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What is QuEST?

The Quantum exact simulation toolkit is an effective simulator designed for quantum circuits, state-vectors, and density matrices. QuEST utilizes advanced technologies such as multithreading, GPU acceleration, and distributed computing to perform tasks quickly across a wide range of devices, from personal laptops to sophisticated networked supercomputers. It is user-friendly and operates without the need for installation, allowing for straightforward compilation and immediate use. Users can easily download, compile, and initiate QuEST within seconds, as it requires no complex setup. Furthermore, it does not rely on any external dependencies, making it compatible with various operating systems such as Windows, Linux, and MacOS. Whether operating on a laptop, desktop, supercomputer, or even a cloud-based microcontroller, launching QuEST usually involves just a few terminal commands, enhancing its accessibility. This streamlined approach makes QuEST an appealing option for researchers and developers interested in exploring the field of quantum simulations. The combination of its performance capabilities and ease of use contributes to its growing popularity in the quantum computing community.

What is Neuri?

We are engaged in cutting-edge research focused on artificial intelligence to gain significant advantages in the realm of financial investments, utilizing innovative neuro-prediction techniques to illuminate market dynamics. Our methodology incorporates sophisticated deep reinforcement learning algorithms and graph-based learning methodologies, along with artificial neural networks, to adeptly model and predict time series data. At Neuri, we prioritize the creation of synthetic datasets that authentically represent global financial markets, which we then analyze through complex simulations of trading behaviors. We hold a positive outlook on the potential of quantum optimization to elevate our simulations beyond what classical supercomputing can achieve, further enhancing our research capabilities. Recognizing the ever-changing nature of financial markets, we design AI algorithms that are capable of real-time adaptation and learning, enabling us to uncover intricate relationships between numerous financial assets, classes, and markets. The convergence of neuroscience-inspired models, quantum algorithms, and machine learning in systematic trading is still largely unexplored, presenting an exciting frontier for future research and innovation. By challenging the limits of existing methodologies, we aspire to transform the formulation and execution of trading strategies in this dynamic environment, paving the way for unprecedented advancements in the field. As we continue to explore these avenues, we remain committed to advancing the intersection of technology and finance.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

QuEST

Company Website

quest.qtechtheory.org

Company Facts

Organization Name

Neuri

Date Founded

2018

Company Location

Singapore

Company Website

www.neuri.ai/

Categories and Features

Categories and Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

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