Introducing Orquestra^TM

Work at the right level- tools to create workflows but get close to the hardware when you need.

Compose workflows in the YAML-compatible Zapata Quantum Workflow Language (ZQWL).  Arrange component tasks and algorithms, and tune parameters across workflows and quantum devices. Organize and share workflows by the project.

Leverage Orquestra’s open-source and proprietary quantum libraries. Wrappers exist for open-source algorithms (e.g., from Qiskit, Cirq, and Forest). ​Industry and use case-specific Orquestra Pro Packs are available, which include Zapata’s proprietary algorithms, optimized implementations of public algorithms, and specialized data post-processing.

Deploy, Scale, parallelize — get the resources you need.

Submit your workflows to the Orquestra Quantum Engine (OQE) servers via REST API. Run-on quantum and classical devices including quantum gate model computers, quantum annealers, and quantum-inspired classical devices.

Data management that gets you answers fast.

The Orquestra Data Correlation Service (ODCS) organizes intermediate and final workflow data in a secured Mongo Database. Export data for analysis in Excel, a Jupyter notebook, or Tableau. Advanced quantum analytics tools and custom post-processors available.

Optimization

• Sampling from risk-neutral probability measure for asset pricing
• Portfolio optimization by quantum annealing or gate-model quantum heuristics
• Improved asset allocation by quantum-inspired optimization

Simulation & Modeling

• Quantum-assisted Monte Carlo for derivative pricing, credit valuation adjustment
• Imaginary-time propagation for multi-asset BlackScholes equation
• Accelerated sampling from stochastic processes for risk analysis

Modeling Machine Learning

• Improved graph clustering analysis for anomaly and fraud detection
• Time series analysis of financial data using quantum Boltzmann machines
• Dimensionality reduction for financial data using quantum-classical hybrid optimization

Optimization

• Optimal healthcare resource allocation e.g. patient treatment matching and priority scheduling of doctors and therapies
• Molecular structure analysis by combinatorial optimization
• Protein design using unconstrained discrete optimization

Simulation & Modeling

• QM/MM method for molecular binding affinity prediction in drug discovery
• Ab initio transition state analysis for catalytic reaction simulation
• Ab initio determination of the crystalline structure of organic molecules

Modeling Machine Learning

• Quantitative structure-activity relationship (QSAR) using quantum-enhanced supervised learning
• Molecular screening in drug discovery using continuous latent space
• Natural language processing for automated lite

Optimization

• Generating efficient transportation routes for vehicle fleets with improved qubit cost
• Improving timing in job scheduling
• Disruption management by optimized traffic re-routing

Machine Learning

• Irregular operation (IROP) prediction using quantum-enhanced supervised learning

Optimization

• Prediction of alloy ground state orderings from cluster expansions

Simulation & Modeling

• Determining thermodynamics of alloys by applying quantum amplitude amplification to cluster expansion models
• Ab initio simulations to accelerate materials discovery(e.g., Li-ion electrolytes/electrodes, photovoltaics, catalysts, alloys)

Optimization

• Finite time-window scheduling in energy allocation for smart grids

Simulation & Modeling

• Turbulent mixing simulation in predictive environmental modeling for climate change
• Quantum accelerated stochastic simulation of Reynolds-Averaged Navier-Stokes (RANS) systems

Optimization

• Identifying failure modes through fault tree analysis as combinatorial optimization

Simulation & Modeling

• Variational methods for general linear PDEs arising in engineering design
• Heat transfer related PDE-constrained optimization for engine design
• Wave equation simulation using variational linear systems solver

Optimization

• Process optimization in chemical reaction networks for maximizing yield

Simulation & Modeling

• Homogeneous and heterogeneous catalysis modeling using electronic structure calculations
• Singlet-triplet transition energy prediction for OLED molecules
• Quantum-enhanced force-field methods for chemical dynamics simulation

Optimization

• Display advertising optimization for maximizing clickthrough rate (CTR)

Machine Learning

• Hybrid quantum-classical generative modeling for content creation

Optimization

• Hash collision for proof-of-work cryptocurrency mining

Simulation & Modeling

• Certified randomness from quantum supremacy for proof-of-stake blockchains

Machine Learning

• Predictive maintenance using variational quantum classifier
• Anomaly detection by time series analysis using quantum Boltzmann machine
• Image and audio generation and classification using quantum-enhanced supervised learning