Algorithm competitions compress everything hard about applied quantum work into weeks: honest problem formulation, classical baselines, hardware limits, and reviewable results. QANTIS Nexus enters the SSB competition carrying the QANTIS research discipline into that compressed format.
From research line to competition workflow
QANTIS Nexus reuses the QANTIS discipline: formulate, baseline, run where justified, and record what the result actually shows.
Research heritage
- QANTIS decision engine: Infer, Risk, Optimise, Verify
- Public arXiv paper with hardware-validated experiments
- QUBO formulation and QAOA experience on real QPUs
- Uncertainty framing as a first-class output
Competition surface
- Optimization and modeling problems from three sectors
- Communications, finance, and banking problem pools
- Time-boxed delivery with a fixed team of 3 to 6
- Identity-verified members, locked roster
Evidence discipline
- Classical baseline before any quantum claim
- Provider and backend context recorded per run
- Resource estimates before paid hardware time
- Reviewer-safe result packets via QFlow records
A submitted application, and what this note is for
On 26 June 2026 our team, QANTIS Nexus, submitted its application to the SSB Quantum Algorithm Competition through the official application center. The team runs with four identity-verified members out of a possible six: Bayram Yüksel Eker as team lead, with Özgür Nazlı, Furkan Deligöz, and Şefik Şuayb Arslan. The public announcement lives in our newsroom; this field note is the analytical companion.
We will not discuss problem sets or solution designs here. What is worth writing about, because it generalizes to any team entering a serious algorithm competition, is the translation problem: how a research line with its own pace and standards becomes a competition team with a deadline.
What the SSB competition actually optimizes for
The SSB Quantum Algorithm Competition is organized under the leadership of the Presidency of Defence Industries, with cooperation across civil institutions, defense industry companies, universities, technoparks, and national and international quantum computing providers. Its declared goals are ecosystem goals: awareness, inter-institutional cooperation, qualified human capital, and sustainable growth of Türkiye's quantum ecosystem.
The format is concrete: teams of three to six verified members solve optimization and modeling problems drawn from banking, finance, and communications. That combination, a national-ecosystem instrument delivered as sector-specific problem solving, is what makes the competition interesting. It rewards teams that can move between abstract algorithm design and the messy constraints of a real sector.
Why communications ranks first on our application
Applicants declare a sector preference. Ours is communications first, then finance, then banking, and the order is a direct readout of where our research weight already sits.
Communications is the sector where our 2026 field notes run deepest: quantum telecom readiness across PQC and QKD boundaries, network evidence, 3GPP and O-RAN signals, and AI-native RAN automation. Telecom optimization problems, from resource allocation to network planning, map naturally onto the QUBO-style formulations our research line has already run on hardware.
Finance and banking follow, not as afterthoughts but as adjacent applications of the same toolset. The G7 central banks' 2026 reference report made quantum readiness a supervisable topic for financial-sector participants, and our quantum finance notes already treat portfolio-style optimization and model-risk evidence as one discipline. Banking shares that toolset with a heavier compliance frame.
- Communications: deepest research base, natural QUBO mappings, live standards context.
- Finance: G7-driven readiness signal, model-risk and evidence discipline already in place.
- Banking: same optimization family under stricter governance expectations.
What QANTIS actually contributes to a competition team
QANTIS is the Neura Parse quantum decision research line: a quantum-native decision platform organized as a framework, a decision engine running Infer, Risk, Optimise, and Verify stages, and applications for decision problems under uncertainty. The original paper is public on arXiv as arXiv:2603.00785, with optimization experiments validated on IBM quantum hardware.
Three habits transfer directly from that work to competition conditions. First, honest formulation: a problem is not quantum because it is fashionable, it is quantum where structure justifies it, and the formulation step decides everything downstream. Second, baseline discipline: every quantum result is reported against the best classical attempt we can produce, because a speedup claim without a baseline is marketing. Third, hardware realism: our published work is explicit about where current devices help and where noise dominates, and a time-boxed competition rewards teams that already know that boundary.
The team name is deliberate. QANTIS Nexus is the point where the research line meets a competitive, deadline-driven surface, staffed by people who have worked inside that discipline rather than assembled for the occasion.
Running a competition like an evidence program
The operational risk in any competition is improvisation under deadline: undocumented experiments, results nobody can reproduce, and a final submission that cannot explain itself. Our answer is to run the competition the way we run research, only faster.
QFlow Studio carries the record-keeping: every experiment keeps its assumptions, provider context, circuit source, baseline comparison, and outcome as a reviewable record. Resource estimates run before any paid hardware time. Decisions that shape the submission, which formulation to pursue, when to stop tuning, what to include, pass through explicit team review rather than accumulating silently in a notebook.
This is not overhead. In a format where the roster is locked and the clock is fixed, the team that can read its own last two weeks clearly has a structural advantage over the team that has to reconstruct them.
What we publish, and what stays inside the program
Everything problem-specific stays inside the competition: problem details, solution designs, intermediate results, and standings. That boundary is the same public-safe discipline we apply to defense work and to unpublished research results, where real numbers surface only through peer-reviewed publications and formal engagements.
What we can and will share are ecosystem-level observations: what the competition format teaches about applied quantum readiness, how evidence-first habits behave under time pressure, and, after the program concludes, whatever the organizers make public. If the competition produces lessons that improve QANTIS, QFlow, or our quantum services, those lessons will show up in future field notes in their public-safe form.
How competition teams lose before the deadline
The first failure mode is formulation drift. Teams fall in love with an algorithm and bend the problem to fit it, instead of letting the problem structure choose the method. The QANTIS discipline runs the opposite direction: formulation first, method second, and a willingness to conclude that the honest answer for a given sub-problem is classical.
The second failure mode is the missing baseline. Under deadline pressure, the classical comparison is the first thing teams cut, and its absence turns every quantum claim into an unsupported one. Judges in an evidence-oriented competition notice. Baselines are not overhead; they are the difference between a result and an anecdote.
The third failure mode is reconstruction debt. A team that cannot explain, two days before submission, why an earlier experiment was abandoned will lose that time reconstructing its own history. Recorded assumptions, provider context, and decision review exist precisely so the final week is spent improving the answer, not excavating it.
- Formulation drift: bending the problem to a favorite algorithm.
- Missing baselines: quantum claims with no classical comparison.
- Reconstruction debt: undocumented experiments consuming the final week.
- Hardware romanticism: paid QPU time where a simulator is the honest instrument.
- Boundary slips: publishing problem specifics that belong inside the program.
What a national competition does that funding programs cannot
A competition changes behavior faster than a grant because it compresses accountability. Teams must formulate, build, and defend a result inside weeks, against other teams, on problems they did not choose. That pressure surfaces real capability differences that proposal documents hide, and it does so publicly enough that the ecosystem learns from the spread.
The SSB format adds a second effect: sector-derived problems pull academic and industrial participants onto the same ground. A telecom optimization problem judged on evidence treats a university team and a defense-industry team identically, which is exactly the inter-institutional cooperation the program's goals describe.
For Türkiye's quantum ecosystem, the durable output is not the ranking. It is the cohort of verified teams that now have a shared reference experience: the same problems, the same constraints, the same evidence expectations. That shared reference is what future collaborations get built on.
01
Treat a competition application as a program decision: declare the sectors where your research weight already is, not where the noise is.
02
Name the team after the discipline you intend to practice; QANTIS Nexus commits us to the QANTIS evidence standard under deadline.
03
Run classical baselines first; a quantum result without one is not a result.
04
Record provider context, assumptions, and resource estimates per experiment so the final submission can explain itself.
05
Keep a hard public-safe boundary: problem specifics stay inside the program, workflow lessons become field notes.
Team checklist: entering a quantum algorithm competition seriously
Derived from how QANTIS Nexus prepared its SSB competition entry. Most items apply to any team entering a time-boxed applied quantum challenge.
- 01
Declare sector preferences from your actual research weight, not from which sector sounds most impressive.
- 02
Lock the roster early and verify every member through the official process before the deadline window tightens.
- 03
Write the classical baseline plan before designing any quantum circuit.
- 04
Decide in advance where hardware runs are justified and where simulators are the honest choice.
- 05
Record assumptions, provider context, and circuit sources per experiment from day one.
- 06
Run resource estimates before any paid hardware time.
- 07
Route submission-shaping decisions through explicit team review instead of individual notebooks.
- 08
Define the public-safe boundary in writing: what the team may say publicly while the competition runs.
- 09
Schedule a post-program retrospective that converts workflow lessons into publishable notes.
Terms used in this note.
- QUBO
- Quadratic Unconstrained Binary Optimization: a standard way of writing optimization problems as binary variables with quadratic interactions, which many quantum algorithms, including QAOA, take as input.
- QAOA
- Quantum Approximate Optimization Algorithm: a hybrid quantum-classical algorithm that runs parameterized circuits on quantum hardware while a classical loop tunes the parameters toward better solutions.
- Classical baseline
- The best solution a team can produce with conventional methods for the same problem. Quantum results are reported against it so any claimed advantage is measurable rather than assumed.
- POMDP
- Partially Observable Markov Decision Process: a framework for sequential decision-making when the true state of the world is only observed indirectly. One of the core problem classes in the QANTIS research line.
- Identity-verified team
- A competition roster in which every member has completed the organizer's identity verification, joined by invite code, and is locked to the team after submission.
- Public-safe boundary
- The written line between what a team may publish while a program runs and what stays inside it: ecosystem lessons outside, problem specifics and results inside.
Questions program teams ask.
Q01Is QANTIS Nexus the same thing as QANTIS?
No. QANTIS is the Neura Parse quantum decision research line, with a public arXiv paper and a decision engine organized around Infer, Risk, Optimise, and Verify stages. QANTIS Nexus is the competition team named after that line: it carries the same people and the same evidence discipline into the SSB Quantum Algorithm Competition, but it is a time-boxed team, not a product or a new research program.
Q02Why did the team rank communications above finance and banking?
The order follows existing research weight. Neura Parse's 2026 field notes run deepest in quantum telecom readiness, network evidence, and RAN automation, so the team's problem intuition is strongest there. Finance and banking use the same optimization toolset, supported by the G7 central banks' quantum report and the model-risk evidence discipline from our quantum finance notes.
Q03Will the team publish its competition solutions or results?
No. Problem details, solution designs, intermediate results, and standings stay inside the program while the competition runs. The public record is the announcement bulletin, this field note, and any ecosystem-level lessons published after the program concludes, in the same public-safe form Neura Parse applies to defense work and unpublished research.
Q04What does hardware validation mean for a competition entry?
It means the team has already run QUBO formulations through QAOA on real quantum processors as part of the published QANTIS work, so it knows where current devices help and where noise dominates. In a time-boxed competition that boundary knowledge prevents two expensive mistakes: spending the clock on circuits the hardware cannot support, and claiming results a classical baseline would beat.
Q05Can other teams use the same evidence-first approach without QFlow?
Yes. The discipline is tool-independent: record assumptions, provider context, and baselines per experiment, estimate resources before paid hardware time, and route submission-shaping decisions through explicit review. QFlow Studio packages that habit as reviewable workflow records, but a rigorous team can hold the same standard with disciplined notebooks and version control.
