Hardware

Hardware and software ecosystem

Potomac intends to be a customer and application partner for quantum computing companies. We are interested in paid compute access, hardware integration, and joint experiments that connect cryptanalytic software to the capabilities of real systems. This interest is stated as procurement intent; no purchase commitment or existing contract is implied.

Division of work

Who builds what

Hardware companies develop devices and their native capabilities. Potomac develops cryptanalytic algorithms, AI research systems, and the software that integrates an application across the layers required to execute it. Specialized compiler, error-correction, simulation, and control tools may come from other providers where they are appropriate.

This separation is a strategic thesis, not a claim that software can ignore hardware. Execution remains dependent on architecture, native operations, connectivity, error characteristics, and provider interfaces. An application that runs well on one system may need substantial work to run on another, and the company does not promise universal compatibility.

Quantum computing companies
Devices, native gate sets, connectivity, error characteristics, control systems, and the access interfaces through which workloads run.
Potomac
Cryptanalytic algorithms and arithmetic kernels, AI research systems, compilation and scheduling for the target, resource estimation, and the integration software that connects them.
Specialist software providers
Compilers, error-correction and decoding tools, simulators, and control software, integrated where they are stronger than an internal implementation.

Integration

Experiments feed back into software design

Every run on a real system teaches something the software did not know: an operation that costs more than modelled, a connectivity constraint that changes the schedule, an error characteristic that decides which kernel to try next. Potomac designs its software to absorb that feedback, so that each experiment improves the compilation, estimation, and algorithm choices behind the next one.

Proposed collaboration model

  1. DefineAgree on a kernel, operand size, and success criterion.
  2. CompileMap the kernel to the platform’s operations and architecture.
  3. RunExecute under agreed access and operating conditions.
  4. MeasureRecord correctness, reliability, resources, and runtime.
  5. ReportIdentify the limiting layer and propose the next experiment.
Each report defines the next experiment.
Potomac brings
Workloads, optimization software, and reproducible analysis.
Providers bring
Device access, platform expertise, and agreed technical interfaces.
Output
A tested workload, an identified bottleneck, and a better next experiment.

Collaboration paths

Ways to work with Potomac

Paid compute evaluation
Purchased access to run selected arithmetic kernels and report reliability, resources, and runtime under the measurement framework.
Scoped hardware experiments
Jointly defined experiments with agreed success criteria, access conditions, and a shared report of the limiting layer.
Compiler and error-correction integration
Connecting specialist compilation, decoding, or simulation tools to Potomac’s workloads and resource accounting.
Shared measurement studies
Comparable Maximum Reliable Kernel reports across platforms, published with declared assumptions and evidence status.

Contact

Hardware and specialist software companies can reach Ivan Miskovic directly.

Discuss compute access or a joint experiment

miskovic@potomac.net

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