QSphera is developing quantum-powered optimization solutions for complex, interdependent systems that classical computing struggles with. Using a hybrid quantum–classical architecture and proprietary methods, QSphera aims to overcome today’s hardware limits to deliver fast, accurate, and constraint-aware decisions across various industries.
Optimization Queries
QSphera supports a wide range of optimization queries, whether you’re searching for a minimum, maximum, best fit, or the optimal action under constraints. Below are the main query types supported by our quantum optimization engine.
Minimization Queries
1
Used to find the smallest value of a function (e.g., minimum cost, minimum energy, minimum risk).
Quantum optimization excels at locating the global minimum even in highly complex landscapes with multiple local minima.
Maximization Queries
2
Used to find the largest value of a function (e.g., maximum yield, maximum throughput, maximum efficiency).
When the search space is large or interdependent, quantum algorithms evaluate many possible maxima simultaneously.
Best-Fit / Closest-Value Queries
3
The system finds the value closest to a target or constraint (e.g., match a measurement, find the closest safe threshold, align with regulations).
Q-DIG in particular is designed to identify the most coherent and consistent value when data is missing or distorted.
Used when the system must find a solution within specific boundaries, such as limited resources, legal limits, or environmental parameters.
Quantum optimization naturally handles multiple overlapping constraints without collapsing into suboptimal solutions.
Constraint-Based Queries
4
Used when several goals must be optimized at the same time (e.g., maximize yield, minimize cost, and reduce risk).
Quantum circuits evaluate the trade-offs, producing balanced and globally consistent outcomes.
Multi-Objective Queries
5
Used when the system must pick the best combination among many options (e.g., best action sequence, best zone allocation, best path).
This is where the quantum systems’ performance is most significant, utilizing the ability to explore an exponential solution space simultaneously to identify higher-quality approximations than classical heuristics.
Discrete / Combinatorial Queries
6
The system can check feasibility across exponentially vast solution spaces, identifying whether a valid state exists within a highly constrained environment (e.g., confirming compliance against multiple, interacting regulations).
Threshold / Feasibility Queries
7
Prediction-linked Optimization
8
Utilizing a Hybrid Quantum-Classical architecture, QSphera integrates predictive insights with accelerated quantum optimization, ensuring the system not only anticipates future conditions but instantaneously selects the optimal strategic response.