Purpose-built software for fault-tolerant quantum computing

Fault-tolerant quantum computing (FTQC) requires software that can operate on an unprecedented scale. PsiQuantum’s software was built to meet this challenge: tools that empower researchers, developers, and enterprises to design useful FTQC algorithms, develop their circuits, estimate their resources, and prepare for the arrival of the first generation of fault-tolerant hardware.

These tools have transformed PsiQuantum’s own algorithmic R&D, reducing workflows from months to days, and are now being made available to the broader community through our open access offerings under our software platform Construct.

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PsiQuantum Construct

PsiQuantum’s FTQC software is tailored for how quantum developers actually work. Whether you’re illustrating circuits for a publication, building a full-scale algorithm in Python, or estimating whether your method will run on a FTQC machine, our tools are designed to work together to guide you through each stage of development. PsiQuantum Construct brings these components together in a fully integrated toolkit in an open-access model to enable broad research community engagement.

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Tools to visualize, share, and communicate algorithmic ideas

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Libraries and environments to write, simulate, and optimize FTQC algorithms

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Tools to estimate and understand algorithmic resources at FTQC scales

Open source & open access tools

We believe open tools, transparent workflows, and shared libraries are essential to accelerating scientific progress. By making complex ideas easier to express, test, and reproduce, we can foster greater collaboration and unlock faster innovation.

By making Construct publicly available, we aim to strengthen the community’s collective capability and help move quantum computing forward.

Explore tools

Core capabilities & features

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Workbench

The backbone of the PsiQuantum Development Kit, Workbench is our Python library for defining numeric and symbolic fault-tolerant quantum algorithms and simulating their results. Efficiently simulate thousands of operations and create code for circuits with billions of operations.

Algorithms

Algorithms is the most robust library of modular, optimized fault-tolerant quantum algorithmic sub-routines (called Qubricks). Each Qubrick is designed to be combined, extended, or customized to support applications in chemistry, materials science, and fluid dynamics.

Circuit Designer

Circuit Designer is a visual editor for constructing and sharing interactive, hierarchical quantum circuits. Define quantum registers, compose them into routines, and assemble routines into complete algorithms without writing code. Embed interactive circuit figures into your research papers to better communicate complex algorithms.

Resource Analyzer

Resource Analyzer is a visual tool for uncovering resource bottlenecks in fault-tolerant algorithms, allowing designers to optimize algorithms for specific hardware capabilities. Through interactive visualizations, quantum developers understand how their quantum algorithms consume resources, leading to more efficient algorithms.

Learning

Construct delivers documentation and training to help researchers apply the latest research breakthroughs to fault-tolerant quantum computing (FTQC) algorithmic development. Built specifically for fault-tolerant quantum computing, Workbench makes it natural to learn FTQC.

Use cases in action

Construct is designed to support the diverse needs of quantum algorithm developers, ranging from quantum information scientists who prefer to work visually and mathematically, to quantum programmers who prefer to work directly in Python code.

Here’s how a team of quantum developers is using Construct today:

A quantum algorithm developer is interested in identifying and optimizing FTQC algorithms for a critical chemistry problem for her organization. Using Construct's collection of pre-defined Qubricks, she identifies several "state of the art" algorithmic approaches. Using Circuit Designer, she visually reviews the algorithms and makes several tweaks that she believes may improve the algorithms for her specific chemistry problem.

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Another quantum developer on her team uses her Circuit Designer algorithms to implement and validate her algorithms using Workbench. He then generates several hundred quantum resource estimates for their chemistry problems, identifying several algorithms that show potential for near-term quantum hardware.

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Using Construct’s Resource Analyzer, another teammate drills into the most promising algorithms to identify resource hotspots that could be further optimized, allowing him to improve the precision of the chemistry calculation without significantly increasing the resource costs.

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