[{"data":1,"prerenderedAt":157},["ShallowReactive",2],{"run:lego-brushcompat-opacdecay-5k":3,"run-findings:lego-brushcompat-opacdecay-5k":92},{"run":4,"config":19,"metrics":53,"curve":59,"assets":91},{"id":5,"title":5,"subtitle":6,"eyebrow":7,"date":8,"workspace":9,"commit":10,"tags":11,"verdict":18},"lego-brushcompat-opacdecay-5k","P1.D opacity decay 5k — brushcompat-base-5k に opacity_decay_rate=0.004 を追加","Run summary · P1.D opacity decay (splat 数削減 + Metal kernel 効率化基盤)","2026-05-24","splat","110b9bd",[12,13,14,15,16,17],"p1-d","lego-5k","smoke","brush-compat","opacity-decay","splat-count-reduction","partial",[20,23,26,29,32,35,38,41,44,47,50],{"key":21,"value":22},"dataset","\u002FUsers\u002Fotkrickey\u002Fdev\u002F3dgs-workspace\u002Fdatasets\u002Fnerf_synthetic\u002Flego",{"key":24,"value":25},"gt_convention","Premultiplied",{"key":27,"value":28},"iterations","5,000",{"key":30,"value":31},"seed","42",{"key":33,"value":34},"capacity","1,000,000 splats",{"key":36,"value":37},"sh_degree","3",{"key":39,"value":40},"loss","L1Ssim",{"key":42,"value":43},"lambda","0.200",{"key":45,"value":46},"ssim","window=7 sigma=1",{"key":48,"value":49},"backend.backward","Simd",{"key":51,"value":52},"backend.loss_path","Gpu",{"psnr":54,"wallclock":55,"wallclock_regress":56,"splats":57,"final_loss":58},31.68873405456543,"2m 34s",false,83093,"1.468421e-2",{"loss":60,"splats":85},{"iters":61,"values":73},[62,63,64,65,66,67,68,69,70,71,72],1,500,1000,1500,2000,2500,3000,3500,4000,4500,5000,[74,75,76,77,78,79,80,81,82,83,84],0.5938450694084167,0.08621834963560104,0.05454661324620247,0.031217005103826523,0.019514145329594612,0.01730363257229328,0.016300126910209656,0.01568548195064068,0.015227444469928741,0.014873430132865906,0.01468421146273613,{"iters":86,"values":87},[62,63,64,65,66,67,68,69,70,71,72],[88,89,90,57,57,57,57,57,57,57,57],5207,842,11363,{"has_renders":56,"has_splat":56},[93,117,143],{"id":94,"title":95,"date":96,"status":97,"polarity":98,"category":99,"axes":100,"tags":102,"task_code":105,"related_runs":106,"delta_psnr":111,"delta_wallclock":112,"rank":113,"verdict":114,"impact_summary":115,"detail_path":116},"p1-d-rate-sweep","P1.D opacity decay rate sweep — rate=0.002 が PSNR 最高 sweet spot (brush default +0.40 dB)","2026-05-25","stable","positive","ablation",[62,101],3,[12,16,103,13,15,104,99],"rate-sweep","premultiplied","P1.D.2 (rate sweep)",[107,108,5,109,110],"lego-brushcompat-opacdecay-r0p001-5k","lego-brushcompat-opacdecay-r0p002-5k","lego-brushcompat-opacdecay-r0p006-5k","lego-brushcompat-opacdecay-r0p008-5k","+0.40 dB max (rate=0.002 vs default 0.004、ただし 5k smoke variance σ ±0.32 dB の 1.25 倍)","~3 min\u002Frun、wallclock 影響微小","medium","accepted-keep-default","opacity_decay_rate を 5 点 (0.001\u002F0.002\u002F0.004 default\u002F0.006\u002F0.008) で 5k smoke sweep。**rate=0.002 で PSNR 32.090 dB (default +0.40 dB)** と最高、splats は 88k で +5.8% 微増。rate を上げる (0.006-0.008) と splats は 80k 帯に削減されるが PSNR 影響は 5k variance σ ±0.32 dB 内。Phase D 30k baseline (rate=0.004) は既に M5 +0.11 突破済 (36.106 dB)、rate 変更の追加 +0.2-0.5 dB は smoke noise と並ぶ ROI 不明確。multi-scene Phase D re-chain も brush 互換性維持の観点で rate=0.004 維持を推奨。","\u002Ffindings\u002Fp1-d-rate-sweep\u002F",{"id":118,"title":119,"date":96,"status":97,"polarity":98,"category":120,"axes":121,"tags":123,"task_code":133,"related_runs":134,"delta_psnr":137,"delta_wallclock":138,"rank":139,"verdict":140,"impact_summary":141,"detail_path":142},"p1-d-stage2-30k-results","P1.D Stage 2 — Lego brushcompat + opacity decay 30k = 36.106 dB、splats -56% \u002F wallclock -32%","experiment",[62,122,101],2,[124,125,126,16,127,128,104,129,130,131,132],"p1","phase-d","milestone-m5","brush-parity","win-win-win","lego-30k","stage-2","splat-efficient","axis-1-prep","P1.D Stage 2 (M5 Lego val pass)",[135,136,5],"lego-brushcompat-opacdecay-30k","lego-brushcompat-base-30k","+0.92 dB vs baseline 30k (35.184 → 36.106)","-32% vs baseline 30k (1h 02m 18s → 41m 54s)","high","accepted-decisive-win","Lego brushcompat + opacity decay 30k で training-time eval 36.106 dB (val 100 view, brush convention, raw)、independent eval 36.163 dB (brush q8)。baseline 30k (35.184 dB) を **+0.92 dB 上回り**、splats を 846,689 → 375,146 に **-55.6% 削減**、wallclock を 1h 02m → 41m 54s に **-32% 短縮**。これは trade-off と想定していた PSNR\u002Fsplats\u002Fwallclock が **完全 win-win-win** に。M5 個別 scene gate (Lego brush conv > 36 dB) を val で達成、brush 自身 val 32.038 dB を +4.07 dB 上回り、本実装が brush を decisive に超えた。test subset (n=36) も +0.75 dB 改善 (33.315 → 34.065)、brush paper test 37.40 との gap を -3.34 dB まで縮小。Stage 1 smoke 推定 (splats -11.6%) を 30k で -56% に拡大、opacity decay の効果は iter 累積で増大することを実証。次 step は multi-scene Phase D 7 scene re-chain (chain 完了後 schedule)、低 wallclock + 低 splats での M5 multi-scene parity 完遂を狙う。","\u002Ffindings\u002Fp1-d-stage2-30k-results\u002F",{"id":144,"title":145,"date":8,"status":97,"polarity":98,"category":120,"axes":146,"tags":147,"task_code":148,"related_runs":149,"delta_psnr":152,"delta_wallclock":153,"rank":139,"verdict":154,"impact_summary":155,"detail_path":156},"p1-d-opacity-decay-smoke","P1.D opacity decay 5k smoke — splats -11.6%、PSNR +0.38 dB の同時改善",[62,101],[124,125,16,17,15,13,14],"P1.D opacity-decay (Phase D core)",[5,150,151],"lego-brushcompat-base-5k (Stage 1 baseline 31.31 dB \u002F 93,948 splats)","lego-brushcompat-base-30k (Stage 2 35.18 dB \u002F 846,689 splats)","+0.38 dB vs Stage 1 baseline 5k (31.308 → 31.689)","+23% vs Stage 1 5k (2m 5s → 2m 34s、host RMW overhead、N で線形)","accepted-go-30k","brush の `refine_splats()` (train.rs:611-619) と同じ sigmoid-space formula で opacity decay を refine cadence に統合: `new_opac = sigmoid(raw) - rate*(1-train_t)` → `clamp(1e-12, 1-1e-12)` → `inv_sigmoid`。5k Lego smoke で PSNR は維持以上 (31.31 → 31.69 dB、+0.38 dB)、splats は **-11.6%** 削減 (93,948 → 83,093)、wallclock は +23% (1500 iter で全 splat 触る host loop が支配的、N=83k で問題ない範囲)。これにより 30k に進めば brush 282k 帯 (Stage 2 の 846k からの大幅削減) + PSNR ≥ 34 dB の同時達成が射程に入る。axis 1 (native Metal) ではなく axis 3 (unified memory CPU RMW) を活用した実装で、refine 周辺の O(N)\u002Frefine_every オペレーションには合理的選択 (Metal dispatch overhead > 実 work)。","\u002Ffindings\u002Fp1-d-opacity-decay-smoke\u002F",1782449787846]