous organic species formed in the warm-up phase are affected slightly. Finally, we find that the entrapment of volatile species in water ice can explain the two-jump behavior of H2CO previously found in observations of protostars.

Maxim Sukharev, Jiha Sung, Kenneth G. Spears et al.

We present theoretical and experimental studies of the optical response of L-shaped silver nanoparticles. The scattering spectrum exhibits several plasmon resonances that depend sensitively on the polarization of the incident electromagnetic field. The physical origin of the resonances is traced to different plasmon phenomena. In particular, a high energy band with unusual properties is interpreted in terms of volume plasmon oscillations arising from the asymmetry of a nanoparticle.

G. Wilk, Z. Wlodarczyk

We present an overview of possible imprints of non-extensitivity in particle and nucler physics. Special emphasis is put on the intrinsic fluctuations present in the system under consideration as the possible source of nonextensivity. The possible connection of nonextensivity and the self organized criticality apparently being observed in some cosmic rays and hadronic experiments will also be discussed.

V. O. Nesterenko, J. Kvasil, P. -G. Reinhard

We propose a practicable method for describing linear dynamics of different finite Fermi systems. The method is based on a general self-consistent procedure for factorization of the two-body residual interaction. It is relevant for diverse density- and current-dependent functionals and, in fact, represents the self-consistent separable random-phase approximation (RPA), hence the name SRPA. SRPA allows to avoid diagonalization of high-rank RPA matrices and thus dwarfs the calculation expense. Besides, SRPA expressions have a transparent analytical form and so the method is very convenient for the analysis and treatment of the obtained results. SRPA demonstrates high numerical accuracy. It is very general and can be applied to diverse systems. Two very different cases, the Kohn-Sham functional for atomic clusters and Skyrme functional for atomic nuclei, are considered in detail as particular examples. SRPA treats both time-even and time-odd dynamical variables and, in this connection, we discuss the origin and properties of time-odd currents and densities in initial functionals. Finally, SRPA is compared with other self-consistent approaches for the excited states, including the coupled-cluster method.

S. Martín, J. Martín-Pintado, R. Mauersberger et al.

Based on observations of the most abundant sulfur-bearing molecules (H2S, CS, NS, SO, H2CS, OCS, and SO2) carried out with the IRAM 30m telescope and SEST, we present the first analysis of the sulfur chemistry of an extragalactic source, the nuclear region of the starburst galaxy NGC 253. This is the first time that H2S and, tentatively, H2CS are detected towards the nucleus of a starburst galaxy. Source averaged fractional abundances of these molecules are a few 10^-9, except for CS and OCS which are more abundant (10^-8). Sulfur isotopic ratios, 32S/34S~8+-2 and 34S/33S>9, are measured through observations of 13CS, C34S, and C33S. A comparison with the observed relative abundances towards different prototypical Galactic sources suggests that the chemical composition of NGC 253 is similar to that found towards the molecular clouds complexes like Sgr B2 in the nuclear region of the Milky Way. The large overabundance of OCS compared to the predictions of time-dependent sulfur chemistry models supports the idea that OCS is likely injected into the gas phase from the grain mantles by low velocity shocks.