{"schema":"pubphys.bundle/1","record":{"author":{"account_ref":null,"orcid":null},"builds_on":[],"content_schema":"pubphys.content.revision/1","content_sha256":"1d7d1e95b97ed52c24c1e7a585e2d75e88f243379289f96d7c6606c15f199a73","created":"2026-10-03T07:17:57Z","files":[],"origin":{"assisted_by":[],"kind":"seed"},"parents":["5475cf5dc5b1a72283d26dc95dc6e00d7ea4e00096a7c6492e409a1816eeb011"],"salt":"00de42282976c3217e986aa4308dfe4a8c6d88d44e00cea2c68243dc3c1f935c","schema":"pubphys.record/2","site":"pubphys.com","target":null,"type":"revision"},"content":{"answer_type":"mechanism","assisted_by":[],"external_id":"bio.collective-behavior.scale-free-correlations","kind":"phenomenon","literature_status":"contested","n":"1","parents":[],"plain":"In starling flocks, a change in one bird's flight is correlated with birds across the whole flock, however large it is. Whether flocks are tuned to a special critical state to achieve this, and how, is debated.","posed_since":"2010","precise":"In wild starling flocks ($10^2\\text{ to }10^4$ birds), connected correlation functions of velocity fluctuations have correlation length $\\xi$ proportional to flock size $L$, for both orientation and speed (Cavagna and co-workers, 2010). Orientation correlations follow from Goldstone modes of broken rotational symmetry; speed correlations require tuning near a critical point or another mechanism. Determine the mechanism for scale-free speed correlations and whether it involves tuning.","problem_ref":null,"references":"","settled_by":"A model with independently inferred interaction parameters that reproduces $\\xi$ proportional to $L$ for speed across flock sizes, with or without tuning to a critical point.","status_note":"","title":"Why speed correlations in starling flocks are scale-free","topic_ref":"169c237bb7dec2b851fb7b715df607d983a88bff09590a878223e10c99e9ed50"},"content_withheld":"false","files":[],"attested":{"attestation":{"batch":null,"client_id":null,"id_token_sha256":null,"kind":"platform"},"record_hash":"ba7cb7f83c93b217eaa06a0ce13ae74648d31556e3786be7a7eb47429fe62161","schema":"pubphys.attested/1"},"id_token":null,"id_token_withheld":"false","envelope":{"attested_hash":"71875f8f53e9a5e27f62b9d11fcde91e3cd5f30061e26406dd3653dd4836e111","platform_signature":{"key_id":"c6afc19b31429869751f06879c75cd64ea92654423d15b44be775bf1310a60da","sig":"FWw2-RzRi5xNS4P95fsJbdSmsOXqg_PMmN6PpqM2oTodRuG6Fv3YFuFUPksy3vftvv1140ZVbkzqDOIf1qpHAQ"},"schema":"pubphys.envelope/1"},"ots":{"attested":["AE9wZW5UaW1lc3RhbXBzAABQcm9vZgC_ieLohOiSlAEIcYdfj1PppeJ_YrnRH83pHjzV8wBh4mQG3TZT3Ug24RHxIHFUY26xX-RwH4fhT2Ag7YcRxg0r6of4iwioqLbxOetiCPEg3rWGRu0AYzWbhIWuL_lcvhdilGDQajV5hrm_LIyMY7sI8SB7SPgqpqoif2TUcSsPO_cGDsRrDmo3gZoCTvpbAo0eywjxINFo5VKdupMzkU5B8v3yYNTSPNXAqQFeNi1XJtPdprIeCPAgC47d1nM3t8ROhFRwLttemx9_SakZRfoOPRGtME3jTRII8CDh2QXHi-VuZhtzPFOidrXNqwGuPhH3gWaCRnu2H03OEwjxIDJ0hos791I16AMy4LVAxMlkg0lgruUSZXcAV2eChFLSCPAgY62IgQuQJxN3qyWDdsSTATEfW2keFBOuI8VrhYhkHBMI8SB8izl_Yn9kR2zBmnu-HVjv452ytRQyuNX-opb_OJzg_gjxINBAKCf3cKChW811B6TkfdlxdONUiLQA88uJMnPer4KuCPEgytIBB3x7TFDT-XqOV-9vpqw1NKoAu0dhtsCbAMql2L0I8CCtNZgmApuKULvPC9nsMCaM05arV-F3o5FTlnJCnRvdMgjwIBGYo5Vxy-d7U5zKv5vp3Ii7hJPH_BDLCzA13c47p9q7CP_wCHbghVgOFMuNCPAQPZK2lHbTMqcCYUotzOQcmQjwIJ7ruRIs6HnufKxCpmLUgeUl0aUu0ov4_3PqcppS-bddCPEgI530vHzdwz_3o9jYQ3WablSaV64Wfn7Pmby5WLyI-A0I8QRqwKw78AhITF7Tr3a1xP8Ag9_jDS75DI4sK2h0dHBzOi8vYm9iLmJ0Yy5jYWxlbmRhci5vcGVudGltZXN0YW1wcy5vcmcI8CBXWeNiWFWltfHE0nkDXsVKIykUUwuObhsnN-2fvBt98gjwIM5Vf7j68sOFgVysYMc5S09Hho-fqxYW3oQ4oKUX7JpPCPAgaKHHQB3sdd9w1hu4NMh7vmb-p0X2r4uyVKKCj1G7S28I8SAW2Mg6Bzi9ygjrrjIYB7w90fwMcxH24SsqLmzPyAMGfwjwIMQ863zlveYIpNKWVrZaDOa4vowwoOg2CcTW8gXtxK3dCPEgrZxGGAf-t8jhz_eLMUyBN1IhNrdYDRcNHWvQcwNG9woI8CCVOUHG1YXudbaFIgUYvrCIevRWvb2ubhQAo-z0duD0rQjxIDBeKerVGkO3J2eXDwdraSioXbIWsdIPEN1s8pIwJIS2CPAgV2kB3n3JZ5HwBQjpRL1CWKnqvdCjZk3RcALk6N2wHigI8CB-wbljNlfqElD25uZkNg6taS81YDRU2vfMqGVQ420O9AjxWQEAAAABJM43UU6MLMRrPlCUqossvu1q_knons5yylyWTgxZzWUAAAAAAP7___8CLgABAAAAAAAWABQrYt3E7OllKRCEmL3FL589l78_5wAAAAAAAAAAImog8ATiyw4ACAjxILmbcIO7ixv3pCtwUMZ1VQGKus54F9lZ8-w5ECD5ZuiICAjwIG6ynCyFTLPE7Rgk-0ZGCtBDyqNQx8YvaSZNHy8D8p8jCAjwIMX8zoD2Be1YWvcx_bexVPRmBX0hK-do8b8t9SarimQVCAjxIG6XtpqIEclLlhzcK1LVjqoPGrjjmLnyno8tcETMzECECAjwIF6mlfXOFY51JhrK4eze8zQlKV75OYZYqbtyi8BWxmAsCAjwIKKUcJmVoz-u-geiRV_-ZHdF0VEPXaEPFWf_JX_0e7G2CAjxIGMeD0Z5QWNKBcAEpHht007FFIILW6aSJ8f3CMkKNsneCAjwIBFr6Je8rkB7kwhPGbq0yRgFwZsvW9JhY5sXDRtrq0QwCAjwIAHAwXaus-yUgKICJB5mVvx8VZuJgjwnpb0qWPg1pi6DCAjxIAJhb8cefkVHTAMymdsxa-_i-tUua62LcpALQnPG7R9_CAjwIDvsFqBhPfAL6TCtXZd7gBWmMpx6iiZ-Ug0Jf_LlcstgCAjwIDJRBX6Q0Vge-ra-k1_g76yJWTEp6WWF13I3JpTnsZPJCAjwILykZCbkC9VQgl5gytPKKir6T9nTvKR6y05iWSHBTQgzCAgABYiWDXPXGQED45c78Ah-sGbmQAwfZwjwEAYqxtHnZiPZnJEGPx_JvKsI8SDXkqDg17YsZIrEz5acRx7mBXCKW5mKNgRYnw_-U2cpDgjxBGrArDrwCEfK6Mono428_wCD3-MNLvkMji4taHR0cHM6Ly9hbGljZS5idGMuY2FsZW5kYXIub3BlbnRpbWVzdGFtcHMub3JnCPAg10nyJ6Jn4kshQQQCKE0Lvj3hBC6nLRBVIzaPV4eh8VwI8CCQaAqWlxEbac_XOq1MOlf9iOKHEsxXspzbjK0vLpy8BwjwII3iRbRXUcDxrhAdkZmFlI15nySCSEZ7g922tF1Xln5DCPEgYYvZ1L4v4rPu_UqLfcHPtwSb2OH2GhPgVcVhhH6DpkQI8CDZCIoR20sC-uchP40oAmcLm9EJFV7xzwplj54AeVadXQjxILvLBjPFpCoz29m9Yf2qRnV7PI9GqxE8ozVQfk9QwCqrCPEgZXcMudvEoB_MJ8tqOW2PLTKAIeQBnE-1bfzptRc2gR8I8VkBAAAAAfXq-bmxWqOz7B5wKkwjzHGv2R4s7Y0Z76LqXWYNhmz0AAAAAAD-____Av0cAAAAAAAAFgAUl-skmdZDtn7Hnub6mF4HP2uVn7oAAAAAAAAAACJqIPAE4MsOAAgI8CBDmQsbEXc46Hu8DivhCBM1LGExa4TTM-wo7HpoCVjBTQgI8CCty5vkQtPHzzs8xqArOYhVSjgaDoG1ou3cojv5_P7wQQgI8SDQWB0kdXCTwbk-TqTt0QfRMyzDNLOtU1XXFgvGSRlW8wgI8CC2PKa_QCIBZtrXodq1GdEzppISMsMRDOnzr2gFjLKOAAgI8CCwQ_QF67bcFk_uJ2s0VCZmf5PGIjTmTCpt_qnVY5p_8AgI8SAbzyx7z-oxPMju6PvtQhzrJIQyH2ZAc9oyLuYemzbmZQgI8CC5bh7J74uUk91r8LwybHQFCNBC3PWeuwtMCCNFKWj19AgI8SAf4R2TUNPjaX_PWDUImpoITK0JoW89zaMKnD1wlEEi8AgI8SC2vNmdm7eyP5Ytl1yTzT0njliMdALl1ViKG-s3bG2zswgI8CCpbIVNz1GFVXdJk2zd82hBUoNFFemUPBt7IJdWEOciPwgI8CBtYdRQcrtX1FtCm1SxF7sx-5cO04U8KzbJh8fqBkyReAgI8CBHs2LGmX6gI-lV7yp1RrV7_tGfdiBAwnEFF6B6yXHzAQgI8CATotVmbXBMAixhZ-QKy5Q4lR0FusdA_wcIC1TbB7GmxAgIAAWIlg1z1xkBA-KXOw"],"envelope":["AE9wZW5UaW1lc3RhbXBzAABQcm9vZgC_ieLohOiSlAEIKipHaSaR9uHW3IZNPX-56CWOUzAINFK06kg-_QWGnZDxICodzn1ISRAhwl6m7FRl7UR9APf1cgYRAjVvdVlqVfYTCPAgNX7hxSgZOg4HJuxepYwr_ptppITYdHj7ni056zKf4W4I8CCSo83lG56TcrXOIQ1hMZGFNxt-O2yYoa8CDTYfv4oyXAjwIAWMI569W6ESVwdYvL9hPMl3_tstQnapF9M6PKVYlI-RCPEgZzNccBh0iAJy_ws0Lb6RLXl-QhUUs_LHsFQnQ6J3vtUI8SDYNluncM-eVAiqOjPn7XpRSNdUXw2Hr4GhsEaRofhQawjwIPOGrwrMj_5YfbHL0sD0Jj1n4GlGp091ctDt5spZ5ttQCPEgc5Po_Haw-Gu8QcBz4e8O7KJqd3pMd1Zgc5xvNgwKRKAI8CDhHjTRDsgFglT04grMuKx-URV-Za14ktgMuGI-MgavMgjxINIT2A3d_DeKxwK521mnlCvK2wl2UdXYsWFx2YY9xgr-CPAg3v2QXfNkDO6Xzu9061umH0rhjRfHBKza3uG2nPQbpd8I8CCtNZgmApuKULvPC9nsMCaM05arV-F3o5FTlnJCnRvdMgjwIBGYo5Vxy-d7U5zKv5vp3Ii7hJPH_BDLCzA13c47p9q7CP_wCHbghVgOFMuNCPAQPZK2lHbTMqcCYUotzOQcmQjwIJ7ruRIs6HnufKxCpmLUgeUl0aUu0ov4_3PqcppS-bddCPEgI530vHzdwz_3o9jYQ3WablSaV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