Coarse-Graining with Equivariant Neural Networks: A Path Towards Accurate and Data-Efficient Models

Machine learning has recently entered into the mainstream of coarse-grained (CG) molecular modeling and simulation. While a variety of methods for incorporating deep learning into these models exist, many of them involve training neural networks to act directly as the CG force field. This has several benefits, the most significant of which is accuracy. Neural networks can inherently incorporate multi-body effects during the calculation of CG forces, and a well-trained neural network force field outperforms pairwise basis sets generated from essentially any methodology. However, this comes at a significant cost. First, these models are typically slower than pairwise force fields even when accounting for specialized hardware which accelerates the training and integration of such networks. The second, and the focus of this paper, is the need for the considerable amount of data needed to train such force fields. It is common to use tens of microseconds of molecular dynamics data to train a single CG model, which approaches the point of eliminating the CG models usefulness in the first place. As we investigate in this work, it is apparent that this data-hunger trap from neural networks for predicting molecular energies and forces is caused in large part by the difficulty in learning force equivariance, i.e., the fact that force vectors should rotate while maintaining their magnitude in response to an equivalent rotation of the system. We demonstrate that for CG water, networks that inherently incorporate this equivariance into their embedding can produce functional models using datasets as small as a single frame of reference data, which networks without inherent symmetry equivariance cannot

Reducing the Read Noise of the James Webb Space Telescope Near Infrared Spectrograph Detector Subsystem

We describe a Wiener optimal approach to using the reference output and reference pixels that are built into Teledyne's HAWAII-2RG detector arrays. In this way, we are reducing the total noise per approximately 1000 second 88 frame up-the-ramp dark integration from about 6.5 e- rms to roughly 5 e- rms. Using a principal components analysis formalism, we achieved these noise improvements without altering the hardware in any way. In addition to being lower, the noise is also cleaner with much less visible correlation. For example, the faint horizontal banding that is often seen in HAWAII-2RG images is almost completely removed. Preliminary testing suggests that the relative gains are even higher when using non flight grade components. We believe that these techniques are applicable to most HAWAII-2RG based instruments

The Gas Transfer through Polar Sea Ice Experiment: Insights into the Rates and Pathways that Determine Geochemical Fluxes

Sea ice is a defining feature of the polar marine environment. It is a critical domain for marine biota and it regulates ocean-atmosphere exchange, including the exchange of greenhouse gases such as CO2 and CH4. In this study, we determined the rates and pathways that govern gas transport through a mixed sea ice cover. N2O, SF6, 3He, 4He, and Ne were used as gas tracers of the exchange processes that take place at the ice-water and air-water interfaces in a laboratory sea ice experiment. Observation of the changes in gas concentrations during freezing revealed that He is indeed more soluble in ice than in water; Ne is less soluble in ice, and the larger gases (N2O and SF6) are mostly excluded during the freezing process. Model estimates of gas diffusion through ice were calibrated using measurements of bulk gas content in ice cores, yielding gas transfer velocity through ice (kice) of ∼5 × 10−4 m d−1. In comparison, the effective air-sea gas transfer velocities (keff) ranged up to 0.33 m d−1 providing further evidence that very little mixed-layer ventilation takes place via gas diffusion through columnar sea ice. However, this ventilation is distinct from air-ice gas fluxes driven by sea ice biogeochemistry. The magnitude of keff showed a clear increasing trend with wind speed and current velocity beneath the ice, as well as the combination of the two. This result indicates that gas transfer cannot be uniquely predicted by wind speed alone in the presence of sea ice

Unusual magnetic-field dependence of partially frustrated triangular ordering in manganese tricyanomethanide

Manganese tricyanomethanide, Mn[C(CN)3]2, consists of two interpenetrating three-dimensional rutile-like networks. In each network, the tridentate C(CN)3- anion gives rise to superexchange interactions between the Mn2+ ions (S=5/2) that can be mapped onto the "row model" for partially frustrated triangular magnets. We present heat capacity measurements that reveal a phase transition at T_N = 1.18K, indicative of magnetic ordering. The zero-field magnetically ordered structure was solved from neutron powder diffraction data taken between 0.04 and 1.2 K. It consists of an incommensurate spiral with a temperature independent propagation vector Q=(2Q 0 0)=(+/-0.622 0 0), where different signs relate to the two different networks. This corresponds to (+/-0.311 +/-0.311 0) in a quasi-hexagonal representation. The ordered moment mu=3.3mu_B is about 2/3 of the full Mn2+ moment. From the values of T_N and Q, the exchange parameters J/k = 0.15 K and J'/J = 0.749 are estimated. The magnetic-field dependence of the intensity of the Bragg reflection, measured for external fields H||Q, indicates the presence of three different magnetic phases. We associate them with the incommensurate spiral (H < 13.5 kOe), an intermediate phase (13.5 kOe 16 kOe) proposed for related compounds. For increasing fields, Q continuously approaches the value 1/3, corresponding to the commensurate magnetic structure of the fully frustrated triangular lattice. This value is reached at H_c = 19 kOe. At this point, the field-dependence reverses and Q adopts a value of 0.327 at 26 kOe, the highest field applied in the experiment. Except for H_c, the magnetic ordering is incommensurate in all three magnetic phases of Mn[C(CN)3]2.Comment: accepted for publication in J. Phys.: Condens. Matte

Measurements and analysis of the upper critical field Hc2H_{c2} on an underdoped and overdoped La2−xSrxCuO4La_{2-x}Sr_xCuO_4 compounds

The upper critical field $H_{c2}$ is one of the many non conventional properties of high-$T_c$ cuprates. It is possible that the $H_{c2}(T)$ anomalies are due to the presence of inhomogeneities in the local charge carrier density $\rho$ of the $CuO_2$ planes. In order to study this point, we have prepared good quality samples of polycrystalline $La_{2-x}Sr_xCuO_{4}$ using the wet-chemical method, which has demonstrated to produce samples with a better cation distribution. In particular, we have studied the temperature dependence of the second critical field, $H_{c2}(T)$, through the magnetization measurements on two samples with opposite average carrier concentration ($\rho_m=x$) and nearly the same critical temperature, namely $\rho_m = 0.08$ (underdoped) and $\rho_m = 0.25$ (overdoped). The results close to $T_c$ do not follow the usual Ginzburg-Landau theory and are interpreted by a theory which takes into account the influence of the inhomogeneities.Comment: Published versio

Protein Pattern Formation

Protein pattern formation is essential for the spatial organization of many intracellular processes like cell division, flagellum positioning, and chemotaxis. A prominent example of intracellular patterns are the oscillatory pole-to-pole oscillations of Min proteins in \textit{E. coli} whose biological function is to ensure precise cell division. Cell polarization, a prerequisite for processes such as stem cell differentiation and cell polarity in yeast, is also mediated by a diffusion-reaction process. More generally, these functional modules of cells serve as model systems for self-organization, one of the core principles of life. Under which conditions spatio-temporal patterns emerge, and how these patterns are regulated by biochemical and geometrical factors are major aspects of current research. Here we review recent theoretical and experimental advances in the field of intracellular pattern formation, focusing on general design principles and fundamental physical mechanisms.Comment: 17 pages, 14 figures, review articl

Reducing the Read Noise of HAWAII-2RG Detector Systems with Improved Reference Sampling and Subtraction (IRS2)

IRS2 is a Wiener-optimal approach to using all of the reference information that Teledyne's HAWAII-2RG detector arrays provide. Using a new readout pattern, IRS2 regularly interleaves reference pixels with the normal pixels during readout. This differs from conventional clocking, in which the reference pixels are read out infrequently, and only in a few rows and columns around the outside edges of the detector array. During calibration, the data are processed in Fourier space, which is <;:lose to the noise's eigenspace. Using IRS2, we have reduced the read noise of the James Webb Space Telescope Near Infrared Spectrograph by 15% compared to conventional readout. We are attempting to achieve further gains by calibrating out recently recognized non-stationary noise that appears at the frame rate