液氨是什么
|
Сь видъ Викиклад? (Wikimedia Commons) съхран?нъ ?стъ ? C? ?гож? опьсани? ?стъ |
опьсани?
| опьсани? |
English: Universal coldness/temperature scale in SI units, where coldness[1][2][3][4][5][6] is one possible name for reciprocal-temperature[7] in non-thermal units[8] i.e. β ≡ 1/kT ≡ 1/k dS/dE. This energy uncertainty-slope dS/dE approaches a common value for systems that randomly (or thermally) share energy E, since heat energy naturally flows from low (even negative) to high coldness (toward more "choice of open-slots" or "ways to play", and therefore clockwise) until sharing systems reach a common (equilibrium) value of this slope. Bottom line: 1 Kelvin of ambient temperature requires one to thermalize about 76.5594 picoJoules of ordered energy for every teraByte of subsystem correlation-information created, and 1 nanoJoule/Kelvin of information takes up about 13.0618 teraBytes of memory. |
| вр?м? сътвор?ни? | |
| клад??ь | сво? твор?ни? |
| творьць | AkanoToE |
| Other versions |
百度 西部证券共为质押乐视网股票融出超10亿截至去年12月31日，西部证券共计为质押股票乐视网融出资金本金人民币亿元。
Own work based on: ColdnessScale.png. Description and Added Notes come from the original file's page. |
| SVG genesis |  This diagram was created with Matplotlib.  This diagram uses translateable embedded text. |
Added notes
The radial lines denote key temperatures, clockwise from bottom including He evaporation (dotted cyan) around 4 K ? 3265 GB/nJ (just CCW from the 4732.51 GB/nJ of the 2.76 K cosmic background) and N2 evaporation (dashed cyan) around 77 K ? 170 GB/nJ, CO2 sublimation around ?78.5 °C ? 67.1 GB/nJ (dot-dashed cyan), H2O liquification around 0 °C ? 47.8 GB/nJ and evaporation around 100 °C ? 35.0 GB/nJ (dot-dashed green), "red-hot" (solid red) around 500 °C ? 16.9 GB/nJ, rock melting around 1500 °C ? 7.37 GB/nJ (solid magenta), graphite sublimation (dashed magenta) around 3642 °C ? 3.34 GB/nJ, and the surface of the sun (dotted magenta) around 5778 K ? 2.26 GB/nJ ≈ 2.01 nat/eV. The dashed red lines represent the min-max European temperature range (from 0 °F ? 51.2 GB/nJ to 100 °F ? 42.0 GB/nJ) on which Fahrenheit based his scale, at top of which is also the human basal temperature at around 98.6 °F ? 42.1 GB/nJ. Room temperature (3 o'clock) is defined as either 20 °C = 68 °F ? 44.6 GB/nJ ≈ 39.6 nat/eV = 1/kT or 22 °C = 71.6 °F ? 44.3 GB/nJ ≈ 39.3 nat/eV = 1/kT, and therefore kTroom is about 1/40 of an electron Volt.
Inverted-population states for finite-energy systems are found on the left half of this plot. These include: (i) 1024 end-on dominoes acting like stonehenge in the earth's gravitational-field (grey-dotted) at ?.001[J]/(kBln[1024]) ≈ ?1.04×1019 K ? ?1.25×10?15 GB/nJ, (ii) a mole of excited Ne atoms in a He-Ne LASER ready for stimulated-emission (grey-dashed) at ?1.96 [eV]/(kBln[6×1023]) ≈ ?415 K ? ?31.5 GB/nJ, and (iii) the orientation-temperature for 500,001 up out of 1,000,000 proton-spins in a 1 Tesla field (grey) at 1.41×10?26 J/(kB(ψ[1 + 1000000 ? 500001] ? ψ[1 + 500001])) ≈ ?1.41×10?26 J/(kBln[1000000/500001 ? 1]) ≈ ?255 K ? ?51.1 GB/nJ where ψ[x] is the PolyGamma function. The dot-dashed grey lines are for 500,002 and 500,003 out of 1,000,000 protons oriented spin-up in that same 1 [Tesla] field.
This plot illustrates that you can use either temperature T or reciprocal-temperature 1/kT to predict the direction of heat-flow. When you use temperature, remember that the highest possible temperature T is minus-zero-Kelvin and the lowest possible T is plus-zero-Kelvin. With coldness 1/kT, the lowest value is minus-infinity and the highest is plus-infinity so that heat energy naturally and simply flows from numerically low to numerically high 1/kT.
| unit to → ↓ from ↓ |
TF in °F |
TC in °C |
T in K |
ε ≡ kT in eV/nat |
β0 ≡ 1/kT in GiB/nJ |
β1 ≡ 1/kT in GB/nJ |
β2 ≡ 1/kT in ZB/Cal |
|---|---|---|---|---|---|---|---|
| TF | 1 | 5/9(TF ? 32) | 5/9(TF ? 32) + 273.15 | ||||
| TC | 9/5TC + 32 | 1 | TC + 273.15 | ||||
| T | 9/5(T ? 273.15) + 32 | T ? 273.15 | 1 | 8.61733×10?5T | 12165/T | 13062/T | 54650/T |
| ε | 11604.5ε | 1 | 1.0483/ε | 1.1256/ε | 4.7049/ε | ||
| β0 | 12165/β0 | 1.0483/β0 | 1 | 1.0737β0 | |||
| β1 | 13062/β1 | 1.1256/β1 | β1/1.0737 | 1 | 4.184β1 | ||
| β2 | 54650/β2 | 4.7049/β2 | β2/4.184 | 1 |
In the table of conversions above, note that the uncertainty-slope or coldness β≡1/kT in [GiB/nJ] or [GB/nJ] is nearly equal to the reciprocal of kT in [eV/nat]. Even more curiously, if we don't mind using binary-multiples i.e. gibiBytes instead of powers of ten, we can say that 1 [nat/eV] = 1.04827 [GiB/nJ] = 1.12557 [GB/nJ]. Hence room temperature coldness is about 40 [GiB/nJ] simply because kT at room temperature is about 1/40 [eV].
Python source code
The following code generated the plot above. The legend and arrowhead were added later in Inkscape.
import numpy as np
import matplotlib.pyplot as plt
kb_inv = 1/1.380649e-23/np.log(2)/8/1e18 # in GB per nJ
TAU = np.math.tau
gib_per_nj = np.array([-140, -120, *np.arange(-100, 110, 10), 120, 140])
scale = 44.3 # Defines the 3 o'clock position
angles = 2 * np.arctan(gib_per_nj/scale)
r = np.ones(len(gib_per_nj))
kelvins = np.arange(-900, 1000, 100)
k_angles = 2 * np.arctan(kb_inv/kelvins/scale)
r_k = np.ones(len(kelvins))
celsius = np.arange(-200, 600, 100)
c_angles = 2 * np.arctan(kb_inv/(273.15 + celsius)/scale)
r_c = np.ones(len(c_angles))
fahrenheit = np.arange(-400, 600, 100)
f_angles = 2 * np.arctan(kb_inv/(273.15 + 5*(fahrenheit-32)/9)/scale)
r_f = np.ones(len(f_angles))
angle_cut = TAU/36
circle_angles = np.linspace(-(TAU/2 - angle_cut), TAU/2, 2**12)
r_circ = np.ones(len(circle_angles))
semi_angles = np.linspace(0, TAU/2, 2**12)
r_semi = np.ones(len(semi_angles))
size = 'x-small'
def get_text(angles, labels, distance, color):
for i, label in enumerate(labels):
rot_angle = angles[i] * 360 / TAU
plt.text(angles[i], distance + 0.1, label, color=color, ha='center', va='center', rotation=90-rot_angle, fontsize=size)
fig = plt.figure(dpi=150)
ax = fig.add_subplot(projection='polar')
gb_distance = 1
k_distance = .8
c_distance = .6
f_distance = .4
get_text(angles, gib_per_nj, gb_distance, 'k')
get_text(k_angles, kelvins, k_distance, 'b')
get_text(c_angles, celsius, c_distance, 'g')
get_text(f_angles, fahrenheit, f_distance, 'r')
# for i, label in enumerate(gib_per_nj):
# rot_angle = angles[i] * 360 / TAU
# plt.text(angles[i], r[i]+.15, label, ha='center', va='center', rotation=90-rot_angle)
# plt.annotate(label, (angles[i], r[i]))
# Plot lines
def plot_line(angle, color, line_type):
ax.plot([angle, angle], [0,1], color=color, linestyle=line_type, lw=1)
# Helium boiling point
plot_line(2 * np.arctan(kb_inv/4./scale), 'c', ':')
# N2 boiling point
plot_line(2 * np.arctan(kb_inv/77./scale), 'c', '--')
# CO2 sublimation
plot_line(2 * np.arctan(kb_inv/(273.15-78.5)/scale), 'c', '-.')
# H20 freezing
freezing_angle = 2 * np.arctan(kb_inv/(273.15)/scale)
plot_line(freezing_angle, 'g', '-.')
# H20 boiling
boiling_angle = 2 * np.arctan(kb_inv/(373.15)/scale)
plot_line(boiling_angle, 'g', '-.')
# Liquid water range
ax.bar((boiling_angle+freezing_angle)/2, c_distance, boiling_angle-freezing_angle, color='g', alpha=0.25)
# Red hot
plot_line(2 * np.arctan(kb_inv/(273.15 + 500)/scale), 'r', '-')
# Rock melting
plot_line(2 * np.arctan(kb_inv/(273.15 + 1500)/scale), 'm', '-')
# Graphite sublimation
plot_line(2 * np.arctan(kb_inv/(273.15 + 3642)/scale), 'm', '--')
# Surface of the Sun
plot_line(2 * np.arctan(kb_inv/5778/scale), 'm', ':')
# 0 °F
plot_line(2 * np.arctan(kb_inv/(273.15+5*(0-32)/9)/scale), 'r', '--')
# 100 °F
plot_line(2 * np.arctan(kb_inv/(273.15+5*(100-32)/9)/scale), 'r', '--')
# 1024 Stonehenge dominoes
plot_line(2 * np.arctan(-1.25e-15/scale), 'darkgrey', ':')
# HeNe laser
plot_line(2 * np.arctan(-31.5/scale), 'darkgrey', '--')
# 500,001 spin-up protons out of 1 million in 1T magnetic field
mu_p = 1.410606797e-26 # proton magnetic moment
plot_line(2 * np.arctan(kb_inv/(mu_p/(1.38e-23*np.log(1000000/500001-1)))/scale), 'darkgrey', '-')
# 500,002 spin-up protons out of 1 million in 1T magnetic field
plot_line(2 * np.arctan(kb_inv/(mu_p/(1.38e-23*np.log(1000000/500002-1)))/scale), 'darkgrey', '-.')
# 500,003 spin-up protons out of 1 million in 1T magnetic field
plot_line(2 * np.arctan(kb_inv/(mu_p/(1.38e-23*np.log(1000000/500003-1)))/scale), 'darkgrey', '-.')
# Plot circles
ax.plot(circle_angles, gb_distance*r_circ, 'k-')
ax.plot(circle_angles, k_distance*r_circ, 'b-')
ax.plot(semi_angles, c_distance * r_semi, 'g-')
ax.plot(semi_angles, f_distance * r_semi, 'r-')
# Plot infinities
ax.plot([TAU/2], [gb_distance], 'k.')
plt.text(TAU/2, 0.075 + gb_distance, r'$+\infty$', ha='center', va='center', rotation = -90, fontsize=size)
ax.plot(0., k_distance, 'b.')
plt.text(0., 0.075 + k_distance, r'$\pm\infty$', color='b', ha='center', va='center', rotation = 90, fontsize=size)
# plt.annotate('$+\infty$', (TAU/2, 1.))
# plt.grid(visible=None)
plt.axis('off')
# Plot points
ax.plot(angles, gb_distance*r, 'k.')
ax.plot(k_angles, k_distance*r_k, 'b.')
ax.plot(c_angles, c_distance * r_c, 'g.')
ax.plot(f_angles, f_distance * r_f, 'r.')
# Orient plot
ax.set_theta_zero_location('N')
ax.set_theta_direction(-1)
# Set linewidths
plt.setp(ax.lines, linewidth=0.6)
plt.title('Universal coldness/temperature scale')
plt.savefig('fig/ColdnessScale-mpl.svg');
Footnotes
- ↑ Claude Garrod (1995) Statistical Mechanics and Thermodynamics (Oxford U. Press).
- ↑ J. Meixner (1975) "Coldness and Temperature", Archive for Rational Mechanics and Analysis 57:3, 281-290 abstract.
- ↑ Ingo Mueller (1972) Entropy, Absolute Temperature and Coldness in Thermodynamics: Boundary conditions in porous materials (Springer-Verlag, Wein GMBH) preview
- ↑ Ingo Müller (1971) "The coldness, a universal function in thermoelastic bodies", Archive for Rational Mechanics and Analysis 41:5, 319-332 abstract.
- ↑ Müller, I. (1971) "Die K?ltefunktion, eine universelle Funktion in der Thermodynamik w?rmeleitender Flüssigkeiten.", Arch. Rational Mech. Anal. 40, 1–36.
- ↑ Day, W.A. and Gurtin, Morton E. (1969) "On the symmetry of the conductivity tensor and other restrictions in the nonlinear theory of heat conduction", Archive for Rational Mechanics and Analysis 33:1, 26-32 (Springer-Verlag) abstract.
- ↑ J. Castle, W. Emmenish, R. Henkes, R. Miller, and J. Rayne (1965) Science by Degrees: Temperature from Zero to Zero (Westinghouse Search Book Series, Walker and Company, New York).
- ↑ P. Fraundorf (2003) "Heat capacity in bits", Amer. J. Phys. 71:11, 1142-1151.
прощ?ни?
- т? мож?ши :
- простр?ти – to copy, distribute and transmit the work
- пр?вращати – пр?творити д?ло
- Under the following conditions:
- attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- share alike – ащ? ж? с? д?ло и?м?ниши · пр?вратиши или ?гож? основ? н?чьто сътвориши · тъ авл?но сл?дьстви? подъ самомь т?мь прощ?ни?мь или подобьномь ?моу положити длъж?нъ ?си
д?ла ?стор??
Click on a date/time to view the file as it appeared at that time.
| дьнь / вр?м? | малъ обра?ъ | м?ра | поль??ват?л?ь | опьсани? | |
|---|---|---|---|---|---|
| н?н?щьн?ь обра?ъ | 00:43, ?оул?? 9 числа, 2022 | | 312 × 324 (76 Х?Б) | AkanoToE | Arrowheads didn't render, fixed |
| 00:37, ?оул?? 9 числа, 2022 |  | 312 × 324 (76 Х?Б) | AkanoToE | Added arrowheads, adjusted legend size | |
| 00:29, ?оул?? 9 числа, 2022 |  | 326 × 324 (75 Х?Б) | AkanoToE | Uploaded own work with UploadWizard |
д?ла поль??вани?
The following page uses this file:
Global file usage
ин? м?ста къд? с? д?ло поль??вано ?стъ :
- поль??вани? въ af.wikipedia.org
- поль??вани? въ arc.wikipedia.org
- поль??вани? въ ar.wikipedia.org
- поль??вани? въ be.wikipedia.org
- поль??вани? въ bn.wikipedia.org
- поль??вани? въ ca.wikipedia.org
- поль??вани? въ ce.wikipedia.org
- поль??вани? въ de.wikipedia.org
- поль??вани? въ en.wikipedia.org
- поль??вани? въ eo.wikipedia.org
- поль??вани? въ es.wikipedia.org
- поль??вани? въ fa.wikipedia.org
- поль??вани? въ hu.wikipedia.org
- поль??вани? въ kv.wikipedia.org
- поль??вани? въ mt.wikipedia.org
- поль??вани? въ no.wikipedia.org
- поль??вани? въ rue.wikipedia.org
- поль??вани? въ ru.wikipedia.org
- поль??вани? въ sv.wikipedia.org
- поль??вани? въ szl.wikipedia.org
- поль??вани? въ tg.wikipedia.org
- поль??вани? въ tt.wikipedia.org
- поль??вани? въ uk.wikipedia.org
- поль??вани? въ www.wikidata.org
- поль??вани? въ zea.wikipedia.org
