arXiv subjects

Baris Basaran

Publications and source records attributed to Baris Basaran.

15 recordsLinked to original sources

arXiv2026

Radial Interaction Tomography: Recognizing Non-Transitive Evolutionary Games from One Range-Expansion Image

Colored sectors in a microbial range expansion encode more than lineage survival counts. We formulate a computer-vision inverse problem: from one endpoint image of an accretive multi-type expansion, recover the radius-indexed pairwise boundary-flow field and test whether the visual pattern is compatible with a transitive scalar fitness hierarchy. The observable is a geometric signal extracted from sector-boundary curves in log-polar coordinates. We prove endpoint observability and stability for frozen fronts, weighted transitive/cyclic decomposition, contact-complete circular design, physical-clock and mechanism non-identifiability, exact Gaussian cyclicity testing, and Bonferroni-valid interval scanning. The benchmark is deterministic: analytic endpoint images, blurred/noisy pixel round trips, scalar-null stress tests, public-image tracing, multi-resolution mechanistic endpoints, and a non-learning frozen-front simulator. The implementation recovers pairwise edge-flow histories from endpoint images, detects cyclic residuals in a mechanistic four-type expansion, and uses those residuals as forcing signals for a dimensionless active design-control layer covering reaction-diffusion control, phenotype-frontier optimization, protocol synthesis, Monte Carlo robustness, and a downstream population-state bridge.

cs.CV↗

arXiv2026

Interface-Variant Dynamics in Software Ecosystems: Resolver-Induced Selection and Adoption in Package Graphs

Compatibility research usually treats an interface change as a local writer-reader decision. Distributed software stacks make that decision population structured: an RPC, telemetry, middleware, or service-contract variant is introduced by one provider release and then spreads, stalls, or is mediated across consumers, transitive dependencies, and resolver rules. This paper asks when that observation is a load-bearing software-engineering estimator rather than evolutionary relabeling. We mine interface histories, audit npm, Maven Central, PyPI, and crates.io package graphs, execute 2100 package-manager resolver probes, estimate an ecosystem-specific selection coefficient $s$ from clean conflict probabilities, and use that measured $s$ to forward evaluate a pairwise-comparison absorbing process on the observed package graph. We separate three evidential roles. Fixation is a forward evaluation, not independent evidence: once $s$ is measured, deviation from $1/N$ follows mechanically from the non-neutral process. Checker-derived direction carries adoption signal: a direction-permutation null gives checker-direction gap MAE 0.07 versus null median 0.43 ($p=0.002$). But because that direction is derived from the same boundary state whose admitting frequency is predicted, it is a diagnostic rather than an orthogonal selection test. The stricter checker-free temporal test asks whether early resolver-channel features predict later blocked-to-admitted flips; in this snapshot they do not beat age-only (Brier 0.28 versus 0.24, AUC 0.51 versus 0.54). The result is a reproducible estimator audit for interface-variant dynamics in distributed package graphs, showing where resolver evidence becomes population input and where the current registry data still fail to close the resolver-to-adoption loop.

cs.SE↗

arXiv2026

Detector-Output Instability near the Kesten-Stigum Boundary: Separating Hard Readout, Relaxation, and Fixed-Point Dispersion

Community-detection algorithms usually return a single partition, even when independent initializations or small data perturbations yield several plausible outputs. We probe this output distribution through three paired observables: hard-partition variation of information (VI), a residual-gated fixed-point VI, and a cutoff-free Jensen-Shannon distance between belief-propagation (BP) marginal fields. For the symmetric sparse stochastic block model, linearizing BP around the uninformative fixed point gives the Kesten-Stigum onset at $\mathrm{snr}=(c_{\rm in}-c_{\rm out})/(q\sqrt{c})=1$. The hard VI maximum is instead a finite-size, readout-dependent detector curve on the detectable side, typically $\mathrm{snr}^\star \simeq 1.05\text{-}1.10$; moving the polarization cutoff from 0.001 to 0.1 shifts it across 1.047-1.128. The nontrivial-readout activation obeys $\mathrm{snr}_{50}(\tau)-1 = 0.0086 + 0.522\,\tau$ ($R^2=0.996$). Long-budget residual gating separates readout and critical slowing from fixed-point dispersion: at $\mathrm{snr}=1.05$ and 1.10 the hard VI is 1.49 and 1.58 bits but the gated subsets have zero VI, whereas from 1.15 to 1.30 nearly all runs pass the gate and retain VI 1.31 down to 1.24 bits. A high-replication audit through $N=100000$ disfavors a zero-asymptote power law and finds a small plateau $\mathrm{snr}^\star-1 \simeq 0.024$ (graph-bootstrap 90% interval [0.0227, 0.0316]). On real networks, a label-free Bethe-Hessian modularity margin with a Chung-Lu null gate is run on political blogs and six SNAP graphs: the measurement stays label-free, while heterogeneous networks can retain null-significant structure even after strong edge subsampling. The result is a detector-output decomposition near the Kesten-Stigum boundary, reporting hard readout, relaxation dynamics, and fixed-point-field dispersion separately.

cs.SI↗

arXiv2026

Dipole Diffusion Error in Thin Geometry: Optical Thickness Laws for Grid-Free Subsurface Scattering

The dipole and its descendants model subsurface scattering with a radial reflectance profile fitted to a flat, semi-infinite slab. This assumption introduces a systematic geometry error on thin and curved objects. We isolate the effect by comparing the dipole with the finite-slab multipole under the same diffusion model and boundary condition. In slab geometry the diffuse-albedo error has a material-independent leading rate, $C e^{-2\tau}$ with $\tau=T/\ell_d$, while the prefactor remains material dependent; the same image series gives the transmitted flux, whose leading decay is $e^{-\tau}$. We give the closed-form albedo and transmittance, relate the exponents to killed random walks, and extend the interpretation to spatially varying media through optical distance. A brute-force volumetric path tracer fits a reflectance-deficit rate of 1.99 and a transmittance rate of 0.99, matching the round-trip and single-pass predictions. The resulting thickness predictor is a useful thin-feature heuristic, but stress tests show that curvature and illumination can dominate away from the slab setting. For the remaining geometry-dependent term we solve the screened-Poisson diffusion problem directly inside the signed-distance domain with Walk on Spheres, without an interior mesh or a tangent half-space approximation; the estimator matches closed-form tests to 0.75%. Against a four-case path-traced benchmark it improves the back-lit, thickness-governed case but not every front-lit or curved case, showing that the method reduces geometry error within diffusion and does not replace radiative transport.

cs.GR↗

arXiv2026

Self-Verifying Measurement Records: Hash-Linked Evidence Graphs for Hardware Benchmarking

Performance numbers reported for hardware are accepted on trust: the reader cannot recompute them, the apparatus is gone, and the silicon itself can be silently wrong, with fleet studies reporting on the order of one core in a thousand returning incorrect arithmetic with no error raised. We make a reported hardware measurement a tamper-evident, independently checkable record. Every quantity in the text, a table, or a figure is bound, by its content hash, to the observation and the verification behind it; the whole is a hash-linked, append-only structure (a transparency log for measurement) that a verifier audits offline without trusting its producer. Matrix products are verified by a probabilistic identity (Freivalds) at O(k n^2) cost under a tolerance we derive from floating-point error analysis and calibrate to the device's own measured residual floor, so a wrong product is rejected with probability 1 - 2^(-k); quantities with no such identity carry an algebraic checksum and a measured reproducibility class. We then treat the check itself as a security object: a probe seed committed for offline reproducibility is an attack surface, and a probe-aware adversary can hide a corruption in the probe's null space, fooling even a quorum of bit-identical witnesses, while a Fiat-Shamir challenge derived from the claimed output closes this. Driving the device from an unprivileged tenant's reach, with a di/dt power virus and a thermal soak, neither moves the calibrated tolerance nor produces a silent error, placing the physical-fault threat at the rare defective part or the privileged attacker and marking the boundary at which the record must compose with a hardware root of trust. We demonstrate the construction across Blackwell and Hopper GPUs and report a residual-floor and reproducibility map by precision, size, and device.

cs.CR↗

arXiv2026

Residual GPU Cache State on Apple M4 Pro

Apple silicon exposes unified CPU-GPU memory, but the cache state left after a completed GPU command is not documented. This paper characterizes that phase boundary on a 14-core Apple M4 Pro. We validate the measurement pipeline against unmodified STREAM 5.10 and BabelStream 5.0, then adapt an 8192-byte system-level-cache occupancy pattern to a synchronized Metal experiment. A GPU kernel touches 0 to 512 MiB and finishes before a 16 MiB CPU probe begins. The first CPU traversal is slower after large GPU footprints, while a second traversal removes most of the cost, showing residual shared-cache displacement rather than simultaneous DRAM contention. A separate matched-block experiment measures GPU slowdown under high-priority CPU traffic and finds background QoS close to baseline. Root PMU measurements and public IOReport histograms provide hardware grounding: they distinguish L1D refill sectors from software cache-line size, expose page-offset-dependent conflict behavior, and separate performance-core, efficiency-core, and AGX demand. The results identify a reproducible post-GPU cache-displacement window on M4 Pro and quantify a simple one-pass software recovery mechanism.

cs.AR↗

arXiv2026

Naturalness Predicts but Does Not Cause Transferability in Image Encodings of Real-World Streams

A common practice converts a one-dimensional signal into an image so that a vision backbone pretrained on natural photographs can be reused for recognition, yet the encoded image is rarely examined. We ask how the visual naturalness of an encoded image relates to its transfer accuracy under a frozen backbone. We build WorldStream, a corpus of 299 heterogeneous current-value series from key-free public APIs (weather, air quality, earthquakes, gold and oil, equities, crypto, foreign exchange, web activity and space weather), with a nine-way source-recognition task over 3143 temporally split windows. Across seven encodings and six frozen backbones, the Frechet distance of an encoding to natural images (FID) predicts its accuracy: Spearman $\rho=-0.72$. Two controlled interventions show this is not causal in the spectrum. Our invertible encoder has a single adjustable part, a spectral exponent $\beta$ (power $\propto |f|^{-\beta}$); varying $\beta$ moves the image toward or away from the natural-image manifold at fixed content. FID is lowest near the natural value $\beta \approx 2$, but frozen accuracy stays flat and far below the structured baselines (19.2% vs. 73.0%), and FID and accuracy are only weakly related over the sweep (Pearson $-0.32$). A second intervention, phase scrambling, holds the power spectrum exactly fixed while removing local structure; now FID and accuracy fall together (Pearson $-0.89$). The cross-encoding correlation is thus mediated by local structure, not spectral naturalness: FID predicts accuracy because Inception reads the same structure the backbones do. Full fine-tuning does not close the gap (27% vs. 67%), so the deficit is structural. The encoder is exactly invertible, recovering the signal from the 8-bit image at 72.9 dB, so the image doubles as a lossless record of the data.

cs.CV↗

arXiv2026

Exact Local Annotations for Regular Languages

A regular language is recognized by a finite monoid, but a locally checkable explanation of that recognition can have a nontrivial update geometry. We study exact bounded-arity annotations for regular word languages under one-symbol substitutions. The cost of an edit is the number of annotation cells that a canonical locally accepted representation must change, together with the corresponding bit movement and the number of local constraints that must be revalidated. For every morphism recognizing a regular language, the balanced product annotation gives constant locality, linear size, O(log n) edit stability, O(log n) revalidation, and constant access to the membership value. The matching lower bound proved here is restricted to product decompositions that expose an edit-active nontrivial group quotient as ordered product labels; in that setting one substitution changes every quotient label on an ancestor path. We also show that annotation-free bounded-window recognition is exactly strict locality, prove closure properties for a two-sided total decision variant, and formulate the remaining constant-stability boundary as a finite obstruction problem. The ancillary files include Lean, CP-SAT, and CUDA certificates, including a context-free interval-chart experiment.

cs.FL↗

arXiv2026

Non-Uniform L2 Cache Latency Across the Streaming Multiprocessors of an NVIDIA L40

The NVIDIA L40 exposes a 96 MiB L2 cache usually modeled as one uniform pool with a single hit latency. We show this is wrong at the granularity a kernel sees: L2-hit latency depends strongly and reproducibly on which physical streaming multiprocessor (SM) issues the load. A turn-serialized, %smid-resolved probe maps the hit latency across all 142 SMs in one launch; it is not a constant near 279 cycles but spans 222-339 cycles (a 52% range), with per-repetition noise below 0.01 cycles. An additive model $L = \mu + a(\mathrm{sm}) + b(\mathrm{slice})$ explains $R^2 = 0.87$ (0.98 with one rank-1 term), and the SM term is two-fold symmetric (two halves of 72 SMs at correlation $r = 0.999$), following the AD102 GPC layout. Independent access patterns agree per SM at $r = 1.000$, so the effect is physical. The same probe on a Blackwell RTX 5090 shows it generalizes, while the per-die pattern is device-specific. Read as a fingerprint, a single user-level probe identifies the SM within a device at 92%, and two physically identical L40s are separated at 100% despite near-identical mean latency (per-SM map $r = 0.63$): a per-die hardware identity, not a clock artifact. This is a self-localization and fingerprinting primitive: a kernel reads its own placement and device, not a victim's, and extracts no secret data. The map is stable, unchanged after an hour at full utilization on both devices. As a consequence, distributing latency-bound work by the map cuts makespan by up to 11%. Single-thread capacity, line-tag, prefetch-modifier, and persisting-L2 results appear as controls. The artifact contains seeds, raw observations, the trained model, and regeneration scripts.

cs.AR↗

arXiv2026

Single-Event Upsets in 3D Gaussian Splatting Rendering: Bit-Level Criticality, Spatial Extent, and a Parallel Support Guard

Three-dimensional Gaussian splatting is a standard real-time scene representation increasingly deployed on hardware exposed to transient faults, such as spaceborne processors and robotic edge devices where silent data corruption occurs. A trained model is a large array of floating-point parameters in GPU memory, where a single-event upset corresponds to a single flipped bit. This paper measures these effects and constructs a defense. A GPU-resident parallel fault-injection engine applies over 3.8 million controlled single-bit upsets across four scenes, six fields, all bit positions, and three numeric formats (fp32, fp16, bf16), using 5.3 GPU-hours. The effect is highly concentrated: most upsets leave the image perceptually unchanged due to high redundancy, but a small set of high-order bits principally the logarithmic scale's sign bit enlarge a single primitive to cover up to 75.7% of the frame. A closed-form perturbation bound derived from the IEEE-754 layout and pipeline activations predicts this per-bit ordering. This concentration motivates a support guard: a per-primitive clamp of each parameter to the coordinate box observed during training, costing 76 us per frame. Over 768,000 guarded upsets, the worst corruption footprint is restricted to 11.68% of the frame. We prove the guard leaves clean models unchanged and prevents frame-covering corruption. Under an accumulated dose of 20,000 simultaneous upsets, the unguarded renderer degrades to 10.6 dB, whereas the guarded renderer remains at 21.8 dB. The corruption footprint also dictates the number of tile/compositing nodes contaminated in distributed renderers, where the per-node guard contains it.

cs.GR↗

arXiv2026

Rendering Separoid Information: Rate-Distortion Reconstruction of Convex Apartness Scenes

A convex scene communicates more than shape: the pattern of which groups of objects are mutually apart and which cross is a discrete relational payload. We treat the apartness table of a finite family of convex bodies, a separoid, as a source signal; a renderable convex scene as its encoder; and the rendered image as a noisy visual channel from which the apartness structure is decoded. For disjoint index sets $A,B$, the source bit records whether $\operatorname{conv}(\bigcup_{a\in A} C_a)$ and $\operatorname{conv}(\bigcup_{b\in B} C_b)$ are disjoint. Within this view, apartness-preserving rendering becomes a rate--distortion problem: the rate is a differentiable geometric code length for the carrier scene, while the distortion is closure-aware and weights maximal separations and minimal Radon partitions by the number of consequences they control. A differentiable support-function realization turns separability into a soft directional margin and represents each separation by a distribution over witnessing directions, yielding a variational lower bound on apartness mutual information $I(\Sigma;Y)$ and an information-theoretic account of view selection. Experiments on planar convex scenes show that scenes are recovered from the apartness table alone at 99.9% bit accuracy, with the certificate skeleton already determining the full table; coordinate quantization gives a clean operational rate--distortion frontier where certificate distortion is more stringent than Hamming error; and rendered $48\times48$ images transmit about 0.72 of the apartness-graph entropy under mild noise. Increasing the viewpoint-robustness term widens separating cones with only a modest geometry-rate surcharge. The result is a certificate-aware rendering objective for scenes whose purpose is to make relational convex structure recoverable rather than merely pixel-faithful.

cs.GR↗

arXiv2026

GPU-Accelerated Search and Certification of Bounded Indistinguishability in Finite Kripke Semantics

We study finite Kripke semantics as an explicit search and certification problem for modal formulas. Sets of worlds are encoded as integer bitmasks, so Boolean connectives, $\Box$, and $\Diamond$ reduce to word-level containment and intersection tests. This gives a deterministic evaluator with an independent certificate checker, then scales it through a fused CUDA kernel for exhaustive small-frame scans. Over $K,T,S4,S5$, a corpus of 5,624 formulas is evaluated on all frames through five worlds, performing $1.63\times 10^{14}$ formula evaluations in 45 minutes on one H100. All 20,990 emitted countermodel certificates verify. In this bounded corpus, every $K$-refutable formula has a countermodel on at most two worlds, far below the standard filtration bound $2^{|\mathrm{Sub}(\varphi)|}$. We then turn pairwise formula equivalence into a minimal-countermodel problem for biconditionals and synthesize semantic mirages: formulas that agree on every model up to a finite size and split only later. In particular, $\alpha_2=(\Box\Diamond)^2\top$ and $\alpha_3=(\Box\Diamond)^3\top$ agree on all frames of at most five worlds but are separated by a checked six-world path. Finally, we build a density-aggregated semantic atlas for representation-guided candidate retrieval and compare raw features, PCA, UMAP, spectral layouts, and random layouts under a common million-pair verifier budget. The result is a reproducible bridge between modal finite-model theory, GPU enumeration, certificate checking, and graphics-supported semantic exploration.

cs.LO↗

arXiv2026

A Calculus of Apartness over Separoids: Effective Convex Representation, Stratified Conservativity, and the Complexity of Entailment

Every finite family of compact convex bodies in Euclidean space induces an apartness relation between disjoint index sets: two sets are apart when the convex hulls of the corresponding unions are disjoint. This paper studies the finite theory obtained by taking apartness as the primitive relation. Its basic laws are symmetry, bilateral subsumption, and vacuity, equivalently the separation-polarity form of acyclic separoids. The main contribution is an effective rational realization theorem with uniform margins and the exact consequence theory it supports. Every finite apartness separoid is realized by rational polytopes whose coordinates are indexed by maximal separations. Maximal separations and minimal Radon partitions can be enumerated from a full table, generators, or a membership oracle; the coordinate values have controlled bit height; and each coordinate records a readable certificate of one maximal separation. The realization separates every apart pair with clearance at least 2, remains correct under outer parallel enlargement by any radius below 1, and yields full-dimensional convex bodies after thickening. The distance-function layer records standard convex-analytic stability through Lipschitz comparison, monotonicity under inclusion, and outer parallel bodies. On the logical side, positive entailment is exactly one-premise subsumption. Boolean consequence over Euclidean scenes is sound, complete, and decidable; satisfiability is NP-complete, validity is coNP-complete, and positive entailment is linear for sorted encodings. A stratification theorem shows that Boolean reasoning introduces no new atomic apartness beyond separoid closure. Fixed-dimensional consequence relations form a strictly decreasing hierarchy that stabilizes in dimension n minus 1 for n sites.

cs.LO↗

arXiv2026

Cone-Induced Observation Congruences for Vector-Valued Quantitative Languages

We study the observation congruences induced by rational polyhedral cones on vector-valued quantitative languages. The extreme rays of the dual cone define intrinsic covectors, and these covectors classify every incremental residual future by a finite sign cell: negative, tight, or positive along each extremal Farkas direction. The resulting carrier is the right-stable carrier of this cone-induced observation family, whose source is canonical: the restricted covector geometry of the order cone on the residual span of the language. We organize this construction through an observation-refinement correspondence, a cone-refinement calculus, and a separation between the qualitative conic observation quotient and the numerical residual carrier needed for potential certificates. A bounded-horizon fragment is fully computable by enumeration of accumulated futures, and reproducible evaluation runs show how the conic layer detects qualitative obstruction cells before numerical refinement.

cs.FL↗

arXiv2026

Biprofile Deviation Logic: Report-Replacement Frames and Audit Witnesses

Biprofile deviation logic models strategic social choice states as pairs $(R,P)$, where $R$ is the true profile used for welfare comparisons and $P$ is the submitted report profile used by the rule. Coalition modalities replace only the reports of the coalition, and their relations satisfy the fixed law $E_C \circ E_D = E_{C \cup D}$. The paper proves soundness and completeness of $H_{\mathrm{bp}}$ for the abstract frame class $\mathrm{Dev}(N)$, with the reverse-composition midpoint displayed inside the canonical proof. It then separates abstract $\mathrm{Dev}(N)$-components from genuine report-coordinate products by coordinate separation. On the social-choice side, the classical facts supply the source notions; the paper-specific contribution is the audit layer for representation changes: typed manipulation witnesses, a boundary-row theorem for off-domain extensions, and a factor-closure criterion for public deletions. The ancillary material contains the input formats, an executable certificate checker, Lean and Alloy companions for the finite relational lemmas and update patterns, recorded run logs, and checksums.

cs.LO↗