Postquant Labs has launched the Quip Virtual Machine and its first quantum smart contracts, creating a shared programming and execution environment for quantum and classical computing across multiple hardware platforms. The QVM is live on the Aglais testnet and is designed to reduce the portability and pricing fragmentation developers face when moving between quantum systems.
Researchers at Monash University, the University of Notre Dame, and Purdue University are evaluating the QVM, while SiC Systems is exploring its use for complex industrial optimization problems, including AI-driven manufacturing and the design, control, and operation of chemical and biological processes.
In a live demonstration at Quantum.Tech, the QVM ran 1,930 head-to-head portfolio optimization races between quantum and classical solvers using problems created by roughly 100 visitors. Results within 0.5% were treated as ties. Postquant said the quantum solver matched or beat the classical solver in every race, and when results differed by more than 0.5%, the quantum solver produced the better portfolio by a median of 2.56%. Both systems typically returned answers in 0.1 to 0.3 seconds.
The QVM uses a unified instruction set and a gas-based pricing model. Costs are based on qubit space, execution time, and entanglement, with the maximum possible cost quoted before execution. Programs can span annealers, gate-based quantum systems, and classical hardware, with classical systems used to benchmark and validate outputs.
Postquant said every computation passes through a three-tier verification system that includes classical simulation checks, independent benchmarking, and cryptographic attestations. New testnet users receive free compute credits, while mainnet computation is expected to use network tokens. QuipSwap is launching alongside the QVM as the ecosystem’s quantum-resistant settlement layer.
KEY QUOTES:
“We created the QVM because quantum computing is still fractured between competing instruction sets and assemblers, providing few easy onramps to outsiders. Our virtual machine has three major goals: to unify and clarify pricing of quantum operations and memory across architectures, to distribute hybrid computation across available machines on our network, and to provide an easier abstraction for new quantum programmers that doesn’t require them to think directly in quantum gates or qubit layouts. This initial release brings together annealers, gate-based systems, and classical computers under one constraint-based programming language, and marks our first steps toward a unified representation for all of computing.”
Colton Dillon, CEO And Co-Founder Of Postquant Labs
“At SiC Systems, we face a variety of combinatorial optimization problems, and time is of the essence. We want to explore as many solutions as possible in as short a time as possible. This is particularly important in our physics-informed agent architecture to design, control and operate complex chemical and biological manufacturing processes. Quip Network’s QVM can help us meet that requirement and better serve our customers.”
Dr. Soheil Mansouri, Co-Founder And Chief Science Officer At SiC Systems
“Oftentimes, when we put a student on a project, it takes them the whole semester just to learn how to program using the latest quantum paradigms. As we evaluate Quip’s virtual machine, we believe it can speed up student training and give them more time to do real research instead of spending cycles learning a specific programming language or how to program quantum circuits.”
Dr. Terrence Mak, Professor In The Department Of Data Science & AI At Monash University
“Working with Quip’s QVM can help researchers and students spend less time learning specific quantum programming tools and more time applying quantum methods to practical research problems, including our work on the Lagrangian operator.”
Shravan Kumar Sharma, PhD Candidate At The University Of Notre Dame
“Using a pay-as-you-go “gas-based” cost model is the missing piece that demonstrates quantum computing is commercially viable and practical. When you can predict exactly what a computation will cost before you run it, quantum tests that began as a research experiment become a real tool for engineering because you can quantify exactly how much value it can bring to your products. This is the shift we will be delivering.”
Dr. Richard Carback, Chief Technology Officer And Co-Founder Of Postquant Labs
