TetraBox: Advanced Simulation
TetraBox is Terra Quantum's cutting-edge simulation toolset that harnesses the power of tensor networks, through tensor trains and quantum-inspired algorithms, to solve complex computational problems with unprecedented efficiency. From quantum chemistry to financial modeling, TetraBox provides the computational power needed to navigate today's most challenging fields.
TetraBox enables you to:
Harness advanced simulation tools to accelerate discovery, optimize performance, and gain deeper insights into complex systems—faster and with greater accuracy.
Model intricate physical and financial systems accurately
Explore a vast array of scenarios and parameters quickly
Accelerate research and development across industries
Make data-driven decisions based on precise simulations
Why TetraBox?
TetraBox is built for high-performance simulation—offering speed, precision, and adaptability across classical and quantum environments.
Superior Performance
Simulate systems with exponentially faster runtimes compared to traditional methods
Better Problem Solving
Tackle simulations with coupled variables, revealing intricate correlations in datasets.
Scalability
Physics-driven methods on classical hardware, adapting smoothly to quantum hardware.
Versatility
Address diverse simulation challenges, from molecular dynamics to financial modeling and beyond.
In the TetraBox Toolset
Explore a modular suite of quantum-inspired tools designed to tackle complex simulations, multi-objective problems, and high-dimensional PDEs—all optimized for performance, scalability, and ease of use.
- Tensor train-based optimizer for complex, high-dimensional problem-solving
- Efficiently handles cases with limited function evaluations available
- Achieves lower cost function values faster than other existing algorithms
- Designed to be highly parallelizable and user-friendly, making it easy to use for a wide range of applications
- Maximizes hypervolume in solution-space with minimal function evaluations
- Handles non-linear constraints and provides well-distributed Pareto front solutions
- Parallelizable for efficient evaluation of multiple solution candidates
- Leverages TetraOpt for optimizing the acquisition function
- Solver specialized for partial differential equations with tensor train methods
- Efficiently handles high-dimensional PDEs in physics and engineering fields
- Uses adaptive time-stepping and multi-grid techniques for better convergence
- Supports solving both linear and non-linear PDE systems effectively
Tensor Networks & Quantum-Ready Foundations
TetraBox combines efficient tensor methods with hybrid quantum tools to power fast, scalable simulations and enable quantum transition.
Essential Tensor Network Functionality
- Core tensor train operations for efficient data representation and manipulation
- Advanced tensor contraction algorithms for high-performance computations
- Cross-approximation techniques for compact representation of high-dimensional data
- Tensor rounding and truncation methods for managing computational complexity
Tensor Quantum Programming
- Framework for mapping tensor network algorithms to quantum circuits
- Hybrid classical-quantum approach for maximizing computational efficiency
- Quantum-inspired preprocessing to enhance quantum algorithm performance
- Seamless integration pathway from classical tensor methods to quantum hardware
Key Features
Our core solutions leverage two powerful building blocks:
Cutting-edge Tensor Network Algorithms
Advanced tensor methods for efficient, scalable processing of high-dimensional data.
- Proprietary tensor train methods for efficient high-dimensional data processing
- Advanced cross-approximation for rapid tensor construction from sparse data
- Optimized contraction algorithms for high-performance computing
- Continuous updates based on latest R&D breakthroughs
Flexible Problem Formulation
Adaptable to complex models, enabling seamless integration of custom physics and constraints.
- Support for diverse physical and mathematical models
- Easy integration of custom equations and boundary conditions
- Adaptive discretization for optimal accuracy-performance balance
- Handling of multi-scale and multi-physics simulations
Scalable Performance
Designed for parallel, GPU-accelerated scaling with quantum-ready efficiency.
- Efficient parallelization and GPU acceleration
- Automatic load balancing for optimal resource use
- Quantum-ready algorithms for future hardware integration
- Polynomial scaling with problem size for many applicatio
Hardware-Efficient Implementation
Optimized for classical systems today and future quantum platforms tomorrow.
- Designed for execution today on classical hardware and on quantum hardware, as it matures
- Optimized for current high-performance computing infrastructures
- Tensor Quantum Programming for seamless classical-quantum transition
- Leverage of tensor network structures for efficient quantum circuit implementation
How TetraBox Works
TetraBox leverages the power of tensor networks, particularly the tensor train format, to efficiently represent and manipulate high-dimensional data and operators.
Tensor Train Decomposition
- Represents high-dimensional tensors as a series of lower-dimensional core tensors
- Enables compact storage and efficient manipulation of complex data structures
- Reduces computational complexity from exponential to polynomial in many cases
Physics-driven Tensor Train Algorithms
- Utilizes techniques inspired by quantum computing to enhance classical simulations
- Employs probabilistic sampling methods to estimate high-dimensional integrals
- Implements variational approaches for solving eigenvalue problems
Benefits of TetraBox versus Classical Simulation Approaches
TetraBox delivers faster, more accurate, and scalable simulations than classical methods—built for today and ready for quantum.
- Overcome the curse of dimensionality in high-dimensional problems
- Achieve exponential speedup in many simulation scenarios
- Handle larger system sizes and longer time scales than classical methods
- Capture intricate correlations and interactions in multi-component systems
- Maintain high precision even for long-time dynamics simulations
- Provide reliable results in regimes where classical methods break down
- Efficiently represent systems with widely varying spatial or temporal scales
- Seamlessly integrate microscopic and macroscopic models
- Capture emergent behaviors in complex systems
- Automatically identify and exploit low-rank structures in data and operators
- Dynamically adjust tensor ranks for optimal accuracy-to-performance trade-off
- Seamlessly switch between different tensor network formats as needed
- Benefit from physics-driven speedups today on classical hardware
- Easily transition to quantum hardware as it becomes available
- Future-proof your simulation workflows with quantum-compatible algorithms
Example Problem Types and Applications
TetraBox excels in solving complex, high-dimensional simulation problems across various domains. Here are examples of key problem types:
- Speed up molecular design by up to 50x, accelerating drug and material design
- Efficient modeling of complex molecular structures and electronic properties
- Accurate calculation of quantum many-body systems for advanced material science
- High-fidelity simulations of complex fluid flows
- Efficient handling of turbulence and multi-phase systems
- Accelerated design optimization for aerospace andautomotive applications
- Fast and accurate pricing of complex financial instruments
- Efficient Monte Carlo simulations for risk assessment
- High-dimensional portfolio optimization
- Solving multi-dimensional PDEs in physics and engineering
- Efficient handling of coupled systems of equations
- Accurate long-time simulations for complex dynamical systems
TetraBox Options Pricing
Challenge
Cirdan Capital, a London-based investment bank, needed to optimize the pricing of exotic options, such as multi-asset autocallable options. Traditional Monte Carlo methods were computationally expensive and time-consuming, limiting their ability to assess risks and identify market imbalances quickly.
Solution
- Efficiently handle high-dimensional financial models
- Leverage tensor train decomposition for compact representation of complex financial data
- Accelerate Monte Carlo-like simulations using quantum-inspired techniques
Results
- 75% improvement in pricing speed for exotic options and related Greeks
- 75% reduction in computing power required for pricing calculations
- Potential savings of millions in compute costs annually for large trading banks
- Ability for traders and risk managers to understand risk positions faster
Impact
The TetraBox-powered solution significantly enhanced Cirdan Capital's capabilities to:
- Respond more quickly to volatile market conditions
- Assess risks more frequently by valuing their books more often during the day
- Identify intra-day market imbalances more effectively
- Reduce operational costs through more efficient use of computational resources
Dive Deeper with Our Research Publications
Explore breakthroughs in quantum-powered machine learning.
Pushing the Limits of Quantum Simulation
The team at Terra Quantum develops innovative tensor network solutions—enhancing performance in industries like chemistry, finance, and logistics while preparing for future quantum hardware.
Dr. Michael Perelshtein
At Terra Quantum, we're challenging the existing illusion of complexity that simulating nature must always be exponentially hard. Our tensor networks framework, utilizing tensor trains, tackles intricate numerical challenges in chemistry, finance, and logistics through innovative approaches to function approximation, data compression, black-box optimization, and linear equation solving. It's rewarding to see our clients integrate our physics-driven solutions, which do not immediately require quantum hardware, already gaining significant performance improvements today while preparing for the mature QPUs to come.
Accessing TetraBox
Work with Our Experts for Custom Development Services
- Collaborate with our simulation specialists to address your specific challenges
- Benefit from tailored solutions that integrate seamlessly with your existing processes
- Receive ongoing support and optimization as your simulation needs evolve
Access TetraOpt in TQ42
- Access our blackbox optimiser in TQ42, via CLI or Python SDK
- Benefit from the scalability and security of our cloud-based platform
Take the Tensor Networks course in TQ Academy
- Access a specialized platform for hands-on experience with Tensor Networks capabilities
- Participate in guided tutorials and workshops led by our simulation experts
- Explore real-world use cases and benchmark your problems against TetraBox performance
Ready to Transform Your Simulation Capabilities?
