Algorithms R&D

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PARFAITE

PARFAITE

Full spectrum 3D forward simulations and inverse methods

Designed for full spectrum three-dimensional forward simulations and inversion, particularly Extremely Low Frequency (ELF) & Very Low Frequency (VLF) electromagnetic (EM) waves, PARFAITE’s improved performance provides superresolution images quickly.

 

PARFAITE is based on new patented algorithm advances to perform this forward simulation and inversion in linear time, making problems that would otherwise be intractable, feasible in low-power, low-footprint form factors. PARFAITE can provide quantitative resolution estimates that are measurably better than current state-of-the-art.

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Core Capabilities

Complex Structures

PARFAITE’s unique framework is highly versatile and can treat a broad array of complex three-dimensional structures, including earth, water, and buildings.

Improved Resolution

PARFAITE’s imaging and localization techniques achieve resolution levels significantly beyond any existing low-frequency techniques.

3D Low-Frequency Imaging

PARFAITE provides full spectrum forward simulations and inversion needed to image, localize and interpret scattering at low frequencies. Coupled with new approaches for transmitting and receiving low frequency signals, PARFAITE opens up decisive new capabilities in defense and science.

High-Performance

PARFAITE relies on state-of-the-art algorithms and software implementation. Large-scale problems can be solved in minutes on a small workstation without the need for expensive resources.

The Latest

LLVM Virtual Developers’ Meeting Oct 6-8, 2020

The LLVM Developers’ Meeting gathers developers and users of LLVM, Clang, and related subprojects to learn the latest in novel compiler & toolchain technology through technical talks, BoFs, posters, networking and more.    Reservoir Labs is proud to sponsor this

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Recent Publications

On the Bottleneck Structure of Congestion-Controlled Networks

In this paper, we introduce the Theory of Bottleneck Ordering, a mathematical framework that reveals the bottleneck structure of data networks. This theoretical framework provides insights into the inherent topological properties of a network at least in three areas: (1) It identifies the regions of influence of each bottleneck; (2)

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Low-Frequency Electromagnetic Imaging Using Sensitivity Functions and Beamforming

We present a computational technique for low-frequency electromagnetic imaging in inhomogeneous media that provides superior three-dimensional resolution over existing techniques. The method is enabled through large-scale, fast (low-complexity) algorithms that we introduce for simulating electromagnetic wave propagation. We numerically study the performance of the technique on various problems including the

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